diff --git a/examples/03_Frequency_Domain_Analysis_RAFT/01_platform.yaml b/examples/03_Frequency_Domain_Analysis_RAFT/01_platform.yaml
index a860d818..4e733a4a 100644
--- a/examples/03_Frequency_Domain_Analysis_RAFT/01_platform.yaml
+++ b/examples/03_Frequency_Domain_Analysis_RAFT/01_platform.yaml
@@ -27,7 +27,7 @@ platform:
       rB        :  [ 0, 0,  15]              # [m]    and B coordinates
       shape     :  circ                      # [-]    circular or rectangular
       gamma     :  0.0                       # [deg]  twist angle about the member's z-axis
-      potMod    :  True                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
+      potMod    :  False                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
       # --- outer shell including hydro---
       stations  :  [0, 1]                    # [-]    location of stations along axis. Will be normalized such that start value maps to rA and end value to rB
       d         :  10.0                      # [m]    diameters if circular or side lengths if rectangular (can be pairs)
@@ -50,7 +50,7 @@ platform:
       heading   :  [ 60, 180, 300]           # [deg]  heading rotation of column about z axis (for repeated members)
       shape     :  circ                      # [-]    circular or rectangular
       gamma     :  0.0                       # [deg]  twist angle about the member's z-axis
-      potMod    :  True                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
+      potMod    :  False                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
       # --- outer shell including hydro---
       stations  :  [0, 35]                    # [-]    location of stations along axis. Will be normalized such that start value maps to rA and end value to rB
       d         :  12.5                      # [m]    diameters if circular or side lengths if rectangular (can be pairs)
diff --git a/examples/03_Frequency_Domain_Analysis_RAFT/02_FOWT.yaml b/examples/03_Frequency_Domain_Analysis_RAFT/02_FOWT.yaml
index 533b143e..7d5dd939 100644
--- a/examples/03_Frequency_Domain_Analysis_RAFT/02_FOWT.yaml
+++ b/examples/03_Frequency_Domain_Analysis_RAFT/02_FOWT.yaml
@@ -1123,7 +1123,7 @@ platform:
       rB        :  [ 0, 0,  15]              # [m]    and B coordinates
       shape     :  circ                      # [-]    circular or rectangular
       gamma     :  0.0                       # [deg]  twist angle about the member's z-axis
-      potMod    :  True                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
+      potMod    :  False                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
       # --- outer shell including hydro---
       stations  :  [0, 1]                    # [-]    location of stations along axis. Will be normalized such that start value maps to rA and end value to rB
       d         :  10.0                      # [m]    diameters if circular or side lengths if rectangular (can be pairs)
@@ -1146,7 +1146,7 @@ platform:
       heading   :  [ 60, 180, 300]           # [deg]  heading rotation of column about z axis (for repeated members)
       shape     :  circ                      # [-]    circular or rectangular
       gamma     :  0.0                       # [deg]  twist angle about the member's z-axis
-      potMod    :  True                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
+      potMod    :  False                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
       # --- outer shell including hydro---
       stations  :  [0, 35]                    # [-]    location of stations along axis. Will be normalized such that start value maps to rA and end value to rB
       d         :  12.5                      # [m]    diameters if circular or side lengths if rectangular (can be pairs)
diff --git a/examples/05_Anchors/anchor_drilled.py b/examples/05_Anchors/anchor_drilled.py
new file mode 100644
index 00000000..e252be61
--- /dev/null
+++ b/examples/05_Anchors/anchor_drilled.py
@@ -0,0 +1,64 @@
+
+from famodel.anchors.anchor import Anchor
+
+# --- Define soil profile ---
+profile_map = [
+    {
+        'name': 'CPT_D1',
+        'x': 0.0, 'y': 0.0,
+        'layers': [
+            {'top':  1.5, 'bottom':  5.0, 'soil_type': 'rock', 'UCS_top':  6.0, 'UCS_bot':  8.0, 'Em_top':  175, 'Em_bot':  290},
+            {'top':  5.0, 'bottom':  9.0, 'soil_type': 'rock', 'UCS_top':  8.0, 'UCS_bot': 10.7, 'Em_top':  277, 'Em_bot':  297},
+            {'top':  9.0, 'bottom': 30.0, 'soil_type': 'rock', 'UCS_top':  8.0, 'UCS_bot': 10.5, 'Em_top':  280, 'Em_bot': 305}
+        ]
+    }
+]
+
+# --- Create driven pile anchor ---
+anchor = Anchor(
+    dd = {
+        'type': 'drilled',
+        'design': {
+            'L': 10.0,        # Embedded length
+            'D': 2.85,        # Diameter
+            'zlug': 1.0       # Padeye depth
+        }
+    },
+    r = [0.0, 0.0, 0.0])
+
+# Assign mooring loads
+anchor.loads = {
+    'Hm': 5.0e6,
+    'Vm': 2.5e5}
+
+anchor.line_type = 'chain'
+anchor.d = 0.16
+anchor.w = 5000.0
+
+# Assign local soil
+anchor.setSoilProfile(profile_map)
+
+# --- Step 1: Capacity ---
+anchor.getCapacityAnchor(
+    Hm = anchor.loads['Hm'],
+    Vm = anchor.loads['Vm'],
+    zlug = anchor.dd['design']['zlug'],
+    line_type = anchor.line_type,
+    d = anchor.d,
+    w = anchor.w,
+    plot = True)
+
+print('\nCapacity Results:')
+for key, val in anchor.anchorCapacity.items():
+    print(f'{key}: {val:.2f}')
+
+# --- Step 2: Optimize Anchor Geometry ---
+anchor.getSizeAnchor(
+    geom = [anchor.dd['design']['L'], anchor.dd['design']['D']],
+    geomKeys = ['L', 'D'],
+    geomBounds = [(2.0, 30.0), (2.25, 5.0)],
+    loads = None,
+    lambdap_con = [4, 50],
+    zlug_fix = True,
+    safety_factor = {'SF_horizontal': 1, 'SF_vertical': 1},
+    plot = True)
\ No newline at end of file
diff --git a/examples/05_Anchors/anchor_driven_rock.py b/examples/05_Anchors/anchor_driven_rock.py
new file mode 100644
index 00000000..8564bea6
--- /dev/null
+++ b/examples/05_Anchors/anchor_driven_rock.py
@@ -0,0 +1,65 @@
+
+from famodel.anchors.anchor import Anchor
+
+# --- Define soil profile ---
+profile_map = [
+    {
+        'name': 'CPT_D1',
+        'x': 0.0, 'y': 0.0,
+        'layers': [
+            {'top':  1.5, 'bottom':  6.0, 'soil_type': 'rock', 'UCS_top':  5.0, 'UCS_bot':  5.0, 'Em_top':  7, 'Em_bot': 7},
+            {'top':  6.0, 'bottom': 15.0, 'soil_type': 'rock', 'UCS_top':  6.0, 'UCS_bot':  6.7, 'Em_top':  7, 'Em_bot': 7},
+            {'top': 15.0, 'bottom': 35.0, 'soil_type': 'rock', 'UCS_top': 10.0, 'UCS_bot': 10.5, 'Em_top':  7, 'Em_bot': 7}
+        ]
+    }
+]
+
+# --- Create driven pile anchor ---
+anchor = Anchor(
+    dd = {
+        'type': 'driven',
+        'design': {
+            'L': 15.0,        # Embedded length
+            'D': 1.85,        # Diameter
+            'zlug': 1.5       # Padeye depth
+        }
+    },
+    r = [0.0, 0.0, 0.0]
+)
+
+# Assign mooring loads
+anchor.loads = {
+    'Hm': 2.5e6,
+    'Vm': 2.5e5}
+
+anchor.line_type = 'chain'
+anchor.d = 0.16
+anchor.w = 5000.0
+
+# Assign local soil
+anchor.setSoilProfile(profile_map)
+
+# --- Step 1: Capacity ---
+anchor.getCapacityAnchor(
+    Hm = anchor.loads['Hm'],
+    Vm = anchor.loads['Vm'],
+    zlug = anchor.dd['design']['zlug'],
+    line_type = anchor.line_type,
+    d = anchor.d,
+    w = anchor.w,
+    plot = True)
+
+print('\nCapacity Results:')
+for key, val in anchor.anchorCapacity.items():
+    print(f'{key}: {val:.2f}')
+
+# --- Step 2: Optimize Anchor Geometry ---
+anchor.getSizeAnchor(
+    geom = [anchor.dd['design']['L'], anchor.dd['design']['D']],
+    geomKeys = ['L', 'D'],
+    geomBounds = [(2.0, 70.0), (0.25, 3.0)],
+    loads = None,
+    lambdap_con = [4, 50],
+    zlug_fix = True,
+    safety_factor = {'SF_horizontal': 1, 'SF_vertical': 1},
+    plot = True)
\ No newline at end of file
diff --git a/famodel/anchors/getCapacityPile_map.py b/examples/05_Anchors/anchor_driven_soil.py
similarity index 55%
rename from famodel/anchors/getCapacityPile_map.py
rename to examples/05_Anchors/anchor_driven_soil.py
index 38998786..4ea2efd1 100644
--- a/famodel/anchors/getCapacityPile_map.py
+++ b/examples/05_Anchors/anchor_driven_soil.py
@@ -1,5 +1,5 @@
 
-from anchor_map import Anchor
+from famodel.anchors.anchor import Anchor
 
 # --- Define soil profile ---
 profile_map = [
@@ -7,9 +7,9 @@
         'name': 'CPT_D1',
         'x': 0.0, 'y': 0.0,
         'layers': [
-            {'top':  1.0, 'bottom':  6.0, 'soil_type': 'clay', 'gamma_top':  9.0, 'gamma_bot': 10.0, 'Su_top': 45, 'Su_bot':  60},
-            {'top':  6.0, 'bottom': 15.0, 'soil_type': 'clay', 'gamma_top': 10.0, 'gamma_bot': 10.0, 'Su_top': 60, 'Su_bot':  80},
-            {'top': 15.0, 'bottom': 35.0, 'soil_type': 'clay', 'gamma_top': 10.0, 'gamma_bot': 10.5, 'Su_top': 80, 'Su_bot': 100}
+            {'top':  1.5, 'bottom':  6.0, 'soil_type': 'clay', 'gamma_top':  9.0, 'gamma_bot': 10.0, 'Su_top':  25, 'Su_bot': 200},
+            {'top':  6.0, 'bottom': 15.0, 'soil_type': 'sand', 'gamma_top': 10.0, 'gamma_bot': 10.0, 'phi_top': 28, 'phi_bot': 32, 'Dr_top':  80, 'Dr_bot': 85},
+            {'top': 15.0, 'bottom': 35.0, 'soil_type': 'clay', 'gamma_top': 10.0, 'gamma_bot': 10.5, 'Su_top': 100, 'Su_bot': 100}
         ]
     }
 ]
@@ -20,8 +20,8 @@
         'type': 'driven',
         'design': {
             'L': 25.0,        # Embedded length
-            'D': 2.0,         # Diameter
-            'zlug': 10.0      # Padeye depth
+            'D': 2.00,        # Diameter
+            'zlug': 3.0       # Padeye depth
         }
     },
     r = [0.0, 0.0, 0.0]
@@ -29,9 +29,9 @@
 
 # Assign mooring loads
 anchor.loads = {
-    'Hm': 4.0e6,
-    'Vm': 2.5e6
-}
+    'Hm': 7.0e5,
+    'Vm': 2.5e5}
+
 anchor.line_type = 'chain'
 anchor.d = 0.16
 anchor.w = 5000.0
@@ -47,8 +47,7 @@
     line_type = anchor.line_type,
     d = anchor.d,
     w = anchor.w,
-    plot = True
-)
+    plot = True)
 
 print('\nLug Forces Computed:')
 print(f'Ha = {Ha:.2f} N')
@@ -62,9 +61,19 @@
     line_type = anchor.line_type,
     d = anchor.d,
     w = anchor.w,
-    plot = True
-)
+    plot = True)
 
 print('\nCapacity Results:')
-for key, val in anchor.capacity_results.items():
+for key, val in anchor.anchorCapacity.items():
     print(f'{key}: {val:.2f}')
+
+# --- Step 3: Optimize Anchor Geometry ---
+anchor.getSizeAnchor(
+    geom = [anchor.dd['design']['L'], anchor.dd['design']['D']],
+    geomKeys = ['L', 'D'],
+    geomBounds = [(2.0, 50.0), (0.25, 3.5)],
+    loads = None,
+    lambdap_con = [3, 50],
+    zlug_fix = True,
+    safety_factor = {'SF_horizontal': 1, 'SF_vertical': 1},
+    plot = True)
\ No newline at end of file
diff --git a/famodel/anchors/getCapacityHelical_clay.py b/examples/05_Anchors/anchor_helical.py
similarity index 62%
rename from famodel/anchors/getCapacityHelical_clay.py
rename to examples/05_Anchors/anchor_helical.py
index f1367126..3c6c81e5 100644
--- a/famodel/anchors/getCapacityHelical_clay.py
+++ b/examples/05_Anchors/anchor_helical.py
@@ -1,5 +1,5 @@
 
-from anchor_map import Anchor
+from famodel.anchors.anchor import Anchor
 
 # --- Soil profile for helical pile in clay ---
 profile_map = [
@@ -7,9 +7,9 @@
         'name': 'CPT_H1',
         'x': 0.0, 'y': 0.0,
         'layers': [
-            {'top': 1.0, 'bottom': 3.0, 'soil_type': 'clay', 'gamma_top': 8.0, 'gamma_bot': 9.0, 'Su_top': 60, 'Su_bot': 50},
-            {'top': 3.0, 'bottom': 7.0, 'soil_type': 'clay', 'gamma_top': 15.0, 'gamma_bot': 25.0, 'Su_top': 100, 'Su_bot': 150},
-            {'top': 7.0, 'bottom': 15.0, 'soil_type': 'clay', 'gamma_top': 25.0, 'gamma_bot': 50.0, 'Su_top': 200, 'Su_bot': 400}
+            {'top': 1.0, 'bottom':  3.0, 'soil_type': 'clay', 'gamma_top':  8.0, 'gamma_bot':  9.0, 'Su_top':  60, 'Su_bot':  50},
+            {'top': 3.0, 'bottom':  7.0, 'soil_type': 'clay', 'gamma_top': 15.0, 'gamma_bot': 25.0, 'Su_top': 100, 'Su_bot': 150},
+            {'top': 7.0, 'bottom': 25.0, 'soil_type': 'clay', 'gamma_top': 25.0, 'gamma_bot': 50.0, 'Su_top': 200, 'Su_bot': 400}
         ]
     }
 ]
@@ -30,9 +30,9 @@
 
 # --- Assign mooring loads and properties ---
 anchor.loads = {
-    'Hm': 80e4,
-    'Vm': 50e3
-}
+    'Hm': 8e5,
+    'Vm': 1e5}
+
 anchor.line_type = 'chain'
 anchor.d = 0.16
 anchor.w = 5000.0
@@ -48,8 +48,7 @@
     line_type = anchor.line_type,
     d = anchor.d,
     w = anchor.w,
-    plot = True
-)
+    plot = True)
 
 print('\nLug Forces Computed:')
 print(f'Ha = {Ha:.2f} N')
@@ -63,9 +62,19 @@
     line_type = anchor.line_type,
     d = anchor.d,
     w = anchor.w,
-    plot = True
-)
+    plot = False)
 
 print('\nCapacity Results:')
-for key, val in anchor.capacity_results.items():
+for key, val in anchor.anchorCapacity.items():
     print(f'{key}: {val:.2f}')
+
+# --- Step 3: Optimize Anchor Geometry ---
+anchor.getSizeAnchor(
+    geom = [anchor.dd['design']['L'], anchor.dd['design']['D']],
+    geomKeys = ['L', 'D'],
+    geomBounds = [(6.0, 25.0), (0.5, 2.0)],
+    loads = None,
+    lambdap_con = [6, 15],
+    zlug_fix = True,
+    safety_factor = {'SF_horizontal': 1, 'SF_vertical': 1},   
+    plot = False)
diff --git a/famodel/anchors/getCapacityPlate_map.py b/examples/05_Anchors/anchor_plate.py
similarity index 67%
rename from famodel/anchors/getCapacityPlate_map.py
rename to examples/05_Anchors/anchor_plate.py
index 088cd40b..f04c3675 100644
--- a/famodel/anchors/getCapacityPlate_map.py
+++ b/examples/05_Anchors/anchor_plate.py
@@ -1,7 +1,6 @@
 
-from anchor_map import Anchor
-import numpy as np
-from famodel.anchors.anchors_famodel_map.capacity_plots_map import plot_load
+from famodel.anchors.anchor import Anchor
+from famodel.anchors.anchors_famodel.support_plots import plot_load
 
 # --- Define soil profile ---
 profile_map = [
@@ -10,7 +9,7 @@
         'x': 0.0, 'y': 0.0,
         'layers': [
             {'top':  2.0, 'bottom':  4.0, 'soil_type': 'clay', 'gamma_top':  8.0, 'gamma_bot':  8.5, 'Su_top':  10, 'Su_bot':  25},
-            {'top':  4.0, 'bottom':  6.0, 'soil_type': 'clay', 'gamma_top':  8.5, 'gamma_bot':  9.0, 'Su_top':  25, 'Su_bot':  50},
+            {'top':  4.0, 'bottom':  6.0, 'soil_type': 'clay', 'gamma_top':  8.5, 'gamma_bot':  9.0, 'Su_top':  15, 'Su_bot':  40},
             {'top':  6.0, 'bottom': 16.0, 'soil_type': 'clay', 'gamma_top':  9.0, 'gamma_bot':  9.5, 'Su_top':  50, 'Su_bot': 100},
             {'top': 16.0, 'bottom': 25.0, 'soil_type': 'clay', 'gamma_top':  9.5, 'gamma_bot':  9.5, 'Su_top': 100, 'Su_bot': 100}
         ]
@@ -19,15 +18,14 @@
 
 # --- Create plate anchor ---
 anchor = Anchor(
-    dd = {'type': 'plate', 'design': {'B': 3.0, 'L': 6.0, 'zlug': 5.0, 'beta': 30.0}},
-    r = [100.0, 100.0, 0.0]
-)
+    dd = {'type': 'plate', 'design': {'B': 3.0, 'L': 6.0, 'zlug': 14.0, 'beta': 30.0}},
+    r = [0.0, 0.0, 0.0])
 
 # --- Assign load and mooring properties ---
 anchor.loads = {
-    'Hm': 2.5e6,
-    'Vm': 1.5e6
-}
+    'Hm': 3.5e6,
+    'Vm': 2.5e6}
+
 anchor.line_type = 'chain'
 anchor.d = 0.16
 anchor.w = 5000.0
@@ -43,8 +41,7 @@
     line_type = anchor.line_type,
     d = anchor.d,
     w = anchor.w,
-    plot = True
-)
+    plot = True)
 
 print('\nLug Forces Computed:')
 print(f'Ha = {Ha:.2f} N')
@@ -58,9 +55,20 @@
     line_type = anchor.line_type,
     d = anchor.d,
     w = anchor.w,
-    plot = True
-)
+    plot = True)
 
 print('\nCapacity Results:')
-for key, value in anchor.capacity_results.items():
+for key, value in anchor.anchorCapacity.items():
     print(f'{key}: {value:.2f}')
+
+# --- Step 3: Optimize Anchor Geometry ---
+anchor.getSizeAnchor(
+    geom = [anchor.dd['design']['B'], anchor.dd['design']['L']],
+    geomKeys = ['B', 'L'],
+    geomBounds = [(0.5, 6.0), (2.0, 12.0)],
+    loads = None,
+    lambdap_con = [2, 4],  # less critical for plates
+    zlug_fix = True,
+    safety_factor = {'SF_horizontal': 2, 'SF_vertical': 3},
+    #safety_factor = {'SF_combined': 3},
+    plot = True)
diff --git a/examples/05_Anchors/anchor_soil_layered.py b/examples/05_Anchors/anchor_soil_layered.py
new file mode 100644
index 00000000..714eaefd
--- /dev/null
+++ b/examples/05_Anchors/anchor_soil_layered.py
@@ -0,0 +1,65 @@
+
+
+from famodel import Project
+from famodel.anchors.anchor import Anchor
+
+# Step 1: Initialize and load soil
+proj = Project()
+proj.loadSoil(
+    filename='inputs/GulfOfMaine_soil_layered_100x100.txt',
+    soil_mode='layered',
+    profile_source='inputs/GulfOfMaine_soil_profiles.yaml')
+
+for label, props in proj.soilProps.items():
+    print(f"{label}: {props}")
+
+# Step 2: Create and register an anchor at a known position in the grid
+anchor = Anchor(
+    dd = {'type': 'suction', 'design': {'D': 3.5, 'L': 12.0, 'zlug': 9.67}},
+    r  = [54.0, -4450.0, 0.0])
+
+# Step 3: Assign local soil profile from project (nearest neighbor lookup)
+soil_id, soil_profile = proj.getSoilAtLocation(anchor.r[0], anchor.r[1])
+anchor.soilProps = {soil_id: soil_profile}
+anchor.setSoilProfile([{'name': soil_id, 'layers': soil_profile}])  # ensures `anchor.soil_profile` is set
+
+# Step 4: Assign loads and line
+anchor.loads = {'Hm': 2e6, 'Vm': 1.5e6}
+anchor.line_type = 'chain'
+anchor.d = 0.16
+anchor.w = 5000.0
+
+# Step 5: Run capacity check and optimization
+anchor.getLugForces(
+    Hm=anchor.loads['Hm'], Vm=anchor.loads['Vm'], 
+    zlug = anchor.dd['design']['zlug'], 
+    d=anchor.d, w=anchor.w,  
+    plot=True)
+
+anchor.getCapacityAnchor(
+    Hm=anchor.loads['Hm'], Vm=anchor.loads['Vm'], 
+    zlug = anchor.dd['design']['zlug'], 
+    line_type=anchor.line_type, d=anchor.d, w=anchor.w,   
+    mass_update=True,
+    plot=True)
+anchor.getCost()
+print(f'Material cost: {anchor.cost["Material cost"]:.2f} USD [2024]')
+
+results = anchor.getSizeAnchor(
+    geom = [anchor.dd['design']['L'], anchor.dd['design']['D']],
+    geomKeys = ['L', 'D'],
+    geomBounds = [(8.0, 15.0), (2.0, 4.0)],
+    loads = None,
+    lambdap_con = [3, 6],
+    zlug_fix = False,
+    safety_factor = {'SF_combined': 1},
+    plot = True)
+
+# Step 6: Report
+print('\nFinal Optimized Anchor:')
+print('Design:', anchor.dd['design'])
+print('Capacity Results:', anchor.anchorCapacity)
+anchor.getCost()
+print(f'Material cost: {anchor.cost["Material cost"]:.2f} USD [2024]')
+
+
diff --git a/examples/05_Anchors/anchor_soil_uniform.py b/examples/05_Anchors/anchor_soil_uniform.py
new file mode 100644
index 00000000..01886c7f
--- /dev/null
+++ b/examples/05_Anchors/anchor_soil_uniform.py
@@ -0,0 +1,69 @@
+
+from famodel import Project
+from famodel.anchors.anchor import Anchor
+
+# Step 1: Initialize and load soil
+proj = Project()
+proj.loadSoil(
+    filename='inputs/GulfOfMaine_soil_layered_100x100.txt',
+    soil_mode='uniform')  # 'uniform' soil does not need from the profile_source yaml file
+
+for label, props in proj.soilProps.items():
+    print(f"{label}: {props}")
+    
+# Convert to profile_map format so anchor capacity models can use it
+proj.convertUniformToLayered(default_layer=50.0)
+
+for label, props in proj.profile_map.items():
+    print(f"{label}: {props}")
+
+# Step 2: Create and register an anchor at a known position in the grid
+anchor = Anchor(
+    dd = {'type': 'suction', 'design': {'D': 3.5, 'L': 12.0, 'zlug': 9.67}},
+    r  = [54.0, -4450.0, 0.0])
+
+# Step 3: Assign local soil profile from project (nearest neighbor lookup)
+soil_id, _ = proj.getSoilAtLocation(anchor.r[0], anchor.r[1])
+soil_profile = proj.profile_map[soil_id]  # get compatible layered format
+anchor.soilProps = {soil_id: soil_profile}
+anchor.setSoilProfile([{'name': soil_id, 'layers': soil_profile}])  # ensures `anchor.soil_profile` is set
+
+# Step 4: Assign loads and line
+anchor.loads = {'Hm': 1e6, 'Vm': 5e4}
+anchor.line_type = 'chain'
+anchor.d = 0.16
+anchor.w = 5000.0
+
+# Step 5: Run capacity check and optimization
+anchor.getLugForces(
+    Hm=anchor.loads['Hm'], Vm=anchor.loads['Vm'], 
+    zlug = anchor.dd['design']['zlug'], 
+    d=anchor.d, w=anchor.w,  
+    plot=True)
+
+anchor.getCapacityAnchor(
+    Hm=anchor.loads['Hm'], Vm=anchor.loads['Vm'], 
+    zlug = anchor.dd['design']['zlug'], 
+    line_type=anchor.line_type, d=anchor.d, w=anchor.w,   
+    mass_update=True,
+    plot=True)
+anchor.getCost()
+print(f'Material cost: {anchor.cost["Material cost"]:.2f} USD [2024]')
+
+results = anchor.getSizeAnchor(
+    geom = [anchor.dd['design']['L'], anchor.dd['design']['D']],
+    geomKeys = ['L', 'D'],
+    geomBounds = [(8.0, 15.0), (2.0, 4.0)],
+    lambdap_con = [3, 6],
+    zlug_fix = False,
+    safety_factor = {'SF_combined': 1},
+    plot = True)
+
+# Step 6: Report
+print('\nFinal Optimized Anchor:')
+print('Design:', anchor.dd['design'])
+print('Capacity Results:', anchor.anchorCapacity)
+anchor.getCost()
+print(f'Material cost: {anchor.cost["Material cost"]:.2f} USD [2024]')
+
+
diff --git a/famodel/anchors/getCapacitySuction_map.py b/examples/05_Anchors/anchor_suction.py
similarity index 58%
rename from famodel/anchors/getCapacitySuction_map.py
rename to examples/05_Anchors/anchor_suction.py
index 1c41ac6e..ccc4ea57 100644
--- a/famodel/anchors/getCapacitySuction_map.py
+++ b/examples/05_Anchors/anchor_suction.py
@@ -1,7 +1,6 @@
 
-from anchor_map import Anchor
-import numpy as np
-from famodel.anchors.anchors_famodel_map.capacity_plots_map import plot_load
+from famodel.anchors.anchor import Anchor
+from famodel.anchors.anchors_famodel.support_plots import plot_suction
 
 # --- Define soil profile ---
 profile_map = [
@@ -9,10 +8,10 @@
         'name': 'CPT_A1',
         'x': 0.0, 'y': 0.0,
         'layers': [
-            {'top':  2.0, 'bottom':  4.0, 'soil_type': 'clay', 'gamma_top':  8.0, 'gamma_bot':  8.5, 'Su_top':  10, 'Su_bot':  25},
-            {'top':  4.0, 'bottom':  6.0, 'soil_type': 'clay', 'gamma_top':  8.5, 'gamma_bot':  9.0, 'Su_top':  25, 'Su_bot':  50},
-            {'top':  6.0, 'bottom': 16.0, 'soil_type': 'clay', 'gamma_top':  9.0, 'gamma_bot':  9.5, 'Su_top':  50, 'Su_bot': 100},
-            {'top': 16.0, 'bottom': 25.0, 'soil_type': 'clay', 'gamma_top':  9.5, 'gamma_bot':  9.5, 'Su_top': 100, 'Su_bot': 100}
+            {'top':  2.0, 'bottom':  4.0, 'soil_type': 'clay', 'gamma_top': 8.0, 'gamma_bot': 8.5, 'Su_top':  10, 'Su_bot':  25},
+            {'top':  4.0, 'bottom':  6.0, 'soil_type': 'clay', 'gamma_top': 8.5, 'gamma_bot': 9.0, 'Su_top':  25, 'Su_bot':  50},
+            {'top':  6.0, 'bottom': 16.0, 'soil_type': 'clay', 'gamma_top': 9.0, 'gamma_bot': 9.5, 'Su_top':  50, 'Su_bot': 100},
+            {'top': 16.0, 'bottom': 25.0, 'soil_type': 'clay', 'gamma_top': 9.5, 'gamma_bot': 9.5, 'Su_top': 100, 'Su_bot': 100}
         ]
     },
     {
@@ -29,10 +28,10 @@
         'name': 'CPT_A2',
         'x': 0.0, 'y': 500.0,
         'layers': [
-            {'top':  2.0, 'bottom':  4.0, 'soil_type': 'clay', 'gamma_top':  7.5, 'gamma_bot':  8.0, 'Su_top':   5, 'Su_bot':  20},
-            {'top':  4.0, 'bottom':  8.0, 'soil_type': 'clay', 'gamma_top':  8.0, 'gamma_bot':  8.5, 'Su_top':  20, 'Su_bot':  45},
-            {'top':  8.0, 'bottom': 16.0, 'soil_type': 'clay', 'gamma_top':  8.5, 'gamma_bot':  9.0, 'Su_top':  45, 'Su_bot':  95},
-            {'top': 16.0, 'bottom': 25.0, 'soil_type': 'clay', 'gamma_top':  9.0, 'gamma_bot':  9.0, 'Su_top':  95, 'Su_bot':  95}
+            {'top':  2.0, 'bottom':  4.0, 'soil_type': 'clay', 'gamma_top': 7.5, 'gamma_bot': 8.0, 'Su_top':  5, 'Su_bot': 20},
+            {'top':  4.0, 'bottom':  8.0, 'soil_type': 'clay', 'gamma_top': 8.0, 'gamma_bot': 8.5, 'Su_top': 20, 'Su_bot': 45},
+            {'top':  8.0, 'bottom': 16.0, 'soil_type': 'clay', 'gamma_top': 8.5, 'gamma_bot': 9.0, 'Su_top': 45, 'Su_bot': 95},
+            {'top': 16.0, 'bottom': 25.0, 'soil_type': 'clay', 'gamma_top': 9.0, 'gamma_bot': 9.0, 'Su_top': 95, 'Su_bot': 95}
         ]
     },
     {
@@ -49,14 +48,27 @@
 
 
 anchor = Anchor(
-    dd = {'type': 'suction', 'design': {'D': 2.5, 'L': 12.0, 'zlug': 9.0}},
-    r = [250.0, 000.0, 000.0]
-)
+    dd = {'type': 'suction', 'design': {'D': 2.5, 'L': 12.0, 'zlug': 8.67}},
+    r = [250.0, 250.0, 000.0])
+
+# --- Step 0: Create anchor based grid CPTs ---
+anchor.interpolateSoilProfile(profile_map)
+
+# --- Step 1: Plot suction pile and soil profile ---
+# Access anchor geometrical properties
+L = anchor.dd['design']['L']
+D = anchor.dd['design']['D']
+zlug = anchor.dd['design']['zlug']
+# Access matched profile
+layers = anchor.soil_profile[0]['layers']
+z0 = layers[0]['top']
+
+plot_suction(layers, L=L, D=D, z0=z0, zlug=zlug)
 
 # Assign loads manually
 anchor.loads = {
-    'Hm': 3e6,     # Horizontal mudline load (N)
-    'Vm': 2e6      # Vertical mudline load (N)
+    'Hm': 3.0e6,    # Horizontal mudline load (N)
+    'Vm': 1.0e6     # Vertical mudline load (N)
 }
 
 # Assign line properties manually
@@ -64,11 +76,8 @@
 anchor.d = 0.16    # Chain diameter (m)
 anchor.w = 5000.0  # Nominal submerged weight (N/m)
 
-# --- Step 0: Create anchor based grid CPTs ---
-anchor.setSoilProfile(profile_map)
-
 
-# --- Step 1: Compute Lug Forces ---
+# --- Step 2: Compute Lug Forces ---
 layers, Ha, Va = anchor.getLugForces(
     Hm = anchor.loads['Hm'],
     Vm = anchor.loads['Vm'],
@@ -76,43 +85,55 @@
     line_type = anchor.line_type,
     d = anchor.d,
     w = anchor.w,
-    plot = True
-)
+    plot = True)
 
 print('\nLug Forces Computed:')
 print(f'Ha = {Ha:.2f} N')
 print(f'Va = {Va:.2f} N')
 
-# --- Step 2: Compute Capacity ---
+# --- Step 3: Compute Capacity ---
 anchor.getCapacityAnchor(
     Hm = anchor.loads['Hm'],
     Vm = anchor.loads['Vm'],
     zlug = anchor.dd['design']['zlug'],
     line_type = anchor.line_type,
-    d = anchor.d,
-    w = anchor.w,
-    plot = True
-)
+    d = anchor.d, w = anchor.w,
+    mass_update=False,
+    plot = True)
 
 print('\nCapacity Results:')
-for key, value in anchor.capacity_results.items():
+for key, value in anchor.anchorCapacity.items():
     print(f'{key}: {value:.2f}')
+    
+# --- Step 4: Compute Costs ---     
+anchor.getCost()  
+
+print(f"Mass: {anchor.anchorCapacity['Weight pile']/9.81:.2f} kg")
+print(f"Material unit cost: {anchor.cost['unit_cost']:.2f} USD/kg")
+print(f'Material cost: {anchor.cost["Material cost"]:.2f} USD [2024]')
 
-# --- Step 3: Optimize Anchor Geometry ---
+#%%
+# --- Step 5: Optimize Anchor Geometry ---
 anchor.getSizeAnchor(
     geom = [anchor.dd['design']['L'], anchor.dd['design']['D']],
     geomKeys = ['L', 'D'],
-    geomBounds = [(5.0, 15.0), (2.0, 6.0)],
+    geomBounds = [(5.0, 15.0), (1.0, 4.0)],
     loads = None,
-    minfs = {'Ha': 1.0, 'Va': 1.0},
     lambdap_con = [3, 6],
     zlug_fix = False,
-    plot = True
-)
+    safety_factor = {'SF_horizontal': 2, 'SF_vertical': 3},
+    plot = True)
 
 print('\nFinal Optimized Anchor:')
 print('Design:', anchor.dd['design'])
-print('Capacity Results:', anchor.capacity_results)
+print('Capacity Results:', anchor.anchorCapacity)
+
+# # --- Step 6: Compute Costs ---     
+anchor.getCost()  
+
+print(f"Mass: {anchor.anchorCapacity['Weight pile']/9.81:.2f} kg")
+print(f"Material unit cost: {anchor.cost['unit_cost']:.2f} USD/kg")
+print(f'Material cost: {anchor.cost["Material cost"]:.2f} USD [2024]')
 
-# --- Step 4: Visualize Anchor Geometry ---
-anchor.getCombinedPlot()
+# --- Step 7: Visualize Anchor Geometry ---
+# anchor.getCombinedPlot()
diff --git a/famodel/anchors/getCapacityTorpedo_map.py b/examples/05_Anchors/anchor_torpedo.py
similarity index 85%
rename from famodel/anchors/getCapacityTorpedo_map.py
rename to examples/05_Anchors/anchor_torpedo.py
index 6ecb01cb..9201f289 100644
--- a/famodel/anchors/getCapacityTorpedo_map.py
+++ b/examples/05_Anchors/anchor_torpedo.py
@@ -1,6 +1,6 @@
 
-from anchor_map import Anchor
-from famodel.anchors.anchors_famodel_map.capacity_plots_map import plot_load
+from famodel.anchors.anchor import Anchor
+from famodel.anchors.anchors_famodel.support_plots import plot_load
 
 # --- Define soil profile ---
 profile_map = [
@@ -10,7 +10,7 @@
         'layers': [
             {'top':  0.0, 'bottom': 20.0, 'soil_type': 'clay', 'gamma_top': 8.0, 'gamma_bot': 8.5, 'Su_top':  50, 'Su_bot':  70},
             {'top': 20.0, 'bottom': 25.0, 'soil_type': 'clay', 'gamma_top': 8.5, 'gamma_bot': 8.5, 'Su_top':  80, 'Su_bot': 100},
-            {'top': 25.0, 'bottom': 50.0, 'soil_type': 'clay', 'gamma_top': 8.5, 'gamma_bot': 9.0, 'Su_top': 125, 'Su_bot': 150}
+            {'top': 25.0, 'bottom': 50.0, 'soil_type': 'clay', 'gamma_top': 8.5, 'gamma_bot': 9.0, 'Su_top': 100, 'Su_bot': 150}
         ]
     }
 ]
@@ -24,7 +24,7 @@
             'D2': 1.5,     # Shaft diameter
             'L1': 11.0,    # Winged section length
             'L2': 5.0,     # Shaft section length
-            'zlug': 20.0,  # Padeye depth
+            'zlug': 15.0,  # Padeye depth
             'ballast': 10000
         }
     },
@@ -71,7 +71,7 @@
 )
 
 print('\nCapacity Results:')
-for key, value in anchor.capacity_results.items():
+for key, value in anchor.anchorCapacity.items():
     print(f'{key}: {value:.2f}')
 
 
@@ -84,15 +84,14 @@
     geomKeys = ['L1', 'D1'],
     geomBounds = [(7.0, 25.0), (2.5, 4.5)],
     loads = None,
-    minfs = {'Ha': 1.0, 'Va': 1.0},
     lambdap_con = [2, 8],
     zlug_fix = True,
-    plot = True
-)
+    safety_factor = {'SF_combined': 1},
+    plot = True)
 
 print('\nFinal Optimized Anchor:')
 print('Design:', anchor.dd['design'])
-print('Capacity Results:', anchor.capacity_results)
+print('Capacity Results:', anchor.anchorCapacity)
 
 # --- Step 4: Visualize Anchor Geometry ---
 # anchor.getCombinedPlot()
diff --git a/examples/05_Anchors/example_suction.ipynb b/examples/05_Anchors/example_suction.ipynb
new file mode 100644
index 00000000..34149187
--- /dev/null
+++ b/examples/05_Anchors/example_suction.ipynb
@@ -0,0 +1,544 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "ef2db749",
+   "metadata": {},
+   "source": [
+    "# Suction Anchor Capacity – Jupyter Notebook"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cf0c1c98",
+   "metadata": {},
+   "source": [
+    "### Step 1: Import required libraries\n",
+    "\n",
+    "We begin by importing the essential modules:\n",
+    "\n",
+    "- `Anchor` from `famodel.anchors.anchor`: the main class that encapsulates the suction anchor's capacity methods - soil properties, anchor geometry and extreme loads.\n",
+    "- `plot_suction` from `famodel.anchors.anchors_famodel.capacity_plots`: a custom plotting utility that visualizes anchor geometry and soil properties.\n",
+    "\n",
+    "These imports set up the environment to define, simulate, and visualize the anchor system."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "9f2d8d4b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from famodel.anchors.anchor import Anchor\n",
+    "from famodel.anchors.anchors_famodel.support_plots import plot_suction"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b84ceffb",
+   "metadata": {},
+   "source": [
+    "### Step 2: Define the layered soil profile map\n",
+    "We create a list of CPT locations in the vertices of a 500x500 m square within the Lease Area, each with a set of layered clay soil parameters."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "935551c4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "profile_map = [\n",
+    "    {\n",
+    "        'name': 'CPT_A1',\n",
+    "        'x': 0.0, 'y': 0.0,\n",
+    "        'layers': [\n",
+    "            {'top':  2.0, 'bottom':  4.0, 'soil_type': 'clay', 'gamma_top': 8.0, 'gamma_bot': 8.5, 'Su_top':  10, 'Su_bot':  25},\n",
+    "            {'top':  4.0, 'bottom':  6.0, 'soil_type': 'clay', 'gamma_top': 8.5, 'gamma_bot': 9.0, 'Su_top':  25, 'Su_bot':  50},\n",
+    "            {'top':  6.0, 'bottom': 16.0, 'soil_type': 'clay', 'gamma_top': 9.0, 'gamma_bot': 9.5, 'Su_top':  50, 'Su_bot': 100},\n",
+    "            {'top': 16.0, 'bottom': 25.0, 'soil_type': 'clay', 'gamma_top': 9.5, 'gamma_bot': 9.5, 'Su_top': 100, 'Su_bot': 100}\n",
+    "        ]\n",
+    "    },\n",
+    "    {\n",
+    "        'name': 'CPT_B1',\n",
+    "        'x': 500.0, 'y': 0.0,\n",
+    "        'layers': [\n",
+    "            {'top':  2.0, 'bottom':  4.0, 'soil_type': 'clay', 'gamma_top':  8.5, 'gamma_bot':  9.0, 'Su_top':  15, 'Su_bot':  30},\n",
+    "            {'top':  4.0, 'bottom':  6.0, 'soil_type': 'clay', 'gamma_top':  9.0, 'gamma_bot':  9.5, 'Su_top':  30, 'Su_bot':  55},\n",
+    "            {'top':  6.0, 'bottom': 16.0, 'soil_type': 'clay', 'gamma_top':  9.5, 'gamma_bot': 10.0, 'Su_top':  55, 'Su_bot': 105},\n",
+    "            {'top': 16.0, 'bottom': 25.0, 'soil_type': 'clay', 'gamma_top': 10.0, 'gamma_bot': 10.0, 'Su_top': 105, 'Su_bot': 105}\n",
+    "        ]\n",
+    "    },\n",
+    "    {\n",
+    "        'name': 'CPT_A2',\n",
+    "        'x': 0.0, 'y': 500.0,\n",
+    "        'layers': [\n",
+    "            {'top':  2.0, 'bottom':  4.0, 'soil_type': 'clay', 'gamma_top': 7.5, 'gamma_bot': 8.0, 'Su_top':  5, 'Su_bot': 20},\n",
+    "            {'top':  4.0, 'bottom':  8.0, 'soil_type': 'clay', 'gamma_top': 8.0, 'gamma_bot': 8.5, 'Su_top': 20, 'Su_bot': 45},\n",
+    "            {'top':  8.0, 'bottom': 16.0, 'soil_type': 'clay', 'gamma_top': 8.5, 'gamma_bot': 9.0, 'Su_top': 45, 'Su_bot': 95},\n",
+    "            {'top': 16.0, 'bottom': 25.0, 'soil_type': 'clay', 'gamma_top': 9.0, 'gamma_bot': 9.0, 'Su_top': 95, 'Su_bot': 95}\n",
+    "        ]\n",
+    "    },\n",
+    "    {\n",
+    "        'name': 'CPT_B2',\n",
+    "        'x': 500.0, 'y': 500.0,\n",
+    "        'layers': [\n",
+    "            {'top':  1.0, 'bottom':  2.0, 'soil_type': 'clay', 'gamma_top':  9.0, 'gamma_bot':  9.5, 'Su_top':  20, 'Su_bot':  35},\n",
+    "            {'top':  2.0, 'bottom':  8.0, 'soil_type': 'clay', 'gamma_top':  9.5, 'gamma_bot': 10.0, 'Su_top':  35, 'Su_bot':  60},\n",
+    "            {'top':  8.0, 'bottom': 16.0, 'soil_type': 'clay', 'gamma_top': 10.0, 'gamma_bot': 10.5, 'Su_top':  60, 'Su_bot': 110},\n",
+    "            {'top': 16.0, 'bottom': 25.0, 'soil_type': 'clay', 'gamma_top': 10.5, 'gamma_bot': 10.5, 'Su_top': 110, 'Su_bot': 110}\n",
+    "        ]\n",
+    "    }\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6d32c699",
+   "metadata": {},
+   "source": [
+    "### Step 3: Initialize the anchor object\n",
+    "We define a suction anchor with its type, initial geometry and anchor location within the defined area."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "3aab0b15",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "zlug: 8.67\n",
+      "L: 12.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "anchor = Anchor(\n",
+    "    dd = {'type': 'suction', 'design': {'D': 2.5, 'L': 12.0, 'zlug': 8.67}},\n",
+    "    r = [250.0, 250.0, 0.0]\n",
+    ")\n",
+    "print('zlug:', anchor.dd['design']['zlug'])\n",
+    "print('L:', anchor.dd['design']['L'])\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c26832ae",
+   "metadata": {},
+   "source": [
+    "### Step 4: Assign soil profile to anchor location\n",
+    "This connects the anchor object to the appropriate CPT soil data based on proximity."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "368fac90",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "zlug: 8.67\n",
+      "L: 12.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "anchor.interpolateSoilProfile(profile_map)\n",
+    "print('zlug:', anchor.dd['design']['zlug'])\n",
+    "print('L:', anchor.dd['design']['L'])\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b7ca698d",
+   "metadata": {},
+   "source": [
+    "### Step 5: Plot suction anchor and soil profile\n",
+    "We represent a suction anchor embedded in the soil."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "71419ebe",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "zlug: 8.67\n",
+      "L: 12.0\n",
+      "{'soil_type': 'clay', 'top': 1.75, 'bottom': 3.5, 'gamma_top': 8.25, 'gamma_bot': 8.75, 'Su_top': 12.5, 'Su_bot': 27.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Access anchor geometrical properties\n",
+    "L = anchor.dd['design']['L']\n",
+    "D = anchor.dd['design']['D']\n",
+    "zlug = anchor.dd['design']['zlug']\n",
+    "print('zlug:', anchor.dd['design']['zlug'])\n",
+    "print('L:', anchor.dd['design']['L'])\n",
+    "# Access matched profile\n",
+    "layers = anchor.soil_profile[0]['layers']\n",
+    "print(layers[0])\n",
+    "z0 = layers[0]['top']  \n",
+    "\n",
+    "plot_suction(layers, L=L, D=D, z0=z0, zlug=zlug)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3d5ee57b",
+   "metadata": {},
+   "source": [
+    "### Step 6: Assign external loads and line properties\n",
+    "We assign horizontal and vertical loads and specify the mooring line type and its physical properties (nominal diameter and weight (N/m))."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "38df38f6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "anchor.loads = {\n",
+    "    'Hm': 3e6,\n",
+    "    'Vm': 2e6\n",
+    "}\n",
+    "anchor.line_type = 'chain'\n",
+    "anchor.d = 0.16\n",
+    "anchor.w = 5000.0\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b70c8102",
+   "metadata": {},
+   "source": [
+    "### Step 7: Compute lug forces\n",
+    "We compute the forces acting at the lug using load, geometry, and soil interaction. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "4ae865bd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Lug Forces Computed:\n",
+      "Ha = 1904935.43 N\n",
+      "Va = 2787196.16 N\n"
+     ]
+    }
+   ],
+   "source": [
+    "layers, Ha, Va = anchor.getLugForces(\n",
+    "    Hm = anchor.loads['Hm'],\n",
+    "    Vm = anchor.loads['Vm'],\n",
+    "    zlug = anchor.dd['design']['zlug'],\n",
+    "    line_type = anchor.line_type,\n",
+    "    d = anchor.d,\n",
+    "    w = anchor.w,\n",
+    "    plot = True\n",
+    ")\n",
+    "\n",
+    "print('\\nLug Forces Computed:')\n",
+    "print(f'Ha = {Ha:.2f} N')\n",
+    "print(f'Va = {Va:.2f} N')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "97f25452",
+   "metadata": {},
+   "source": [
+    "### Step 8: Compute the anchor capacity\n",
+    "This checks whether the current anchor design meets load requirements. Results and plots are printed for reference."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "aea072d6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 600x500 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Capacity Results:\n",
+      "Hmax: 8496895.31\n",
+      "Vmax: 6037871.08\n",
+      "Ha: 1904935.43\n",
+      "Va: 2787196.16\n",
+      "zlug: 8.67\n",
+      "z0: 1.75\n",
+      "UC: 0.01\n",
+      "Weight pile: 457496.77\n",
+      "Initial mass from dd: Not defined\n"
+     ]
+    }
+   ],
+   "source": [
+    "anchor.getCapacityAnchor(\n",
+    "    Hm = anchor.loads['Hm'],\n",
+    "    Vm = anchor.loads['Vm'],\n",
+    "    zlug = anchor.dd['design']['zlug'],\n",
+    "    line_type = anchor.line_type,\n",
+    "    d = anchor.d,\n",
+    "    w = anchor.w,\n",
+    "    plot = True\n",
+    ")\n",
+    "\n",
+    "print('\\nCapacity Results:')\n",
+    "for key, value in anchor.anchorCapacity.items():\n",
+    "    print(f'{key}: {value:.2f}')\n",
+    "print('Initial mass from dd:', anchor.dd['design'].get('mass', 'Not defined'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "052f68ee",
+   "metadata": {},
+   "source": [
+    "### Step 9: Anchor material costs\n",
+    "We assess the cost of the suction pile defined by the manufacturing cost (USD/kg)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "2858630b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Mass: 46635.76 kg\n",
+      "Material unit cost: 10.25 USD/kg\n",
+      "Material cost: 478016.50 USD [2024]\n"
+     ]
+    }
+   ],
+   "source": [
+    "anchor.getCost()\n",
+    "\n",
+    "print(f\"Mass: {anchor.anchorCapacity['Weight pile']/9.81:.2f} kg\")\n",
+    "print(f\"Material unit cost: {anchor.cost['unit_cost']:.2f} USD/kg\")\n",
+    "print(f'Material cost: {anchor.cost[\"Material cost\"]:.2f} USD [2024]')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ec72f15a",
+   "metadata": {},
+   "source": [
+    "### Step 10: Optimize anchor geometry\n",
+    "We optimize anchor length and diameter to ensure capacity requirements are met efficiently within given bounds. Note that a safety factor (SF_combined) = 2 is used in this optimization process. This means that the unity check (UC = 1/SF) equals 0.5. This way the design can accept some extra capacity based on input preference."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "304da340",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[Debug] Anchor type parsed: 'suction'\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 600x500 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Final Optimized Anchor (UC-based):\n",
+      "Design: {'D': 1.427702436403329, 'L': 8.565624503775082, 'zlug': 5.710416335850054}\n",
+      "Capacity Results: {'Hmax': 0.1, 'Vmax': 1719845.4215692256, 'Ha': 2528247.4234612333, 'Va': 2414423.5137604806, 'zlug': 5.710416335850054, 'z0': 1.75, 'UC': 1.0997495198266297e+39, 'Weight pile': 114372.69697445678}\n",
+      "\n",
+      "Final Optimized Anchor:\n",
+      "Design: {'D': 1.427702436403329, 'L': 8.565624503775082, 'zlug': 5.710416335850054}\n",
+      "Capacity Results: {'Hmax': 0.1, 'Vmax': 1719845.4215692256, 'Ha': 2528247.4234612333, 'Va': 2414423.5137604806, 'zlug': 5.710416335850054, 'z0': 1.75, 'UC': 1.0997495198266297e+39, 'Weight pile': 114372.69697445678}\n"
+     ]
+    }
+   ],
+   "source": [
+    "anchor.getSizeAnchor(\n",
+    "    geom = [anchor.dd['design']['L'], anchor.dd['design']['D']],\n",
+    "    geomKeys = ['L', 'D'],\n",
+    "    geomBounds = [(5.0, 15.0), (1.0, 4.0)],\n",
+    "    loads = None,\n",
+    "    lambdap_con = [3, 6],\n",
+    "    zlug_fix = False,\n",
+    "    safety_factor = {'SF_combined': 2},\n",
+    "    plot = True\n",
+    ")\n",
+    "\n",
+    "print('\\nFinal Optimized Anchor:')\n",
+    "print('Design:', anchor.dd['design'])\n",
+    "print('Capacity Results:', anchor.anchorCapacity)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b7c5fff6",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "490a71e1",
+   "metadata": {},
+   "source": [
+    "### Step 11: Optimized anchor material costs\n",
+    "We assess the cost of the optimized suction pile defined by the manufacturing cost (USD/kg)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "a439735f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Mass: 11658.79 kg\n",
+      "Material unit cost: 10.25 USD/kg\n",
+      "Material cost: 119502.56 USD [2024]\n"
+     ]
+    }
+   ],
+   "source": [
+    "anchor.getCost()\n",
+    "\n",
+    "print(f\"Mass: {anchor.anchorCapacity['Weight pile']/9.81:.2f} kg\")\n",
+    "print(f\"Material unit cost: {anchor.cost['unit_cost']:.2f} USD/kg\")\n",
+    "print(f'Material cost: {anchor.cost[\"Material cost\"]:.2f} USD [2024]')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "fam",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/examples/05_Anchors/inputs/GulfOfMaine_bathymetry_100x100.txt b/examples/05_Anchors/inputs/GulfOfMaine_bathymetry_100x100.txt
new file mode 100644
index 00000000..22b0bc97
--- /dev/null
+++ b/examples/05_Anchors/inputs/GulfOfMaine_bathymetry_100x100.txt
@@ -0,0 +1,104 @@
+--- MoorPy Bathymetry Input File ---
+nGridX 100
+nGridY 100
+      -4420.52 -4345.53 -4270.54 -4195.55 -4120.57 -4045.58 -3970.59 -3895.60 -3820.61 -3745.62 -3670.63 -3595.64 -3520.66 -3445.67 -3370.68 -3295.69 -3220.70 -3145.71 -3070.72 -2995.74 -2920.75 -2845.76 -2770.77 -2695.78 -2620.79 -2545.80 -2470.81 -2395.83 -2320.84 -2245.85 -2170.86 -2095.87 -2020.88 -1945.89 -1870.90 -1795.92 -1720.93 -1645.94 -1570.95 -1495.96 -1420.97 -1345.98 -1270.99 -1196.01 -1121.02 -1046.03 -971.04 -896.05 -821.06 -746.07 -671.08 -596.10 -521.11 -446.12 -371.13 -296.14 -221.15 -146.16 -71.17 3.81 78.80 153.79 228.78 303.77 378.76 453.75 528.74 603.72 678.71 753.70 828.69 903.68 978.67 1053.66 1128.64 1203.63 1278.62 1353.61 1428.60 1503.59 1578.58 1653.57 1728.55 1803.54 1878.53 1953.52 2028.51 2103.50 2178.49 2253.48 2328.46 2403.45 2478.44 2553.43 2628.42 2703.41 2778.40 2853.39 2928.37 3003.36 
+-3873.36  176.051  176.899  177.747  178.595  179.442  179.494  178.011  176.528  175.045  173.562  172.871  172.659  172.447  172.235  172.023  172.577  173.212  173.848  174.483  175.080  175.503  175.927  176.350  176.773  176.902  176.690  176.479  176.267  176.056  175.370  174.523  173.676  172.829  172.010  172.221  172.432  172.643  172.854  173.000  173.002  173.004  173.006  173.007  173.256  173.677  174.098  174.519  174.939  174.812  174.602  174.391  174.181  174.003  174.004  174.006  174.007  174.008  174.100  174.310  174.521  174.732  174.942  174.551  173.917  173.282  172.648  172.013  172.426  172.847  173.268  173.689  174.225  175.069  175.914  176.758  177.602  177.745  177.323  176.901  176.479  176.057  175.281  174.435  173.589  172.743  171.946  171.523  171.101  170.678  170.255  169.916  169.705  169.494  169.283  169.072  169.291  169.714  170.137  170.561  170.984 
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+-3733.10  176.888  177.556  178.224  178.892  179.560  179.556  178.253  176.950  175.647  174.344  173.682  173.410  173.138  172.867  172.595  173.087  173.663  174.239  174.814  175.351  175.715  176.078  176.442  176.805  176.930  176.778  176.627  176.475  176.324  175.698  174.911  174.124  173.337  172.573  172.664  172.755  172.846  172.937  173.056  173.237  173.419  173.600  173.782  173.928  174.049  174.170  174.292  174.413  174.402  174.372  174.342  174.311  174.304  174.425  174.546  174.667  174.788  174.896  174.987  175.078  175.169  175.260  174.919  174.405  173.890  173.375  172.861  172.977  173.098  173.220  173.341  173.562  174.046  174.531  175.015  175.500  175.582  175.340  175.097  174.855  174.613  174.017  173.350  172.684  172.018  171.394  171.091  170.788  170.486  170.183  169.964  169.873  169.781  169.690  169.599  169.816  170.179  170.543  170.906  171.270 
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diff --git a/examples/05_Anchors/inputs/GulfOfMaine_soil_layered_100x100.txt b/examples/05_Anchors/inputs/GulfOfMaine_soil_layered_100x100.txt
new file mode 100644
index 00000000..50ba5b79
--- /dev/null
+++ b/examples/05_Anchors/inputs/GulfOfMaine_soil_layered_100x100.txt
@@ -0,0 +1,112 @@
+--- MoorPy Soil Input File ---
+nGridX 100
+nGridY 100
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+2718.97  pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_2    pro_2    pro_2    pro_2    pro_2    pro_2    pro_2    pro_2    pro_2    pro_2    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_2    pro_2    pro_2    pro_2    pro_2    pro_2    pro_2    pro_2    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_0    pro_0    pro_0    pro_0    pro_0   
+2789.10  pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_2    pro_2    pro_2    pro_2    pro_2    pro_2    pro_2    pro_2    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_2    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_0    pro_0    pro_0    pro_0    pro_0   
+2859.23  pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_2    pro_2    pro_2    pro_2    pro_2    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_0    pro_0    pro_0    pro_0    pro_0   
+2929.37  pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_2    pro_2    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_0    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_0    pro_0    pro_0    pro_0    pro_0   
+2999.50  pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_0    pro_0    pro_0    pro_0    pro_0    pro_0    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_0    pro_0    pro_0    pro_0    pro_0   
+3069.63  pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_0    pro_0    pro_0    pro_0    pro_0    pro_0    pro_0    pro_0    pro_0    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_0    pro_0    pro_0    pro_0    pro_0   
+--- SOIL TYPES ---
+Class 		 gamma 	  Su0 	  k	   alpha	phi	   UCS	   Em
+(name) 		(kN/m^3) (kPa) 	(kPa/m) (-)    (deg)  (MPa)   (MPa)
+pro_0         8.00   14.0    2.8    0.7     -       -       -
+pro_1         8.00   12.0    2.4    0.7     -       -       -
+pro_2         8.00   10.0    2.0    0.7     -       -       -
+pro_3         8.00    8.0    1.6    0.7     -       -       -
+pro_4         8.00    6.0    1.2    0.7     -       -       -
\ No newline at end of file
diff --git a/examples/05_Anchors/inputs/GulfOfMaine_soil_profiles.yaml b/examples/05_Anchors/inputs/GulfOfMaine_soil_profiles.yaml
new file mode 100644
index 00000000..d0308033
--- /dev/null
+++ b/examples/05_Anchors/inputs/GulfOfMaine_soil_profiles.yaml
@@ -0,0 +1,116 @@
+pro_0:
+  layers:
+    - soil_type: clay
+      top: 0
+      bottom: 12
+      gamma_top: 8.0
+      gamma_bot: 8.0
+      Su_top: 10.0
+      Su_bot: 20.0
+    - soil_type: clay
+      top: 12
+      bottom: 22
+      gamma_top: 8.0
+      gamma_bot: 8.0
+      Su_top: 15.0
+      Su_bot: 25.0
+    - soil_type: clay
+      top: 22
+      bottom: 30
+      gamma_top: 8.0
+      gamma_bot: 8.0
+      Su_top: 55.0
+      Su_bot: 70.0
+pro_1:
+  layers:
+    - soil_type: clay
+      top: 0
+      bottom: 5
+      gamma_top: 8.2
+      gamma_bot: 8.2
+      Su_top: 12.0
+      Su_bot: 22.0
+    - soil_type: clay
+      top: 5
+      bottom: 15
+      gamma_top: 8.0
+      gamma_bot: 8.0
+      Su_top: 22.0
+      Su_bot: 22.0
+    - soil_type: clay
+      top: 15
+      bottom: 30
+      gamma_top: 8.0
+      gamma_bot: 8.0
+      Su_top: 22.0
+      Su_bot: 50.0
+pro_2:
+  layers:
+    - soil_type: clay
+      top: 0
+      bottom: 8
+      gamma_top: 8.4
+      gamma_bot: 8.4
+      Su_top: 14.0
+      Su_bot: 14.0
+    - soil_type: clay
+      top: 8
+      bottom: 18
+      gamma_top: 8.4
+      gamma_bot: 8.4
+      Su_top: 15.0
+      Su_bot: 25.0
+    - soil_type: clay
+      top: 18
+      bottom: 30
+      gamma_top: 8.0
+      gamma_bot: 8.0
+      Su_top: 25.0
+      Su_bot: 25.0
+
+pro_3:
+  layers:
+    - soil_type: clay
+      top: 0
+      bottom: 15
+      gamma_top: 8.6
+      gamma_bot: 8.6
+      Su_top: 20.0
+      Su_bot: 26.0
+    - soil_type: clay
+      top: 15
+      bottom: 25
+      gamma_top: 8.6
+      gamma_bot: 8.6
+      Su_top: 20.0
+      Su_bot: 40.0
+    - soil_type: clay
+      top: 25
+      bottom: 30
+      gamma_top: 8.0
+      gamma_bot: 8.0
+      Su_top: 40.0
+      Su_bot: 40.0
+pro_4:
+  layers:
+    - soil_type: clay
+      top: 0
+      bottom: 3
+      gamma_top: 8.8
+      gamma_bot: 8.8
+      Su_top: 10.0
+      Su_bot: 10.0
+    - soil_type: clay
+      top: 3
+      bottom: 10
+      gamma_top: 8.8
+      gamma_bot: 8.8
+      Su_top: 16.0
+      Su_bot: 40.0
+    - soil_type: clay
+      top: 10
+      bottom: 30
+      gamma_top: 8.8
+      gamma_bot: 8.8
+      Su_top: 40.0
+      Su_bot: 60.0
\ No newline at end of file
diff --git a/examples/GulfOfMaine_bathymetry_100x100.txt b/examples/GulfOfMaine_bathymetry_100x100.txt
new file mode 100644
index 00000000..22b0bc97
--- /dev/null
+++ b/examples/GulfOfMaine_bathymetry_100x100.txt
@@ -0,0 +1,104 @@
+--- MoorPy Bathymetry Input File ---
+nGridX 100
+nGridY 100
+      -4420.52 -4345.53 -4270.54 -4195.55 -4120.57 -4045.58 -3970.59 -3895.60 -3820.61 -3745.62 -3670.63 -3595.64 -3520.66 -3445.67 -3370.68 -3295.69 -3220.70 -3145.71 -3070.72 -2995.74 -2920.75 -2845.76 -2770.77 -2695.78 -2620.79 -2545.80 -2470.81 -2395.83 -2320.84 -2245.85 -2170.86 -2095.87 -2020.88 -1945.89 -1870.90 -1795.92 -1720.93 -1645.94 -1570.95 -1495.96 -1420.97 -1345.98 -1270.99 -1196.01 -1121.02 -1046.03 -971.04 -896.05 -821.06 -746.07 -671.08 -596.10 -521.11 -446.12 -371.13 -296.14 -221.15 -146.16 -71.17 3.81 78.80 153.79 228.78 303.77 378.76 453.75 528.74 603.72 678.71 753.70 828.69 903.68 978.67 1053.66 1128.64 1203.63 1278.62 1353.61 1428.60 1503.59 1578.58 1653.57 1728.55 1803.54 1878.53 1953.52 2028.51 2103.50 2178.49 2253.48 2328.46 2403.45 2478.44 2553.43 2628.42 2703.41 2778.40 2853.39 2928.37 3003.36 
+-3873.36  176.051  176.899  177.747  178.595  179.442  179.494  178.011  176.528  175.045  173.562  172.871  172.659  172.447  172.235  172.023  172.577  173.212  173.848  174.483  175.080  175.503  175.927  176.350  176.773  176.902  176.690  176.479  176.267  176.056  175.370  174.523  173.676  172.829  172.010  172.221  172.432  172.643  172.854  173.000  173.002  173.004  173.006  173.007  173.256  173.677  174.098  174.519  174.939  174.812  174.602  174.391  174.181  174.003  174.004  174.006  174.007  174.008  174.100  174.310  174.521  174.732  174.942  174.551  173.917  173.282  172.648  172.013  172.426  172.847  173.268  173.689  174.225  175.069  175.914  176.758  177.602  177.745  177.323  176.901  176.479  176.057  175.281  174.435  173.589  172.743  171.946  171.523  171.101  170.678  170.255  169.916  169.705  169.494  169.283  169.072  169.291  169.714  170.137  170.561  170.984 
+-3803.23  176.470  177.228  177.985  178.743  179.501  179.525  178.132  176.739  175.346  173.953  173.276  173.035  172.793  172.551  172.309  172.832  173.438  174.043  174.649  175.215  175.609  176.002  176.396  176.789  176.916  176.734  176.553  176.371  176.190  175.534  174.717  173.900  173.083  172.291  172.443  172.594  172.745  172.895  173.028  173.120  173.211  173.303  173.395  173.592  173.863  174.134  174.405  174.676  174.607  174.487  174.367  174.246  174.153  174.215  174.276  174.337  174.398  174.498  174.649  174.799  174.950  175.101  174.735  174.161  173.586  173.012  172.437  172.702  172.973  173.244  173.515  173.893  174.558  175.222  175.887  176.551  176.663  176.331  175.999  175.667  175.335  174.649  173.893  173.137  172.381  171.670  171.307  170.945  170.582  170.219  169.940  169.789  169.638  169.486  169.335  169.553  169.947  170.340  170.734  171.127 
+-3733.10  176.888  177.556  178.224  178.892  179.560  179.556  178.253  176.950  175.647  174.344  173.682  173.410  173.138  172.867  172.595  173.087  173.663  174.239  174.814  175.351  175.715  176.078  176.442  176.805  176.930  176.778  176.627  176.475  176.324  175.698  174.911  174.124  173.337  172.573  172.664  172.755  172.846  172.937  173.056  173.237  173.419  173.600  173.782  173.928  174.049  174.170  174.292  174.413  174.402  174.372  174.342  174.311  174.304  174.425  174.546  174.667  174.788  174.896  174.987  175.078  175.169  175.260  174.919  174.405  173.890  173.375  172.861  172.977  173.098  173.220  173.341  173.562  174.046  174.531  175.015  175.500  175.582  175.340  175.097  174.855  174.613  174.017  173.350  172.684  172.018  171.394  171.091  170.788  170.486  170.183  169.964  169.873  169.781  169.690  169.599  169.816  170.179  170.543  170.906  171.270 
+-3662.97  177.307  177.885  178.463  179.041  179.619  179.588  178.374  177.161  175.948  174.735  174.088  173.786  173.484  173.182  172.881  173.343  173.889  174.434  174.980  175.487  175.820  176.154  176.488  176.821  176.944  176.822  176.700  176.579  176.457  175.862  175.105  174.348  173.591  172.854  172.885  172.916  172.947  172.978  173.083  173.355  173.626  173.897  174.169  174.264  174.235  174.207  174.178  174.150  174.198  174.257  174.317  174.376  174.454  174.635  174.816  174.997  175.178  175.295  175.326  175.356  175.387  175.418  175.103  174.649  174.194  173.739  173.284  173.253  173.224  173.195  173.167  173.230  173.534  173.839  174.144  174.449  174.500  174.348  174.196  174.044  173.891  173.385  172.808  172.232  171.656  171.118  170.875  170.632  170.389  170.146  169.988  169.956  169.925  169.894  169.862  170.079  170.412  170.745  171.079  171.412 
+-3592.83  177.725  178.213  178.702  179.190  179.678  179.619  178.495  177.372  176.249  175.126  174.494  174.162  173.830  173.498  173.166  173.599  174.114  174.630  175.146  175.623  175.926  176.230  176.534  176.837  176.958  176.866  176.774  176.683  176.591  176.026  175.299  174.572  173.845  173.135  173.106  173.078  173.049  173.020  173.111  173.472  173.833  174.195  174.556  174.600  174.422  174.243  174.065  173.887  173.993  174.142  174.292  174.441  174.605  174.846  175.086  175.327  175.568  175.693  175.664  175.635  175.606  175.577  175.287  174.893  174.498  174.103  173.708  173.528  173.350  173.171  172.993  172.897  173.022  173.148  173.273  173.398  173.419  173.357  173.294  173.232  173.170  172.753  172.266  171.780  171.294  170.843  170.660  170.476  170.293  170.110  170.011  170.040  170.069  170.097  170.126  170.341  170.645  170.948  171.252  171.555 
+-3522.70  178.144  178.542  178.941  179.339  179.737  179.650  178.616  177.583  176.550  175.516  174.899  174.538  174.176  173.814  173.452  173.854  174.340  174.826  175.311  175.758  176.032  176.306  176.579  176.853  176.971  176.910  176.848  176.786  176.725  176.190  175.493  174.796  174.098  173.416  173.328  173.239  173.150  173.062  173.138  173.589  174.041  174.492  174.943  174.936  174.608  174.280  173.952  173.624  173.788  174.028  174.267  174.506  174.755  175.056  175.357  175.658  175.958  176.091  176.002  175.913  175.825  175.736  175.471  175.137  174.802  174.467  174.132  173.804  173.475  173.147  172.819  172.565  172.511  172.456  172.401  172.347  172.338  172.365  172.393  172.420  172.448  172.121  171.724  171.328  170.931  170.567  170.444  170.321  170.197  170.074  170.035  170.124  170.212  170.301  170.389  170.604  170.877  171.151  171.424  171.698 
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diff --git a/examples/GulfOfMaine_soil_layered_100x100.txt b/examples/GulfOfMaine_soil_layered_100x100.txt
new file mode 100644
index 00000000..50ba5b79
--- /dev/null
+++ b/examples/GulfOfMaine_soil_layered_100x100.txt
@@ -0,0 +1,112 @@
+--- MoorPy Soil Input File ---
+nGridX 100
+nGridY 100
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+2929.37  pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_2    pro_2    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_0    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_0    pro_0    pro_0    pro_0    pro_0   
+2999.50  pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_0    pro_0    pro_0    pro_0    pro_0    pro_0    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_0    pro_0    pro_0    pro_0    pro_0   
+3069.63  pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_0    pro_0    pro_0    pro_0    pro_0    pro_0    pro_0    pro_0    pro_0    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_1    pro_0    pro_0    pro_0    pro_0    pro_0   
+--- SOIL TYPES ---
+Class 		 gamma 	  Su0 	  k	   alpha	phi	   UCS	   Em
+(name) 		(kN/m^3) (kPa) 	(kPa/m) (-)    (deg)  (MPa)   (MPa)
+pro_0         8.00   14.0    2.8    0.7     -       -       -
+pro_1         8.00   12.0    2.4    0.7     -       -       -
+pro_2         8.00   10.0    2.0    0.7     -       -       -
+pro_3         8.00    8.0    1.6    0.7     -       -       -
+pro_4         8.00    6.0    1.2    0.7     -       -       -
\ No newline at end of file
diff --git a/examples/GulfOfMaine_soil_profiles.yaml b/examples/GulfOfMaine_soil_profiles.yaml
new file mode 100644
index 00000000..71b43efd
--- /dev/null
+++ b/examples/GulfOfMaine_soil_profiles.yaml
@@ -0,0 +1,67 @@
+pro_0:
+  layers:
+    - soil_type: clay
+      top: 0
+      bottom: 10
+      gamma_top: 8.0
+      gamma_bot: 8.0
+      Su_top: 10.0
+      Su_bot: 20.0
+    - soil_type: clay
+      top: 10
+      bottom: 20
+      gamma_top: 8.0
+      gamma_bot: 8.0
+      Su_top: 15.0
+      Su_bot: 25.0
+pro_1:
+  layers:
+    - soil_type: clay
+      top: 0
+      bottom: 20
+      gamma_top: 8.2
+      gamma_bot: 8.2
+      Su_top: 12.0
+      Su_bot: 22.0
+pro_2:
+  layers:
+    - soil_type: clay
+      top: 0
+      bottom: 5
+      gamma_top: 8.4
+      gamma_bot: 8.4
+      Su_top: 14.0
+      Su_bot: 24.0
+    - soil_type: clay
+      top: 5
+      bottom: 20
+      gamma_top: 8.0
+      gamma_bot: 8.0
+      Su_top: 15.0
+      Su_bot: 25.0
+
+pro_3:
+  layers:
+    - soil_type: clay
+      top: 0
+      bottom: 5
+      gamma_top: 8.6
+      gamma_bot: 8.6
+      Su_top: 16.0
+      Su_bot: 26.0
+    - soil_type: clay
+      top: 5
+      bottom: 20
+      gamma_top: 8.0
+      gamma_bot: 8.0
+      Su_top: 25.0
+      Su_bot: 35.0
+pro_4:
+  layers:
+    - soil_type: clay
+      top: 0
+      bottom: 20
+      gamma_top: 8.8
+      gamma_bot: 8.8
+      Su_top: 18.0
+      Su_bot: 28.0
\ No newline at end of file
diff --git a/examples/GulfOfMaine_soil_uniform_100x100.txt b/examples/GulfOfMaine_soil_uniform_100x100.txt
new file mode 100644
index 00000000..14d5d515
--- /dev/null
+++ b/examples/GulfOfMaine_soil_uniform_100x100.txt
@@ -0,0 +1,112 @@
+--- MoorPy Soil Input File ---
+nGridX 100
+nGridY 100
+        -4420.52 -4345.53 -4270.54 -4195.55 -4120.57 -4045.58 -3970.59 -3895.60 -3820.61 -3745.62 -3670.63 -3595.64 -3520.66 -3445.67 -3370.68 -3295.69 -3220.70 -3145.71 -3070.72 -2995.74 -2920.75 -2845.76 -2770.77 -2695.78 -2620.79 -2545.80 -2470.81 -2395.83 -2320.84 -2245.85 -2170.86 -2095.87 -2020.88 -1945.89 -1870.90 -1795.92 -1720.93 -1645.94 -1570.95 -1495.96 -1420.97 -1345.98 -1270.99 -1196.01 -1121.02 -1046.03 -971.04 -896.05 -821.06 -746.07 -671.08 -596.10 -521.11 -446.12 -371.13 -296.14 -221.15 -146.16 -71.17 3.81 78.80 153.79 228.78 303.77 378.76 453.75 528.74 603.72 678.71 753.70 828.69 903.68 978.67 1053.66 1128.64 1203.63 1278.62 1353.61 1428.60 1503.59 1578.58 1653.57 1728.55 1803.54 1878.53 1953.52 2028.51 2103.50 2178.49 2253.48 2328.46 2403.45 2478.44 2553.43 2628.42 2703.41 2778.40 2853.39 2928.37 3003.36
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+--- SOIL TYPES ---
+Class 		 gamma 	  Su0 	  k	   alpha	phi	   UCS	   Em
+(name) 		(kN/m^3) (kPa) 	(kPa/m) (-)    (deg)  (MPa)   (MPa)
+mud_0         8.00   14.0    2.8    0.7     -       -       -
+mud_1         8.00   12.0    2.4    0.7     -       -       -
+mud_2         8.00   10.0    2.0    0.7     -       -       -
+mud_3         8.00    8.0    1.6    0.7     -       -       -
+mud_4         8.00    6.0    1.2    0.7     -       -       -
\ No newline at end of file
diff --git a/examples/OntologySample200m.yaml b/examples/OntologySample200m.yaml
index 64bcd8f6..c37ab097 100644
--- a/examples/OntologySample200m.yaml
+++ b/examples/OntologySample200m.yaml
@@ -43,23 +43,42 @@ site:
       
       soil_types:  
         mud_soft:
-          Su0 : [2.39]  # [kPa]
-          k : [1.41]    # [kPa/m]
-          gamma : [10]  # [kN/m^3]
-          depth: [0]    # [m]
+            layers: 
+            - soil_type: clay
+              top: 0
+              bottom: 50
+              gamma_top: 10.0
+              gamma_bot: 10.0
+              Su_top: 2.39
+              Su_bot: 59.39
         mud_firm:
-          Su0 : [23.94] # [kPa]
-          k : [2.67]    # [kPa/m]
-          gamma: [15]
-          depth: [0]    # [m]
-        mud_hard:
-          Su0: [50]
-          k: [1.0]
-          gamma: [9.5]
-          depth: [0]  
+            layers:
+            - soil_type: clay            
+              top: 0
+              bottom: 50
+              gamma_top: 10.0
+              gamma_bot: 50.0
+              Su_top: 23.4
+              Su_bot: 157.44
+        mud_hard: 
+            layers:
+            - soil_type: clay            
+              top: 0
+              bottom: 50
+              gamma_top: 8.5
+              gamma_bot: 8.5
+              Su_top: 50.0
+              Su_bot: 100.00  
         rock:
-          UCS: [5] # [MPa]
-          Em: [7] # [MPa]
+            layers:
+            - soil_type: rock
+              top: 0
+              bottom: 50
+              UCS_top: 5.0
+              UCS_bot: 5.0
+              Em_top: 7.0
+              Em_bot: 7.0
+
     
     metocean:
         extremes:  # extreme values for specified return periods (in years)
@@ -331,26 +350,27 @@ mooring_connector_types:
 anchor_types:
 
     drag-embedment1:
-        type   :  DEA   # type of anchor
-        A      :    10 # net area of anchor's fluke [m^2]
-        zlug   :    20 # embedded depth of padeye [m]
+        type   :  DEA  # type of anchor
+        B      :     5 # net area of anchor's fluke [m^2]
+        L      :     2
+        zlug   :    10 # embedded depth of padeye [m]
     suction_pile1:
-        type   :  suction_pile
+        type   :  suction
         L      :     16.4  # length of pile [m]
         D      :     5.45  # diameter of pile [m]
         zlug   :     9.32  # embedded depth of padeye [m]
     dandg_pile1:
-        type   :  dandg_pile
+        type   :  dandg
         L      :     50 # length of pile [m]
         D      :     3 # diameter of pile [m]
         zlug   :     0 # embedded depth [m]
     driven_pile1:
-        type   :  driven_pile
+        type   :  driven
         L      :     20 # pile length [m]
         D      :     1.5 # pile diameter [m]
         zlug   :     3 # embedded depth [m]
     driven_pile2:
-        type   :  driven_pile
+        type   :  driven
         L      :     20 # pile length [m]
         D      :     1.5 # pile diameter [m]
         zlug   :     -3 # embedded depth [m]
@@ -360,14 +380,14 @@ anchor_types:
         zlug : 10
         #beta: 30
     torpedo_pile1:
-        type: torpedo_pile 
+        type: torpedo 
         D1 : 3
         D2: 1.1
         L1: 10
         L2: 4
         zlug: 16
     helical_pile1:
-        type: helical_pile
+        type: helical
         L : 25.1
         d : 1
         D : 5.01
diff --git a/examples/OntologySample200m_1turb.yaml b/examples/OntologySample200m_1turb.yaml
index 3ff93e9e..738755bd 100644
--- a/examples/OntologySample200m_1turb.yaml
+++ b/examples/OntologySample200m_1turb.yaml
@@ -1295,7 +1295,7 @@ anchor_types:
         zlug   :    10 # embedded depth of padeye [m]
 
     suction1:
-        type   :  suction_pile
+        type   :  suction
         L      :     16.4  # length of pile [m]
         D      :     5.45  # diameter of pile [m]
         zlug   :     9.32  # embedded depth of padeye [m]
diff --git a/examples/OntologySample200mbis_1turb.yaml b/examples/OntologySample200mbis_1turb.yaml
new file mode 100644
index 00000000..1cd07b83
--- /dev/null
+++ b/examples/OntologySample200mbis_1turb.yaml
@@ -0,0 +1,1323 @@
+type: draft/example of floating array ontology under construction
+name: 
+comments: 
+# Site condition information
+site:
+    general:
+        water_depth : 200        # [m]      uniform water depth
+        rho_water   : 1025.0     # [kg/m^3] water density
+        rho_air     : 1.225      # [kg/m^3] air density
+        mu_air      : 1.81e-05   #          air dynamic viscosity
+        #...
+        
+    boundaries:  # project or lease area boundary, via file or vertex list
+        file:   # filename of x-y vertex coordinates [m]
+        x_y:    # list of polygon vertices in order [m]
+          - [-3000, -3000]
+          - [-3000, 3000]
+          - [3000, 3000]
+          - [3000, -3000]
+    
+    bathymetry:
+        file:   './bathymetry200m_sample.txt'
+    
+    seabed:
+      x : [-10901,    0,    10000]
+      y : [-10900,     0,  10000 ]
+    
+      type_array:
+        - [mud_soft ,  mud_firm ,   mud_soft]  
+        - [mud_soft ,  mud_firm ,   mud_soft]  
+        - [mud_soft ,  mud_firm ,   mud_soft]
+      
+      soil_types:  
+        mud_soft:
+            layers: 
+            - soil_type: clay
+              top: 0
+              bottom: 50
+              gamma_top: 10.0
+              gamma_bot: 10.0
+              Su_top: 2.39
+              Su_bot: 59.39
+        mud_firm:
+            layers:
+            - soil_type: clay            
+              top: 0
+              bottom: 50
+              gamma_top: 10.0
+              gamma_bot: 50.0
+              Su_top: 23.4
+              Su_bot: 157.44
+        sand_dense:
+            layers:
+            - soil_type: sand
+              top: 0
+              bottom: 20
+              gamma_top: 9.0
+              gamma_bot: 9.0
+              phi_top: 28
+              phi_bot: 33
+              Dr_top: 50
+              Dr_bot: 55
+  
+    metocean:
+        extremes:  # extreme values for specified return periods (in years)
+            keys :   [ Hs  , Tp  , WindSpeed, TI, Shear, Gamma, CurrentSpeed ]
+            data :
+                1:   [   1  ,2     ,3     ]
+                10:  [ 1    ,  2   , 3    ]
+                50:  [  1   ,  2   ,  3   ]
+                500: [  1   ,  2   ,   3  ]
+                
+        probabalistic_bins:
+            keys : [ prob , Hs  , Tp, WindSpeed, TI, Shear, Gamma, CurrentSpeed, WindDir, WaveDir, CurrentDir  ]
+            data :
+                -  [ 0.010  ,  1 ,  1 ]
+                -  [ 0.006  , 1  ,  1 ]
+                -  [ 0.005  , 1  ,  1 ]
+                
+        time_series :
+            file: 'metocean_timeseries.csv'
+            
+    resource :
+        file: 'windresource'
+        
+    RAFT_cases:
+        keys : [wind_speed, wind_heading, turbulence, turbine_status, yaw_misalign, wave_spectrum, wave_period, wave_height, wave_heading  ]
+        data :  #   m/s        deg    % or e.g. IIB_NTM    string            deg         string          (s)         (m)         (deg)
+            -  [     0,         0,            0,          operating,          0,        JONSWAP,         12,         6,           0        ]
+            # -  [    16,         0,            IIB_NTM,    operating,          0,        JONSWAP,         12,         6,           30       ]
+            # -  [    10.59,         0,            0.05,    operating,          0,        JONSWAP,         15.75,         11.86,         0       ]
+
+    RAFT_settings:   
+        min_freq     :  0.001    #  [Hz]       lowest frequency to consider, also the frequency bin width     
+        max_freq     :  0.20    #  [Hz]       highest frequency to consider
+        XiStart      :   0      # sets initial amplitude of each DOF for all frequencies
+        nIter        :   4      # sets how many iterations to perform in Model.solveDynamics()
+# ----- Array-level inputs -----
+
+# Wind turbine array layout
+array:
+    keys : [ID, topsideID, platformID, mooringID,   x_location,     y_location,   heading_adjust]
+    data : #    ID#        ID#        ID#          [m]             [m]           [deg]
+        -  [fowt0,     1,         1,         ms1,          -1600,         -1600,          180   ]    # 2 array, shared moorings
+        # -  [FOWT3,     1,         1,         ms3,          1600,           -1600,            0   ]
+        # -  [FOWT4,     1,         2,         ms4,          -1600,          0,            0   ]
+        # -  [FOWT5,     1,         1,         ms5,          0,              0,            45   ]
+        # -  [FOWT6,     1,         1,         ms10,          1600,              0,            0   ]
+        # -  [FOWT7,     1,         1,         ms6,          -1600,           1600,            0   ]
+        # -  [FOWT8,     1,         1,         ms6,          0,              1600,            0   ]
+        # -  [FOWT9,     1,         1,         ms6,          1600,           1600,            0   ] 
+
+# ----- turbines and platforms -----
+
+topsides:
+        
+  - type          :     turbine
+    mRNA          :     991000        #  [kg]       RNA mass 
+    IxRNA         :          0        #  [kg-m2]    RNA moment of inertia about local x axis (assumed to be identical to rotor axis for now, as approx) [kg-m^2]
+    IrRNA         :          0        #  [kg-m2]    RNA moment of inertia about local y or z axes [kg-m^2]
+    xCG_RNA       :          0        #  [m]        x location of RNA center of mass [m] (Actual is ~= -0.27 m)
+    hHub          :        150.0      #  [m]        hub height above water line [m]
+    Fthrust       :       1500.0E3    #  [N]        temporary thrust force to use
+    
+    I_drivetrain: 318628138.0   # full rotor + drivetrain inertia as felt on the high-speed shaft
+    
+    nBlades     : 3          # number of blades
+    Zhub        : 150.0      # hub height [m]
+    Rhub        : 3.97       # hub radius [m]
+    precone     : 4.0        # [deg]
+    shaft_tilt  : 6.0        # [deg]
+    overhang    : -12.0313    # [m]
+    aeroMod     : 1          # 0 aerodynamics off; 1 aerodynamics on
+
+    
+    blade: 
+        precurveTip : -3.9999999999999964  # 
+        presweepTip : 0.0  # 
+        Rtip        : 120.96999999936446         # rotor radius
+
+        #    r    chord   theta  precurve  presweep  
+        geometry: 
+          - [     8.004,      5.228,     15.474,      0.035,      0.000 ]
+          - [    12.039,      5.321,     14.692,      0.084,      0.000 ]
+          - [    16.073,      5.458,     13.330,      0.139,      0.000 ]
+          - [    20.108,      5.602,     11.644,      0.192,      0.000 ]
+          - [    24.142,      5.718,      9.927,      0.232,      0.000 ]
+          - [    28.177,      5.767,      8.438,      0.250,      0.000 ]
+          - [    32.211,      5.713,      7.301,      0.250,      0.000 ]
+          - [    36.246,      5.536,      6.232,      0.246,      0.000 ]
+          - [    40.280,      5.291,      5.230,      0.240,      0.000 ]
+          - [    44.315,      5.035,      4.348,      0.233,      0.000 ]
+          - [    48.349,      4.815,      3.606,      0.218,      0.000 ]
+          - [    52.384,      4.623,      2.978,      0.178,      0.000 ]
+          - [    56.418,      4.432,      2.423,      0.100,      0.000 ]
+          - [    60.453,      4.245,      1.924,      0.000,      0.000 ]
+          - [    64.487,      4.065,      1.467,     -0.112,      0.000 ]
+          - [    68.522,      3.896,      1.056,     -0.244,      0.000 ]
+          - [    72.556,      3.735,      0.692,     -0.415,      0.000 ]
+          - [    76.591,      3.579,      0.355,     -0.620,      0.000 ]
+          - [    80.625,      3.425,      0.019,     -0.846,      0.000 ]
+          - [    84.660,      3.268,     -0.358,     -1.080,      0.000 ]
+          - [    88.694,      3.112,     -0.834,     -1.330,      0.000 ]
+          - [    92.729,      2.957,     -1.374,     -1.602,      0.000 ]
+          - [    96.763,      2.800,     -1.848,     -1.895,      0.000 ]
+          - [   100.798,      2.637,     -2.136,     -2.202,      0.000 ]
+          - [   104.832,      2.464,     -2.172,     -2.523,      0.000 ]
+          - [   108.867,      2.283,     -2.108,     -2.864,      0.000 ]
+          - [   112.901,      2.096,     -1.953,     -3.224,      0.000 ]
+          - [   116.936,      1.902,     -1.662,     -3.605,      0.000 ]
+        #    station(rel)      airfoil name 
+        airfoils: 
+          - [   0.00000, circular ]
+          - [   0.02000, circular ]
+          - [   0.15000, SNL-FFA-W3-500 ]
+          - [   0.24517, FFA-W3-360 ]
+          - [   0.32884, FFA-W3-330blend ]
+          - [   0.43918, FFA-W3-301 ]
+          - [   0.53767, FFA-W3-270blend ]
+          - [   0.63821, FFA-W3-241 ]
+          - [   0.77174, FFA-W3-211 ]
+          - [   1.00000, FFA-W3-211 ]
+
+
+    airfoils: 
+      - name               : circular  # 
+        relative_thickness : 1.0  # 
+        data:  #  alpha    c_l    c_d     c_m   
+          - [ -179.9087,    0.00010,    0.35000,   -0.00010 ] 
+          - [  179.9087,    0.00010,    0.35000,   -0.00010 ] 
+      - name               : SNL-FFA-W3-500  # 
+        relative_thickness : 0.5  # 
+        data:  #  alpha    c_l    c_d     c_m   
+          - [ -179.9660,    0.00000,    0.08440,    0.00000 ] 
+          - [ -170.0000,    0.44190,    0.08440,    0.31250 ] 
+          - [ -160.0002,    0.88370,    0.12680,    0.28310 ] 
+          - [ -149.9998,    0.96740,    0.29270,    0.26320 ] 
+          - [ -139.9999,    0.78010,    0.49700,    0.20480 ] 
+          - [ -130.0001,    0.62930,    0.71610,    0.19320 ] 
+          - [ -120.0003,    0.47850,    0.92460,    0.20080 ] 
+          - [ -109.9999,    0.31890,    1.09850,    0.21360 ] 
+          - [ -100.0000,    0.15530,    1.21820,    0.22210 ] 
+          - [  -90.0002,    0.00000,    1.27070,    0.21980 ] 
+          - [  -79.9998,   -0.15530,    1.21820,    0.19600 ] 
+          - [  -70.0000,   -0.31890,    1.09850,    0.16350 ] 
+          - [  -60.0001,   -0.47840,    0.92460,    0.12850 ] 
+          - [  -49.9997,   -0.62930,    0.71610,    0.09650 ] 
+          - [  -39.9999,   -0.78010,    0.49700,    0.07160 ] 
+          - [  -30.0001,   -0.96740,    0.29270,    0.05220 ] 
+          - [  -20.0002,   -1.02810,    0.14990,   -0.00630 ] 
+          - [  -19.7499,   -1.02430,    0.14720,   -0.00890 ] 
+          - [  -19.2502,   -1.00520,    0.14470,   -0.00990 ] 
+          - [  -18.9999,   -0.99710,    0.14330,   -0.01050 ] 
+          - [  -18.7500,   -1.00520,    0.14030,   -0.01100 ] 
+          - [  -18.5002,   -0.99950,    0.13860,   -0.01160 ] 
+          - [  -18.2499,   -0.99080,    0.13730,   -0.01200 ] 
+          - [  -18.0000,   -0.98150,    0.13600,   -0.01260 ] 
+          - [  -17.4998,   -0.97640,    0.13220,   -0.01350 ] 
+          - [  -17.2500,   -0.97050,    0.13060,   -0.01390 ] 
+          - [  -17.0002,   -0.96550,    0.12900,   -0.01430 ] 
+          - [  -16.7498,   -0.96620,    0.12680,   -0.01470 ] 
+          - [  -16.5000,   -0.95440,    0.12580,   -0.01510 ] 
+          - [  -16.2502,   -0.94440,    0.12460,   -0.01550 ] 
+          - [  -15.9998,   -0.94050,    0.12290,   -0.01580 ] 
+          - [  -15.7500,   -0.94330,    0.12060,   -0.01610 ] 
+          - [  -15.5002,   -0.93300,    0.11950,   -0.01640 ] 
+          - [  -15.2498,   -0.92110,    0.11850,   -0.01680 ] 
+          - [  -14.7502,   -0.91580,    0.11500,   -0.01730 ] 
+          - [  -14.4998,   -0.90700,    0.11380,   -0.01750 ] 
+          - [  -14.2500,   -0.89590,    0.11270,   -0.01780 ] 
+          - [  -14.0002,   -0.89260,    0.11100,   -0.01810 ] 
+          - [  -13.7498,   -0.88080,    0.11000,   -0.01840 ] 
+          - [  -13.5000,   -0.87220,    0.10890,   -0.01860 ] 
+          - [  -13.2502,   -0.86600,    0.10750,   -0.01880 ] 
+          - [  -12.9998,   -0.86260,    0.10590,   -0.01880 ] 
+          - [  -12.7500,   -0.84890,    0.10510,   -0.01920 ] 
+          - [  -12.5002,   -0.83630,    0.10420,   -0.01940 ] 
+          - [  -12.2498,   -0.83630,    0.10230,   -0.01940 ] 
+          - [  -12.0000,   -0.82710,    0.10130,   -0.01960 ] 
+          - [  -11.7502,   -0.81410,    0.10040,   -0.01980 ] 
+          - [  -11.4998,   -0.80040,    0.09970,   -0.02000 ] 
+          - [  -11.0002,   -0.78900,    0.09710,   -0.01990 ] 
+          - [  -10.7498,   -0.78620,    0.09560,   -0.01960 ] 
+          - [  -10.5000,   -0.77470,    0.09480,   -0.01940 ] 
+          - [  -10.2502,   -0.77010,    0.09400,   -0.01840 ] 
+          - [   -9.9998,   -0.76740,    0.09250,   -0.01830 ] 
+          - [   -9.7500,   -0.75060,    0.09170,   -0.01920 ] 
+          - [   -9.5002,   -0.72900,    0.09120,   -0.02050 ] 
+          - [   -9.2498,   -0.70950,    0.09020,   -0.02240 ] 
+          - [   -9.0000,   -0.68550,    0.08950,   -0.02470 ] 
+          - [   -8.7502,   -0.65900,    0.08910,   -0.02670 ] 
+          - [   -8.4998,   -0.63190,    0.08870,   -0.02870 ] 
+          - [   -8.2500,   -0.60190,    0.08790,   -0.03200 ] 
+          - [   -8.0002,   -0.57180,    0.08750,   -0.03450 ] 
+          - [   -7.7498,   -0.54240,    0.08730,   -0.03670 ] 
+          - [   -7.5000,   -0.50980,    0.08680,   -0.03990 ] 
+          - [   -7.2502,   -0.47670,    0.08640,   -0.04300 ] 
+          - [   -6.9998,   -0.44540,    0.08620,   -0.04530 ] 
+          - [   -6.7500,   -0.41420,    0.08600,   -0.04760 ] 
+          - [   -6.5002,   -0.37910,    0.08560,   -0.05100 ] 
+          - [   -6.2498,   -0.34600,    0.08530,   -0.05380 ] 
+          - [   -6.0000,   -0.31440,    0.08520,   -0.05600 ] 
+          - [   -5.7502,   -0.28170,    0.08500,   -0.05860 ] 
+          - [   -5.4998,   -0.24610,    0.08470,   -0.06190 ] 
+          - [   -5.2500,   -0.21330,    0.08460,   -0.06440 ] 
+          - [   -5.0002,   -0.18270,    0.08450,   -0.06630 ] 
+          - [   -4.7498,   -0.14940,    0.08430,   -0.06880 ] 
+          - [   -4.5000,   -0.11580,    0.08420,   -0.07150 ] 
+          - [   -4.2502,   -0.08370,    0.08400,   -0.07370 ] 
+          - [   -3.9998,   -0.05290,    0.08400,   -0.07560 ] 
+          - [   -3.7500,   -0.02250,    0.08390,   -0.07740 ] 
+          - [   -3.5002,    0.00890,    0.08380,   -0.07930 ] 
+          - [   -3.2498,    0.03920,    0.08380,   -0.08110 ] 
+          - [   -3.0000,    0.06860,    0.08380,   -0.08260 ] 
+          - [   -2.7502,    0.09740,    0.08380,   -0.08380 ] 
+          - [   -2.4998,    0.12600,    0.08380,   -0.08520 ] 
+          - [   -2.2500,    0.15550,    0.08380,   -0.08670 ] 
+          - [   -2.0002,    0.18530,    0.08380,   -0.08830 ] 
+          - [   -1.7498,    0.21460,    0.08370,   -0.08970 ] 
+          - [   -1.5000,    0.24300,    0.08370,   -0.09100 ] 
+          - [   -1.2502,    0.27130,    0.08380,   -0.09210 ] 
+          - [   -0.9998,    0.30060,    0.08380,   -0.09360 ] 
+          - [   -0.7500,    0.32950,    0.08380,   -0.09490 ] 
+          - [   -0.5002,    0.35780,    0.08380,   -0.09610 ] 
+          - [   -0.2498,    0.38570,    0.08380,   -0.09720 ] 
+          - [    0.0000,    0.41350,    0.08380,   -0.09830 ] 
+          - [    0.2298,    0.44250,    0.08390,   -0.09950 ] 
+          - [    0.4698,    0.47150,    0.08390,   -0.10080 ] 
+          - [    0.7002,    0.50030,    0.08390,   -0.10190 ] 
+          - [    0.9402,    0.52860,    0.08400,   -0.10290 ] 
+          - [    1.1700,    0.55670,    0.08400,   -0.10400 ] 
+          - [    1.3997,    0.58500,    0.08410,   -0.10500 ] 
+          - [    1.6398,    0.61350,    0.08410,   -0.10610 ] 
+          - [    1.8701,    0.64170,    0.08420,   -0.10720 ] 
+          - [    2.1102,    0.66970,    0.08420,   -0.10820 ] 
+          - [    2.3400,    0.69750,    0.08430,   -0.10910 ] 
+          - [    2.5697,    0.72510,    0.08430,   -0.11000 ] 
+          - [    2.8098,    0.75280,    0.08440,   -0.11090 ] 
+          - [    3.0401,    0.78070,    0.08450,   -0.11190 ] 
+          - [    3.2802,    0.80830,    0.08460,   -0.11280 ] 
+          - [    3.5099,    0.83580,    0.08460,   -0.11370 ] 
+          - [    3.7403,    0.86310,    0.08470,   -0.11460 ] 
+          - [    3.9798,    0.89020,    0.08470,   -0.11530 ] 
+          - [    4.2101,    0.91730,    0.08480,   -0.11610 ] 
+          - [    4.4502,    0.94440,    0.08490,   -0.11700 ] 
+          - [    4.6799,    0.97130,    0.08500,   -0.11780 ] 
+          - [    4.9102,    0.99810,    0.08510,   -0.11850 ] 
+          - [    5.1497,    1.02490,    0.08520,   -0.11920 ] 
+          - [    5.3801,    1.05150,    0.08530,   -0.11990 ] 
+          - [    5.6201,    1.07790,    0.08530,   -0.12060 ] 
+          - [    5.8499,    1.10410,    0.08540,   -0.12120 ] 
+          - [    6.0802,    1.13020,    0.08560,   -0.12180 ] 
+          - [    6.3197,    1.15600,    0.08570,   -0.12240 ] 
+          - [    6.5501,    1.18180,    0.08580,   -0.12300 ] 
+          - [    6.7901,    1.20760,    0.08590,   -0.12350 ] 
+          - [    7.0199,    1.23340,    0.08600,   -0.12400 ] 
+          - [    7.2502,    1.25890,    0.08610,   -0.12450 ] 
+          - [    7.4903,    1.28410,    0.08620,   -0.12500 ] 
+          - [    7.7200,    1.30880,    0.08640,   -0.12540 ] 
+          - [    7.9601,    1.33310,    0.08650,   -0.12570 ] 
+          - [    8.1899,    1.35700,    0.08670,   -0.12590 ] 
+          - [    8.4202,    1.38100,    0.08690,   -0.12620 ] 
+          - [    8.6603,    1.40540,    0.08700,   -0.12650 ] 
+          - [    8.8900,    1.42950,    0.08710,   -0.12670 ] 
+          - [    9.1198,    1.45310,    0.08730,   -0.12700 ] 
+          - [    9.8801,    1.51540,    0.08790,   -0.12650 ] 
+          - [   10.6398,    1.57490,    0.08860,   -0.12560 ] 
+          - [   11.4001,    1.61510,    0.08950,   -0.12140 ] 
+          - [   12.1501,    1.64430,    0.09120,   -0.11630 ] 
+          - [   12.9099,    1.68240,    0.09300,   -0.11330 ] 
+          - [   13.6702,    1.71460,    0.09540,   -0.11070 ] 
+          - [   14.4202,    1.73620,    0.09890,   -0.10800 ] 
+          - [   15.1799,    1.76270,    0.10240,   -0.10630 ] 
+          - [   15.9403,    1.77060,    0.10760,   -0.10420 ] 
+          - [   16.6903,    1.76390,    0.11440,   -0.10250 ] 
+          - [   17.4500,    1.76040,    0.12110,   -0.10130 ] 
+          - [   18.2097,    1.72510,    0.13100,   -0.10010 ] 
+          - [   18.9701,    1.70350,    0.13990,   -0.09980 ] 
+          - [   19.7201,    1.67840,    0.14920,   -0.10010 ] 
+          - [   20.4798,    1.65050,    0.15910,   -0.10160 ] 
+          - [   21.2401,    1.62270,    0.16910,   -0.10360 ] 
+          - [   21.9901,    1.60670,    0.17780,   -0.10640 ] 
+          - [   22.7499,    1.59720,    0.18580,   -0.10990 ] 
+          - [   23.5102,    1.58920,    0.19370,   -0.11360 ] 
+          - [   24.2602,    1.58150,    0.20140,   -0.11800 ] 
+          - [   25.0199,    1.55630,    0.21350,   -0.12490 ] 
+          - [   25.7802,    1.52720,    0.22670,   -0.13250 ] 
+          - [   26.5302,    1.49820,    0.23990,   -0.14000 ] 
+          - [   27.2900,    1.46910,    0.25310,   -0.14760 ] 
+          - [   28.0497,    1.44010,    0.26630,   -0.15510 ] 
+          - [   28.8100,    1.41100,    0.27950,   -0.16270 ] 
+          - [   29.5600,    1.38200,    0.29270,   -0.17030 ] 
+          - [   30.3198,    1.36220,    0.30780,   -0.17400 ] 
+          - [   31.0801,    1.34240,    0.32300,   -0.17770 ] 
+          - [   31.8301,    1.32250,    0.33810,   -0.18150 ] 
+          - [   32.5898,    1.30270,    0.35320,   -0.18520 ] 
+          - [   33.3502,    1.28290,    0.36840,   -0.18890 ] 
+          - [   34.1002,    1.26310,    0.38350,   -0.19260 ] 
+          - [   34.8599,    1.24330,    0.39870,   -0.19640 ] 
+          - [   35.6202,    1.22340,    0.41380,   -0.20010 ] 
+          - [   36.3800,    1.20360,    0.42890,   -0.20390 ] 
+          - [   37.1300,    1.18380,    0.44410,   -0.20760 ] 
+          - [   37.8903,    1.16400,    0.45920,   -0.21130 ] 
+          - [   38.6500,    1.14420,    0.47430,   -0.21500 ] 
+          - [   39.4000,    1.12430,    0.48950,   -0.21880 ] 
+          - [   40.1598,    1.10640,    0.50520,   -0.22180 ] 
+          - [   40.9201,    1.09050,    0.52140,   -0.22420 ] 
+          - [   41.6701,    1.07450,    0.53760,   -0.22660 ] 
+          - [   42.4298,    1.05860,    0.55380,   -0.22890 ] 
+          - [   43.1901,    1.04260,    0.57010,   -0.23130 ] 
+          - [   43.9401,    1.02670,    0.58630,   -0.23370 ] 
+          - [   44.6999,    1.01070,    0.60250,   -0.23610 ] 
+          - [   45.4602,    0.99480,    0.61880,   -0.23840 ] 
+          - [   46.2199,    0.97880,    0.63500,   -0.24080 ] 
+          - [   46.9699,    0.96280,    0.65120,   -0.24320 ] 
+          - [   47.7302,    0.94690,    0.66750,   -0.24550 ] 
+          - [   48.4900,    0.93090,    0.68370,   -0.24790 ] 
+          - [   49.2400,    0.91500,    0.69990,   -0.25030 ] 
+          - [   49.9997,    0.89900,    0.71610,   -0.25270 ] 
+          - [   60.0001,    0.68360,    0.92460,   -0.28330 ] 
+          - [   70.0000,    0.45560,    1.09850,   -0.31560 ] 
+          - [   79.9998,    0.22190,    1.21820,   -0.34820 ] 
+          - [   90.0002,    0.00000,    1.27070,   -0.37730 ] 
+          - [  100.0000,   -0.15530,    1.21820,   -0.38770 ] 
+          - [  109.9999,   -0.31890,    1.09850,   -0.38650 ] 
+          - [  120.0003,   -0.47840,    0.92460,   -0.38060 ] 
+          - [  130.0001,   -0.62930,    0.71610,   -0.38030 ] 
+          - [  139.9999,   -0.78010,    0.49700,   -0.40320 ] 
+          - [  149.9998,   -0.96740,    0.29270,   -0.48540 ] 
+          - [  160.0002,   -0.88370,    0.12680,   -0.53250 ] 
+          - [  170.0000,   -0.44180,    0.08440,   -0.39060 ] 
+          - [  179.9660,    0.00000,    0.08440,    0.00000 ] 
+      - name               : FFA-W3-211  # 
+        relative_thickness : 0.211  # 
+        data:  #  alpha    c_l    c_d     c_m   
+          - [ -179.9087,    0.00000,    0.02464,    0.00000 ] 
+          - [ -177.7143,    0.05403,    0.02534,    0.09143 ] 
+          - [ -175.4286,    0.10805,    0.02742,    0.18286 ] 
+          - [ -173.1429,    0.16208,    0.03088,    0.27429 ] 
+          - [ -170.8572,    0.21610,    0.03570,    0.36571 ] 
+          - [ -168.5716,    0.27013,    0.05599,    0.39192 ] 
+          - [ -166.2857,    0.32415,    0.08143,    0.37898 ] 
+          - [ -164.0000,    0.37818,    0.11112,    0.36605 ] 
+          - [ -161.7145,    0.43220,    0.14485,    0.35312 ] 
+          - [ -159.4284,    0.48623,    0.18242,    0.34768 ] 
+          - [ -157.1428,    0.54025,    0.22359,    0.36471 ] 
+          - [ -154.8573,    0.59428,    0.26810,    0.38175 ] 
+          - [ -152.5714,    0.64830,    0.31566,    0.39878 ] 
+          - [ -150.2857,    0.70233,    0.36597,    0.41581 ] 
+          - [ -148.0000,    0.75635,    0.41871,    0.41955 ] 
+          - [ -143.8571,    0.73188,    0.51941,    0.42287 ] 
+          - [ -139.7143,    0.70655,    0.62488,    0.42632 ] 
+          - [ -135.5714,    0.67760,    0.73293,    0.43163 ] 
+          - [ -131.4286,    0.64333,    0.84130,    0.43694 ] 
+          - [ -127.2857,    0.60277,    0.94773,    0.44389 ] 
+          - [ -123.1429,    0.55550,    1.05001,    0.45171 ] 
+          - [ -119.0000,    0.50156,    1.14600,    0.45897 ] 
+          - [ -114.8571,    0.44131,    1.23371,    0.46448 ] 
+          - [ -110.7143,    0.37542,    1.31129,    0.46998 ] 
+          - [ -106.5714,    0.30482,    1.37714,    0.47096 ] 
+          - [ -102.4286,    0.23063,    1.42988,    0.47101 ] 
+          - [  -98.2857,    0.15413,    1.46842,    0.46824 ] 
+          - [  -94.1429,    0.07675,    1.49196,    0.46149 ] 
+          - [  -90.0000,    0.00000,    1.50000,    0.45474 ] 
+          - [  -85.8571,   -0.07675,    1.49196,    0.44026 ] 
+          - [  -81.7143,   -0.15413,    1.46842,    0.42578 ] 
+          - [  -77.5714,   -0.23063,    1.42988,    0.40821 ] 
+          - [  -73.4286,   -0.30482,    1.37714,    0.38846 ] 
+          - [  -69.2857,   -0.37542,    1.31129,    0.36815 ] 
+          - [  -65.1429,   -0.44131,    1.23371,    0.34519 ] 
+          - [  -61.0000,   -0.50156,    1.14600,    0.32223 ] 
+          - [  -56.8571,   -0.55550,    1.05001,    0.29864 ] 
+          - [  -52.7143,   -0.60277,    0.94773,    0.27486 ] 
+          - [  -48.5714,   -0.64333,    0.84130,    0.25128 ] 
+          - [  -44.4286,   -0.67760,    0.73293,    0.22810 ] 
+          - [  -40.2857,   -0.70655,    0.62488,    0.20491 ] 
+          - [  -36.1429,   -0.73188,    0.51941,    0.15416 ] 
+          - [  -32.0000,   -0.75635,    0.41871,    0.10137 ] 
+          - [  -28.0000,   -0.85636,    0.28691,    0.06527 ] 
+          - [  -24.0000,   -1.18292,    0.13960,    0.01647 ] 
+          - [  -20.0000,   -1.23596,    0.08345,   -0.00352 ] 
+          - [  -18.0000,   -1.22536,    0.06509,   -0.00672 ] 
+          - [  -16.0000,   -1.20476,    0.04888,   -0.00881 ] 
+          - [  -14.0000,   -1.18332,    0.03417,   -0.01101 ] 
+          - [  -12.0000,   -1.10093,    0.02132,   -0.02269 ] 
+          - [  -10.0000,   -0.88209,    0.01386,   -0.04397 ] 
+          - [   -8.0000,   -0.62981,    0.01075,   -0.05756 ] 
+          - [   -6.0000,   -0.37670,    0.00882,   -0.06747 ] 
+          - [   -4.0000,   -0.12177,    0.00702,   -0.07680 ] 
+          - [   -2.0000,    0.12810,    0.00663,   -0.08283 ] 
+          - [   -1.0000,    0.25192,    0.00664,   -0.08534 ] 
+          - [    0.0000,    0.37535,    0.00670,   -0.08777 ] 
+          - [    1.0000,    0.49828,    0.00681,   -0.09011 ] 
+          - [    2.0000,    0.62052,    0.00698,   -0.09234 ] 
+          - [    3.0000,    0.74200,    0.00720,   -0.09447 ] 
+          - [    4.0000,    0.86238,    0.00751,   -0.09646 ] 
+          - [    5.0000,    0.98114,    0.00796,   -0.09828 ] 
+          - [    6.0000,    1.09662,    0.00872,   -0.09977 ] 
+          - [    7.0000,    1.20904,    0.00968,   -0.10095 ] 
+          - [    8.0000,    1.31680,    0.01097,   -0.10163 ] 
+          - [    9.0000,    1.42209,    0.01227,   -0.10207 ] 
+          - [   10.0000,    1.52361,    0.01369,   -0.10213 ] 
+          - [   11.0000,    1.61988,    0.01529,   -0.10174 ] 
+          - [   12.0000,    1.70937,    0.01717,   -0.10087 ] 
+          - [   13.0000,    1.78681,    0.01974,   -0.09936 ] 
+          - [   14.0000,    1.84290,    0.02368,   -0.09720 ] 
+          - [   15.0000,    1.85313,    0.03094,   -0.09410 ] 
+          - [   16.0000,    1.80951,    0.04303,   -0.09144 ] 
+          - [   18.0000,    1.66033,    0.07730,   -0.09242 ] 
+          - [   20.0000,    1.56152,    0.11202,   -0.09871 ] 
+          - [   24.0000,    1.43327,    0.18408,   -0.11770 ] 
+          - [   28.0000,    1.29062,    0.27589,   -0.14566 ] 
+          - [   32.0000,    1.08050,    0.41871,   -0.18266 ] 
+          - [   36.1429,    1.04554,    0.51941,   -0.20913 ] 
+          - [   40.2857,    1.00936,    0.62488,   -0.23534 ] 
+          - [   44.4286,    0.96801,    0.73293,   -0.25784 ] 
+          - [   48.5714,    0.91904,    0.84130,   -0.28035 ] 
+          - [   52.7143,    0.86109,    0.94773,   -0.30163 ] 
+          - [   56.8571,    0.79357,    1.05001,   -0.32226 ] 
+          - [   61.0000,    0.71651,    1.14600,   -0.34247 ] 
+          - [   65.1429,    0.63044,    1.23371,   -0.36135 ] 
+          - [   69.2857,    0.53632,    1.31129,   -0.38024 ] 
+          - [   73.4286,    0.43546,    1.37714,   -0.39704 ] 
+          - [   77.5714,    0.32947,    1.42988,   -0.41341 ] 
+          - [   81.7143,    0.22019,    1.46842,   -0.42844 ] 
+          - [   85.8571,    0.10965,    1.49196,   -0.44159 ] 
+          - [   90.0000,    0.00000,    1.50000,   -0.45474 ] 
+          - [   94.1429,   -0.07675,    1.49196,   -0.46149 ] 
+          - [   98.2857,   -0.15413,    1.46842,   -0.46824 ] 
+          - [  102.4286,   -0.23063,    1.42988,   -0.47101 ] 
+          - [  106.5714,   -0.30482,    1.37714,   -0.47096 ] 
+          - [  110.7143,   -0.37542,    1.31129,   -0.46998 ] 
+          - [  114.8571,   -0.44131,    1.23371,   -0.46448 ] 
+          - [  119.0000,   -0.50156,    1.14600,   -0.45897 ] 
+          - [  123.1429,   -0.55550,    1.05001,   -0.45171 ] 
+          - [  127.2857,   -0.60277,    0.94773,   -0.44389 ] 
+          - [  131.4286,   -0.64333,    0.84130,   -0.43694 ] 
+          - [  135.5714,   -0.67760,    0.73293,   -0.43163 ] 
+          - [  139.7143,   -0.70655,    0.62488,   -0.42632 ] 
+          - [  143.8571,   -0.73188,    0.51941,   -0.42287 ] 
+          - [  148.0000,   -0.75635,    0.41871,   -0.41955 ] 
+          - [  150.2857,   -0.70233,    0.36597,   -0.41581 ] 
+          - [  152.5714,   -0.64830,    0.31566,   -0.39878 ] 
+          - [  154.8571,   -0.59428,    0.26810,   -0.38175 ] 
+          - [  157.1429,   -0.54025,    0.22359,   -0.36471 ] 
+          - [  159.4286,   -0.48623,    0.18242,   -0.34768 ] 
+          - [  161.7143,   -0.43220,    0.14485,   -0.37026 ] 
+          - [  164.0000,   -0.37818,    0.11112,   -0.40605 ] 
+          - [  166.2857,   -0.32415,    0.08143,   -0.44184 ] 
+          - [  168.5714,   -0.27013,    0.05599,   -0.47763 ] 
+          - [  170.8571,   -0.21610,    0.03570,   -0.45714 ] 
+          - [  173.1429,   -0.16208,    0.03088,   -0.34286 ] 
+          - [  175.4286,   -0.10805,    0.02742,   -0.22857 ] 
+          - [  177.7143,   -0.05403,    0.02534,   -0.11429 ] 
+          - [  179.9087,    0.00000,    0.02464,    0.00000 ] 
+      - name               : FFA-W3-241  # 
+        relative_thickness : 0.241  # 
+        data:  #  alpha    c_l    c_d     c_m   
+          - [ -179.9087,    0.00000,    0.01178,    0.00000 ] 
+          - [ -177.7143,    0.05818,    0.01248,    0.09143 ] 
+          - [ -175.4286,    0.11636,    0.01460,    0.18286 ] 
+          - [ -173.1429,    0.17453,    0.01811,    0.27429 ] 
+          - [ -170.8572,    0.23271,    0.02300,    0.36571 ] 
+          - [ -168.5716,    0.29089,    0.02922,    0.39568 ] 
+          - [ -166.2857,    0.34907,    0.05382,    0.38876 ] 
+          - [ -164.0000,    0.40725,    0.08379,    0.38184 ] 
+          - [ -161.7145,    0.46542,    0.11786,    0.37492 ] 
+          - [ -159.4284,    0.52360,    0.15581,    0.37408 ] 
+          - [ -157.1428,    0.58178,    0.19740,    0.39148 ] 
+          - [ -154.8573,    0.63996,    0.24237,    0.40888 ] 
+          - [ -152.5714,    0.69814,    0.29043,    0.42628 ] 
+          - [ -150.2857,    0.75631,    0.34128,    0.44368 ] 
+          - [ -148.0000,    0.81449,    0.39460,    0.44537 ] 
+          - [ -143.8571,    0.77925,    0.49645,    0.44436 ] 
+          - [ -139.7143,    0.74511,    0.60319,    0.44360 ] 
+          - [ -135.5714,    0.70881,    0.71263,    0.44609 ] 
+          - [ -131.4286,    0.66835,    0.82249,    0.44858 ] 
+          - [ -127.2857,    0.62253,    0.93051,    0.45370 ] 
+          - [ -123.1429,    0.57080,    1.03447,    0.46020 ] 
+          - [ -119.0000,    0.51307,    1.13222,    0.46633 ] 
+          - [ -114.8571,    0.44965,    1.22176,    0.47130 ] 
+          - [ -110.7143,    0.38115,    1.30123,    0.47627 ] 
+          - [ -106.5714,    0.30846,    1.36903,    0.47705 ] 
+          - [ -102.4286,    0.23266,    1.42376,    0.47695 ] 
+          - [  -98.2857,    0.15503,    1.46433,    0.47409 ] 
+          - [  -94.1429,    0.07698,    1.48990,    0.46732 ] 
+          - [  -90.0000,    0.00000,    1.50000,    0.46055 ] 
+          - [  -85.8571,   -0.07698,    1.48990,    0.44509 ] 
+          - [  -81.7143,   -0.15503,    1.46433,    0.42964 ] 
+          - [  -77.5714,   -0.23266,    1.42376,    0.41125 ] 
+          - [  -73.4286,   -0.30846,    1.36903,    0.39081 ] 
+          - [  -69.2857,   -0.38115,    1.30123,    0.36988 ] 
+          - [  -65.1429,   -0.44965,    1.22176,    0.34663 ] 
+          - [  -61.0000,   -0.51307,    1.13222,    0.32339 ] 
+          - [  -56.8571,   -0.57080,    1.03447,    0.29984 ] 
+          - [  -52.7143,   -0.62253,    0.93051,    0.27618 ] 
+          - [  -48.5714,   -0.66835,    0.82249,    0.25280 ] 
+          - [  -44.4286,   -0.70881,    0.71263,    0.22992 ] 
+          - [  -40.2857,   -0.74511,    0.60319,    0.20705 ] 
+          - [  -36.1429,   -0.77925,    0.49645,    0.14561 ] 
+          - [  -32.0000,   -0.81449,    0.39460,    0.08131 ] 
+          - [  -28.0000,   -1.07781,    0.22252,    0.04592 ] 
+          - [  -24.0000,   -1.12692,    0.15159,    0.01901 ] 
+          - [  -20.0000,   -1.14480,    0.09699,    0.00063 ] 
+          - [  -18.0000,   -1.12797,    0.07744,   -0.00342 ] 
+          - [  -16.0000,   -1.09392,    0.06122,   -0.00587 ] 
+          - [  -14.0000,   -1.05961,    0.04667,   -0.00652 ] 
+          - [  -12.0000,   -1.03121,    0.03302,   -0.00755 ] 
+          - [  -10.0000,   -0.93706,    0.02027,   -0.02243 ] 
+          - [   -8.0000,   -0.67380,    0.01168,   -0.05583 ] 
+          - [   -6.0000,   -0.40391,    0.00918,   -0.07159 ] 
+          - [   -4.0000,   -0.14226,    0.00839,   -0.08123 ] 
+          - [   -2.0000,    0.11580,    0.00810,   -0.08892 ] 
+          - [   -1.0000,    0.24382,    0.00808,   -0.09235 ] 
+          - [    0.0000,    0.37113,    0.00813,   -0.09556 ] 
+          - [    1.0000,    0.49766,    0.00824,   -0.09857 ] 
+          - [    2.0000,    0.62334,    0.00842,   -0.10139 ] 
+          - [    3.0000,    0.74798,    0.00867,   -0.10403 ] 
+          - [    4.0000,    0.87137,    0.00901,   -0.10645 ] 
+          - [    5.0000,    0.99320,    0.00945,   -0.10863 ] 
+          - [    6.0000,    1.11325,    0.00998,   -0.11057 ] 
+          - [    7.0000,    1.23037,    0.01070,   -0.11214 ] 
+          - [    8.0000,    1.34496,    0.01153,   -0.11337 ] 
+          - [    9.0000,    1.45407,    0.01269,   -0.11396 ] 
+          - [   10.0000,    1.55911,    0.01396,   -0.11403 ] 
+          - [   11.0000,    1.65779,    0.01545,   -0.11336 ] 
+          - [   12.0000,    1.74834,    0.01724,   -0.11187 ] 
+          - [   13.0000,    1.82666,    0.01961,   -0.10935 ] 
+          - [   14.0000,    1.88831,    0.02293,   -0.10606 ] 
+          - [   15.0000,    1.92579,    0.02795,   -0.10238 ] 
+          - [   16.0000,    1.92722,    0.03609,   -0.09887 ] 
+          - [   18.0000,    1.80055,    0.06534,   -0.09497 ] 
+          - [   20.0000,    1.63088,    0.10459,   -0.09996 ] 
+          - [   24.0000,    1.43345,    0.19148,   -0.12589 ] 
+          - [   28.0000,    1.28805,    0.28629,   -0.15453 ] 
+          - [   32.0000,    1.16356,    0.39460,   -0.18396 ] 
+          - [   36.1429,    1.11321,    0.49645,   -0.21099 ] 
+          - [   40.2857,    1.06444,    0.60319,   -0.23768 ] 
+          - [   44.4286,    1.01259,    0.71263,   -0.25992 ] 
+          - [   48.5714,    0.95478,    0.82249,   -0.28216 ] 
+          - [   52.7143,    0.88932,    0.93051,   -0.30323 ] 
+          - [   56.8571,    0.81542,    1.03447,   -0.32368 ] 
+          - [   61.0000,    0.73296,    1.13222,   -0.34380 ] 
+          - [   65.1429,    0.64236,    1.22176,   -0.36292 ] 
+          - [   69.2857,    0.54450,    1.30123,   -0.38204 ] 
+          - [   73.4286,    0.44065,    1.36903,   -0.39944 ] 
+          - [   77.5714,    0.33237,    1.42376,   -0.41648 ] 
+          - [   81.7143,    0.22148,    1.46433,   -0.43231 ] 
+          - [   85.8571,    0.10997,    1.48990,   -0.44643 ] 
+          - [   90.0000,    0.00000,    1.50000,   -0.46055 ] 
+          - [   94.1429,   -0.07698,    1.48990,   -0.46732 ] 
+          - [   98.2857,   -0.15503,    1.46433,   -0.47409 ] 
+          - [  102.4286,   -0.23266,    1.42376,   -0.47695 ] 
+          - [  106.5714,   -0.30846,    1.36903,   -0.47705 ] 
+          - [  110.7143,   -0.38115,    1.30123,   -0.47627 ] 
+          - [  114.8571,   -0.44965,    1.22176,   -0.47130 ] 
+          - [  119.0000,   -0.51307,    1.13222,   -0.46633 ] 
+          - [  123.1429,   -0.57080,    1.03447,   -0.46020 ] 
+          - [  127.2857,   -0.62253,    0.93051,   -0.45370 ] 
+          - [  131.4286,   -0.66835,    0.82249,   -0.44858 ] 
+          - [  135.5714,   -0.70881,    0.71263,   -0.44609 ] 
+          - [  139.7143,   -0.74511,    0.60319,   -0.44360 ] 
+          - [  143.8571,   -0.77925,    0.49645,   -0.44436 ] 
+          - [  148.0000,   -0.81449,    0.39460,   -0.44537 ] 
+          - [  150.2857,   -0.75631,    0.34128,   -0.44368 ] 
+          - [  152.5714,   -0.69814,    0.29043,   -0.42628 ] 
+          - [  154.8571,   -0.63996,    0.24237,   -0.40888 ] 
+          - [  157.1429,   -0.58178,    0.19740,   -0.39148 ] 
+          - [  159.4286,   -0.52360,    0.15581,   -0.37408 ] 
+          - [  161.7143,   -0.46542,    0.11786,   -0.39207 ] 
+          - [  164.0000,   -0.40725,    0.08379,   -0.42184 ] 
+          - [  166.2857,   -0.34907,    0.05382,   -0.45162 ] 
+          - [  168.5714,   -0.29089,    0.02922,   -0.48139 ] 
+          - [  170.8571,   -0.23271,    0.02300,   -0.45714 ] 
+          - [  173.1429,   -0.17453,    0.01811,   -0.34286 ] 
+          - [  175.4286,   -0.11636,    0.01460,   -0.22857 ] 
+          - [  177.7143,   -0.05818,    0.01248,   -0.11429 ] 
+          - [  179.9087,    0.00000,    0.01178,    0.00000 ] 
+      - name               : FFA-W3-270blend  # 
+        relative_thickness : 0.27  # 
+        data:  #  alpha    c_l    c_d     c_m   
+          - [ -179.9087,    0.00000,    0.01545,    0.00000 ] 
+          - [ -177.7143,    0.06213,    0.01611,    0.09143 ] 
+          - [ -175.4286,    0.12426,    0.01807,    0.18286 ] 
+          - [ -173.1429,    0.18639,    0.02133,    0.27429 ] 
+          - [ -170.8572,    0.24852,    0.02587,    0.36571 ] 
+          - [ -168.5716,    0.31064,    0.03289,    0.39874 ] 
+          - [ -166.2857,    0.37277,    0.05681,    0.39672 ] 
+          - [ -164.0000,    0.43490,    0.08471,    0.39470 ] 
+          - [ -161.7145,    0.49703,    0.11643,    0.39268 ] 
+          - [ -159.4284,    0.55916,    0.15176,    0.39544 ] 
+          - [ -157.1428,    0.62129,    0.19048,    0.41254 ] 
+          - [ -154.8573,    0.68342,    0.23234,    0.42964 ] 
+          - [ -152.5714,    0.74555,    0.27708,    0.44674 ] 
+          - [ -150.2857,    0.80768,    0.32441,    0.46384 ] 
+          - [ -148.0000,    0.86981,    0.37404,    0.46186 ] 
+          - [ -143.8571,    0.81660,    0.46882,    0.45335 ] 
+          - [ -139.7143,    0.76812,    0.56814,    0.44523 ] 
+          - [ -135.5714,    0.72040,    0.66995,    0.44237 ] 
+          - [ -131.4286,    0.67095,    0.77214,    0.43951 ] 
+          - [ -127.2857,    0.61828,    0.87258,    0.44072 ] 
+          - [ -123.1429,    0.56158,    0.96921,    0.44407 ] 
+          - [ -119.0000,    0.50057,    1.06002,    0.44739 ] 
+          - [ -114.8571,    0.43540,    1.14315,    0.45063 ] 
+          - [ -110.7143,    0.36655,    1.21688,    0.45387 ] 
+          - [ -106.5714,    0.29475,    1.27969,    0.45377 ] 
+          - [ -102.4286,    0.22098,    1.33030,    0.45298 ] 
+          - [  -98.2857,    0.14639,    1.36768,    0.44973 ] 
+          - [  -94.1429,    0.07227,    1.39107,    0.44302 ] 
+          - [  -90.0000,    0.00000,    1.40000,    0.43630 ] 
+          - [  -85.8571,   -0.07227,    1.39107,    0.42180 ] 
+          - [  -81.7143,   -0.14639,    1.36768,    0.40730 ] 
+          - [  -77.5714,   -0.22098,    1.33030,    0.39020 ] 
+          - [  -73.4286,   -0.29475,    1.27969,    0.37125 ] 
+          - [  -69.2857,   -0.36655,    1.21688,    0.35190 ] 
+          - [  -65.1429,   -0.43540,    1.14315,    0.33068 ] 
+          - [  -61.0000,   -0.50057,    1.06002,    0.30945 ] 
+          - [  -56.8571,   -0.56158,    0.96921,    0.28815 ] 
+          - [  -52.7143,   -0.61828,    0.87258,    0.26684 ] 
+          - [  -48.5714,   -0.67095,    0.77214,    0.24576 ] 
+          - [  -44.4286,   -0.72040,    0.66995,    0.22512 ] 
+          - [  -40.2857,   -0.76812,    0.56814,    0.20447 ] 
+          - [  -36.1429,   -0.81660,    0.46882,    0.13957 ] 
+          - [  -32.0000,   -0.86981,    0.37404,    0.07138 ] 
+          - [  -28.0000,   -1.09837,    0.21880,    0.04400 ] 
+          - [  -24.0000,   -1.08339,    0.15982,    0.02166 ] 
+          - [  -20.0000,   -1.06990,    0.10744,    0.00422 ] 
+          - [  -18.0000,   -1.05454,    0.08690,   -0.00035 ] 
+          - [  -16.0000,   -1.03432,    0.06844,   -0.00334 ] 
+          - [  -14.0000,   -1.08360,    0.04733,   -0.00283 ] 
+          - [  -12.0000,   -1.09489,    0.03085,   -0.00556 ] 
+          - [  -10.0000,   -0.92665,    0.01984,   -0.02952 ] 
+          - [   -8.0000,   -0.69676,    0.01439,   -0.04822 ] 
+          - [   -6.0000,   -0.43628,    0.01155,   -0.06483 ] 
+          - [   -4.0000,   -0.16252,    0.01026,   -0.07919 ] 
+          - [   -2.0000,    0.10709,    0.00976,   -0.09041 ] 
+          - [   -1.0000,    0.23993,    0.00967,   -0.09517 ] 
+          - [    0.0000,    0.37158,    0.00968,   -0.09953 ] 
+          - [    1.0000,    0.50210,    0.00976,   -0.10355 ] 
+          - [    2.0000,    0.63139,    0.00993,   -0.10725 ] 
+          - [    3.0000,    0.75951,    0.01016,   -0.11068 ] 
+          - [    4.0000,    0.88638,    0.01045,   -0.11385 ] 
+          - [    5.0000,    1.01172,    0.01082,   -0.11673 ] 
+          - [    6.0000,    1.13430,    0.01140,   -0.11923 ] 
+          - [    7.0000,    1.25536,    0.01198,   -0.12145 ] 
+          - [    8.0000,    1.37379,    0.01267,   -0.12328 ] 
+          - [    9.0000,    1.48841,    0.01353,   -0.12460 ] 
+          - [   10.0000,    1.59782,    0.01460,   -0.12526 ] 
+          - [   11.0000,    1.70005,    0.01597,   -0.12505 ] 
+          - [   12.0000,    1.79190,    0.01777,   -0.12370 ] 
+          - [   13.0000,    1.86782,    0.02035,   -0.12093 ] 
+          - [   14.0000,    1.92687,    0.02385,   -0.11725 ] 
+          - [   15.0000,    1.90901,    0.03236,   -0.10931 ] 
+          - [   16.0000,    1.88548,    0.04259,   -0.10525 ] 
+          - [   18.0000,    1.72106,    0.07672,   -0.10292 ] 
+          - [   20.0000,    1.54737,    0.11914,   -0.11017 ] 
+          - [   24.0000,    1.37176,    0.20189,   -0.13431 ] 
+          - [   28.0000,    1.33611,    0.27981,   -0.15777 ] 
+          - [   32.0000,    1.24258,    0.37404,   -0.18432 ] 
+          - [   36.1429,    1.16657,    0.46882,   -0.21002 ] 
+          - [   40.2857,    1.09731,    0.56814,   -0.23531 ] 
+          - [   44.4286,    1.02914,    0.66995,   -0.25508 ] 
+          - [   48.5714,    0.95850,    0.77214,   -0.27485 ] 
+          - [   52.7143,    0.88325,    0.87258,   -0.29346 ] 
+          - [   56.8571,    0.80225,    0.96921,   -0.31145 ] 
+          - [   61.0000,    0.71510,    1.06002,   -0.32925 ] 
+          - [   65.1429,    0.62200,    1.14315,   -0.34641 ] 
+          - [   69.2857,    0.52364,    1.21688,   -0.36357 ] 
+          - [   73.4286,    0.42107,    1.27969,   -0.37949 ] 
+          - [   77.5714,    0.31569,    1.33030,   -0.39517 ] 
+          - [   81.7143,    0.20913,    1.36768,   -0.40983 ] 
+          - [   85.8571,    0.10324,    1.39107,   -0.42306 ] 
+          - [   90.0000,    0.00000,    1.40000,   -0.43630 ] 
+          - [   94.1429,   -0.07227,    1.39107,   -0.44302 ] 
+          - [   98.2857,   -0.14639,    1.36768,   -0.44973 ] 
+          - [  102.4286,   -0.22098,    1.33030,   -0.45298 ] 
+          - [  106.5714,   -0.29475,    1.27969,   -0.45377 ] 
+          - [  110.7143,   -0.36655,    1.21688,   -0.45387 ] 
+          - [  114.8571,   -0.43540,    1.14315,   -0.45063 ] 
+          - [  119.0000,   -0.50057,    1.06002,   -0.44739 ] 
+          - [  123.1429,   -0.56158,    0.96921,   -0.44407 ] 
+          - [  127.2857,   -0.61828,    0.87258,   -0.44072 ] 
+          - [  131.4286,   -0.67095,    0.77214,   -0.43951 ] 
+          - [  135.5714,   -0.72040,    0.66995,   -0.44237 ] 
+          - [  139.7143,   -0.76812,    0.56814,   -0.44523 ] 
+          - [  143.8571,   -0.81660,    0.46882,   -0.45335 ] 
+          - [  148.0000,   -0.86981,    0.37404,   -0.46186 ] 
+          - [  150.2857,   -0.80768,    0.32441,   -0.46384 ] 
+          - [  152.5714,   -0.74555,    0.27708,   -0.44674 ] 
+          - [  154.8571,   -0.68342,    0.23234,   -0.42964 ] 
+          - [  157.1429,   -0.62129,    0.19048,   -0.41254 ] 
+          - [  159.4286,   -0.55916,    0.15176,   -0.39544 ] 
+          - [  161.7143,   -0.49703,    0.11643,   -0.40982 ] 
+          - [  164.0000,   -0.43490,    0.08471,   -0.43470 ] 
+          - [  166.2857,   -0.37277,    0.05681,   -0.45958 ] 
+          - [  168.5714,   -0.31064,    0.03289,   -0.48445 ] 
+          - [  170.8571,   -0.24852,    0.02587,   -0.45714 ] 
+          - [  173.1429,   -0.18639,    0.02133,   -0.34286 ] 
+          - [  175.4286,   -0.12426,    0.01807,   -0.22857 ] 
+          - [  177.7143,   -0.06213,    0.01611,   -0.11429 ] 
+          - [  179.9087,    0.00000,    0.01545,    0.00000 ] 
+      - name               : FFA-W3-301  # 
+        relative_thickness : 0.301  # 
+        data:  #  alpha    c_l    c_d     c_m   
+          - [ -179.9087,    0.00000,    0.02454,    0.00000 ] 
+          - [ -177.7143,    0.06508,    0.02514,    0.09143 ] 
+          - [ -175.4286,    0.13016,    0.02694,    0.18286 ] 
+          - [ -173.1429,    0.19525,    0.02993,    0.27429 ] 
+          - [ -170.8572,    0.26033,    0.03408,    0.36571 ] 
+          - [ -168.5716,    0.32541,    0.03938,    0.40085 ] 
+          - [ -166.2857,    0.39049,    0.05910,    0.40220 ] 
+          - [ -164.0000,    0.45557,    0.08495,    0.40356 ] 
+          - [ -161.7145,    0.52066,    0.11433,    0.40492 ] 
+          - [ -159.4284,    0.58574,    0.14704,    0.41010 ] 
+          - [ -157.1428,    0.65082,    0.18290,    0.42678 ] 
+          - [ -154.8573,    0.71590,    0.22166,    0.44345 ] 
+          - [ -152.5714,    0.78098,    0.26309,    0.46013 ] 
+          - [ -150.2857,    0.84607,    0.30692,    0.47680 ] 
+          - [ -148.0000,    0.91115,    0.35287,    0.47162 ] 
+          - [ -143.8571,    0.84257,    0.44061,    0.45656 ] 
+          - [ -139.7143,    0.78187,    0.53255,    0.44202 ] 
+          - [ -135.5714,    0.72448,    0.62677,    0.43452 ] 
+          - [ -131.4286,    0.66755,    0.72131,    0.42701 ] 
+          - [ -127.2857,    0.60928,    0.81421,    0.42483 ] 
+          - [ -123.1429,    0.54868,    0.90355,    0.42544 ] 
+          - [ -119.0000,    0.48530,    0.98748,    0.42634 ] 
+          - [ -114.8571,    0.41915,    1.06425,    0.42813 ] 
+          - [ -110.7143,    0.35056,    1.13227,    0.42992 ] 
+          - [ -106.5714,    0.28017,    1.19015,    0.42916 ] 
+          - [ -102.4286,    0.20881,    1.23669,    0.42788 ] 
+          - [  -98.2857,    0.13754,    1.27093,    0.42444 ] 
+          - [  -94.1429,    0.06751,    1.29218,    0.41794 ] 
+          - [  -90.0000,    0.00000,    1.30000,    0.41144 ] 
+          - [  -85.8571,   -0.06751,    1.29218,    0.39804 ] 
+          - [  -81.7143,   -0.13754,    1.27093,    0.38464 ] 
+          - [  -77.5714,   -0.20881,    1.23669,    0.36892 ] 
+          - [  -73.4286,   -0.28017,    1.19015,    0.35157 ] 
+          - [  -69.2857,   -0.35056,    1.13227,    0.33391 ] 
+          - [  -65.1429,   -0.41915,    1.06425,    0.31474 ] 
+          - [  -61.0000,   -0.48530,    0.98748,    0.29557 ] 
+          - [  -56.8571,   -0.54868,    0.90355,    0.27653 ] 
+          - [  -52.7143,   -0.60928,    0.81421,    0.25754 ] 
+          - [  -48.5714,   -0.66755,    0.72131,    0.23873 ] 
+          - [  -44.4286,   -0.72448,    0.62677,    0.22027 ] 
+          - [  -40.2857,   -0.78187,    0.53255,    0.20181 ] 
+          - [  -36.1429,   -0.84257,    0.44061,    0.13644 ] 
+          - [  -32.0000,   -0.91115,    0.35287,    0.06760 ] 
+          - [  -28.0000,   -1.10349,    0.21721,    0.04231 ] 
+          - [  -24.0000,   -1.10737,    0.15629,    0.02026 ] 
+          - [  -20.0000,   -1.11815,    0.10335,    0.00407 ] 
+          - [  -18.0000,   -1.12332,    0.08180,    0.00017 ] 
+          - [  -16.0000,   -1.11865,    0.06331,   -0.00167 ] 
+          - [  -14.0000,   -1.11620,    0.04718,   -0.00120 ] 
+          - [  -12.0000,   -1.09588,    0.03280,   -0.00463 ] 
+          - [  -10.0000,   -0.91767,    0.02351,   -0.02494 ] 
+          - [   -8.0000,   -0.69311,    0.01793,   -0.04304 ] 
+          - [   -6.0000,   -0.45396,    0.01431,   -0.05868 ] 
+          - [   -4.0000,   -0.17779,    0.01242,   -0.07601 ] 
+          - [   -2.0000,    0.10480,    0.01160,   -0.09121 ] 
+          - [   -1.0000,    0.24383,    0.01143,   -0.09763 ] 
+          - [    0.0000,    0.38111,    0.01138,   -0.10341 ] 
+          - [    1.0000,    0.51660,    0.01143,   -0.10861 ] 
+          - [    2.0000,    0.65044,    0.01156,   -0.11333 ] 
+          - [    3.0000,    0.78267,    0.01177,   -0.11762 ] 
+          - [    4.0000,    0.91326,    0.01204,   -0.12154 ] 
+          - [    5.0000,    1.04207,    0.01239,   -0.12510 ] 
+          - [    6.0000,    1.16873,    0.01283,   -0.12828 ] 
+          - [    7.0000,    1.29296,    0.01338,   -0.13104 ] 
+          - [    8.0000,    1.41390,    0.01406,   -0.13332 ] 
+          - [    9.0000,    1.53088,    0.01488,   -0.13503 ] 
+          - [   10.0000,    1.64208,    0.01592,   -0.13599 ] 
+          - [   11.0000,    1.74568,    0.01726,   -0.13605 ] 
+          - [   12.0000,    1.83887,    0.01908,   -0.13514 ] 
+          - [   13.0000,    1.91764,    0.02169,   -0.13322 ] 
+          - [   14.0000,    1.97413,    0.02572,   -0.13020 ] 
+          - [   15.0000,    1.99916,    0.03222,   -0.12641 ] 
+          - [   16.0000,    1.99377,    0.04157,   -0.12265 ] 
+          - [   18.0000,    1.91720,    0.06731,   -0.11675 ] 
+          - [   20.0000,    1.73683,    0.10526,   -0.11652 ] 
+          - [   24.0000,    1.47321,    0.19229,   -0.13790 ] 
+          - [   28.0000,    1.36017,    0.27449,   -0.16242 ] 
+          - [   32.0000,    1.30164,    0.35287,   -0.18463 ] 
+          - [   36.1429,    1.20367,    0.44061,   -0.20894 ] 
+          - [   40.2857,    1.11695,    0.53255,   -0.23276 ] 
+          - [   44.4286,    1.03498,    0.62677,   -0.25011 ] 
+          - [   48.5714,    0.95364,    0.72131,   -0.26746 ] 
+          - [   52.7143,    0.87040,    0.81421,   -0.28365 ] 
+          - [   56.8571,    0.78383,    0.90355,   -0.29923 ] 
+          - [   61.0000,    0.69329,    0.98748,   -0.31472 ] 
+          - [   65.1429,    0.59878,    1.06425,   -0.32988 ] 
+          - [   69.2857,    0.50080,    1.13227,   -0.34505 ] 
+          - [   73.4286,    0.40024,    1.19015,   -0.35942 ] 
+          - [   77.5714,    0.29831,    1.23669,   -0.37363 ] 
+          - [   81.7143,    0.19648,    1.27093,   -0.38702 ] 
+          - [   85.8571,    0.09644,    1.29218,   -0.39923 ] 
+          - [   90.0000,    0.00000,    1.30000,   -0.41144 ] 
+          - [   94.1429,   -0.06751,    1.29218,   -0.41794 ] 
+          - [   98.2857,   -0.13754,    1.27093,   -0.42444 ] 
+          - [  102.4286,   -0.20881,    1.23669,   -0.42788 ] 
+          - [  106.5714,   -0.28017,    1.19015,   -0.42916 ] 
+          - [  110.7143,   -0.35056,    1.13227,   -0.42992 ] 
+          - [  114.8571,   -0.41915,    1.06425,   -0.42813 ] 
+          - [  119.0000,   -0.48530,    0.98748,   -0.42634 ] 
+          - [  123.1429,   -0.54868,    0.90355,   -0.42544 ] 
+          - [  127.2857,   -0.60928,    0.81421,   -0.42483 ] 
+          - [  131.4286,   -0.66755,    0.72131,   -0.42701 ] 
+          - [  135.5714,   -0.72448,    0.62677,   -0.43452 ] 
+          - [  139.7143,   -0.78187,    0.53255,   -0.44202 ] 
+          - [  143.8571,   -0.84257,    0.44061,   -0.45656 ] 
+          - [  148.0000,   -0.91115,    0.35287,   -0.47162 ] 
+          - [  150.2857,   -0.84607,    0.30692,   -0.47680 ] 
+          - [  152.5714,   -0.78098,    0.26309,   -0.46013 ] 
+          - [  154.8571,   -0.71590,    0.22166,   -0.44345 ] 
+          - [  157.1429,   -0.65082,    0.18290,   -0.42678 ] 
+          - [  159.4286,   -0.58574,    0.14704,   -0.41010 ] 
+          - [  161.7143,   -0.52066,    0.11433,   -0.42206 ] 
+          - [  164.0000,   -0.45557,    0.08495,   -0.44356 ] 
+          - [  166.2857,   -0.39049,    0.05910,   -0.46506 ] 
+          - [  168.5714,   -0.32541,    0.03938,   -0.48656 ] 
+          - [  170.8571,   -0.26033,    0.03408,   -0.45714 ] 
+          - [  173.1429,   -0.19525,    0.02993,   -0.34286 ] 
+          - [  175.4286,   -0.13016,    0.02694,   -0.22857 ] 
+          - [  177.7143,   -0.06508,    0.02514,   -0.11429 ] 
+          - [  179.9087,    0.00000,    0.02454,    0.00000 ] 
+      - name               : FFA-W3-330blend  # 
+        relative_thickness : 0.33  # 
+        data:  #  alpha    c_l    c_d     c_m   
+          - [ -179.9087,    0.00000,    0.03169,    0.00000 ] 
+          - [ -177.7143,    0.06960,    0.03228,    0.09143 ] 
+          - [ -175.4286,    0.13920,    0.03406,    0.18286 ] 
+          - [ -173.1429,    0.20880,    0.03702,    0.27429 ] 
+          - [ -170.8572,    0.27841,    0.04114,    0.36571 ] 
+          - [ -168.5716,    0.34801,    0.04638,    0.40308 ] 
+          - [ -166.2857,    0.41761,    0.05732,    0.40801 ] 
+          - [ -164.0000,    0.48721,    0.08319,    0.41294 ] 
+          - [ -161.7145,    0.55681,    0.11258,    0.41788 ] 
+          - [ -159.4284,    0.62641,    0.14533,    0.42586 ] 
+          - [ -157.1428,    0.69601,    0.18121,    0.44302 ] 
+          - [ -154.8573,    0.76562,    0.22000,    0.46017 ] 
+          - [ -152.5714,    0.83522,    0.26146,    0.47732 ] 
+          - [ -150.2857,    0.90482,    0.30532,    0.49447 ] 
+          - [ -148.0000,    0.97442,    0.35131,    0.48743 ] 
+          - [ -143.8571,    0.89412,    0.43913,    0.46839 ] 
+          - [ -139.7143,    0.82382,    0.53115,    0.44996 ] 
+          - [ -135.5714,    0.75845,    0.62546,    0.43985 ] 
+          - [ -131.4286,    0.69477,    0.72010,    0.42974 ] 
+          - [ -127.2857,    0.63079,    0.81310,    0.42589 ] 
+          - [ -123.1429,    0.56532,    0.90255,    0.42535 ] 
+          - [ -119.0000,    0.49783,    0.98659,    0.42528 ] 
+          - [ -114.8571,    0.42823,    1.06348,    0.42673 ] 
+          - [ -110.7143,    0.35680,    1.13162,    0.42817 ] 
+          - [ -106.5714,    0.28412,    1.18963,    0.42745 ] 
+          - [ -102.4286,    0.21103,    1.23629,    0.42628 ] 
+          - [  -98.2857,    0.13851,    1.27067,    0.42303 ] 
+          - [  -94.1429,    0.06775,    1.29204,    0.41683 ] 
+          - [  -90.0000,    0.00000,    1.30000,    0.41063 ] 
+          - [  -85.8571,   -0.06775,    1.29204,    0.39752 ] 
+          - [  -81.7143,   -0.13851,    1.27067,    0.38441 ] 
+          - [  -77.5714,   -0.21103,    1.23629,    0.36905 ] 
+          - [  -73.4286,   -0.28412,    1.18963,    0.35212 ] 
+          - [  -69.2857,   -0.35680,    1.13162,    0.33491 ] 
+          - [  -65.1429,   -0.42823,    1.06348,    0.31634 ] 
+          - [  -61.0000,   -0.49783,    0.98659,    0.29777 ] 
+          - [  -56.8571,   -0.56532,    0.90255,    0.27947 ] 
+          - [  -52.7143,   -0.63079,    0.81310,    0.26125 ] 
+          - [  -48.5714,   -0.69477,    0.72010,    0.24322 ] 
+          - [  -44.4286,   -0.75845,    0.62546,    0.22556 ] 
+          - [  -40.2857,   -0.82382,    0.53115,    0.20789 ] 
+          - [  -36.1429,   -0.89412,    0.43913,    0.13731 ] 
+          - [  -32.0000,   -0.97442,    0.35131,    0.06280 ] 
+          - [  -28.0000,   -1.16308,    0.20648,    0.03905 ] 
+          - [  -24.0000,   -1.14892,    0.15001,    0.01853 ] 
+          - [  -20.0000,   -1.09451,    0.10600,    0.00441 ] 
+          - [  -18.0000,   -1.05801,    0.08732,   -0.00061 ] 
+          - [  -16.0000,   -1.02281,    0.07051,   -0.00342 ] 
+          - [  -14.0000,   -0.99810,    0.05474,   -0.00401 ] 
+          - [  -12.0000,   -0.98515,    0.04052,   -0.00272 ] 
+          - [  -10.0000,   -0.89583,    0.02929,   -0.01198 ] 
+          - [   -8.0000,   -0.67539,    0.02207,   -0.03458 ] 
+          - [   -6.0000,   -0.43247,    0.01735,   -0.05466 ] 
+          - [   -4.0000,   -0.15881,    0.01473,   -0.07425 ] 
+          - [   -2.0000,    0.13456,    0.01362,   -0.09270 ] 
+          - [   -1.0000,    0.28014,    0.01339,   -0.10074 ] 
+          - [    0.0000,    0.42386,    0.01330,   -0.10802 ] 
+          - [    1.0000,    0.56519,    0.01333,   -0.11450 ] 
+          - [    2.0000,    0.70410,    0.01345,   -0.12028 ] 
+          - [    3.0000,    0.84071,    0.01366,   -0.12546 ] 
+          - [    4.0000,    0.97500,    0.01397,   -0.13011 ] 
+          - [    5.0000,    1.10680,    0.01437,   -0.13425 ] 
+          - [    6.0000,    1.23603,    0.01486,   -0.13793 ] 
+          - [    7.0000,    1.36223,    0.01547,   -0.14108 ] 
+          - [    8.0000,    1.48424,    0.01623,   -0.14363 ] 
+          - [    9.0000,    1.60097,    0.01718,   -0.14545 ] 
+          - [   10.0000,    1.71010,    0.01841,   -0.14636 ] 
+          - [   11.0000,    1.80957,    0.02010,   -0.14635 ] 
+          - [   12.0000,    1.89473,    0.02258,   -0.14544 ] 
+          - [   13.0000,    1.95698,    0.02671,   -0.14378 ] 
+          - [   14.0000,    1.98576,    0.03380,   -0.14185 ] 
+          - [   15.0000,    1.99260,    0.04333,   -0.14004 ] 
+          - [   16.0000,    1.99617,    0.05354,   -0.13823 ] 
+          - [   18.0000,    1.96398,    0.07706,   -0.13351 ] 
+          - [   20.0000,    1.81179,    0.11169,   -0.13135 ] 
+          - [   24.0000,    1.56073,    0.19103,   -0.14660 ] 
+          - [   28.0000,    1.46798,    0.27199,   -0.17242 ] 
+          - [   32.0000,    1.39203,    0.35131,   -0.19417 ] 
+          - [   36.1429,    1.27731,    0.43913,   -0.21792 ] 
+          - [   40.2857,    1.17689,    0.53115,   -0.24115 ] 
+          - [   44.4286,    1.08350,    0.62546,   -0.25734 ] 
+          - [   48.5714,    0.99253,    0.72010,   -0.27354 ] 
+          - [   52.7143,    0.90112,    0.81310,   -0.28862 ] 
+          - [   56.8571,    0.80760,    0.90255,   -0.30311 ] 
+          - [   61.0000,    0.71119,    0.98659,   -0.31757 ] 
+          - [   65.1429,    0.61175,    1.06348,   -0.33194 ] 
+          - [   69.2857,    0.50971,    1.13162,   -0.34631 ] 
+          - [   73.4286,    0.40589,    1.18963,   -0.36014 ] 
+          - [   77.5714,    0.30146,    1.23629,   -0.37385 ] 
+          - [   81.7143,    0.19788,    1.27067,   -0.38681 ] 
+          - [   85.8571,    0.09679,    1.29204,   -0.39872 ] 
+          - [   90.0000,    0.00000,    1.30000,   -0.41063 ] 
+          - [   94.1429,   -0.06775,    1.29204,   -0.41683 ] 
+          - [   98.2857,   -0.13851,    1.27067,   -0.42303 ] 
+          - [  102.4286,   -0.21103,    1.23629,   -0.42628 ] 
+          - [  106.5714,   -0.28412,    1.18963,   -0.42745 ] 
+          - [  110.7143,   -0.35680,    1.13162,   -0.42817 ] 
+          - [  114.8571,   -0.42823,    1.06348,   -0.42673 ] 
+          - [  119.0000,   -0.49783,    0.98659,   -0.42528 ] 
+          - [  123.1429,   -0.56532,    0.90255,   -0.42535 ] 
+          - [  127.2857,   -0.63079,    0.81310,   -0.42589 ] 
+          - [  131.4286,   -0.69477,    0.72010,   -0.42974 ] 
+          - [  135.5714,   -0.75845,    0.62546,   -0.43985 ] 
+          - [  139.7143,   -0.82382,    0.53115,   -0.44996 ] 
+          - [  143.8571,   -0.89412,    0.43913,   -0.46839 ] 
+          - [  148.0000,   -0.97442,    0.35131,   -0.48743 ] 
+          - [  150.2857,   -0.90482,    0.30532,   -0.49447 ] 
+          - [  152.5714,   -0.83522,    0.26146,   -0.47732 ] 
+          - [  154.8571,   -0.76562,    0.22000,   -0.46017 ] 
+          - [  157.1429,   -0.69601,    0.18121,   -0.44302 ] 
+          - [  159.4286,   -0.62641,    0.14533,   -0.42586 ] 
+          - [  161.7143,   -0.55681,    0.11258,   -0.43502 ] 
+          - [  164.0000,   -0.48721,    0.08319,   -0.45294 ] 
+          - [  166.2857,   -0.41761,    0.05732,   -0.47087 ] 
+          - [  168.5714,   -0.34801,    0.04638,   -0.48880 ] 
+          - [  170.8571,   -0.27841,    0.04114,   -0.45714 ] 
+          - [  173.1429,   -0.20880,    0.03702,   -0.34286 ] 
+          - [  175.4286,   -0.13920,    0.03406,   -0.22857 ] 
+          - [  177.7143,   -0.06960,    0.03228,   -0.11429 ] 
+          - [  179.9087,    0.00000,    0.03169,    0.00000 ] 
+      - name               : FFA-W3-360  # 
+        relative_thickness : 0.36  # 
+        data:  #  alpha    c_l    c_d     c_m   
+          - [ -179.9087,    0.00000,    0.03715,    0.00000 ] 
+          - [ -177.7143,    0.07178,    0.03774,    0.09143 ] 
+          - [ -175.4286,    0.14356,    0.03951,    0.18286 ] 
+          - [ -173.1429,    0.21534,    0.04245,    0.27429 ] 
+          - [ -170.8572,    0.28713,    0.04653,    0.36571 ] 
+          - [ -168.5716,    0.35891,    0.05174,    0.40313 ] 
+          - [ -166.2857,    0.43069,    0.06068,    0.40814 ] 
+          - [ -164.0000,    0.50247,    0.08651,    0.41315 ] 
+          - [ -161.7145,    0.57425,    0.11586,    0.41816 ] 
+          - [ -159.4284,    0.64603,    0.14856,    0.42627 ] 
+          - [ -157.1428,    0.71781,    0.18439,    0.44370 ] 
+          - [ -154.8573,    0.78960,    0.22313,    0.46114 ] 
+          - [ -152.5714,    0.86138,    0.26453,    0.47857 ] 
+          - [ -150.2857,    0.93316,    0.30832,    0.49600 ] 
+          - [ -148.0000,    1.00494,    0.35424,    0.48830 ] 
+          - [ -143.8571,    0.91898,    0.44192,    0.46784 ] 
+          - [ -139.7143,    0.84406,    0.53379,    0.44803 ] 
+          - [ -135.5714,    0.77483,    0.62793,    0.43697 ] 
+          - [ -131.4286,    0.70790,    0.72238,    0.42591 ] 
+          - [ -127.2857,    0.64116,    0.81520,    0.42150 ] 
+          - [ -123.1429,    0.57335,    0.90444,    0.42058 ] 
+          - [ -119.0000,    0.50388,    0.98826,    0.42024 ] 
+          - [ -114.8571,    0.43261,    1.06493,    0.42168 ] 
+          - [ -110.7143,    0.35981,    1.13285,    0.42312 ] 
+          - [ -106.5714,    0.28603,    1.19061,    0.42258 ] 
+          - [ -102.4286,    0.21209,    1.23704,    0.42163 ] 
+          - [  -98.2857,    0.13899,    1.27116,    0.41864 ] 
+          - [  -94.1429,    0.06787,    1.29229,    0.41277 ] 
+          - [  -90.0000,    0.00000,    1.30000,    0.40690 ] 
+          - [  -85.8571,   -0.06787,    1.29229,    0.39426 ] 
+          - [  -81.7143,   -0.13899,    1.27116,    0.38162 ] 
+          - [  -77.5714,   -0.21209,    1.23704,    0.36676 ] 
+          - [  -73.4286,   -0.28603,    1.19061,    0.35033 ] 
+          - [  -69.2857,   -0.35981,    1.13285,    0.33362 ] 
+          - [  -65.1429,   -0.43261,    1.06493,    0.31561 ] 
+          - [  -61.0000,   -0.50388,    0.98826,    0.29759 ] 
+          - [  -56.8571,   -0.57335,    0.90444,    0.27989 ] 
+          - [  -52.7143,   -0.64116,    0.81520,    0.26230 ] 
+          - [  -48.5714,   -0.70790,    0.72238,    0.24491 ] 
+          - [  -44.4286,   -0.77483,    0.62793,    0.22794 ] 
+          - [  -40.2857,   -0.84406,    0.53379,    0.21097 ] 
+          - [  -36.1429,   -0.91898,    0.44192,    0.13525 ] 
+          - [  -32.0000,   -1.00494,    0.35424,    0.05517 ] 
+          - [  -28.0000,   -1.11306,    0.20494,    0.03211 ] 
+          - [  -24.0000,   -1.05425,    0.15434,    0.01268 ] 
+          - [  -20.0000,   -0.98247,    0.10967,   -0.00282 ] 
+          - [  -18.0000,   -0.94173,    0.09249,   -0.00741 ] 
+          - [  -16.0000,   -0.89333,    0.07597,   -0.01107 ] 
+          - [  -14.0000,   -0.85472,    0.06054,   -0.01250 ] 
+          - [  -12.0000,   -0.82348,    0.04641,   -0.01177 ] 
+          - [  -10.0000,   -0.79541,    0.03441,   -0.01082 ] 
+          - [   -8.0000,   -0.63650,    0.02548,   -0.02769 ] 
+          - [   -6.0000,   -0.39095,    0.01994,   -0.05107 ] 
+          - [   -4.0000,   -0.13071,    0.01653,   -0.07148 ] 
+          - [   -2.0000,    0.16173,    0.01507,   -0.09179 ] 
+          - [   -1.0000,    0.31121,    0.01477,   -0.10119 ] 
+          - [    0.0000,    0.45956,    0.01465,   -0.10988 ] 
+          - [    1.0000,    0.60566,    0.01466,   -0.11776 ] 
+          - [    2.0000,    0.74868,    0.01481,   -0.12477 ] 
+          - [    3.0000,    0.88862,    0.01507,   -0.13098 ] 
+          - [    4.0000,    1.02544,    0.01544,   -0.13648 ] 
+          - [    5.0000,    1.15878,    0.01593,   -0.14130 ] 
+          - [    6.0000,    1.28822,    0.01654,   -0.14540 ] 
+          - [    7.0000,    1.41282,    0.01731,   -0.14875 ] 
+          - [    8.0000,    1.53090,    0.01831,   -0.15118 ] 
+          - [    9.0000,    1.64065,    0.01963,   -0.15262 ] 
+          - [   10.0000,    1.73926,    0.02150,   -0.15310 ] 
+          - [   11.0000,    1.81971,    0.02445,   -0.15254 ] 
+          - [   12.0000,    1.87065,    0.02966,   -0.15121 ] 
+          - [   13.0000,    1.89221,    0.03770,   -0.14969 ] 
+          - [   14.0000,    1.87910,    0.04824,   -0.14562 ] 
+          - [   15.0000,    1.88111,    0.05838,   -0.14358 ] 
+          - [   16.0000,    1.86359,    0.06992,   -0.14095 ] 
+          - [   18.0000,    1.73324,    0.10166,   -0.13711 ] 
+          - [   20.0000,    1.59357,    0.13916,   -0.14082 ] 
+          - [   24.0000,    1.46708,    0.21002,   -0.15693 ] 
+          - [   28.0000,    1.44834,    0.28200,   -0.17979 ] 
+          - [   32.0000,    1.43563,    0.35424,   -0.20147 ] 
+          - [   36.1429,    1.31283,    0.44192,   -0.22409 ] 
+          - [   40.2857,    1.20580,    0.53379,   -0.24619 ] 
+          - [   44.4286,    1.10690,    0.62793,   -0.26133 ] 
+          - [   48.5714,    1.01129,    0.72238,   -0.27648 ] 
+          - [   52.7143,    0.91594,    0.81520,   -0.29062 ] 
+          - [   56.8571,    0.81907,    0.90444,   -0.30424 ] 
+          - [   61.0000,    0.71982,    0.98826,   -0.31787 ] 
+          - [   65.1429,    0.61801,    1.06493,   -0.33154 ] 
+          - [   69.2857,    0.51401,    1.13285,   -0.34522 ] 
+          - [   73.4286,    0.40862,    1.19061,   -0.35846 ] 
+          - [   77.5714,    0.30299,    1.23704,   -0.37161 ] 
+          - [   81.7143,    0.19855,    1.27116,   -0.38405 ] 
+          - [   85.8571,    0.09695,    1.29229,   -0.39547 ] 
+          - [   90.0000,    0.00000,    1.30000,   -0.40690 ] 
+          - [   94.1429,   -0.06787,    1.29229,   -0.41277 ] 
+          - [   98.2857,   -0.13899,    1.27116,   -0.41864 ] 
+          - [  102.4286,   -0.21209,    1.23704,   -0.42163 ] 
+          - [  106.5714,   -0.28603,    1.19061,   -0.42258 ] 
+          - [  110.7143,   -0.35981,    1.13285,   -0.42312 ] 
+          - [  114.8571,   -0.43261,    1.06493,   -0.42168 ] 
+          - [  119.0000,   -0.50388,    0.98826,   -0.42024 ] 
+          - [  123.1429,   -0.57335,    0.90444,   -0.42058 ] 
+          - [  127.2857,   -0.64116,    0.81520,   -0.42150 ] 
+          - [  131.4286,   -0.70790,    0.72238,   -0.42591 ] 
+          - [  135.5714,   -0.77483,    0.62793,   -0.43697 ] 
+          - [  139.7143,   -0.84406,    0.53379,   -0.44803 ] 
+          - [  143.8571,   -0.91898,    0.44192,   -0.46784 ] 
+          - [  148.0000,   -1.00494,    0.35424,   -0.48830 ] 
+          - [  150.2857,   -0.93316,    0.30832,   -0.49600 ] 
+          - [  152.5714,   -0.86138,    0.26453,   -0.47857 ] 
+          - [  154.8571,   -0.78960,    0.22313,   -0.46114 ] 
+          - [  157.1429,   -0.71781,    0.18439,   -0.44370 ] 
+          - [  159.4286,   -0.64603,    0.14856,   -0.42627 ] 
+          - [  161.7143,   -0.57425,    0.11586,   -0.43530 ] 
+          - [  164.0000,   -0.50247,    0.08651,   -0.45315 ] 
+          - [  166.2857,   -0.43069,    0.06068,   -0.47100 ] 
+          - [  168.5714,   -0.35891,    0.05174,   -0.48884 ] 
+          - [  170.8571,   -0.28713,    0.04653,   -0.45714 ] 
+          - [  173.1429,   -0.21534,    0.04245,   -0.34286 ] 
+          - [  175.4286,   -0.14356,    0.03951,   -0.22857 ] 
+          - [  177.7143,   -0.07178,    0.03774,   -0.11429 ] 
+          - [  179.9087,    0.00000,    0.03715,    0.00000 ] 
+
+
+        
+    pitch_control:
+      GS_Angles: [0.06019804, 0.08713416, 0.10844806, 0.12685912, 0.14339822,       0.1586021 , 0.17279614, 0.18618935, 0.19892772, 0.21111989,             0.22285021, 0.23417256, 0.2451469 , 0.25580691, 0.26619545,           0.27632495, 0.28623134, 0.29593266, 0.30544521, 0.314779  ,       0.32395154, 0.33297489, 0.3418577 , 0.35060844, 0.35923641,       0.36774807, 0.37614942, 0.38444655, 0.39264363, 0.40074407]
+      GS_Kp: [-0.9394215 , -0.80602855, -0.69555026, -0.60254912, -0.52318192,       -0.45465531, -0.39489024, -0.34230736, -0.29568537, -0.25406506,       -0.2166825 , -0.18292183, -0.15228099, -0.12434663, -0.09877533,       -0.0752794 , -0.05361604, -0.0335789 , -0.01499149,  0.00229803,  0.01842102,  0.03349169,  0.0476098 ,  0.0608629 ,  0.07332812,  0.0850737 ,  0.0961602 ,  0.10664158,  0.11656607,  0.12597691]
+      GS_Ki: [-0.07416547, -0.06719673, -0.0614251 , -0.05656651, -0.0524202 ,       -0.04884022, -0.04571796, -0.04297091, -0.04053528, -0.03836094,       -0.03640799, -0.03464426, -0.03304352, -0.03158417, -0.03024826,       -0.02902079, -0.02788904, -0.02684226, -0.02587121, -0.02496797,       -0.02412567, -0.02333834, -0.02260078, -0.02190841, -0.0212572 ,       -0.02064359, -0.0200644 , -0.01951683, -0.01899836, -0.01850671]
+      Fl_Kp:   -9.35
+    wt_ops:
+        v: [3.0, 3.266896551724138, 3.533793103448276, 3.800689655172414, 4.067586206896552, 4.334482758620689, 4.601379310344828, 4.868275862068966, 5.135172413793104, 5.402068965517241, 5.6689655172413795, 5.935862068965518, 6.2027586206896554, 6.469655172413793, 6.736551724137931, 7.00344827586207, 7.270344827586207, 7.537241379310345, 7.804137931034483, 8.071034482758622, 8.337931034482759, 8.604827586206897, 8.871724137931036, 9.138620689655173, 9.405517241379311, 9.672413793103448, 9.939310344827586, 10.206206896551725, 10.473103448275863, 10.74, 11.231724137931035, 11.723448275862069, 12.215172413793104, 12.706896551724139, 13.198620689655172, 13.690344827586207, 14.182068965517242, 14.673793103448276, 15.16551724137931, 15.657241379310346, 16.14896551724138, 16.640689655172416, 17.13241379310345, 17.624137931034483, 18.11586206896552, 18.607586206896553, 19.099310344827586, 19.591034482758623, 20.082758620689653, 20.57448275862069, 21.066206896551726, 21.557931034482756, 22.049655172413793, 22.54137931034483, 23.03310344827586, 23.524827586206897, 24.016551724137933, 24.508275862068963, 25.0]
+        pitch_op: [-0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, 3.57152, 5.12896, 6.36736, 7.43866, 8.40197, 9.28843, 10.1161, 10.8974,  11.641, 12.3529,  13.038, 13.6997, 14.3409, 14.9642, 15.5713, 16.1639, 16.7435, 17.3109, 17.8673, 18.4136, 18.9506, 19.4788, 19.9989, 20.5112, 21.0164, 21.5147, 22.0067, 22.4925, 22.9724]
+        omega_op: [2.1486, 2.3397, 2.5309,  2.722, 2.9132, 3.1043, 3.2955, 3.4866, 3.6778, 3.8689, 4.0601, 4.2512, 4.4424, 4.6335, 4.8247, 5.0159,  5.207, 5.3982, 5.5893, 5.7805, 5.9716, 6.1628, 6.3539, 6.5451, 6.7362, 6.9274, 7.1185, 7.3097, 7.5008, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56]
+    gear_ratio: 1
+    torque_control:
+        VS_KP: -38609162.66552
+        VS_KI: -4588245.18720
+    
+    
+    tower:  # (could remove some entries that don't apply for the tower)
+        dlsMax       :  5.0     # maximum node splitting section amount; can't be 0
+    
+        name      :  tower                     # [-]    an identifier (no longer has to be number)       
+        type      :  1                         # [-]    
+        rA        :  [ 0, 0,  15]              # [m]    end A coordinates
+        rB        :  [ 0, 0, 144.582]          # [m]    and B coordinates
+        shape     :  circ                      # [-]    circular or rectangular
+        gamma     :  0.0                       # [deg]   twist angle about the member's z-axis
+        
+        # --- outer shell including hydro---
+        stations  :  [ 15,  28,  28.001,  41,  41.001,  54,  54.001,  67,  67.001,  80,  80.001,  93,  93.001,  106,  106.001,  119,  119.001,  132,  132.001,  144.582 ]    # [-]    location of stations along axis. Will be normalized such that start value maps to rA and end value to rB
+        d         :  [ 10,  9.964,  9.964,  9.967,  9.967,  9.927,  9.927,  9.528,  9.528,  9.149,  9.149,  8.945,  8.945,  8.735,  8.735,  8.405,  8.405,  7.321,  7.321,  6.5 ]    # [m]    diameters if circular or side lengths if rectangular (can be pairs)
+        t         :  [ 0.082954,  0.082954,  0.083073,  0.083073,  0.082799,  0.082799,  0.0299,  0.0299,  0.027842,  0.027842,  0.025567,  0.025567,  0.022854,  0.022854,  0.02025,  0.02025,  0.018339,  0.018339,  0.021211,  0.021211 ]                     # [m]    wall thicknesses (scalar or list of same length as stations)
+        Cd        :  0.0                       # [-]    transverse drag coefficient       (optional, scalar or list of same length as stations)
+        Ca        :  0.0                       # [-]    transverse added mass coefficient (optional, scalar or list of same length as stations)
+        # (neglecting axial coefficients for now)
+        CdEnd     :  0.0                       # [-]    end axial drag coefficient        (optional, scalar or list of same length as stations)
+        CaEnd     :  0.0                       # [-]    end axial added mass coefficient  (optional, scalar or list of same length as stations)
+        rho_shell :  7850                      # [kg/m3]   material density 
+
+platform:
+
+  type         :  FOWT
+  potModMaster :   1      # [int] master switch for potMod variables; 0=keeps all member potMod vars the same, 1=turns all potMod vars to False (no HAMS), 2=turns all potMod vars to True (no strip)
+  dlsMax       :  5.0     # maximum node splitting section amount for platform members; can't be 0
+  qtfPath      :  'IEA-15-240-RWT-UMaineSemi.12d'      # path to the qtf file for the platform
+  rFair        :  58
+  zFair        :  -14
+
+  members:   # list all members here
+      
+    - name      :  center_column             # [-]    an identifier (no longer has to be number)       
+      type      :  2                         # [-]    
+      rA        :  [ 0, 0, -20]              # [m]    end A coordinates
+      rB        :  [ 0, 0,  15]              # [m]    and B coordinates
+      shape     :  circ                      # [-]    circular or rectangular
+      gamma     :  0.0                       # [deg]  twist angle about the member's z-axis
+      potMod    :  False                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
+      # --- outer shell including hydro---
+      stations  :  [0, 1]                    # [-]    location of stations along axis. Will be normalized such that start value maps to rA and end value to rB
+      d         :  10.0                      # [m]    diameters if circular or side lengths if rectangular (can be pairs)
+      t         :  0.05                      # [m]    wall thicknesses (scalar or list of same length as stations)
+      Cd        :  0.6                       # [-]    transverse drag coefficient       (optional, scalar or list of same length as stations)
+      Ca        :  0.93                      # [-]    transverse added mass coefficient (optional, scalar or list of same length as stations)
+      CdEnd     :  0.6                       # [-]    end axial drag coefficient        (optional, scalar or list of same length as stations)
+      CaEnd     :  1.0                       # [-]    end axial added mass coefficient  (optional, scalar or list of same length as stations)
+      rho_shell :  7850                      # [kg/m3] 
+      # --- handling of end caps or any internal structures if we need them ---
+      cap_stations :  [ 0    ]               # [m]  location along member of any inner structures (in same scaling as set by 'stations')
+      cap_t        :  [ 0.001  ]             # [m]  thickness of any internal structures
+      cap_d_in     :  [ 0    ]               # [m]  inner diameter of internal structures (0 for full cap/bulkhead, >0 for a ring shape)
+
+      
+    - name      :  outer_column              # [-]    an identifier (no longer has to be number)       
+      type      :  2                         # [-]    
+      rA        :  [51.75, 0, -20]           # [m]    end A coordinates
+      rB        :  [51.75, 0,  15]           # [m]    and B coordinates
+      heading   :  [ 60, 180, 300]           # [deg]  heading rotation of column about z axis (for repeated members)
+      shape     :  circ                      # [-]    circular or rectangular
+      gamma     :  0.0                       # [deg]  twist angle about the member's z-axis
+      potMod    :  False                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
+      # --- outer shell including hydro---
+      stations  :  [0, 35]                    # [-]    location of stations along axis. Will be normalized such that start value maps to rA and end value to rB
+      d         :  12.5                      # [m]    diameters if circular or side lengths if rectangular (can be pairs)
+      t         :  0.05                      # [m]    wall thicknesses (scalar or list of same length as stations)
+      Cd        :  0.6                       # [-]    transverse drag coefficient       (optional, scalar or list of same length as stations)
+      Ca        :  0.93                      # [-]    transverse added mass coefficient (optional, scalar or list of same length as stations)
+      CdEnd     :  1.0                       # [-]    end axial drag coefficient        (optional, scalar or list of same length as stations)
+      CaEnd     :  0.7 # value of 3.0 gives more heave response        # [-]    end axial added mass coefficient  (optional, scalar or list of same length as stations)
+      rho_shell :  7850                      # [kg/m3] 
+      # --- ballast ---
+      l_fill    :  1.4                       # [m]
+      rho_fill  :  5000                      # [kg/m3]
+      # --- handling of end caps or any internal structures if we need them ---
+      cap_stations :  [ 0    ]               # [m]  location along member of any inner structures (in same scaling as set by 'stations')
+      cap_t        :  [ 0.001  ]             # [m]  thickness of any internal structures
+      cap_d_in     :  [ 0    ]               # [m]  inner diameter of internal structures (0 for full cap/bulkhead, >0 for a ring shape)
+
+      
+    - name      :  pontoon                   # [-]    an identifier (no longer has to be number)       
+      type      :  2                         # [-]    
+      rA        :  [  5  , 0, -16.5]         # [m]    end A coordinates
+      rB        :  [ 45.5, 0, -16.5]         # [m]    and B coordinates
+      heading   :  [ 60, 180, 300]           # [deg]  heading rotation of column about z axis (for repeated members)
+      shape     :  rect                      # [-]    circular or rectangular
+      gamma     :  0.0                       # [deg]  twist angle about the member's z-axis
+      potMod    :  False                     # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
+      # --- outer shell including hydro---
+      stations  :  [0, 40.5]                    # [-]    location of stations along axis. Will be normalized such that start value maps to rA and end value to rB
+      d         :  [12.4, 7.0]               # [m]    diameters if circular or side lengths if rectangular (can be pairs)
+      t         :  0.05                      # [m]    wall thicknesses (scalar or list of same length as stations)
+      Cd        :  [1.5, 2.2 ]               # [-]    transverse drag coefficient       (optional, scalar or list of same length as stations)
+      Ca        :  [2.2, 0.2 ]               # [-]    transverse added mass coefficient (optional, scalar or list of same length as stations)
+      CdEnd     :  0.0                       # [-]    end axial drag coefficient        (optional, scalar or list of same length as stations)
+      CaEnd     :  0.0                       # [-]    end axial added mass coefficient  (optional, scalar or list of same length as stations)
+      rho_shell :  7850                      # [kg/m3]
+      l_fill    :  40.5                      # [m]
+      rho_fill  :  1025.0                    # [kg/m3]
+      
+      
+    - name      :  upper_support             # [-]    an identifier (no longer has to be number)       
+      type      :  2                         # [-]    
+      rA        :  [  5  , 0, 14.545]        # [m]    end A coordinates
+      rB        :  [ 45.5, 0, 14.545]        # [m]    and B coordinates
+      heading   :  [ 60, 180, 300]           # [deg]  heading rotation of column about z axis (for repeated members)
+      shape     :  circ                      # [-]    circular or rectangular
+      gamma     :  0.0                       # [deg]  twist angle about the member's z-axis
+      potMod    :  False                     # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
+      # --- outer shell including hydro---
+      stations  :  [0, 1]                    # [-]    location of stations along axis. Will be normalized such that start value maps to rA and end value to rB
+      d         :  0.91                      # [m]    diameters if circular or side lengths if rectangular (can be pairs)
+      t         :  0.01                      # [m]    wall thicknesses (scalar or list of same length as stations)
+      Cd        :  0.0                       # [-]    transverse drag coefficient       (optional, scalar or list of same length as stations)
+      Ca        :  0.0                       # [-]    transverse added mass coefficient (optional, scalar or list of same length as stations)
+      CdEnd     :  0.0                       # [-]    end axial drag coefficient        (optional, scalar or list of same length as stations)
+      CaEnd     :  0.0                       # [-]    end axial added mass coefficient  (optional, scalar or list of same length as stations)
+      rho_shell :  7850                      # [kg/m3]
+
+
+# ----- Mooring system -----
+
+# Mooring system descriptions (each for an individual FOWT with no sharing)
+mooring_systems:
+ 
+    ms1:
+        name: 2-line semi-taut polyester mooring system with a third line shared
+        
+        keys: [MooringConfigID,  heading, anchorType, lengthAdjust] 
+        data:
+          - [  semitaut-poly_1,  150 ,   suction1,   0 ]
+          - [  semitaut-poly_1,  270 ,   suction1,   0 ]
+          - [  semitaut-poly_1,   30 ,   suction1,   0 ]
+
+
+# Mooring line configurations
+mooring_line_configs:
+
+    semitaut-poly_1:  # mooring line configuration identifier
+    
+        name: Semitaut polyester configuration 1  # descriptive name
+        
+        span: 642
+        
+        sections:                 #in order from anchor to fairlead
+          - mooringFamily: chain      # ID of a mooring line section type
+            d_nom: .1549
+            length: 497.7            # [m] usntretched length of line section
+            adjustable: True      # flags that this section could be adjusted to accommodate different spacings...
+          - connectorType: h_link   
+          - mooringFamily: polyester        # ID of a mooring line section type
+            d_nom: .182
+            length: 199.8           # [m] length (unstretched)
+
+# Mooring connector properties
+mooring_connector_types:
+    
+    h_link:
+        m  : 140    # [kg]  component mass
+        v : 0.13   # [m^3] component volumetric displacement
+
+# Anchor type properties
+anchor_types:
+
+    drag-embedment1:
+        type   :   DEA   # type of anchor
+        A      :    10   # net area of anchor's fluke [m^2]
+        zlug   :     8   # embedded depth of padeye [m]
+
+    suction1:
+        type   :  suction
+        L      :     8.40  # length of pile [m]
+        D      :     2.45  # diameter of pile [m]
+        zlug   :     5.32  # embedded depth of padeye [m]
+
diff --git a/examples/OntologySample600m_shared.yaml b/examples/OntologySample600m_shared.yaml
index 7052f83f..a26591dd 100644
--- a/examples/OntologySample600m_shared.yaml
+++ b/examples/OntologySample600m_shared.yaml
@@ -37,7 +37,7 @@ site:
         
         type_array:
           - [mud_soft ,  mud_firm ,   mud_soft]  
-          - [mud_soft ,  mud_soft     ,   mud_soft]  
+          - [mud_soft ,  mud_soft ,   mud_soft]  
           - [mud_soft ,  mud_firm ,   mud_soft]  
 
         soil_types:   # dictionary-based approach
@@ -1224,7 +1224,7 @@ platforms:
         rB        :  [ 0, 0,  15]              # [m]    and B coordinates
         shape     :  circ                      # [-]    circular or rectangular
         gamma     :  0.0                       # [deg]  twist angle about the member's z-axis
-        potMod    :  True                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
+        potMod    :  False                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
         # --- outer shell including hydro---
         stations  :  [0, 1]                    # [-]    location of stations along axis. Will be normalized such that start value maps to rA and end value to rB
         d         :  10.0                      # [m]    diameters if circular or side lengths if rectangular (can be pairs)
@@ -1247,7 +1247,7 @@ platforms:
         heading   :  [ 60, 180, 300]           # [deg]  heading rotation of column about z axis (for repeated members)
         shape     :  circ                      # [-]    circular or rectangular
         gamma     :  0.0                       # [deg]  twist angle about the member's z-axis
-        potMod    :  True                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
+        potMod    :  False                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
         # --- outer shell including hydro---
         stations  :  [0, 35]                   # [-]    location of stations along axis. Will be normalized such that start value maps to rA and end value to rB
         d         :  12.5                      # [m]    diameters if circular or side lengths if rectangular (can be pairs)
@@ -1562,17 +1562,17 @@ mooring_connector_types:
 # Anchor type properties
 anchor_types:
   suction_pile1:
-    type   :  suction_pile
+    type   :  suction
     L      :     16.4  # length of pile [m]
     D      :     5.45  # diameter of pile [m]
     zlug   :     9.32  # embedded depth of padeye [m]
   d-g_pile1:
-    type   :  dandg_pile
+    type   :  dandg
     L      :     50 # length of pile [m]
     D      :     3 # diameter of pile [m]
     zlug   :     0 # embedded depth [m]
   driven_pile1:
-    type   :  driven_pile
+    type   :  driven
     L      :     20 # pile length [m]
     D      :     1.5 # pile diameter [m]
     zlug   :     3 # embedded depth [m
diff --git a/examples/README.md b/examples/README.md
index 2a14129a..e5b846d4 100644
--- a/examples/README.md
+++ b/examples/README.md
@@ -54,7 +54,3 @@ This example shows how to make an FAModel project with platforms, anchors, and m
 
 There are many ways to manually fill in a project class with array components and site information.
 In this case, site information is loaded in from files, and a platform, moorings, and anchors are loaded in from a moorpy array (which comes from a MoorDyn file). Further platforms are added by using the duplicate() function to "copy" the platform and associated moorings and anchors and place in a specific location.
-
-## Anchor capacity examples
-This example calculates the anchor capacity for each different type of anchor, determines the load on the anchor, and then determines the safety factor. 
-This is provided to show an example of what information is required for each anchor type, and how results can differ for different anchor types.
\ No newline at end of file
diff --git a/examples/checkyaml.yaml b/examples/checkyaml.yaml
new file mode 100644
index 00000000..59a84805
--- /dev/null
+++ b/examples/checkyaml.yaml
@@ -0,0 +1,1331 @@
+site:
+  seabed:
+    x: [-10901.0, 0.0, 10000.0]
+    y: [-10900.0, 0.0, 10000.0]
+    type_array:
+    - [mud_soft, mud_firm, mud_soft]
+    - [mud_soft, mud_firm, mud_soft]
+    - [mud_soft, mud_firm, mud_soft]
+    soil_types:
+      mud_soft:
+        layers:
+        - Su0: [2.39]
+          k: [1.41]
+          depth: [0]
+          top: 0
+          bottom: 50
+          soil_type: mud_soft
+        Su0: [2.39]
+        k: [1.41]
+        alpha: [0.7]
+        gamma: [8.7]
+        phi: [0.0]
+        UCS: [7.0]
+        Em: [50.0]
+      mud_firm:
+        layers:
+        - Su0: [23.94]
+          k: [2.67]
+          depth: [0]
+          top: 0
+          bottom: 50
+          soil_type: mud_firm
+        Su0: [2.39]
+        k: [1.41]
+        alpha: [0.7]
+        gamma: [8.7]
+        phi: [0.0]
+        UCS: [7.0]
+        Em: [50.0]
+  bathymetry:
+    x: [-3000.0, 3500.0, 10000.0]
+    y: [-3000.0, 3500.0, 10000.0]
+    depths:
+    - [200.1, 207.25625, 240.0]
+    - [200.34375, 206.133984375, 208.3125]
+    - [210.7, 196.29375000000002, 185.0]
+  boundaries:
+    x_y:
+    - [-2000.0, -2000.0]
+    - [-2000.0, 8000.0]
+    - [8000.0, 8000.0]
+    - [8000.0, -2000.0]
+    - [-2000.0, -2000.0]
+  general:
+    water_depth: 200.0
+    rho_air: 1.225
+    rho_water: 1025.0
+    mu_air: 1.81e-05
+array:
+  keys: [ID, topsideID, platformID, mooringID, x_location, y_location, 
+      z_location, heading_adjust]
+  data:
+  - [fowt0, 1, 1, ms0, -600.0, -800.0, 0.0, 0.0]
+  - [fowt1, 1, 1, ms0, 1100.0, -800.0, 0.0, 0.0]
+  - [fowt2, 1, 1, ms0, 2800.0, -800.0, 0.0, 0.0]
+  - [fowt3, 1, 1, ms0, 4500.0, -800.0, 0.0, 0.0]
+  - [fowt4, 1, 1, ms0, 6200.0, -800.0, 0.0, 0.0]
+  - [fowt5, 1, 1, ms0, -600.0, 1100.0, 0.0, 0.0]
+  - [fowt6, 1, 1, ms0, 1100.0, 1100.0, 0.0, 0.0]
+  - [fowt7, 1, 1, ms0, 2800.0, 1100.0, 0.0, 0.0]
+  - [fowt8, 1, 1, ms0, 4500.0, 1100.0, 0.0, 0.0]
+  - [fowt9, 1, 1, ms0, 6200.0, 1100.0, 0.0, 0.0]
+  - [fowt10, 1, 1, ms0, -600.0, 3000.0, 0.0, 0.0]
+  - [fowt11, 1, 1, ms0, 1100.0, 3000.0, 0.0, 0.0]
+  - [fowt12, 1, 1, ms0, 2800.0, 3000.0, 0.0, 0.0]
+  - [fowt13, 1, 1, ms0, 4500.0, 3000.0, 0.0, 0.0]
+  - [fowt14, 1, 1, ms0, 6200.0, 3000.0, 0.0, 0.0]
+  - [fowt15, 1, 1, ms0, -600.0, 4900.0, 0.0, 0.0]
+  - [fowt16, 1, 1, ms0, 1100.0, 4900.0, 0.0, 0.0]
+  - [fowt17, 1, 1, ms0, 2800.0, 4900.0, 0.0, 0.0]
+  - [fowt18, 1, 1, ms0, 4500.0, 4900.0, 0.0, 0.0]
+  - [fowt19, 1, 1, ms0, 6200.0, 4900.0, 0.0, 0.0]
+  - [fowt20, 1, 1, ms0, -600.0, 6800.0, 0.0, 0.0]
+  - [fowt21, 1, 1, ms0, 1100.0, 6800.0, 0.0, 0.0]
+  - [fowt22, 1, 1, ms0, 2800.0, 6800.0, 0.0, 0.0]
+  - [fowt23, 1, 1, ms0, 4500.0, 6800.0, 0.0, 0.0]
+  - [fowt24, 1, 1, ms0, 6200.0, 6800.0, 0.0, 0.0]
+platform:
+  type: FOWT
+  potModMaster: 1
+  dlsMax: 5.0
+  qtfPath: IEA-15-240-RWT-UMaineSemi.12d
+  rFair: 58
+  zFair: -14
+  members:
+  - name: center_column
+    type: 2
+    rA: [0, 0, -20]
+    rB: [0, 0, 15]
+    shape: circ
+    gamma: 0.0
+    potMod: false
+    stations: [0, 1]
+    d: 10.0
+    t: 0.05
+    Cd: 0.6
+    Ca: 0.93
+    CdEnd: 0.6
+    CaEnd: 1.0
+    rho_shell: 7850
+    cap_stations: [0]
+    cap_t: [0.001]
+    cap_d_in: [0]
+    dlsMax: 5.0
+    headings: 0.0
+  - name: outer_column
+    type: 2
+    rA: [51.75, 0, -20]
+    rB: [51.75, 0, 15]
+    heading: [60, 180, 300]
+    shape: circ
+    gamma: 0.0
+    potMod: false
+    stations: [0, 35]
+    d: 12.5
+    t: 0.05
+    Cd: 0.6
+    Ca: 0.93
+    CdEnd: 1.0
+    CaEnd: 0.7
+    rho_shell: 7850
+    l_fill: 1.4
+    rho_fill: 5000
+    cap_stations: [0]
+    cap_t: [0.001]
+    cap_d_in: [0]
+    dlsMax: 5.0
+    headings: [60.0, 180.0, 300.0]
+  - name: pontoon
+    type: 2
+    rA: [5, 0, -16.5]
+    rB: [45.5, 0, -16.5]
+    heading: [60, 180, 300]
+    shape: rect
+    gamma: 0.0
+    potMod: false
+    stations: [0, 40.5]
+    d: [12.4, 7.0]
+    t: 0.05
+    Cd: [1.5, 2.2]
+    Ca: [2.2, 0.2]
+    CdEnd: 0.0
+    CaEnd: 0.0
+    rho_shell: 7850
+    l_fill: 40.5
+    rho_fill: 1025.0
+    dlsMax: 5.0
+    headings: [60.0, 180.0, 300.0]
+  - name: upper_support
+    type: 2
+    rA: [5, 0, 14.545]
+    rB: [45.5, 0, 14.545]
+    heading: [60, 180, 300]
+    shape: circ
+    gamma: 0.0
+    potMod: false
+    stations: [0, 1]
+    d: 0.91
+    t: 0.01
+    Cd: 0.0
+    Ca: 0.0
+    CdEnd: 0.0
+    CaEnd: 0.0
+    rho_shell: 7850
+    dlsMax: 5.0
+    headings: [60.0, 180.0, 300.0]
+topsides:
+- type: Turbine
+  mRNA: 991000
+  IxRNA: 0
+  IrRNA: 0
+  xCG_RNA: 0
+  hHub: 150.0
+  Fthrust: '1500.0E3'
+  I_drivetrain: 318628138.0
+  nBlades: 3
+  Zhub: 150.0
+  Rhub: 3.97
+  precone: 4.0
+  shaft_tilt: 6.0
+  overhang: -12.0313
+  aeroMod: 1
+  blade:
+    precurveTip: -3.9999999999999964
+    presweepTip: 0.0
+    Rtip: 120.96999999936446
+    geometry:
+    - [8.004, 5.228, 15.474, 0.035, 0.0]
+    - [12.039, 5.321, 14.692, 0.084, 0.0]
+    - [16.073, 5.458, 13.33, 0.139, 0.0]
+    - [20.108, 5.602, 11.644, 0.192, 0.0]
+    - [24.142, 5.718, 9.927, 0.232, 0.0]
+    - [28.177, 5.767, 8.438, 0.25, 0.0]
+    - [32.211, 5.713, 7.301, 0.25, 0.0]
+    - [36.246, 5.536, 6.232, 0.246, 0.0]
+    - [40.28, 5.291, 5.23, 0.24, 0.0]
+    - [44.315, 5.035, 4.348, 0.233, 0.0]
+    - [48.349, 4.815, 3.606, 0.218, 0.0]
+    - [52.384, 4.623, 2.978, 0.178, 0.0]
+    - [56.418, 4.432, 2.423, 0.1, 0.0]
+    - [60.453, 4.245, 1.924, 0.0, 0.0]
+    - [64.487, 4.065, 1.467, -0.112, 0.0]
+    - [68.522, 3.896, 1.056, -0.244, 0.0]
+    - [72.556, 3.735, 0.692, -0.415, 0.0]
+    - [76.591, 3.579, 0.355, -0.62, 0.0]
+    - [80.625, 3.425, 0.019, -0.846, 0.0]
+    - [84.66, 3.268, -0.358, -1.08, 0.0]
+    - [88.694, 3.112, -0.834, -1.33, 0.0]
+    - [92.729, 2.957, -1.374, -1.602, 0.0]
+    - [96.763, 2.8, -1.848, -1.895, 0.0]
+    - [100.798, 2.637, -2.136, -2.202, 0.0]
+    - [104.832, 2.464, -2.172, -2.523, 0.0]
+    - [108.867, 2.283, -2.108, -2.864, 0.0]
+    - [112.901, 2.096, -1.953, -3.224, 0.0]
+    - [116.936, 1.902, -1.662, -3.605, 0.0]
+    airfoils:
+    - [0.0, circular]
+    - [0.02, circular]
+    - [0.15, SNL-FFA-W3-500]
+    - [0.24517, FFA-W3-360]
+    - [0.32884, FFA-W3-330blend]
+    - [0.43918, FFA-W3-301]
+    - [0.53767, FFA-W3-270blend]
+    - [0.63821, FFA-W3-241]
+    - [0.77174, FFA-W3-211]
+    - [1.0, FFA-W3-211]
+  airfoils:
+  - name: circular
+    relative_thickness: 1.0
+    data:
+    - [-179.9087, 0.0001, 0.35, -0.0001]
+    - [179.9087, 0.0001, 0.35, -0.0001]
+  - name: SNL-FFA-W3-500
+    relative_thickness: 0.5
+    data:
+    - [-179.966, 0.0, 0.0844, 0.0]
+    - [-170.0, 0.4419, 0.0844, 0.3125]
+    - [-160.0002, 0.8837, 0.1268, 0.2831]
+    - [-149.9998, 0.9674, 0.2927, 0.2632]
+    - [-139.9999, 0.7801, 0.497, 0.2048]
+    - [-130.0001, 0.6293, 0.7161, 0.1932]
+    - [-120.0003, 0.4785, 0.9246, 0.2008]
+    - [-109.9999, 0.3189, 1.0985, 0.2136]
+    - [-100.0, 0.1553, 1.2182, 0.2221]
+    - [-90.0002, 0.0, 1.2707, 0.2198]
+    - [-79.9998, -0.1553, 1.2182, 0.196]
+    - [-70.0, -0.3189, 1.0985, 0.1635]
+    - [-60.0001, -0.4784, 0.9246, 0.1285]
+    - [-49.9997, -0.6293, 0.7161, 0.0965]
+    - [-39.9999, -0.7801, 0.497, 0.0716]
+    - [-30.0001, -0.9674, 0.2927, 0.0522]
+    - [-20.0002, -1.0281, 0.1499, -0.0063]
+    - [-19.7499, -1.0243, 0.1472, -0.0089]
+    - [-19.2502, -1.0052, 0.1447, -0.0099]
+    - [-18.9999, -0.9971, 0.1433, -0.0105]
+    - [-18.75, -1.0052, 0.1403, -0.011]
+    - [-18.5002, -0.9995, 0.1386, -0.0116]
+    - [-18.2499, -0.9908, 0.1373, -0.012]
+    - [-18.0, -0.9815, 0.136, -0.0126]
+    - [-17.4998, -0.9764, 0.1322, -0.0135]
+    - [-17.25, -0.9705, 0.1306, -0.0139]
+    - [-17.0002, -0.9655, 0.129, -0.0143]
+    - [-16.7498, -0.9662, 0.1268, -0.0147]
+    - [-16.5, -0.9544, 0.1258, -0.0151]
+    - [-16.2502, -0.9444, 0.1246, -0.0155]
+    - [-15.9998, -0.9405, 0.1229, -0.0158]
+    - [-15.75, -0.9433, 0.1206, -0.0161]
+    - [-15.5002, -0.933, 0.1195, -0.0164]
+    - [-15.2498, -0.9211, 0.1185, -0.0168]
+    - [-14.7502, -0.9158, 0.115, -0.0173]
+    - [-14.4998, -0.907, 0.1138, -0.0175]
+    - [-14.25, -0.8959, 0.1127, -0.0178]
+    - [-14.0002, -0.8926, 0.111, -0.0181]
+    - [-13.7498, -0.8808, 0.11, -0.0184]
+    - [-13.5, -0.8722, 0.1089, -0.0186]
+    - [-13.2502, -0.866, 0.1075, -0.0188]
+    - [-12.9998, -0.8626, 0.1059, -0.0188]
+    - [-12.75, -0.8489, 0.1051, -0.0192]
+    - [-12.5002, -0.8363, 0.1042, -0.0194]
+    - [-12.2498, -0.8363, 0.1023, -0.0194]
+    - [-12.0, -0.8271, 0.1013, -0.0196]
+    - [-11.7502, -0.8141, 0.1004, -0.0198]
+    - [-11.4998, -0.8004, 0.0997, -0.02]
+    - [-11.0002, -0.789, 0.0971, -0.0199]
+    - [-10.7498, -0.7862, 0.0956, -0.0196]
+    - [-10.5, -0.7747, 0.0948, -0.0194]
+    - [-10.2502, -0.7701, 0.094, -0.0184]
+    - [-9.9998, -0.7674, 0.0925, -0.0183]
+    - [-9.75, -0.7506, 0.0917, -0.0192]
+    - [-9.5002, -0.729, 0.0912, -0.0205]
+    - [-9.2498, -0.7095, 0.0902, -0.0224]
+    - [-9.0, -0.6855, 0.0895, -0.0247]
+    - [-8.7502, -0.659, 0.0891, -0.0267]
+    - [-8.4998, -0.6319, 0.0887, -0.0287]
+    - [-8.25, -0.6019, 0.0879, -0.032]
+    - [-8.0002, -0.5718, 0.0875, -0.0345]
+    - [-7.7498, -0.5424, 0.0873, -0.0367]
+    - [-7.5, -0.5098, 0.0868, -0.0399]
+    - [-7.2502, -0.4767, 0.0864, -0.043]
+    - [-6.9998, -0.4454, 0.0862, -0.0453]
+    - [-6.75, -0.4142, 0.086, -0.0476]
+    - [-6.5002, -0.3791, 0.0856, -0.051]
+    - [-6.2498, -0.346, 0.0853, -0.0538]
+    - [-6.0, -0.3144, 0.0852, -0.056]
+    - [-5.7502, -0.2817, 0.085, -0.0586]
+    - [-5.4998, -0.2461, 0.0847, -0.0619]
+    - [-5.25, -0.2133, 0.0846, -0.0644]
+    - [-5.0002, -0.1827, 0.0845, -0.0663]
+    - [-4.7498, -0.1494, 0.0843, -0.0688]
+    - [-4.5, -0.1158, 0.0842, -0.0715]
+    - [-4.2502, -0.0837, 0.084, -0.0737]
+    - [-3.9998, -0.0529, 0.084, -0.0756]
+    - [-3.75, -0.0225, 0.0839, -0.0774]
+    - [-3.5002, 0.0089, 0.0838, -0.0793]
+    - [-3.2498, 0.0392, 0.0838, -0.0811]
+    - [-3.0, 0.0686, 0.0838, -0.0826]
+    - [-2.7502, 0.0974, 0.0838, -0.0838]
+    - [-2.4998, 0.126, 0.0838, -0.0852]
+    - [-2.25, 0.1555, 0.0838, -0.0867]
+    - [-2.0002, 0.1853, 0.0838, -0.0883]
+    - [-1.7498, 0.2146, 0.0837, -0.0897]
+    - [-1.5, 0.243, 0.0837, -0.091]
+    - [-1.2502, 0.2713, 0.0838, -0.0921]
+    - [-0.9998, 0.3006, 0.0838, -0.0936]
+    - [-0.75, 0.3295, 0.0838, -0.0949]
+    - [-0.5002, 0.3578, 0.0838, -0.0961]
+    - [-0.2498, 0.3857, 0.0838, -0.0972]
+    - [0.0, 0.4135, 0.0838, -0.0983]
+    - [0.2298, 0.4425, 0.0839, -0.0995]
+    - [0.4698, 0.4715, 0.0839, -0.1008]
+    - [0.7002, 0.5003, 0.0839, -0.1019]
+    - [0.9402, 0.5286, 0.084, -0.1029]
+    - [1.17, 0.5567, 0.084, -0.104]
+    - [1.3997, 0.585, 0.0841, -0.105]
+    - [1.6398, 0.6135, 0.0841, -0.1061]
+    - [1.8701, 0.6417, 0.0842, -0.1072]
+    - [2.1102, 0.6697, 0.0842, -0.1082]
+    - [2.34, 0.6975, 0.0843, -0.1091]
+    - [2.5697, 0.7251, 0.0843, -0.11]
+    - [2.8098, 0.7528, 0.0844, -0.1109]
+    - [3.0401, 0.7807, 0.0845, -0.1119]
+    - [3.2802, 0.8083, 0.0846, -0.1128]
+    - [3.5099, 0.8358, 0.0846, -0.1137]
+    - [3.7403, 0.8631, 0.0847, -0.1146]
+    - [3.9798, 0.8902, 0.0847, -0.1153]
+    - [4.2101, 0.9173, 0.0848, -0.1161]
+    - [4.4502, 0.9444, 0.0849, -0.117]
+    - [4.6799, 0.9713, 0.085, -0.1178]
+    - [4.9102, 0.9981, 0.0851, -0.1185]
+    - [5.1497, 1.0249, 0.0852, -0.1192]
+    - [5.3801, 1.0515, 0.0853, -0.1199]
+    - [5.6201, 1.0779, 0.0853, -0.1206]
+    - [5.8499, 1.1041, 0.0854, -0.1212]
+    - [6.0802, 1.1302, 0.0856, -0.1218]
+    - [6.3197, 1.156, 0.0857, -0.1224]
+    - [6.5501, 1.1818, 0.0858, -0.123]
+    - [6.7901, 1.2076, 0.0859, -0.1235]
+    - [7.0199, 1.2334, 0.086, -0.124]
+    - [7.2502, 1.2589, 0.0861, -0.1245]
+    - [7.4903, 1.2841, 0.0862, -0.125]
+    - [7.72, 1.3088, 0.0864, -0.1254]
+    - [7.9601, 1.3331, 0.0865, -0.1257]
+    - [8.1899, 1.357, 0.0867, -0.1259]
+    - [8.4202, 1.381, 0.0869, -0.1262]
+    - [8.6603, 1.4054, 0.087, -0.1265]
+    - [8.89, 1.4295, 0.0871, -0.1267]
+    - [9.1198, 1.4531, 0.0873, -0.127]
+    - [9.8801, 1.5154, 0.0879, -0.1265]
+    - [10.6398, 1.5749, 0.0886, -0.1256]
+    - [11.4001, 1.6151, 0.0895, -0.1214]
+    - [12.1501, 1.6443, 0.0912, -0.1163]
+    - [12.9099, 1.6824, 0.093, -0.1133]
+    - [13.6702, 1.7146, 0.0954, -0.1107]
+    - [14.4202, 1.7362, 0.0989, -0.108]
+    - [15.1799, 1.7627, 0.1024, -0.1063]
+    - [15.9403, 1.7706, 0.1076, -0.1042]
+    - [16.6903, 1.7639, 0.1144, -0.1025]
+    - [17.45, 1.7604, 0.1211, -0.1013]
+    - [18.2097, 1.7251, 0.131, -0.1001]
+    - [18.9701, 1.7035, 0.1399, -0.0998]
+    - [19.7201, 1.6784, 0.1492, -0.1001]
+    - [20.4798, 1.6505, 0.1591, -0.1016]
+    - [21.2401, 1.6227, 0.1691, -0.1036]
+    - [21.9901, 1.6067, 0.1778, -0.1064]
+    - [22.7499, 1.5972, 0.1858, -0.1099]
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+    - [32.0, 1.39203, 0.35131, -0.19417]
+    - [36.1429, 1.27731, 0.43913, -0.21792]
+    - [40.2857, 1.17689, 0.53115, -0.24115]
+    - [44.4286, 1.0835, 0.62546, -0.25734]
+    - [48.5714, 0.99253, 0.7201, -0.27354]
+    - [52.7143, 0.90112, 0.8131, -0.28862]
+    - [56.8571, 0.8076, 0.90255, -0.30311]
+    - [61.0, 0.71119, 0.98659, -0.31757]
+    - [65.1429, 0.61175, 1.06348, -0.33194]
+    - [69.2857, 0.50971, 1.13162, -0.34631]
+    - [73.4286, 0.40589, 1.18963, -0.36014]
+    - [77.5714, 0.30146, 1.23629, -0.37385]
+    - [81.7143, 0.19788, 1.27067, -0.38681]
+    - [85.8571, 0.09679, 1.29204, -0.39872]
+    - [90.0, 0.0, 1.3, -0.41063]
+    - [94.1429, -0.06775, 1.29204, -0.41683]
+    - [98.2857, -0.13851, 1.27067, -0.42303]
+    - [102.4286, -0.21103, 1.23629, -0.42628]
+    - [106.5714, -0.28412, 1.18963, -0.42745]
+    - [110.7143, -0.3568, 1.13162, -0.42817]
+    - [114.8571, -0.42823, 1.06348, -0.42673]
+    - [119.0, -0.49783, 0.98659, -0.42528]
+    - [123.1429, -0.56532, 0.90255, -0.42535]
+    - [127.2857, -0.63079, 0.8131, -0.42589]
+    - [131.4286, -0.69477, 0.7201, -0.42974]
+    - [135.5714, -0.75845, 0.62546, -0.43985]
+    - [139.7143, -0.82382, 0.53115, -0.44996]
+    - [143.8571, -0.89412, 0.43913, -0.46839]
+    - [148.0, -0.97442, 0.35131, -0.48743]
+    - [150.2857, -0.90482, 0.30532, -0.49447]
+    - [152.5714, -0.83522, 0.26146, -0.47732]
+    - [154.8571, -0.76562, 0.22, -0.46017]
+    - [157.1429, -0.69601, 0.18121, -0.44302]
+    - [159.4286, -0.62641, 0.14533, -0.42586]
+    - [161.7143, -0.55681, 0.11258, -0.43502]
+    - [164.0, -0.48721, 0.08319, -0.45294]
+    - [166.2857, -0.41761, 0.05732, -0.47087]
+    - [168.5714, -0.34801, 0.04638, -0.4888]
+    - [170.8571, -0.27841, 0.04114, -0.45714]
+    - [173.1429, -0.2088, 0.03702, -0.34286]
+    - [175.4286, -0.1392, 0.03406, -0.22857]
+    - [177.7143, -0.0696, 0.03228, -0.11429]
+    - [179.9087, 0.0, 0.03169, 0.0]
+  - name: FFA-W3-360
+    relative_thickness: 0.36
+    data:
+    - [-179.9087, 0.0, 0.03715, 0.0]
+    - [-177.7143, 0.07178, 0.03774, 0.09143]
+    - [-175.4286, 0.14356, 0.03951, 0.18286]
+    - [-173.1429, 0.21534, 0.04245, 0.27429]
+    - [-170.8572, 0.28713, 0.04653, 0.36571]
+    - [-168.5716, 0.35891, 0.05174, 0.40313]
+    - [-166.2857, 0.43069, 0.06068, 0.40814]
+    - [-164.0, 0.50247, 0.08651, 0.41315]
+    - [-161.7145, 0.57425, 0.11586, 0.41816]
+    - [-159.4284, 0.64603, 0.14856, 0.42627]
+    - [-157.1428, 0.71781, 0.18439, 0.4437]
+    - [-154.8573, 0.7896, 0.22313, 0.46114]
+    - [-152.5714, 0.86138, 0.26453, 0.47857]
+    - [-150.2857, 0.93316, 0.30832, 0.496]
+    - [-148.0, 1.00494, 0.35424, 0.4883]
+    - [-143.8571, 0.91898, 0.44192, 0.46784]
+    - [-139.7143, 0.84406, 0.53379, 0.44803]
+    - [-135.5714, 0.77483, 0.62793, 0.43697]
+    - [-131.4286, 0.7079, 0.72238, 0.42591]
+    - [-127.2857, 0.64116, 0.8152, 0.4215]
+    - [-123.1429, 0.57335, 0.90444, 0.42058]
+    - [-119.0, 0.50388, 0.98826, 0.42024]
+    - [-114.8571, 0.43261, 1.06493, 0.42168]
+    - [-110.7143, 0.35981, 1.13285, 0.42312]
+    - [-106.5714, 0.28603, 1.19061, 0.42258]
+    - [-102.4286, 0.21209, 1.23704, 0.42163]
+    - [-98.2857, 0.13899, 1.27116, 0.41864]
+    - [-94.1429, 0.06787, 1.29229, 0.41277]
+    - [-90.0, 0.0, 1.3, 0.4069]
+    - [-85.8571, -0.06787, 1.29229, 0.39426]
+    - [-81.7143, -0.13899, 1.27116, 0.38162]
+    - [-77.5714, -0.21209, 1.23704, 0.36676]
+    - [-73.4286, -0.28603, 1.19061, 0.35033]
+    - [-69.2857, -0.35981, 1.13285, 0.33362]
+    - [-65.1429, -0.43261, 1.06493, 0.31561]
+    - [-61.0, -0.50388, 0.98826, 0.29759]
+    - [-56.8571, -0.57335, 0.90444, 0.27989]
+    - [-52.7143, -0.64116, 0.8152, 0.2623]
+    - [-48.5714, -0.7079, 0.72238, 0.24491]
+    - [-44.4286, -0.77483, 0.62793, 0.22794]
+    - [-40.2857, -0.84406, 0.53379, 0.21097]
+    - [-36.1429, -0.91898, 0.44192, 0.13525]
+    - [-32.0, -1.00494, 0.35424, 0.05517]
+    - [-28.0, -1.11306, 0.20494, 0.03211]
+    - [-24.0, -1.05425, 0.15434, 0.01268]
+    - [-20.0, -0.98247, 0.10967, -0.00282]
+    - [-18.0, -0.94173, 0.09249, -0.00741]
+    - [-16.0, -0.89333, 0.07597, -0.01107]
+    - [-14.0, -0.85472, 0.06054, -0.0125]
+    - [-12.0, -0.82348, 0.04641, -0.01177]
+    - [-10.0, -0.79541, 0.03441, -0.01082]
+    - [-8.0, -0.6365, 0.02548, -0.02769]
+    - [-6.0, -0.39095, 0.01994, -0.05107]
+    - [-4.0, -0.13071, 0.01653, -0.07148]
+    - [-2.0, 0.16173, 0.01507, -0.09179]
+    - [-1.0, 0.31121, 0.01477, -0.10119]
+    - [0.0, 0.45956, 0.01465, -0.10988]
+    - [1.0, 0.60566, 0.01466, -0.11776]
+    - [2.0, 0.74868, 0.01481, -0.12477]
+    - [3.0, 0.88862, 0.01507, -0.13098]
+    - [4.0, 1.02544, 0.01544, -0.13648]
+    - [5.0, 1.15878, 0.01593, -0.1413]
+    - [6.0, 1.28822, 0.01654, -0.1454]
+    - [7.0, 1.41282, 0.01731, -0.14875]
+    - [8.0, 1.5309, 0.01831, -0.15118]
+    - [9.0, 1.64065, 0.01963, -0.15262]
+    - [10.0, 1.73926, 0.0215, -0.1531]
+    - [11.0, 1.81971, 0.02445, -0.15254]
+    - [12.0, 1.87065, 0.02966, -0.15121]
+    - [13.0, 1.89221, 0.0377, -0.14969]
+    - [14.0, 1.8791, 0.04824, -0.14562]
+    - [15.0, 1.88111, 0.05838, -0.14358]
+    - [16.0, 1.86359, 0.06992, -0.14095]
+    - [18.0, 1.73324, 0.10166, -0.13711]
+    - [20.0, 1.59357, 0.13916, -0.14082]
+    - [24.0, 1.46708, 0.21002, -0.15693]
+    - [28.0, 1.44834, 0.282, -0.17979]
+    - [32.0, 1.43563, 0.35424, -0.20147]
+    - [36.1429, 1.31283, 0.44192, -0.22409]
+    - [40.2857, 1.2058, 0.53379, -0.24619]
+    - [44.4286, 1.1069, 0.62793, -0.26133]
+    - [48.5714, 1.01129, 0.72238, -0.27648]
+    - [52.7143, 0.91594, 0.8152, -0.29062]
+    - [56.8571, 0.81907, 0.90444, -0.30424]
+    - [61.0, 0.71982, 0.98826, -0.31787]
+    - [65.1429, 0.61801, 1.06493, -0.33154]
+    - [69.2857, 0.51401, 1.13285, -0.34522]
+    - [73.4286, 0.40862, 1.19061, -0.35846]
+    - [77.5714, 0.30299, 1.23704, -0.37161]
+    - [81.7143, 0.19855, 1.27116, -0.38405]
+    - [85.8571, 0.09695, 1.29229, -0.39547]
+    - [90.0, 0.0, 1.3, -0.4069]
+    - [94.1429, -0.06787, 1.29229, -0.41277]
+    - [98.2857, -0.13899, 1.27116, -0.41864]
+    - [102.4286, -0.21209, 1.23704, -0.42163]
+    - [106.5714, -0.28603, 1.19061, -0.42258]
+    - [110.7143, -0.35981, 1.13285, -0.42312]
+    - [114.8571, -0.43261, 1.06493, -0.42168]
+    - [119.0, -0.50388, 0.98826, -0.42024]
+    - [123.1429, -0.57335, 0.90444, -0.42058]
+    - [127.2857, -0.64116, 0.8152, -0.4215]
+    - [131.4286, -0.7079, 0.72238, -0.42591]
+    - [135.5714, -0.77483, 0.62793, -0.43697]
+    - [139.7143, -0.84406, 0.53379, -0.44803]
+    - [143.8571, -0.91898, 0.44192, -0.46784]
+    - [148.0, -1.00494, 0.35424, -0.4883]
+    - [150.2857, -0.93316, 0.30832, -0.496]
+    - [152.5714, -0.86138, 0.26453, -0.47857]
+    - [154.8571, -0.7896, 0.22313, -0.46114]
+    - [157.1429, -0.71781, 0.18439, -0.4437]
+    - [159.4286, -0.64603, 0.14856, -0.42627]
+    - [161.7143, -0.57425, 0.11586, -0.4353]
+    - [164.0, -0.50247, 0.08651, -0.45315]
+    - [166.2857, -0.43069, 0.06068, -0.471]
+    - [168.5714, -0.35891, 0.05174, -0.48884]
+    - [170.8571, -0.28713, 0.04653, -0.45714]
+    - [173.1429, -0.21534, 0.04245, -0.34286]
+    - [175.4286, -0.14356, 0.03951, -0.22857]
+    - [177.7143, -0.07178, 0.03774, -0.11429]
+    - [179.9087, 0.0, 0.03715, 0.0]
+  pitch_control:
+    GS_Angles: [0.06019804, 0.08713416, 0.10844806, 0.12685912, 0.14339822, 
+        0.1586021, 0.17279614, 0.18618935, 0.19892772, 0.21111989, 0.22285021, 
+        0.23417256, 0.2451469, 0.25580691, 0.26619545, 0.27632495, 0.28623134, 
+        0.29593266, 0.30544521, 0.314779, 0.32395154, 0.33297489, 0.3418577, 
+        0.35060844, 0.35923641, 0.36774807, 0.37614942, 0.38444655, 0.39264363, 
+        0.40074407]
+    GS_Kp: [-0.9394215, -0.80602855, -0.69555026, -0.60254912, -0.52318192, 
+        -0.45465531, -0.39489024, -0.34230736, -0.29568537, -0.25406506, 
+        -0.2166825, -0.18292183, -0.15228099, -0.12434663, -0.09877533, 
+        -0.0752794, -0.05361604, -0.0335789, -0.01499149, 0.00229803, 0.01842102,
+      0.03349169, 0.0476098, 0.0608629, 0.07332812, 0.0850737, 0.0961602, 
+        0.10664158, 0.11656607, 0.12597691]
+    GS_Ki: [-0.07416547, -0.06719673, -0.0614251, -0.05656651, -0.0524202, 
+        -0.04884022, -0.04571796, -0.04297091, -0.04053528, -0.03836094, 
+        -0.03640799, -0.03464426, -0.03304352, -0.03158417, -0.03024826, 
+        -0.02902079, -0.02788904, -0.02684226, -0.02587121, -0.02496797, 
+        -0.02412567, -0.02333834, -0.02260078, -0.02190841, -0.0212572, 
+        -0.02064359, -0.0200644, -0.01951683, -0.01899836, -0.01850671]
+    Fl_Kp: -9.35
+  wt_ops:
+    v: [3.0, 3.266896551724138, 3.533793103448276, 3.800689655172414, 
+        4.067586206896552, 4.334482758620689, 4.601379310344828, 
+        4.868275862068966, 5.135172413793104, 5.402068965517241, 
+        5.6689655172413795, 5.935862068965518, 6.2027586206896554, 
+        6.469655172413793, 6.736551724137931, 7.00344827586207, 
+        7.270344827586207, 7.537241379310345, 7.804137931034483, 
+        8.071034482758622, 8.337931034482759, 8.604827586206897, 
+        8.871724137931036, 9.138620689655173, 9.405517241379311, 
+        9.672413793103448, 9.939310344827586, 10.206206896551725, 
+        10.473103448275863, 10.74, 11.231724137931035, 11.723448275862069, 
+        12.215172413793104, 12.706896551724139, 13.198620689655172, 
+        13.690344827586207, 14.182068965517242, 14.673793103448276, 
+        15.16551724137931, 15.657241379310346, 16.14896551724138, 
+        16.640689655172416, 17.13241379310345, 17.624137931034483, 
+        18.11586206896552, 18.607586206896553, 19.099310344827586, 
+        19.591034482758623, 20.082758620689653, 20.57448275862069, 
+        21.066206896551726, 21.557931034482756, 22.049655172413793, 
+        22.54137931034483, 23.03310344827586, 23.524827586206897, 
+        24.016551724137933, 24.508275862068963, 25.0]
+    pitch_op: [-0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, 
+        -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, 
+        -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, -0.25, 
+        -0.25, 3.57152, 5.12896, 6.36736, 7.43866, 8.40197, 9.28843, 10.1161, 
+        10.8974, 11.641, 12.3529, 13.038, 13.6997, 14.3409, 14.9642, 15.5713, 
+        16.1639, 16.7435, 17.3109, 17.8673, 18.4136, 18.9506, 19.4788, 19.9989, 
+        20.5112, 21.0164, 21.5147, 22.0067, 22.4925, 22.9724]
+    omega_op: [2.1486, 2.3397, 2.5309, 2.722, 2.9132, 3.1043, 3.2955, 3.4866, 
+        3.6778, 3.8689, 4.0601, 4.2512, 4.4424, 4.6335, 4.8247, 5.0159, 5.207, 
+        5.3982, 5.5893, 5.7805, 5.9716, 6.1628, 6.3539, 6.5451, 6.7362, 6.9274, 
+        7.1185, 7.3097, 7.5008, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 
+        7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 
+        7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56, 7.56]
+  gear_ratio: 1
+  torque_control:
+    VS_KP: -38609162.66552
+    VS_KI: -4588245.1872
+  tower:
+    dlsMax: 5.0
+    name: tower
+    type: 1
+    rA: [0, 0, 15]
+    rB: [0, 0, 144.582]
+    shape: circ
+    gamma: 0.0
+    stations: [15, 28, 28.001, 41, 41.001, 54, 54.001, 67, 67.001, 80, 80.001, 
+        93, 93.001, 106, 106.001, 119, 119.001, 132, 132.001, 144.582]
+    d: [10, 9.964, 9.964, 9.967, 9.967, 9.927, 9.927, 9.528, 9.528, 9.149, 9.149,
+      8.945, 8.945, 8.735, 8.735, 8.405, 8.405, 7.321, 7.321, 6.5]
+    t: [0.082954, 0.082954, 0.083073, 0.083073, 0.082799, 0.082799, 0.0299, 
+        0.0299, 0.027842, 0.027842, 0.025567, 0.025567, 0.022854, 0.022854, 
+        0.02025, 0.02025, 0.018339, 0.018339, 0.021211, 0.021211]
+    Cd: 0.0
+    Ca: 0.0
+    CdEnd: 0.0
+    CaEnd: 0.0
+    rho_shell: 7850
+array_mooring:
+  anchor_keys: [ID, type, x, y, embedment]
+  anchor_data: []
+  line_keys: [MooringConfigID, endA, endB, headingA, headingB, lengthAdjust]
+  line_data: []
+mooring_systems:
+  ms0:
+    keys: [MooringConfigID, heading, anchorType, lengthAdjust]
+    data:
+    - ['0', 150.0, drag-embedment1, 0]
+    - ['0', 270.0, drag-embedment1, 0]
+    - ['0', 30.0, drag-embedment1, 0]
+mooring_line_configs:
+  '0':
+    name: '0'
+    span: 642.0
+    sections:
+    - type: 0
+      length: 497.7
+    - connectorType: h_link
+    - type: 1
+      length: 199.8
+mooring_line_types:
+  0:
+    name: 0
+    d_vol: 0.27882
+    m: 479.88020000000006
+    EA: 2053741190.7845445
+    w: 4093.6781602294
+    MBL: 20893381.207590003
+    EAd: 0.0
+    EAd_Lm: 0.0
+    d_nom: 0.1549
+    cost: 2005.5584560000004
+    notes: made with getLineProps
+    material: chain
+    Cd: 1.333
+    CdAx: 0.639
+    Ca: 1.0
+    CaAx: 0.5
+  1:
+    name: 1
+    d_vol: 0.14405282886514317
+    m: 22.491196000000002
+    EA: 142830688.0
+    w: 56.75848886217392
+    MBL: 10202192.0
+    EAd: 118345427.2
+    EAd_Lm: 40.0
+    d_nom: 0.182
+    cost: 441.9688
+    notes: made with getLineProps
+    material: polyester
+    Cd: 2.021
+    CdAx: 0.0
+    Ca: 1.1
+    CaAx: 0.15
+mooring_connector_types:
+  h_link:
+    m: 140.0
+    v: 0.13
+    type: h_link
+    CdA: 0
+anchor_types:
+  drag-embedment1:
+    type: DEA
+    A: 10
+    zlug: 10
+cables: []
+dynamic_cable_configs: {}
+cable_types: {}
+cable_appendages: {}
diff --git a/examples/example_anchors.py b/examples/example_anchors.py
deleted file mode 100644
index 95bd77ed..00000000
--- a/examples/example_anchors.py
+++ /dev/null
@@ -1,148 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Example showing how to call forces and 
-anchor capacity functions, along with safety factors and material costs.
-"""
-# import necessary packages
-from famodel.project import Project
-import os
-
-dir = os.path.dirname(os.path.realpath(__file__))
-
-# set yaml file location and name
-ontology_file = dir+'\OntologySample200m_1turb.yaml'
-
-# create project class
-project = Project(file=ontology_file)
-project.getMoorPyArray()
-
-# let's choose a single anchor from the array to look at
-anch = project.anchorList['fowt0a']
-
-# now let's get the mudline and lug forces on this anchor
-anch.getLugForces() # getLugForces calls getMudlineForces() to get the anchor forces at both locations
-
-# establish a factor of safety in horizontal (Ha) and vertical (Va) directions
-minfs = {'Ha': 1.8, 'Va': 2}
-
-# let's get the loads with the factor of safety included 
-loads_with_FS = {'Ha':anch.loads['Ha']*minfs['Ha'],'Va':anch.loads['Va']*minfs['Va']}
-
-# get anchor capacity for one anchor (this case is for suction pile in clay)
-anch.getAnchorCapacity(loads=loads_with_FS) # loads are used in capacity calculation, so let's send in the loads with factor of safety applied
-
-# get anchor cost
-startGeom = [10,2,6.6]
-geomKeys = ['L','D','zlug']
-geomBounds = [(5, 50), (1, 7), (3.3,16.7)]
-FSDiff_max = {'Ha':5,'Va':5}
-anch.getSize(startGeom,geomKeys,geomBounds,minfs=minfs,FSdiff_max=FSDiff_max, plot=True)
-anch.getCost()
-print('\nClay suction pile capacity is: ',anch.anchorCapacity)
-print('Clay suction pile safety factor is: ',anch.getFS())
-print('Clay suction pile cost is: ', anch.cost,'\n')
-# try suction pile with sand
-newdd = anch.dd
-anch.soilProps['sand'] = anch.soilProps.pop('mud_firm')
-anch.soilProps['sand']['phi'] = 33
-anch.soilProps['sand']['Dr'] = 70
-anch.soilProps['sand']['delta'] = 25
-# update anchor loads at lug point (mudline load should be constant), then get anchor capacity
-anch.getLugForces()
-anch.getSize(startGeom,geomKeys,geomBounds,plot=True)
-anch.getAnchorCapacity(loads=loads_with_FS)
-anch.getCost()
-print('\nSand suction pile capacity is: ',anch.anchorCapacity,' N')
-print('Sand suction pile safety factor is: ',anch.getFS())
-print('Sand suction pile cost is: ', anch.cost,' USD\n')
-
-# check plate anchor type   
-newdd['type'] = 'DEA'
-newdd['design'] = {'type':'DEA','A':20,'zlug':20,'beta':10}
-anch.soilProps['clay'] = anch.soilProps.pop('sand')
-
-startGeom = [10,20]
-geomKeys = ['A','zlug']
-
-anch.getLugForces()
-anch.getAnchorCapacity(loads=loads_with_FS)
-# let's fix the zlug for the plate anchor - set fix_zlug=True to prevent it being changed
-anch.getSize(startGeom,geomKeys,minfs={'Ha':2,'Va':0}, fix_zlug = True)
-anch.getCost()
-print('\nClay plate capacity is: ',anch.anchorCapacity,' N')
-print('Clay plate safety factor is: ',anch.getFS())
-print('Clay plate cost is: ', anch.cost,' USD\n')
-
-# check drilled and grouted pile anchor type
-newdd['type'] = 'dandg_pile'
-newdd['design'] = {'type':'dandg_pile','L':50,'D':3,'zlug':0}
-anch.soilProps['rock'] = anch.soilProps.pop('clay') # soil_properties has default rock info in there already, just change name
-
-# startGeom = [5,50]
-# geomKeys = ['L','D']
-anch.getLugForces()
-# anch.getSize(startGeom,geomKeys,minfs={'Ha':2,'Va':2})
-anch.getAnchorCapacity(loads=loads_with_FS)
-print('\nRock drilled and grouted pile capacity is: ',anch.anchorCapacity,' N')
-print('Rock drilled and grouted pile safety factor is: ',anch.getFS())
-
-# check driven pile anchor in rock
-newdd['type'] = 'driven'
-anch.soilProps['weak_rock'] = anch.soilProps.pop('rock')
-newdd['design'] = {'type':'driven','L':20,'D':1.5,'zlug':-3} # zlug should be negative (above mudline) for rock!
-
-anch.getLugForces()
-anch.getAnchorCapacity(loads=loads_with_FS)
-print('\nWeak rock driven pile capacity is: ',anch.anchorCapacity,' N')
-print('Weak rock driven pile safety factor is: ',anch.getFS())
-
-# check driven pile anchor in clay
-anch.soilProps['clay'] = anch.soilProps.pop('weak_rock')
-newdd['design'] = {'type':'driven','L':40,'D':4,'zlug':10}
-
-anch.getLugForces()
-anch.getAnchorCapacity(loads=loads_with_FS)
-print('\nClay driven pile capacity is: ',anch.anchorCapacity,' N')
-print('Clay driven pile safety factor is: ',anch.getFS())
-
-# check driven pile anchor in sand
-anch.soilProps['sand'] = anch.soilProps.pop('clay')
-anch.soilProps['sand']['Dr'] = 50
-
-anch.getLugForces()
-anch.getAnchorCapacity(loads=loads_with_FS)
-print('\nSand driven pile capacity is: ',anch.anchorCapacity,' N')
-print('Sand driven pile safety factor is: ',anch.getFS())
-
-# check helical pile anchor with sand
-newdd['type'] = 'helical_pile'
-newdd['design'] = {'type':'helical_pile','L':25.1,'d':1,'D':5.01, 'zlug':5}
-
-anch.getLugForces()
-anch.getAnchorCapacity(loads=loads_with_FS)
-print('\nSand helical pile capacity is: ',anch.anchorCapacity,' N')
-print('Sand helical pile safety factor is: ',anch.getFS())
-
-# check helical pile anchor with clay
-anch.soilProps['clay'] = anch.soilProps.pop('sand')
-newdd['type'] = 'helical_pile'
-newdd['design'] = {'type':'helical_pile','L':25.1,'d':1,'D':5.01,'zlug':5}
-
-anch.getLugForces()
-anch.getAnchorCapacity(loads=loads_with_FS)
-print('\nClay helical pile capacity is: ',anch.anchorCapacity,' N')
-print('Clay helical pile safety factor is: ',anch.getFS())
-
-# check torpedo anchor in clay
-newdd['type'] = 'torpedo_pile'
-newdd['design'] = {'type':'torpedo_pile','D1':3,'D2':1.1,'L1':10,'L2':4,'zlug':16}
-
-anch.getLugForces()
-anch.getAnchorCapacity(loads=loads_with_FS)
-print('\nClay torpedo pile capacity is: ',anch.anchorCapacity,' N')
-print('Clay torpedo pile safety factor is: ',anch.getFS())
-
-
-
-
-
diff --git a/examples/example_driver.py b/examples/example_driver.py
index 730535c2..690062f9 100644
--- a/examples/example_driver.py
+++ b/examples/example_driver.py
@@ -76,27 +76,35 @@
 # plot motion envelopes with 2d plot
 project.plot2d(save=True,plot_bathymetry=False)
 
-
+#%% Section 5: Anchor capabilities
 #### get anchor capacities, loads, and safety factors ####
 print('\nGetting anchor capacities, loads, and safety factors\n')
 # let's look at one anchor in the farm
 
 # define anchor to analyze
 anchor = project.anchorList['FOWT1a']
-# get anchor capacity
-anchor.getAnchorCapacity()
+
+name, soil_def = project.getSoilAtLocation(anchor.r[0], anchor.r[1])
+profile_map = [{'name': name, 'layers': soil_def['layers']}]
+anchor.setSoilProfile(profile_map)
+
+Hm = anchor.loads['Hm']
+Vm = anchor.loads['Vm']
+zlug = anchor.dd['design']['zlug']
+
+# Now use these in lug and capacity checks
+anchor.getLugForces(Hm, Vm, zlug)
+anchor.getCapacityAnchor(Hm, Vm, zlug)
 capacities = anchor.anchorCapacity
-# get anchor loads at mudline and anchor lug depth (if applicable)
-loads = anchor.getLugForces()
+
 # size an anchor
-starting_geometry = [15,20] # geometry values
-starting_geom_labels = ['A','zlug'] # corresponding labels for the geometry list
-min_safety_factors = {'Ha':2,'Va':2} # minimum safety factors
-FSdiff_max = {'Ha':.1,'Va':.1} # allowable difference between actual and desired FS for final result
-anchor.getSize(starting_geometry, starting_geom_labels, minfs=min_safety_factors,
-               FSdiff_max=FSdiff_max)
+geom_start = [anchor.dd['design']['B'], anchor.dd['design']['L']] # geometry values
+geom_labels = ['B','L'] # corresponding labels for the geometry list
+geom_bounds = [(0.5, 4.0), (0.5, 4.0)]
+safety_factor = {'SF_combined': 1.0} # minimum safety factors
+anchor.getSizeAnchor(geom_start, geom_labels, geom_bounds, loads = None, safety_factor={'SF_combined': 1.0})
 # get safety factor
-sfs = anchor.getFS()
+sfs = anchor.getSafetyFactor()
     
 print('\nAnchor safety factors: ',sfs) # NOTE that Va will show as 'inf' because there is no vertical force on the anchor.
     
diff --git a/famodel/anchors/AnchorDesign_temp.py b/famodel/anchors/AnchorDesign_temp.py
new file mode 100644
index 00000000..2223096e
--- /dev/null
+++ b/famodel/anchors/AnchorDesign_temp.py
@@ -0,0 +1,672 @@
+# -*- coding: utf-8 -*-
+"""
+temp storage of different anchor sizing functions that use different 
+optimization methods. These were built-in methods to Anchor class.
+
+Eventually can be converted into a full AnchorDesign class...
+"""
+
+def getSizeAnchor(self, geom, geomKeys, geomBounds=None, loads=None, lambdap_con=[4, 8],
+                   zlug_fix=True, safety_factor={}, plot=False, display=0):
+    '''
+    Generalized optimization method for all anchor types, using dictionary-based safety factors.
+    '''
+    self.display = display
+
+    anchType_clean = self.dd['type'].strip().lower()
+    print(f"[Debug] Anchor type parsed: '{anchType_clean}'")
+
+    if loads is None:
+        loads = self.loads
+    
+    sf_Hm = safety_factor.get('Hm', safety_factor.get('SF_horizontal', 1.0))
+    sf_Vm = safety_factor.get('Vm', safety_factor.get('SF_vertical', 1.0))
+    sf_uc = safety_factor.get('SF_combined', max(sf_Hm, sf_Vm))  # conservative by default
+
+    Hm = loads['Hm']*sf_Hm
+    Vm = loads['Vm']*sf_Vm
+
+    line_type = getattr(self, 'line_type', 'chain')
+    d = getattr(self, 'd', 0.16)
+    w = getattr(self, 'w', 5000.0)
+
+    def update_zlug():
+        if 'suction' in anchType_clean and not zlug_fix and 'zlug' not in geomKeys:
+            self.dd['design']['zlug'] = (2/3)*self.dd['design']['L']
+        elif np.any([name in anchType_clean for name in ['driven', 'helical']]) and not zlug_fix:    
+            ratio = self.dd['design'].get('zlug_ratio', self.dd['design']['zlug']/self.dd['design']['L'])
+            self.dd['design']['zlug_ratio'] = ratio
+            self.dd['design']['zlug'] = ratio*self.dd['design']['L']
+        elif 'drilled' in anchType_clean:
+            self.dd['design']['zlug'] = 0
+
+    def get_lambda():
+        if 'torpedo' in anchType_clean:
+            L = self.dd['design']['L1'] + self.dd['design']['L2']
+            A_wing = (self.dd['design']['D1'] - self.dd['design']['D2']) * self.dd['design']['L1']
+            A_shaft = self.dd['design']['D2'] * L
+            D = (A_wing + A_shaft) / L
+        elif np.any([name in anchType_clean for name in ['driven', 'drilled', 'helical', 'suction']]):
+            L = self.dd['design']['L']
+            D = self.dd['design']['D']
+        elif np.any([name in anchType_clean for name in ['plate', 'sepla', 'dea', 'depla', 'vla']]):
+            L = self.dd['design']['L']
+            D = self.dd['design']['B']
+        else:
+            raise ValueError(f'lambda not defined for anchor type: {anchType_clean}')
+        return L/D
+
+    def constraint_lambda_min(vars):
+        for i, key in enumerate(geomKeys):
+            self.dd['design'][key] = vars[i]
+        update_zlug()
+        self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+        return get_lambda() - lambdap_con[0]
+
+    def constraint_lambda_max(vars):
+        return lambdap_con[1] - get_lambda()
+    
+    def constraint_bounds(vars):
+        con_bound_return = np.zeros(len(geomKeys)*2)
+        for i,var in enumerate(geomKeys):
+            con_bound_return[2*i] = self.dd['design'][var] - geomBounds[i][0]
+            con_bound_return[2*i+1] = geomBounds[i][1] - self.dd['design'][var]
+        return con_bound_return
+
+    if np.any([name in anchType_clean for name in ['suction', 'torpedo', 'plate', 'sepla', 'dea', 'depla', 'vla']]):
+        target_UC = 1.0/sf_uc
+
+        def objective_uc(vars):
+            '''
+            for i, key in enumerate(geomKeys):
+                self.dd['design'][key] = vars[i]
+            update_zlug()
+            self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                   line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+            '''
+            #UC = self.anchorCapacity.get('UC', 2.0)
+            #return (UC - target_UC)**2
+            #return self.anchorCapacity.get('Weight pile')
+            if any(name in anchType_clean for name in ['plate', 'sepla', 'dea', 'depla', 'vla']):
+                return self.anchorCapacity.get('Weight plate')
+            else:
+                return self.anchorCapacity.get('Weight pile')
+
+        def constraint_uc_envelope(vars):
+            return self.anchorCapacity.get('UC', 0.0) - target_UC
+
+        constraints_uc = [
+            {'type': 'ineq', 'fun': constraint_lambda_min},
+            {'type': 'ineq', 'fun': constraint_lambda_max},
+            {'type': 'ineq', 'fun': constraint_uc_envelope},
+            {'type': 'ineq', 'fun': constraint_bounds},
+        ]
+
+        result_uc = minimize(
+            objective_uc,
+            geom,
+            method='COBYLA',
+            constraints=constraints_uc,
+            options={'rhobeg': 0.1, 'catol': 0.01, 'maxiter': 500}
+        )
+
+        endGeom = dict(zip(geomKeys, result_uc.x))
+        self.dd['design'].update(endGeom)
+        update_zlug()
+        self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                               line_type=line_type, d=d, w=w, mass_update=True, plot=plot, display=display)
+
+        print('\nFinal Optimized Anchor (UC-based):')
+        print('Design:', self.dd['design'])
+        print('Capacity Results:', self.anchorCapacity)
+        return
+    
+    def near_border():
+        UC_h = self.anchorCapacity['Ha']/self.anchorCapacity['Hmax']
+        UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+        disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+        disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+        limit_lat = 0.05*self.dd['design']['D']  # 10% of the pile diameter
+        limit_rot = 10.0                         # 10 deg
+    
+        near_UC_h = 0.95 <= UC_h <= 1.0
+        near_UC_v = 0.95 <= UC_v <= 1.0
+        near_disp_lat = 0.95*limit_lat <= disp_lat <= limit_lat
+        near_disp_rot = 4.75 <= disp_rot <= limit_rot
+    
+        return near_UC_h or near_UC_v or near_disp_lat or near_disp_rot
+
+    def termination_condition():
+        UC_h = self.anchorCapacity['Ha']/self.anchorCapacity['Hmax']
+        UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+        disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+        disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+        limit_lat = 0.05*self.dd['design']['D']  # 10% of the pile diameter
+        limit_rot = 10.0                         # 10 deg
+    
+        all_satisfied = (UC_h <= 1.0 and UC_v <= 1.0 and disp_lat <= limit_lat and disp_rot <= limit_rot)
+    
+        if all_satisfied:
+            if near_border():
+                if self.display > 0: print('[Termination] All criteria satisfied and near border.')
+                return 'terminate'
+            else:
+                if self.display > 0: print('[Safe but not near border] Continue shrinking...')
+                return 'continue'
+        return 'continue'
+    
+    def termination_condition_drilled():
+        UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+        disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+        disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+        limit_lat = 0.05*self.dd['design']['D']  # 10% of the pile diameter
+        limit_rot = 10.0                         # 10 deg
+    
+        all_satisfied = (UC_v <= 1.0 and disp_lat <= limit_lat and disp_rot <= limit_rot)
+    
+        if all_satisfied:
+            if near_border():
+                if self.display > 0: print('[Termination] All criteria satisfied and near border.')
+                return 'terminate'
+            else:
+                if self.display > 0: print('[Safe but not near border] Continue shrinking...')
+                return 'continue'
+        return 'continue'
+       
+    def is_valid(value):
+        return np.isfinite(value) and not np.isnan(value) and abs(value) < 1e6
+    
+    if anchType_clean in ['helical', 'driven']:
+        L0, D0 = geom if len(geom) == 2 else [5.0, 1.0]
+        self.dd['design']['L'] = L0
+        self.dd['design']['D'] = D0
+        Lmin, Lmax = geomBounds[0]
+        Dmin, Dmax = geomBounds[1]
+        update_zlug()
+        self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                               line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+    
+        UC_h = self.anchorCapacity['Ha']/self.anchorCapacity['Hmax']
+        UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+        disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+        disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+        limit_disp = 0.10*D0    # 10% of the pile diameter
+        limit_rot = 10.0        # 10 deg 
+        direction = 'shrink' if (UC_h <= 1.0 and UC_v <= 1.0 and disp_lat <= limit_disp and disp_rot <= limit_rot) else 'grow'
+
+        max_iter = 200
+        iter_count = 0
+
+        if direction == 'shrink':
+            for L in np.arange(L0, Lmin - 1e-6, -0.25):
+                self.dd['design']['L'] = L
+                for D in np.arange(Dmax, Dmin - 1e-6, -0.05):
+                    if L/D > lambdap_con[1] or L/D < lambdap_con[0]:
+                        continue
+                    self.dd['design']['L'] = L
+                    update_zlug()
+                    self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                           line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+                    UC_h = self.anchorCapacity['Ha']/self.anchorCapacity['Hmax']
+                    UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+                    disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+                    disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+                    if self.display > 0: print(f'[Iter {iter_count}] L={L:.2f}, D={D:.2f}, UC_h={UC_h:.3f}, UC_v={UC_v:.3f}, lat={disp_lat:.3f} m, rot={disp_rot:.3f} deg')
+                    iter_count += 1
+                    if not all(is_valid(v) for v in [UC_h, UC_v, disp_lat, disp_rot]):
+                        continue
+                    if termination_condition():
+                        print(f'\nTermination criteria met.')
+                        print('Design:', self.dd['design'])
+                        print('Capacity Results:', self.anchorCapacity)
+                        return
+        elif direction == 'grow':
+            for L in np.arange(L0, Lmax + 1e-6, 0.25):
+                self.dd['design']['L'] = L
+                for D in np.arange(Dmin, Dmax + 1e-6, 0.05):   
+                    if L/D > lambdap_con[1] or L/D < lambdap_con[0]:
+                        continue
+                    self.dd['design']['L'] = L
+                    update_zlug()
+                    self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                           line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+                    UC_h = self.anchorCapacity['Ha']/self.anchorCapacity['Hmax']
+                    UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+                    disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+                    disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+                    if self.display > 0: print(f'[Iter {iter_count}] L={L:.2f}, D={D:.2f}, UC_h={UC_h:.3f}, UC_v={UC_v:.3f}, lat={disp_lat:.3f} m, rot={disp_rot:.3f} deg')
+                    iter_count += 1
+                    status = termination_condition()
+                    if status == 'terminate':
+                        print(f'Termination criteria met.')
+                        print('Design:', self.dd['design'])
+                        print('Capacity Results:', self.anchorCapacity)
+                        return
+                    elif status == 'continue':
+                        continue
+                status = termination_condition()
+                if status == 'terminate':
+                    print(f'\nTermination criteria met.')
+                    print('Design:', self.dd['design'])
+                    print('Capacity Results:', self.anchorCapacity)
+                    return
+        else:
+            raise ValueError(f"Unknown optimization direction: {direction}")
+            
+        if self.display > 0: print('[Warning] While-loop search reached bounds without meeting criteria.')
+                
+    if 'drilled' in anchType_clean:
+        L0, D0 = geom if len(geom) == 2 else [5.0, 1.0]
+        self.dd['design']['L'] = L0
+        self.dd['design']['D'] = D0
+        Lmin, Lmax = geomBounds[0]
+        Dmin, Dmax = geomBounds[1]
+        update_zlug()
+        self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                               line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+    
+        UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+        disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+        disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+        limit_disp = 0.10*D0   # 10% of the pile diameter
+        limit_rot = 10.0        # 10 deg 
+        direction = 'shrink' if (UC_v <= 1.0 and disp_lat <= limit_disp and disp_rot <= limit_rot) else 'grow'
+
+        max_iter = 200
+        iter_count = 0
+
+        if direction == 'shrink':
+            for L in np.arange(L0, Lmin - 1e-6, -0.25):
+                self.dd['design']['L'] = L
+                for D in np.arange(Dmax, Dmin - 1e-6, -0.05):
+                    if L/D > lambdap_con[1] or L/D < lambdap_con[0]:
+                        continue
+                    self.dd['design']['L'] = L
+                    update_zlug()
+                    self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                           line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+                    UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+                    disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+                    disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+                    if self.display > 0: print(f'[Iter {iter_count}] L={L:.2f}, D={D:.2f}, UC_v={UC_v:.3f}, lat={disp_lat:.3f} m, rot={disp_rot:.3f} deg')
+                    iter_count += 1
+                    if not all(is_valid(v) for v in [UC_v, disp_lat, disp_rot]):
+                        continue
+                    if termination_condition_drilled():
+                        print(f'\nTermination criteria met.')
+                        print('Design:', self.dd['design'])
+                        print('Capacity Results:', self.anchorCapacity)
+                        return
+        elif direction == 'grow':
+            for L in np.arange(L0, Lmax + 1e-6, 0.25):
+                self.dd['design']['L'] = L
+                for D in np.arange(Dmin, Dmax + 1e-6, 0.05):
+                    if L/D > lambdap_con[1] or L/D < lambdap_con[0]:
+                        continue
+                    self.dd['design']['L'] = L
+                    update_zlug()
+                    self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                           line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+                    UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+                    disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+                    disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+                    if self.display > 0: print(f'[Iter {iter_count}] L={L:.2f}, D={D:.2f}, UC_v={UC_v:.3f}, lat={disp_lat:.3f} m, rot={disp_rot:.3f} deg')
+                    iter_count += 1
+                    status = termination_condition_drilled()
+                    if status == 'terminate':
+                        print(f'Termination criteria met.')
+                        print('Design:', self.dd['design'])
+                        print('Capacity Results:', self.anchorCapacity)
+                        return
+                    elif status == 'continue':
+                        continue
+                status = termination_condition_drilled()
+                if status == 'terminate':
+                    print(f'\nTermination criteria met.')
+                    print('Design:', self.dd['design'])
+                    print('Capacity Results:', self.anchorCapacity)
+                    return
+        else:
+            raise ValueError(f"Unknown optimization direction: {direction}")
+
+        if self.display > 0: print('[Warning] While-loop search reached bounds without meeting criteria.')
+
+    else:
+        raise ValueError(f"Anchor type '{anchType_clean}' not supported for safety factor input.")
+               
+def getSizeAnchor2(self, geom, geomBounds=None, loads=None, lambdap_con=[3, 6], 
+                   zlug_fix=True, safety_factor={}, plot=False):
+    '''
+    Grid-based optimization method for envelope anchors (suction, torpedo, plate).
+    Evaluates UC over a grid of L and D, and selects the point closest to target UC.
+    '''
+    import matplotlib.pyplot as plt
+    from matplotlib import cm
+    import matplotlib.colors as mcolor
+    import numpy as np
+
+    anchType_clean = self.dd['type'].lower().replace('', '')
+
+    if loads is None:
+        loads = self.loads
+
+    sf_uc = safety_factor.get('SF_combined', 1.0)
+    sf_Hm = safety_factor.get('Hm', 1.0)
+    sf_Vm = safety_factor.get('Vm', 1.0)
+
+    Hm = loads['Hm']*sf_Hm
+    Vm = loads['Vm']*sf_Vm
+
+    line_type = getattr(self, 'line_type', 'chain')
+    d = getattr(self, 'd', 0.16)
+    w = getattr(self, 'w', 5000.0)
+
+    if anchType_clean not in ['suction', 'torpedo', 'plate']:
+        raise ValueError(f"Grid-based getSizeAnchor only supports envelope anchors, not '{anchType_clean}'")
+
+    UC_target = 1.0/sf_uc
+
+    # Unpack bounds and generate grid
+    L_vals = np.linspace(geomBounds[0][0], geomBounds[0][1], 10)
+    D_vals = np.linspace(geomBounds[1][0], geomBounds[1][1], 10)
+
+    L_grid, D_grid = np.meshgrid(L_vals, D_vals)
+    UC_grid = np.full_like(L_grid, np.nan, dtype=float)
+    mask = np.full_like(L_grid, False, dtype=bool)
+
+    best_UC, best_L, best_D = None, None, None
+    results = []
+
+    for i in range(D_grid.shape[0]):  # loop over D
+        for j in range(D_grid.shape[1]):  # loop over L
+            D = D_grid[i, j]
+            L = L_grid[i, j]
+            lambdap = L/D
+
+            if not (lambdap_con[0] <= lambdap <= lambdap_con[1]):
+                continue
+
+            mask[i, j] = True
+            self.dd['design']['L'] = L
+            self.dd['design']['D'] = D
+
+            if anchType_clean == 'suction' and not zlug_fix:
+                self.dd['design']['zlug'] = (2/3)*L
+
+            try:
+                self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                       line_type=line_type, d=d, w=w, 
+                                       mass_update=True, plot=False)
+                UC = self.anchorCapacity.get('UC', np.nan)
+                results.append({
+                    'L': L,
+                    'D': D,
+                    'UC': UC})
+
+                if UC > 1e-2 and UC < 10.0:
+                    UC_grid[i, j] = UC
+                    # Find UC closest to target
+                    if best_UC is None or abs(UC - UC_target) < abs(best_UC - UC_target):
+                        best_UC = UC
+                        best_L = L
+                        best_D = D
+
+            except:
+                continue
+
+    # Update best result
+    # if best_L is not None and best_D is not None:
+    self.dd['design']['L'] = best_L
+    self.dd['design']['D'] = best_D
+    if anchType_clean == 'suction' and not zlug_fix:
+        self.dd['design']['zlug'] = (2/3)*best_L
+
+    self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                           line_type=line_type, d=d, w=w, 
+                           mass_update=True, plot=plot)
+
+    print('\nFinal Optimized Anchor (Grid-based):')
+    print('Design:', self.dd['design'])
+    print('Capacity Results:', self.anchorCapacity)
+
+    # else:
+    #     print('[Warning] No valid combination found in the grid.')
+
+    # Optional plot
+
+    if plot:
+        fig, ax = plt.subplots(figsize=(6, 8))
+        vmin, vmax = 0.01, 10
+        levels = np.logspace(np.log10(vmin), np.log10(vmax), 21)
+        cp = ax.contourf(D_grid, L_grid, UC_grid, levels=levels, cmap='coolwarm', norm=mcolor.LogNorm(vmin=vmin, vmax=vmax))
+        fig.colorbar(cp, ax=ax, label='Unity check (UC)')
+        ax.contour(D_grid, L_grid, UC_grid, levels=levels, colors='k', linewidths=0.3, alpha=0.3)
+        ax.contour(D_grid, L_grid, UC_grid, levels=[1.0], colors='red', linewidths=2, linestyles='--')
+        ax.set_xlabel('Diameter (m)')
+        ax.set_ylabel('Length (m)')
+        ax.set_title('Unity Check (UC')
+        ax.plot(best_D, best_L, 'ro', label='Best match')
+        ax.annotate('Best match', (best_D, best_L), textcoords="offset points", xytext=(10,10), ha='center', color='red')
+        ax.legend()
+        plt.grid(True)
+        plt.tight_layout()
+        plt.show()
+        
+    #UC_target = 1.0
+    closest = min(results, key=lambda x: abs(x['UC'] - UC_target))
+    print("Closest to UC_target:")
+    print(closest)
+        
+    return results
+
+def getSizeAnchor_BO(self, 
+                     geom=[10.0, 2.0],
+                     geomKeys=['L', 'D'],
+                     geomBounds=[(5.0, 15.0), (1.0, 4.0)],
+                     loads=None,
+                     lambdap_con=[3, 6],
+                     zlug_fix=False,
+                     safety_factor={'SF_combined': 1.0},
+                     n_calls=25,
+                     plot=False,
+                     verbose=True):
+    '''
+    Bayesian optimization to find (D, L) for UC closest to UC_target.
+    Uses scikit-optimize for surrogate model and efficient sampling.
+    '''
+    from skopt import gp_minimize
+    from skopt.space import Real
+    from skopt.utils import use_named_args
+    import numpy as np
+
+    if loads is None:
+        loads = self.loads
+
+    Hm = loads['Hm']
+    Vm = loads['Vm']
+
+    line_type = getattr(self, 'line_type', 'chain')
+    d = getattr(self, 'd', 0.16)
+    w = getattr(self, 'w', 5000.0)
+
+    UC_target = 1.0 / safety_factor.get('SF_combined', 1.0)
+
+    # Define the search space
+    space  = [
+        Real(geomBounds[1][0], geomBounds[1][1], name='D'),
+        Real(geomBounds[0][0], geomBounds[0][1], name='L')
+    ]
+
+    @use_named_args(space)
+    def objective(**params):
+        D = params['D']
+        L = params['L']
+
+        # Apply lambda constraint
+        lambdap = L/D
+        if not (lambdap_con[0] <= lambdap <= lambdap_con[1]):
+            return 100.0
+
+        self.dd['design']['D'] = D
+        self.dd['design']['L'] = L
+        if not zlug_fix:
+            self.dd['design']['zlug'] = (2/3)*L
+
+        try:
+            self.getCapacityAnchor(
+                Hm=Hm,
+                Vm=Vm,
+                zlug=self.dd['design']['zlug'],
+                line_type=line_type,
+                d=d,
+                w=w,
+                mass_update=True,
+                plot=False)
+            
+            UC = self.anchorCapacity.get('UC', np.nan)
+        except:
+            UC = np.nan
+
+        if verbose:
+            print(f"Evaluated D={D:.3f}, L={L:.3f} -> UC={UC:.3f}")
+
+        if not np.isfinite(UC):
+            return 100.0
+
+        if UC < UC_target:
+            return (UC_target - UC)**2 * 0.5  # less penalty for overdesign
+        else:
+            return (UC - UC_target)**2 * 10   # higher penalty for failure
+
+    # Run Bayesian optimization
+    res = gp_minimize(
+        objective,
+        space,
+        x0=[geom[1], geom[0]],
+        n_calls=n_calls,
+        random_state=42,
+        verbose=verbose
+    )
+
+    # Best result
+    best_D, best_L = res.x
+    self.dd['design']['D'] = best_D
+    self.dd['design']['L'] = best_L
+    if not zlug_fix:
+        self.dd['design']['zlug'] = (2/3)*best_L
+
+    self.getCapacityAnchor(
+        Hm=Hm,
+        Vm=Vm,
+        zlug=self.dd['design']['zlug'],
+        line_type=line_type,
+        d=d,
+        w=w,
+        mass_update=True,
+        plot=plot
+    )
+    UC = self.anchorCapacity.get('UC', np.nan)
+
+    print('\nBayesian Optimized Anchor:')
+    print('Design:', self.dd['design'])
+    print('Capacity Results:', self.anchorCapacity)
+    print(f'Best UC: {UC:.4f} (target: {UC_target})')
+
+    results = {'D': best_D, 'L': best_L, 'UC': UC, 'result': res}
+
+    return results
+# PATCH for GRADIENT method: wrap getCapacityAnchor in safe evaluator
+def safe_get_uc(self, Hm, Vm, zlug, line_type, d, w, verbose=False):
+    try:
+        self.getCapacityAnchor(Hm, Vm, zlug, line_type, d, w, True, False)
+        return self.anchorCapacity.get('UC', np.nan)
+    except Exception as e:
+        if verbose:
+            print(f"[Safe Error] {str(e)}")
+        return np.nan
+
+def getSizeAnchor_gradient(self, 
+                           geom=[10.0, 2.0],
+                           geomKeys=['L', 'D'],
+                           geomBounds=[(5.0, 15.0), (1.0, 4.0)],
+                           loads=None,
+                           lambdap_con=[3, 6],
+                           zlug_fix=False,
+                           safety_factor={'SF_combined': 1.0},
+                           step_size=0.2,
+                           tol=0.05,
+                           max_iter=30,
+                           verbose=True):
+    '''
+    Gradient-based optimization with early stopping to match UC_target.
+    '''
+    import numpy as np
+
+    if loads is None:
+        loads = self.loads
+
+    Hm = loads['Hm']
+    Vm = loads['Vm']
+
+    line_type = getattr(self, 'line_type', 'chain')
+    d = getattr(self, 'd', 0.16)
+    w = getattr(self, 'w', 5000.0)
+
+    UC_target = 1.0 / safety_factor.get('SF_combined', 1.0)
+
+    L, D = geom
+
+    for iter in range(max_iter):
+        lambdap = L / D
+        if not (lambdap_con[0] <= lambdap <= lambdap_con[1]):
+            if verbose:
+                print(f"[Iter {iter}] λ = {lambdap:.2f} out of bounds. Terminating.")
+            break
+
+        self.dd['design']['L'] = L
+        self.dd['design']['D'] = D
+        if not zlug_fix:
+            self.dd['design']['zlug'] = (2/3)*L
+
+        UC0 = self.safe_get_uc(Hm, Vm, self.dd['design']['zlug'], line_type, d, w, verbose=verbose)
+
+        if not np.isfinite(UC0):
+            break
+
+        if verbose:
+            print(f"[Iter {iter}] L={L:.2f}, D={D:.2f}, UC={UC0:.3f}")
+
+        if abs(UC0 - UC_target) < tol:
+            print("Early stopping: UC within tolerance.")
+            break
+
+        # Gradient estimate
+        delta = 0.1
+        UC_L = self.safe_get_uc(Hm, Vm, (2/3)*(L + delta), line_type, d, w, verbose=verbose)
+        UC_D = self.safe_get_uc(Hm, Vm, (2/3)*L, line_type, d, w, verbose=verbose)
+
+        grad_L = (UC_L - UC0)/delta if np.isfinite(UC_L) else 0.0
+        grad_D = (UC_D - UC0)/delta if np.isfinite(UC_D) else 0.0
+
+        # Update
+        L -= step_size * grad_L
+        D -= step_size * grad_D
+        L = np.clip(L, geomBounds[0][0], geomBounds[0][1])
+        D = np.clip(D, geomBounds[1][0], geomBounds[1][1])
+
+        if not (lambdap_con[0] <= L/D <= lambdap_con[1]):
+            if verbose:
+                print("Terminated: lambda constraint violated after update.")
+            break
+
+    self.dd['design']['L'] = L
+    self.dd['design']['D'] = D
+    self.dd['design']['zlug'] = (2/3)*L
+    self.getCapacityAnchor(Hm, Vm, self.dd['design']['zlug'], line_type, d, w, True, True)
+
+    print('\nGradient Optimized Anchor:')
+    print('Design:', self.dd['design'])
+    print('Capacity Results:', self.anchorCapacity)
+
+    return {'D': D, 'L': L, 'UC': self.anchorCapacity.get('UC', np.nan)}
\ No newline at end of file
diff --git a/famodel/anchors/README.md b/famodel/anchors/README.md
index 84788f66..bbce4321 100644
--- a/famodel/anchors/README.md
+++ b/famodel/anchors/README.md
@@ -1,229 +1,666 @@
 # Anchors Library
 
-This subpackage of FAModel contains the Anchor class as well as modules for anchor capacity 
-calculations. 
+This subpackage of FAModel contains the anchor class and all modules for the  capacity under extreme loads and the installation assessments
 
-## Anchor Class
-The anchor class contains properties and methods related to mooring anchors.
-The supported anchor types are below, with the associated FAModel name in italics.
-- Plate anchors 
-  - *DEA* (drag-embedment anchors)
-  - *SEPLA* (suction embedded plate anchors)
-  - *DEPLA* (dynamically embedded plate anchors)
-  - *VLA* (vertically loaded anchors)
-  - *plate* (unspecified plate anchor)
-- *suction_pile* (Suction caisson/ suction bucket anchors)
-- *torpedo_pile* (Torpedo pile anchors)
-- *helical_pile* (Helical pile anchors)
-- *driven_pile*  (Driven pile anchors)
-- *dandg_pile* (Drilled and grouted piles)
-
-
-The anchor class stores properties and methods that enable a wide range of modeling - from capacity to cost to loads, and more. The [anchor capacity modules](#anchor-capacity-modules) are integrated with the anchor class through the getAnchorCapacity() method. 
-### Anchor Properties
-- **r** : anchor [x,y,z] position
-- **dd** : anchor design dictionary, containing geometric properties, soil properties at the anchor location, cost
-- **ms** : moorpy system associated with this anchor point
-- **aNum** : anchor index in array mooring list (generally only used for shared moorings)
-- **mpAnchor** : moorpy point object that models this anchor
-- **anchorCapacity** : dictionary with horizontal and vertical capacity of the anchor. Generally these are loads in [N], but can also be displacements (generally for driven or drilled and grouted piles)
-- **loads** : dictionary of loads on the anchor, and the method used to obtain these loads (static or dynamic modeling). Loads include horizontal (H) and vertical (V) loads, as well as the angle of the load (theta). The keys for these loads will either include an m (for loads at the mudline) or a (for loads at the anchor lug).
-- **soilProps** : dictionary of soil property information at the location of the anchor
-- **failure_probability** : dictionary of probabilities for failure of the anchor
+## Seabed Conditions
 
+Introduction to different soil types
 
-### Anchor Methods
-- **makeMoorPyAnchor()** : Creates a MoorPy point object representing the anchor in a moorpy system
-- **getAnchorCapacity()** : Calls anchor capacity functions for the correct anchor type
-- **getFS()** : Computes safety factor for loads on the anchor
-- **getCost()** : Finds costs of anchor from MoorProps and stores in design dictionary
-- **getMass()** : Finds mass and/or UHC of anchor from MoorProps and stores in design dictionary
-- **getMudlineForces()** : Finds forces on anchor at mudline using MoorPy Point.getForces method. Use max_force=True to obtain the maximum forces on that anchor from the platform.getWatchCircle() method. For more information on the getWatchCircle() calculations, see the [Platform ReadMe](../platform/README.md). An additional anchor.loads dictionary entry is included to describe the mudline load type. 'mudline_load_type'='max' if max_force=True, and 'mudline_load_type'='current_state' if max_force=False.
-- **getLugForces()** : Finds forces at the anchor lug location with getTransferFunction function in capacity_loads.py. 
-The getTransferLoad function requires **maximum** mudline forces as an input. These forces can be sent in as a dictionary, or anchor.loads dictionary will be searched for 'Hm' and 'Vm' values with additional key-value pair 'mudline_force_type':'max' to indicate these mudline forces are maximums. 
-If there are no max mudline forces in the anchor.loads dictionary, getMudlineForces(max_force=True) will be called. Stores results in loads dictionary. If lug is at mudline or no lug provided, equates mudline forces with lug forces. 
->[!NOTE]
->The getTransferFunction function called by getLugForces() is tuned to work with maximum loads on the anchor. Some anchor configuration, load, and soil condition combinations may produce invalid results in getTransferFunction. For example, the output Va may show as negative. In that case, getLugForces() will warn the user of the invalidity of the result and assign the anchor lug forces = mudline forces.
+Heterogenous soil (mixed layers). Map of soil properties for horizontal and vertical spatial-variability.
 
+The reference elevation of the pile is the pile head (z = 0 m), from here all elevations are derived. Thus, Z0 (mudline elevation) is the distance between the pile head and the top of the first layer of soil. Main padeye locations depend on their relative elevation to z0, if zlug > z0 mooring line is embedded below the mudline elevation
+### Soil properties
+##### Input
+- profile_map 
+	- location_name: CPT or reference in the system (-)
+  - x, y: coordinates of the anchor within the lease area (m), (m)
+  - layers (at least one): 
+    - top, bottom: depth for top and bottom for each layer (m), (m)
+    - soil_type: clay/mud, sand and (weak) rock (-)  
+    - soil properties: 
+      - clay/mud:
+        - gamma: submerged soil unit weight (kN/m³)
+        - Su: undrained shear strength (kPa) 
+      - sand:
+        - gamma: submerged soil unit weight: (kN/m³)
+        - phi: internal friction angle (deg)
+        - Dr: relative density (%)
+      - (weak) rock, 
+        - UCS: unconfined compressive strength at failure (MPa)
+        - Em: rock mass modulus (MPa)
 
-### Anchor Type Requirements
+>[!NOTE]
+Driven piles are only possible on weak rock, defined here as up to UCS = 5 MPa
 
-Different geometric properties and soil conditions are needed for each anchor type. See the [Anchor Capacity Modules](#anchor-capacity-modules) section for details on the requirements of each anchor type.
+> [!IMPORTANT] 
+Units within FAModel follow the SI exclusively. The input soil parameters units follow common industry convention. Soil parameters conversion units to Pa and N/m³ take place in the capacity_soils module exclusively. There is no need to convert units.
 
+    profile_map = [
+        {
+            'name': 'CPT_1',
+            'x': 498234, 'y': 5725141,
+            'layers': [
+                {
+                    'top': 1.0, 'bottom': 6.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.0, 'gamma_bot': 8.0,
+                    'Su_top': 10, 'Su_bot': 50},
+                {
+                    'top': 6.0, 'bottom': 15.0,
+                    'soil_type': 'sand',
+                    'gamma_top': 8.0, 'gamma_bot': 8.0,
+                    'phi_top': 32, 'phi_bot': 38,
+                    'Dr_top': 70, 'Dr_bot': 75},
+                {
+                    'top': 15.0, 'bottom': 30.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.0, 'gamma_bot': 9.0,
+                    'Su_top': 100, 'Su_bot': 200}]
+        }
+    ]
+    Note:
+    - z0 = 1 m, meaning the pile head is 1 m above the mudline
+    - soil_type: clay, sand, clay
+    - this method allows different soil types and gaps in between soil layers of the same or different soil type
+##### Output
+- z0: depth of the mudline relative to the pile head (m)
+- soil types:
+  - clay/mud:
+    - f_gamma: effective unit soil weigtht at depth (N/m³)
+    - f_Su: undrained shear strength at depth (Pa)
+    - f_sigma_v_eff: effective vertical stress at depth (Pa)
+    - f_alpha: adhesion factor from API correlation (-)
+  - sand:
+    - f_gamma: effective unit soil weigtht at depth (N/m³)
+    - f_phi: friction angle at depth (deg)
+    - f_sigma_v_eff: effective vertical stress at depth (Pa)
+    - f_Dr: relative density at depth (%)
+    - f_delta: skin friction angle at depth (-)
+  - rock:
+    - f_UCS: unconfined compressive strength at depth (Pa)
+    - f_Em: rock mass modulus at depth (deg)
+------------------------------------------------------------------------------
 
-## Anchor Capacity Modules
-The following list shows the required soil conditions, soil properties, geometry, and load information for anchor capacity calculations of each anchor type. Soil classification for clay and sand can be found in [Soil Classification Parameters](#soil-classification-parameters).
+Soil classification for clay, sand and rock can be found in [Soil Classification Parameters](#soil-classification-parameters).
 >[!NOTE] 
->Some anchor capacity functions require input loads at the anchor lug point. These loads can be sent in to the getAnchorCapacity() method, or the getAnchorCapacity() method will calculate the loads by calling getLugLoads(). The input loads must be maximum or large loads on the anchor.
-
-### DEA/SEPLA/DEPLA/VLA/plate
-  - soil condition: clay/mud
-    - Su0 (undrained shear strength of soil at mudline) [kPa]
-    - k (rate of change in shear strength with depth) [kPa/m]
-    - gamma (submerged soil unit weight) [kN/m^3]
-  - geometry
-    - A (area of plate) [m^2]
-    - zlug (embedded depth of bridle/padeye below mudline - positive is below mudline, negative is above mudline) [m]
-    - beta (OPTIONAL - angle of plate after keying) [deg]
-  - loads: None
-### suction_pile (Suction caisson/ suction bucket anchors)
-  - soil conditions
-    - sand
-      - phi (internal friction angle) [deg]
-      - Dr (relative density) [%]
-      - delta (interface friction angle at soil-anchor line) [deg] ***only needed for loads calculation*
-    - clay/mud
-      - Su0 (undrained shear strength of soil at mudline) [kPa]
-      - k (rate of change in shear strength with depth) [kPa/m]
-      - alpha (adhesion factor) [-]
-  - geometry
-    - L (length of pile) [m]
-    - D (diameter of pile) [m]
-    - zlug (embedded depth of padeye below mudline) [m]
-  - loads
-    - Ha, Va (horizontal and vertical loads on padeye of anchor) 
-### torpedo_pile (Torpedo pile anchors)
-  - soil condition: clay/mud
-    - Su0 (undrained shear strength of soil at mudline) [kPa]
-    - k (rate of change in shear strength with depth) [kPa/m]
-    - alpha (adhesion factor) [-]
-  - geometry
-    - D1 (wing diameter) [m]
-    - D2 (shaft diameter) [m]
-    - L1 (wing length) [m]
-    - L2 (shaft length) [m]
-    - zlug (embedded depth of padeye below mudline) [m]
-  - loads: None
-### helical_pile (Helical pile anchors)
-  - soil conditions
-    - sand
-      - phi (internal friction angle) [deg]
-      - gamma (submerged soil unit weight) [kN/m^3]
-      - alpha_star (empirical adhesion factor **can use alpha instead*) [-]
-    - clay/mud
-      - Su0 (undrained shear strength of soil at mudline) [kPa]
-      - k (rate of change in shear strength with depth) [kPa/m]
-      - gamma (submerged soil unit weight) [kN/m^3]
-      - alpha_star (empirical adhesion factor **can use alpha instead*) [-]
-  - geometry
-    - D (helix diameter) [m]
-    - L (shaft length) [m]
-    - d (shaft diameter) [m]
-  - loads: None
-### driven_pile (Driven pile anchors)
-  - soil conditions:
-    - weak rock (up to UCS = 5 MPa)
-      - UCS (unconfined compressive strength at failure)
-      - Em (rock mass modulus)
-    - sand
-      - phi (internal friction angle) [deg]
-      - gamma (submerged soil unit weight) [kN/m^3]
-      - Dr (relative density) [%]
-    - clay/mud
-      - Su0 (undrained shear strength of soil at mudline) [kPa]
-      - k (rate of change in shear strength with depth) [kPa/m]
-      - gamma (submerged soil unit weight) [kN/m^3]
-  - geometry
-    - L (length of pile) [m]
-    - D (diameter of pile) [m]
-    - zlug (embedded depth of padeye below mudline) [m]
-  - loads
-    - Ha, Va (horizontal and vertical loads on padeye of anchor)
-
-  #### Output notes 
-  The general output is a lateral and rotational displacement or bending moment. In getAnchorCapacity, the driven pile capacity function is called in a while loop with incremented horizontal input forces until one of the displacements goes past set failure criteria, thus providing a horizontal force capacity output [N]. Vertical capacity [N] is already calculated within the driven pile capacity function.
+>Some anchor capacity functions require input loads at the anchor lug point. These loads can be sent in to the getLugLoads() method, or the getAnchorCapacity() method will calculate the loads by calling getLugLoads(). 
+The input loads must be maximum or large loads on the anchor.
+		
+### Soil classification parameters
+
+The soft, medium and hard clay soil classes are distinguished by the following parameter ranges: 
+| clay/mud     | N-Value  |     Eff. unit weight, gamma (kN/m³)  | Void ratio, e (-) | Water content,  (%) | Undrained shear strength, Su (kN/m2) |
+|:-----------------:|:--------:|:---------------------------------:|:----------:|:--------------------------------------:|:-------------------------------:|
+|     Very Soft     |  0 - 2   |             5.5 - 8.5             |  0.9 - 1.4 |                30 - 50                 |            0 - 12.5             |
+|       Soft        |  2 - 4   |             5.5 - 8.5             |  0.9 - 1.4 |                30 - 50                 |            12.5 - 25            |
+|       Medium      |  4 - 8   |             5.5 - 8.5             |  0.9 - 1.4 |                30 - 50                 |             25 - 50             |
+|       Stiff       |  8 - 15  |             8.5 - 12              |    ~ 0.6   |                20 - 30                 |            50 - 100             |
+|     Very Stiff    | 15 - 30  |             8.5 - 12              |    ~ 0.6   |                20 - 30                 |            100 - 200            |
+|        Hard       |   < 30   |             8.5 - 12              |    ~ 0.6   |                20 - 30                 |              > 200              |
+
+
+Sand can also be classified ranging from soft to hard. and are chracterize by the following ranges:
+
+| sand |  N-Value | Eff. unit weight, gamma (kN/m³) | Void ratio, e (-) | Water content,  (%)| Eff. friction angle, phi (deg) | Relative density, Dr (%) |
+|:----------------:|:--------:|:----------------------------:|:----------:|:--------------------------------------:|:-------------------:|:--------------------:|
+|   Very   Loose   |    > 4   |            7 - 9.5           |    ~ 0.8   |                 25 - 30                |        < 30         |         < 15         |
+|       Loose      |  4 - 10  |            7 - 9.5           |    ~ 0.8   |                 25 - 30                |       30 - 35       |        15 - 35       |
+|     Compact      | 10 - 30  |          9.5 - 11.5          |   ~ 0.45   |                 12 - 16                |       35 - 40       |        35 - 65       |
+|      Dense       | 30 - 50  |          9.5 - 11.5          |   ~ 0.45   |                 12 - 16                |       40 - 45       |       65 - 85        |
+|    Very Dense    |   < 50   |          9.5 - 11.5          |   ~ 0.45   |                 12 - 16                |        > 45         |         > 85         |
+
+## Anchor Types
+The supported anchor types are listed below with their associated FAModel labels in italics (*Labels are not case sensitive*). Anchors types have specific [anchor capacity](#anchor-capacity-modules) and [anchor installation](#anchor-installation-modules) application modules, these are shown for clarity below as well.
+
+|                                                        | Capacity       | Installation |
+|--------------------------------------------------------|----------------|--------------|
+|*DEA*   (drag-embedment anchors)                        | Plate          | Drag         | 
+|*SEPLA* (suction embedded plate anchors)                | Plate          | Suction      | 
+|*DEPLA* (dynamically embedded plate anchors)            | Plate          | Dynamic      |
+|*VLA* (vertically loaded anchors)                       | Plate          | Drag         |
+|*suction* (suction caisson/suction bucket anchors)      | Suction        | Suction      |
+|*torpedo* (torpedo pile anchors)                        | Torpedo        | Dynamic      |
+|*helical* (helical pile anchors)                        | Helical/Driven | Torque-crowd |
+|*driven*  (driven pile anchors)                         | Driven         | Driven       |
+|*dandg* (drilled and grouted pile anchors)              | Drilled&Grout  | Drilled      |
+
+### Anchor geometrical properties
+#### DEA/SEPLA/DEPLA/VLA/plate
+##### Short definition of the anchor concepts included in plates. Variables involved in the design:
+- soil condition: 
+    - z, gamma, Su: clay soil parameters (m), (kN/m3), (kPa) 
+- geometry:
+   - B: width of plate - dimension contained in the vertical plane (m)
+   - L: length of plate - dimension perpendicular to the vertical plane (m)
+   - zlug: embedded depth of bridle/padeye below mudline (m)
+   - beta: angle of plate with horizontal plane (deg)
+- loads:
+  - Ha, Va: horizontal and vertical loads on padeye of anchor (N), (N)
   
-  For non-rock soil, the hinge (bending moment) is also considered as a failure mode along with the lateral and rotational displacement *IF* the zlug is positive (below the mudline)
-### dandg_pile (Drilled and grouted piles)
-  - soil condition: rock
-    - UCS (unconfined compressive strength at failure)
-    - Em (rock mass modulus)
-  - geometry
-    - L (length of pile) [m]
-    - D (diameter of pile) [m]
-    - zlug (lug location (lug above mudline has negative zlug)) [m]
-  - loads
-    - Ha, Va (horizontal and vertical loads on padeye of anchor)
-#### Output notes
- The general output is a lateral and rotational displacement. In getAnchorCapacity, the drilled and grouted pile function is called in a while loop with incremented horizontal input forces until one of the displacements goes past set failure criteria, thus providing a horizontal force capacity output [N]. Vertical capacity [N] is already calculated within the driven pile capacity function. 
+#### suction_pile (suction caisson/ suction bucket anchors)
+##### Short definition of the suction anchor. Variables involved in the design:
+- soil condition:
+    - location_name:
+    - x, y: CPT or reference name
+    - layers:
+      - z, gamma, Su: clay soil parameters (m), (kN/m3), (kPa) 
+      - z, gamma, phi, Dr: sand soil parameters (m), (kN/m3), (deg), (%) 
+    
+- geometry:
+    - D: diameter of pile (m)
+    - L: length of pile (m)
+    - zlug: embedded depth of padeye below mudline (m)
+- loads:
+    - Ha, Va: horizontal and vertical loads on padeye of anchor (N), (N)
+  
+#### torpedo_pile (torpedo pile anchors)
+##### Short definition of the suction anchor. Variables involved in the design:
+- soil condition: 
+    - z, gamma, Su: clay soil parameters () 
+- geometry
+   - D1: wing diameter (m)
+   - D2: shaft diameter (m)
+   - L1: wing length (m)
+   - L2: shaft length (m)
+   - zlug: embedded depth of padeye below mudline (m)
+- loads
+  - Ha, Va: horizontal and vertical loads on padeye of anchor (N), (N)
+
+#### helical_pile (helical pile anchors)
+##### Short definition of the helical anchor. Variables involved in the design:
+- soil condition: 
+    - z, gamma, Su: clay soil parameters (m), (kN/m3), (kPa) 
+    - z, gamma, phi, Dr: sand soil parameters (m), (kN/m3), (deg), (%) 
+- geometry
+    - D: helix diameter (m)
+    - L: shaft length (m)
+    - d: shaft diameter (m)
+    - zlug: embedded depth of padeye below mudline (m)
+- loads
+    - Ha, Va: horizontal and vertical loads on padeye of anchor (N), (N)
+  
+#### driven_pile (driven pile anchors)
+##### Short definition of the helical anchor. Variables involved in the design:
+- soil condition: 
+    - z, gamma, Su: clay soil parameters (m), (kN/m3), (kPa) 
+    - z, gamma, phi, Dr: sand soil parameters (m), (kN/m3), (deg), (%) 
+    - z, UCS, Em: (weak) rock parameters (m), (MPa), (MPa)  
+- geometry
+    - L: length of pile (m)
+    - D: diameter of pile (m)
+    - zlug: embedded depth of padeye below mudline (m)
+- loads
+    - Ha, Va: horizontal and vertical loads on padeye of anchor (N), (N)
+
+> [IMPORTANT!] The general output is a lateral and rotational displacement. In getCapacityAnchor, the driven pile capacity function is called in a while loop with variable (increase or decrease) input geometrical properties until at least one of the accepting criteria past set failure criteria, thus providing a horizontal force capacity output.
+  
+ > [NOTE!] For non-rock soil, the hinge (bending moment) is also considered as a failure mode along with the lateral and rotational displacement 
  
--------------------------------------------------------------------------------
-> [!IMPORTANT] 
-> A positive zlug denotes a lug/padeye/bridle below the mudline, while a negative zlug denotes a lug/padeye/bridle above the mudline. Anchors in rock should have a zlug >= 0.
+#### dandg_pile (drilled and grouted pile anchors)
+##### Short definition of the helical anchor. Variables involved in the design:
+- soil condition: 
+    - z, UCS, Em: (weak) rock parameters (m), (MPa), (MPa)  
+- geometry
+   - L: length of pile (m)
+   - D: diameter of pile (m)
+   - zlug: lug location (m)
+- loads
+   - Ha, Va: horizontal and vertical loads on padeye of anchor
+   
+## Loads
+Loads derived from MoorPy and DRAFT are considered at a fixed point at mudline elevation. These loads need to be transfered from mudline to lug penetration when the main padeye is below the mudline. The transfer function uses soil properties (profile), mooring line properties (line_type, d and w), loads and lueg depth (zlug) to calculate loads at lug elevation (main padeye) 
+
+> [!NOTE] It is cautious to condiser as input the tension load magnitude at mudline since the load will be equal or larger to the tension at lug penetration. Conversely, the angle of the load at lug penetration will equal or larger to the angle at mudline. Therefore, yielding to more vertical componenent. Therefore, Tm >= Ta and thetam <= thetaa 
+
+##### Input
+- profile_map: soil profile 
+- Tm: tension of the load on mudline (N)
+- thetam: angle of the load on mudline (deg)
+- zlug: main padeye embeddment (m)
+- line_type: type of mooring line ('chain' or 'wire') (-)
+- d: mooring line diameter (m)
+- w: mooring line unit weight (N/m)
+	
+##### Output
+- Ta: tension of the load on padeye of anchor (N)
+- thetaa: angle of the load on padeye of anchor (deg)
+- Ha: horizontal component of the load on padeye (N)
+- Va: vertical component of the load on padeye (N) 
+- length: length of the embedded line (m)
+- drag: depth of the embedded line (m)
+
+
+The getTransferLoad function expects maximum mudline forces as input. These can be:
+
+  - Passed directly as a dictionary
+  - Retrieved from the anchor.loads dictionary using the keys 'Hm' and 'Vm', with the flag 'mudline_force_type': 'max'.
+
+If no such values are found, getMudlineForces(max_force=True) will be called automatically to obtain them.
+
+When the lug is located at the mudline, or no lug depth is specified, the function assumes lug forces are equal to mudline forces.
+
+>[!NOTE] See getLugForces() (#anchor-capacity-modules) for more details on the load transfer mechanism from mudline to lug elevation (i.e., below the seabed).
+
+The getTransferFunction, used internally by getLugForces, is calibrated for **maximum load conditions**. In some cases—depending on anchor geometry, load magnitude, and soil conditions—the function may produce invalid results (e.g., negative vertical load Va).
+When this occurs, getLugForces() issues a warning and defaults to assigning **lug forces equal to mudline forces.**
+
+>[!NOTE] Some anchor capacity functions (e.g., suction, driven, helical) require loads to be applied at the lug elevation. These can be passed directly into getCapacityAnchor(), or if not provided, the method will internally compute them using getLugForces().
+
+Always ensure that the loads used in these methods represent maximum or near-maximum force levels to ensure valid and conservative capacity estimates.
+
+
+
+## Equipment
+
+### Installation vessel
+#### Pullard force
+Drag installation. Input
+  - Tmax: maximum pullard force (N)
+
+#### Crane capacity
+Dynamic installation. Output
+  - Wp: dynamically installed plate/pile weight (N)
+
+### Installation device
+#### Suction pump
+Suction installation. Output
+  - delta_u_suction: maximum underpressure given by the suction pump during installation (Pa)
+  - delta_u_retrieve: maxumum overpressure given by the suction pump during retrieval/removal (Pa)
 
-> [!NOTE] 
-> Load inputs to the capacity functions (with the exception of driven & drilled and grouted anchors) are in kN, while the anchor loads dictionary is in N. This conversion is automatically completed in the getAnchorCapacity() function so no manual load conversion is required. Load outputs are automatically converted in the getAnchorCapacity function where necessary. 
+#### Hydraulic drive head
+Torque-crowd installation. Output
+  - Torque: torque (Nm)
+  - Force: crowd compressive force (N)
+
+#### Hammer
+Driven installation. Input
+  - hammer_params: 
+    - r_m: ram mass (kg) 
+    - h: strock height (m) 
+    - efficiency: efficiency of the hammer (-)
+
+#### Drill head
+Drilled installation
 
 -----------------------------------------------------------------------------
-### Model Fidelity
+  
+## Anchor Class
+The anchor class contains properties and methods related to mooring anchors.
 
-There are two levels of fidelity in these models:
+The anchor class stores properties and methods that enable a wide range of modeling. 
+The [anchor capacity modules](#anchor-capacity-modules) and the [anchor installation modules](#anchor-installation-modules) are integrated with FAModel through the anchor class and its methods.
+ 
+### Anchor modules
+Introduction
+ 
+Inspection of the folder: anchors_famodel
 
-- Level 1 basic models are soil-dependent capacity curves for a 
-  range of anchor types based on performing curve fits to 
-  published information in anchor manuals and standards. 
-- Level 2 intermediate models are quantitative calculations for
-  suction caissons and plate anchors that account for quantitative 
-  soil properties as well as their variation with embedment depth.
+|                                              |                |              |
+|----------------------------------------------|----------------|--------------|
+|![Plate anchor](images/Plateanchors/Plate.png)|![Suction pile anchor](images/Suctionpiles/Suction.png)|![Torpedo pile anchor](images/Torpedopiles/Torpedo.png)| 
+|![Helical pile anchor](images/Helicalpiles/Helical.png)|![Driven pile anchor](images/Drivenpiles/Driven.png)|![Drilled and grouted pile anchor](images/Drilledandgroutedpiles/Drilled.png)| 
 
-This plot gives an example of the capacity curves that can be 
-produced by the intermediate model (holding capacity for a suction
-embedded plate anchor) as a function of surface shear strength:
 
-![Capacities](images/SEPLA_curves_small.PNG)
+#### Anchor capacity modules
+Analytical static capacity models for extreme load conditions. These models include static soil-structure interaction but the cyclic loading conditions are not covered yet. They will need to follow from further research.
 
-### Implemented level-1 model anchor and soil types
+- **capacity_plate** : 
+	- getCapacityPlate(profile_map, location_name, D, L, zlug, Ha, Va, plot)
+  - capacityPlate dict:
+    - 'Capacity'
+    - 'Horizontal max.', 'Vertical max.'
+    - 'Unity check'
+    - 'Weight plate' 
 
-|             | DEA       | Suction | VLA | SEPLA |
-|-------------|-----------|---------|-----|-------|
-| Soft clay   | X         | X       | X   | X     |
-| Medium clay | X         | X       | X   | X     |
-| Hard clay   | X         |         |     |       |
-| Sand        | X         |         |     |       |
+- **capacity_suction** : 
+	- getCapacitySuction(profile_map, location_name, D, L, zlug, Ha, Va, thetalug, psilug, plot)
+  - capacitySuction dict:
+    - 'Horizontal max.', 'Vertical max.'
+    - 'Unity check'
+    - 'Weight pile'
+  
+- **capacity_torpedo** : 
+	- getCapacityTorpedo(profile_map, location_name, D1, D2, L1, L2, zlug, ballast, Ha, Va, plot)
+  - capacityTorpedo dict:
+    - 'Horizontal max.', 'Vertical max.'
+    - 'Unity check'
+    - 'Weight pile'
 
-### Parameters needed for level-2 anchor capacity models
+- **capacity_helical** : 
+	- getCapacityHelical(profile_map, location_name, D, L, d, zlug, Ha, Va, plot)
+  - capacityHelical dict:
+    - 'Horizontal max.', 'Vertical max.'
+    - 'Lateral displacement', 'Rotational displacement'
+    - 'Bending moment'
+    - 'Plastic moment'
+    - 'Unity check (vertical)', 'Unity check (horizontal)'
+    - 'Weight pile'
 
-|        **Anchor type** | **Suction** | **Suction** | **VLA**  | **SEPLA** |
-|------------------------|-------------|-------------|----------|-----------|
-|        **Soil type**   | **Clay**    | **Sand**    | **Clay** | **Clay**  |
-| **Anchor parameters**  |             |             |          |           |
-|        Diameter        | x           | x           |          |           |
-|        Length          | x           | x           |          |           |
-|        Area            |             |             | X        | X         |
-|        Thickness       | ratio       | ratio       | ratio    | ratio     |
-|       Embedment depth  |             |             | X        | X         |
-| **Soil parameters**    |             |             |          |           |
-|        gamma           | X           | X           | X        | X         |
-|        Su0             | X           |             | X        | X         |
-|        k               | X           |             | X        | X         |
-|        alpha           | X           |             |          |           |
-|        phi             |             | X           |          |           |
+- **capacity_driven** : 
+	- getCapacityDriven(profile_map, location_name, L, D, zlug, Ha, Va, plot)
+  - capacityDriven dict:
+    - 'Horizontal max.', 'Vertical max.'
+    - 'Lateral displacement', 'Rotational displacement'
+    - 'Bending moment'
+    - 'Plastic moment'
+    - 'Unity check (vertical)', 'Unity check (horizontal)'
+    - 'Weight pile'
+ 
+- **capacity_dandg** : 
+	- getCapacityDandG(profile_map, location_name, L, D, zlug, Ha, Va, plot)
+  - capacityDandG dict:
+    - 'Horizontal max.', 'Vertical max.'
+    - 'Lateral displacement', 'Rotational displacement'
+    - 'Bending moment'
+    - 'Plastic moment'
+    - 'Unity check (vertical)', 'Unity check (horizontal)'
+    - 'Weight pile'
 
+- **capacity_load** : 
+	- getTransferFunction(profile_map, Tm, thetam, zlug, line_type, d, w, plot)
+  - capacityLoads dict:
+    - 'Tm', 'thetam'
+    - 'Hm', 'Vm'
+    - 'Ta', 'thetaa'
+    - 'Ha', 'Va'
+    - 'length'
+    - 'drag_values'
+    - 'depth_values'
 
-These models will continue to be expanded as data sources and time permit.
+#### Anchor installation modules
+Analytical installation models for main anchor types.
 
-## Soil Classification Parameters
+- **installation_drag** : 
+	- getInstallationPlate(profile_map, location_name, B, Lf, Ls, Lca, Lj, plot)
+  - installationDrag dict:
+    - 'Capacity'
+    - 'embedment_depth'
+    - 'drag_distance'
+    - 'Weight plate'
 
-The soft, medium, and hard clay soil classes are distinguished by the following parameter ranges: 
-| Soil Type (Clay)  | N-Value  | Effective Sat. Unit Weight, kN/m3 | Void Ratio | Natural Water Content in Sat. State, % | Undrained Shear Strength, kN/m2 |
-|:-----------------:|:--------:|:---------------------------------:|:----------:|:--------------------------------------:|:-------------------------------:|
-|     Very Soft     |  0 - 2   |             5.5 - 8.5             |  0.9 - 1.4 |                30 - 50                 |            0 - 12.5             |
-|       Soft        |  2 - 4   |             5.5 - 8.5             |  0.9 - 1.4 |                30 - 50                 |            12.5 - 25            |
-|       Medium      |  4 - 8   |             5.5 - 8.5             |  0.9 - 1.4 |                30 - 50                 |             25 - 50             |
-|       Stiff       |  8 - 15  |             8.5 - 12              |    ~ 0.6   |                20 - 30                 |            50 - 100             |
-|     Very Stiff    | 15 - 30  |             8.5 - 12              |    ~ 0.6   |                20 - 30                 |            100 - 200            |
-|        Hard       |   < 30   |             8.5 - 12              |    ~ 0.6   |                20 - 30                 |              > 200              |
+- **installation_suction** : 
+	- getInstallationSuction(profile_map, location_name, D, L, plot)
+  - installationSuction dict:
+    - 'Fi', 'Fo', 'Qw'
+    - 'Rsuction', 'Rretrieval'
+    - 'SWP_depth'
 
+- **buckling_suction** : 
+	- getBucklingSuction(profile_map, location_name, D, L, plot)
+  - installationBuckling dict:
+    - 'UC'
+    - 'PE'
 
-Sand can also be classified ranging from soft to hard, however only a single sand class is supported at this time. In the future, sand classes will follow the parameter ranges in the following table:
+- **installation_dynamic** : 
+	- getInstallationTorpedo(profile_map, location, D1, D2, L1, L2, ballast, drop_height, plot)
+  - installationDynamic dict:
+    - 'final_depth'
+    - 'v_max', 'v_impact'
+
+- **installation_torque** : 
+	- getInstallationHelical(profile_map, location_name, D1, D2, L1, L2, zlug, ballast, Ha, Va, plot)
+  - installationTorque dict:
+    - 'Force', 'Torque'
+    - 'sigma_helix', 'sigma_core', 'sigma_weld'
+    - 'failire_mode'
+
+- **installation_driven** : 
+	- getInstallationDriven(profile_map, location_name, D, L, hammer_params, J_shaft, J_toe, plot)
+  - installationDriven dict
+
+- **installation_drill** : 
+	- getInstallationDrill(profile_map, location_name, D, L, driller_params, plot)
+  - installationDrill dict
+
+#### Anchor support modules
+
+- **anchor_soils** : 
+	- clay_profile(profile)
+        -  **return:** z0, f_gamma, f_Su, f_sigma_v_eff, f_alpha 
+	- sand_profile(profile) 
+        -  **return:** z0, f_gamma, f_phi, f_Dr, f_sigma_v_eff, f_delta
+	- rock_profile(profile)
+        - **return:** z0, f_UCS, f_Em
+
+- **anchor_solvers** : 
+	- fd_solver(n, N, h, D, t, fy, EI, Ha, Va, zlug, z0, k_secant)
+        - **return:** y, Mi, Mp, hinge_formed, hinge_location
+
+- **anchor_pycurves** : 
+	- py_Matlock(z, D, Su, sigma_v_eff, gamma, z0, return_curve)
+        - **return:**  f, (y, p)
+	- py_API(z, D, phi, sigma_v_eff, Dr, z0, return_curve)
+        - **return:**  f, (y, p)
+	- py_Reese(z, D, UCS, Em, z0, return_curve)
+        - **return:**  f, (y, p) 
+	- py_Lovera(z, D, UCS, Em, z0, delta_grout, E_grout, delta_crushed, return_curve)
+        - **return:**  f, (y, p)
+
+- **anchor_plots** : 
+	- plot_pile(layers, y, z, D, L, z0, zlug, hinge_location)
+	- plot_suction(layers, L, D, z0, zlug)
+  - plot_suction(layers, D1, D2, L1, L2, z0, zlug)
+  - plot_helical(layers, D, L, d, z0, zlug, n_helix, spacing)
+  - plot_plate(layers, B, L, z0, zlug, beta)
+  - plot_load(layers, drag_values, depth_values, Tm, thetam, Ta, thetaa, zlug)
+  - plot_pycurve(pycurve_data)
+
+### Anchor class methods
+
+- **Anchor.setSoilProfile(profile_map)** 
+
+  Assign a soil profile directly to the anchor from a single CPT (Cone Penetration Test) record.
+
+  This method sets the internal soil_profile, extracts soil types, and organizes layer properties by soil type. It assumes that the input contains only one CPT entry.
+
+  **Parameters**
+    - **profile_map** : list of dict. A list containing exactly one dictionary representing a CPT profile. The dictionary has:
+      - 'location_name': a string indicating the name of the CPT
+      - 'x', 'y': coordinates of the CPT location
+      - 'layers': a list of layer dictionaries, each with a 'soil_type' key and relevant soil parameters.
+    
+  **Raises**
+    - **ValueError** : If profile_map contains more than one CPT.
+
+  **Attributes Updated**
+  - **self.soil_profile** : list of dict. Stores the soil layers from the CPT.
+  - **self.profile_name** : str. Name of the CPT, default is "CPT_Assigned" if not provided.
+  - **self.soil_type_list** : list of str. Unique soil types present in the profile.
+  - **self.soil_type** : str. If a single soil type is present, its name; otherwise, 'mixed'.
+  - **self.soilProps** : dict. Dictionary grouping layer properties (excluding soil_type) by soil type.
+
+- **Anchor.interpolateSoilProfile(profile_map)**  
+
+  Interpolate a soil profile for the anchor location from the four nearest CPTs using inverse distance weighting.
+
+  This method assumes all CPTs share the same layer structure. Each soil parameter is interpolated layer-by-layer based on the relative proximity of the CPTs to the anchor.
+
+  **Parameters**
+    - **profile_map** : list of dict.  A list containing at least four CPT profile dictionaries. Each dictionary has:
+      - 'location_name': a string indicating the name of the CPT
+      - 'x', 'y': coordinates of the CPT location
+      - 'layers': a list of layer dictionaries, each with a 'soil_type' key and relevant soil parameters.
+    
+  **Raises**
+    - **ValueError** : If fewer than four CPTs are provided in profile_map.
+
+  **Attributes Updated**
+  - **self.soil_profile** : list of dict. Stores the soil layers from the CPT.
+  - **self.profile_name** : str. Set to "Interpolated_2D".
+  - **self.soil_type_list** : list of str. Unique soil types present in the interpolated profile.
+  - **self.soil_type** : str. If a single soil type is present, its name; otherwise, 'mixed'.
+  - **self.soilProps** : dict. Dictionary grouping layer properties (excluding soil_type) by soil type.
+
+- **Anchor.makeMoorPyAnchor(ms)**  
+
+  Create and register a MoorPy anchor point within the given MoorPy system using the anchor's location and design properties.
+
+  The anchor is added as a fixed point in the MoorPy model (Point object) and its mass and diameter are assigned if available. The method also sets the point type based on the anchor type.
+
+    **Parameters**
+    - **ms** : MoorPy system instance. The MoorPy system in which the anchor will be created.
+    
+  **Attributes Updated**
+  - **self.mpAnchor** : MoorPy Point. Reference to the created MoorPy anchor point in the system.
+
+- **Anchor.getLineProperties()**  
+
+  Retrieve the mooring line type, diameter and unit weight from the anchor's attached mooring object.
+
+  This method inspects the attached Mooring object and extracts relevant line properties from its first section. If no chain is present, the method assumes no load transfer below the mudline and returns None for diameter and weight.
+
+    **Parameters**
+    - **line_type** : str.  Type of mooring line (e.g., 'chain', 'wire').
+    - **d** : float or None. Nominal diameter of the mooring line (m) or None if not applicable.
+    - **w** :  float or None. Unit weight of the mooring line (N/m) or None if not applicable.
+        
+    **Raises**
+    - **ValueError** : If no mooring line attachment is found for the anchor.
+
+- **Anchor.getMudlineForces(max_force=False, lines_only=False, seabed=True, xyz=False, project=None)** 
+
+  Compute the forces acting on the anchor at the mudline, either from the current state of the MoorPy system or as the maximum expected force based on platform excursion.
+
+  If max_force=True, the method retrieves the extreme load on the anchor using either the provided project’s arrayWatchCircle() method or the attached platform’s getWatchCircle() method. Otherwise, it calculates the current forces using MoorPy's getForces().
+
+    **Parameters**
+    - **max_force** : bool, optional. If True, compute the maximum expected mudline force based on platform excursion. Default is False.
+    - **lines_only** : bool, optional. If True, considers only mooring line forces (ignores seabed and body effects). Default is False.
+    - **seabed** :  bool, optional. If True, includes seabed reaction force in the calculation. Default is True.
+    - **xyz** :  bool, optional. If True, returns forces in the x, y, z directions. Otherwise returns only the relevant DOFs. Default is False
+    - **project** :  bool, optional. Project object with a arrayWatchCircle() method. Used to compute global platform excursions when max_force=True.
+
+  **Attributes Updated**
+  - **self.loads** : dict. Stores the computed mudline force components and metadata:
+      - 'Hm': horizontal force magnitude at mudline (N)
+      - 'Vm': vertical force at mudline (N)
+      - 'thetam': angle of applied load at mudline (deg)
+      - 'method': load computation method (currently 'static')
+      - 'mudline_load_type': 'current_state' or 'max_force', depending on the mode used   
+
+- **Anchor.getLugForces(Hm, Vm, zlug, line_type=None, d=None, w=None, plot=False)**  
+
+  Calculate the horizontal and vertical loads at the anchor lug (Ha, Va) based on the mudline loads and the load transfer profile along the mooring line.
+
+  If the padeye depth zlug is embedded below the mudline, the method computes the lug loads using the load transfer model. Otherwise, it assigns the mudline loads directly to the lug.
+
+  **Parameters**
+  - **Hm** : float. Horizontal mudline load (N).
+  - **Vm** : float. Vertical mudline load (N).
+  - **zlug** :  float. Padeye embedment depth (m).
+  - **line_type** :  str, optional. Type of mooring line ('chain' or 'wire'). If not provided, inferred from attachments or defaults to 'chain'.
+  - **d** :  float, optional. Mooring line diameter (m).
+  - **w** :  float, optional. Mooring line unit weight (N/m).
+  - **plot** :   bool, optional. If True, generates plots of load transfer and geometry. Default is False.
+
+  **Raises**
+  - **ValueError** : If the soil profile is not assigned to the anchor before calling this method.
+
+  **Attributes Updated**
+  - **self.anchorCapacity** : dict. Stores the anchor's computed capacity results, including:
+      - 'Hmax': maximum horizontal capacity (N).
+      - 'Vmax': maximum vertical capacity (N).
+      - 'Ha','Va': lug-level horizontal and vertical loads (N).
+      - 'UC' or 'Unity check (horizontal)', 'Unity check (vertical)' : capacity utilization checks.
+      - 'Lateral displacement', 'Rotational displacement' : optional displacement results (if available)
+      - 'Weight pile', 'Weight plate' : self-weight of pile or plate depending on type.
+      - 'zlug' : lug depth (m), and 'z0' : mudline reference elevation (m)
+
+- **Anchor.getCapacityAnchor(Hm, Vm, zlug, line_type=None, d=None, w=None, mass_update=False, plot=False)** 
+
+  Calculate the load capacity of the anchor based on its type, geometry and local soil profile.
+
+  This method computes the anchor resistance against applied horizontal and vertical loads using the appropriate capacity model for the anchor type. It optionally performs load transfer from the mudline to the lug and updates the anchor's capacity results.
+
+  **Parameters**
+  - **Hm** : float. Horizontal mudline load (N).
+  - **Vm** : float. Vertical mudline load (N).
+  - **zlug** :  float. Padeye embedment depth (m).
+  - **line_type** :  str, optional. Type of mooring line ('chain' or 'wire'). If not provided, inferred from attachments or defaults to 'chain'.
+  - **d** : float, optional. Mooring line diameter (m).
+  - **w** : float, optional. Mooring line unit weight (N/m).
+  - **mass_update** : bool, optional. If True, updates the anchor's weight based on computed capacity. Default is False.
+  - **plot** : bool, optional. Whether to generate a plot of the load transfer profile. Default is False.
+
+  **Raises**
+  - **ValueError** : If the anchor type is unknown or if the soil profile is not properly assigned.
+
+  **Attributes Updated**
+  - **layers** : list of dict. The soil profile layers used in the load transfer calculation.
+  - **Ha** : float. Horizontal load at the lug (N).
+  - **Va** : float. Vertical load at the lug (N).
+ 
+- **Anchor.getSizeAnchor(geom, geomKeys, geomBounds=None, loads=None, lambda_con=[3, 6], zlug_fix=True,      safety_factor={'SF_combined':1.0}, plot=False)** 
+
+  Generalized optimization method to determine the appropriate geometry for all anchor types based on load conditions and safety factor requirements.
+
+  For suction, torpedo, and plate-type anchors, the method minimizes the difference between the calculated and target Unity Check (UC). For driven, helical, and dandg anchors, the method iteratively searches for the smallest geometry that satisfies combined UC, lateral and rotational displacement limits.
+
+  **Parameters**
+  - **geom** : : list of float. Initial geometry values (e.g., [L, D]).
+  - **geomKeys** : list of str. Keys that define the geometry variables to optimize (e.g., ['L', 'D']).
+  - **geomBounds** :  list of tuple, optional. Bounds for geometry values, e.g., [(5.0, 20.0), (1.0, 4.0)].
+  - **loads** :  dict, optional. Dictionary containing mudline forces ('Hm', 'Vm'). Defaults to self.loads.
+  - **lambdap_con** : list of float, optional. Minimum and maximum slenderness ratio constraints [L/D_min, L/D_max]. Default is [4, 8].
+  - **zlug_fix** : float, optional. If False, allows zlug to vary with geometry. Default is True.
+  - **safety_factor** : bool, optional.  Dictionary with safety factor targets (e.g., {'SF_combined': 1.5}). Default is {'SF_combined': 1.0}.
+  - **plot** : bool, optional. If True, generates plots the final capacity results. Default is False.
+
+  **Raises**
+  - **ValueError** :  If the anchor type is not supported for this optimization method.
+
+  **Attributes Updated**
+  - **self.dd['design']** : list of dict. The soil profile layers used in the load transfer calculation.
+  - **self.anchorCapacity** : float. Horizontal load at the lug (N).
+    - Ha, Va : float. Lug loads (N).
+    - Ha, Va : float. Lug loads (N).
+    - UC or 'Unity check (horizontal)', 'Unity check (vertical)'
+    - Optional displacements and weights if applicable
+
+- **Anchor.getSafetyFactor(ms=None)** 
+
+  Estimate the material cost of the anchor using the MoorPy Point object and its getCost_and_MBL() method.
+
+  If no MoorPy system is provided, the method initializes one and registers the anchor. Cost is based on mass and design parameters, and the Minimum Breaking Load (MBL) is also computed.
+
+  **Parameters**
+  - **ms** : MoorPy system instance, optional. If provided, uses the existing system. Otherwise, creates a new MoorPy system internally.
+
+  **Raises**
+  - **KeyError** : If self.mass is not defined and neither 'Weight pile' nor 'Weight plate' is available in self.anchorCapacity. This typically indicates that getCapacityAnchor() has not been called before getCostAnchor().
+
+  **Attributes Updated**
+  - **self.cost** : dict. Stores cost-related metrics for the anchor:
+    - 'Material cost' : Estimated anchor material cost.
+    - 'MBL' : Minimum Breaking Load (from MoorPy).
+    - 'unit_cost' : Cost per unit mass (cost/mass).
+  - **self.mpAnchor.m** : float. Mass of the MoorPy anchor point (assigned if self.mass is not already set).
+
+### Anchor Object Properties
+
+- **r** : anchor [x, y, z] position
+- **dd** : anchor design dictionary, containing geometric properties, soil properties at the anchor location, cost
+- **ms** : MoorPy system associated with this anchor point
+- **aNum** : anchor index in array mooring list (generally only used for shared moorings)
+- **mpAnchor** : MoorPy point object that models this anchor
+- **anchorCapacity** : dictionary with horizontal and vertical capacity of the anchor. Generally these are loads in [N], but can also be displacements (generally for driven or drilled and grouted piles)
+- **loads** : dictionary of loads on the anchor, and the method used to obtain these loads (static or dynamic modeling). 
+Loads include mooring line tension (T) with the angle of the load (theta) as well as horizontal (H) and vertical (V) loads components. 
+The keys for these loads will either include an m (for loads at the mudline) or a (for loads at the anchor lug / main padeye).
+- **soilProps** : dictionary of soil property information at the location of the anchor
+- **failure_probability** : dictionary of probabilities for failure of the anchor
+
+### Anchor Type Requirements
+
+Different geometric properties and soil conditions are needed for each anchor type. See the [Anchor Capacity Modules](#anchor-capacity-modules) section for details on the requirements of each anchor type.
+
+## Anchor Capacity Modules
+The following list shows the required soil conditions, load information and geometrical properties involved in the anchors' capacity calculations. 
+
+
+#### Output notes
+ The general output is a lateral and rotational displacement. In getAnchorCapacity, the drilled and grouted pile function is called in a while loop with incremented horizontal input forces 
+ until one of the displacements goes past set failure criteria, thus providing a horizontal force capacity output [N]. Vertical capacity [N] is already calculated within the driven pile capacity function. 
+ 
 
-| Soil Type (sand) |  N-Value | Eff. Sat. Unit Weight, kN/m3 | Void Ratio | Natural Water Content in Sat. State, % | Eff. friction Angle | Relative density (%) |
-|:----------------:|:--------:|:----------------------------:|:----------:|:--------------------------------------:|:-------------------:|:--------------------:|
-|   Very   Loose   |    > 4   |            7 - 9.5           |    ~ 0.8   |                 25 - 30                |        < 30         |         < 15         |
-|       Loose      |  4 - 10  |            7 - 9.5           |    ~ 0.8   |                 25 - 30                |       30 - 35       |        15 - 35       |
-|     Compact      | 10 - 30  |          9.5 - 11.5          |   ~ 0.45   |                 12 - 16                |       35 - 40       |        35 - 65       |
-|      Dense       | 30 - 50  |          9.5 - 11.5          |   ~ 0.45   |                 12 - 16                |       40 - 45       |       65 - 85        |
-|    Very Dense    |   < 50   |          9.5 - 11.5          |   ~ 0.45   |                 12 - 16                |        > 45         |         > 85         |
 
-Conversion functions are under development to switch between categories (level 1 anchor models) 
-and quantitative soil metrics (level 2 anchor models).
\ No newline at end of file
diff --git a/famodel/anchors/README_FMO.md b/famodel/anchors/README_FMO.md
deleted file mode 100644
index c4498589..00000000
--- a/famodel/anchors/README_FMO.md
+++ /dev/null
@@ -1,267 +0,0 @@
-# Anchors Library
-
-This subpackage of FAModel contains the Anchor class as well as modules for analytical static anchor capacity assessment. 
-
-## Anchor Class
-The anchor class contains properties and methods related to mooring anchors.
-
-The anchor class stores properties and methods that enable a wide range of modeling - from capacity to cost to loads, and more. 
-The [anchor capacity modules](#anchor-capacity-modules) are integrated with the anchor class through the getAnchorCapacity() method.
- 
-### Anchor Files
-Introduction 
-Inspection of the folder: anchors_famodel
-
-#### Anchor Capacity Files
-- **capacity_plate** : getCapacityPlate
-- **capacity_suction** : getCapacitySuction
-- **capacity_torpedo** : getCapacityTorpedo
-- **capacity_driven** : getCapacityDriven
-- **capacity_dandg** : getCapacityDandG
-- **capacity_helical** : getCapacityHelical
-- **capacity_load** : getTransferFunction
-
-#### Anchor Support Files
-- **capacity_soils** : clay_profile, sand_profile and rock_profile
-- **capacity_solvers** : fd_solver for non-linear solver
-- **capacity_pycurves** : py_Matlock, py_API, py_Reese and py_Lovera
-- **capacity_plots** : plot_driven, plot_suction, plot_helical,plot_plate, plot_dandg, plot_load, plot_pycurve
-
-### Anchor Methods
-- **setSoilProfile()** : Assign a bilinearly interpolated soil profile from the 4 nearest CPTs
-- **makeMoorPyAnchor()** : Creates a MoorPy point object representing the anchor in a moorpy system
-- **getMudlineForces()** : Finds forces on anchor at mudline using MoorPy Point.getForces method. Use max_force=True to obtain the maximum forces on that anchor from the platform.getWatchCircle() method. 
-For more information on the getWatchCircle() calculations, see the [Platform ReadMe](../platform/README.md). An additional anchor.loads dictionary entry is included to describe the mudline load type. 
-'mudline_load_type'='max' if max_force=True, and 'mudline_load_type'='current_state' if max_force=False.
-- **getLugForces()** : Finds forces at the anchor lug location with getTransferFunction function in capacity_loads.py
-- **getCapacityAnchor()** : Calls anchor capacity functions for the correct anchor type using the getLugForces embedded in the method
-- **getSizeAnchor()** : Calls sizing anchor functions for the correct anchor type using the getLugForces embedded in the method
-- **getFS()** : Computes safety factor for loads on the anchor
-- **getCost()** : Finds costs of anchor from MoorProps and stores in design dictionary
-- **getCombinedPlot()** : Create a plot showing the anchor and the inverse catenary overlay in the same coordinate system.
-
-### Anchor Object Properties
-- **r** : anchor [x,y,z] position
-- **dd** : anchor design dictionary, containing geometric properties, soil properties at the anchor location, cost
-- **ms** : moorpy system associated with this anchor point
-- **aNum** : anchor index in array mooring list (generally only used for shared moorings)
-- **mpAnchor** : moorpy point object that models this anchor
-- **anchorCapacity** : dictionary with horizontal and vertical capacity of the anchor. Generally these are loads in [N], but can also be displacements (generally for driven or drilled and grouted piles)
-- **loads** : dictionary of loads on the anchor, and the method used to obtain these loads (static or dynamic modeling). 
-Loads include mooring line tension (T) with the angle of the load (theta) as well as horizontal (H) and vertical (V) loads components. 
-The keys for these loads will either include an m (for loads at the mudline) or a (for loads at the anchor lug / main padeye).
-- **soilProps** : dictionary of soil property information at the location of the anchor
-- **failure_probability** : dictionary of probabilities for failure of the anchor
-
-### Anchor Type Requirements
-
-Different geometric properties and soil conditions are needed for each anchor type. See the [Anchor Capacity Modules](#anchor-capacity-modules) section for details on the requirements of each anchor type.
-
-## Anchor Capacity Modules
-The following list shows the required soil conditions, load information and geometrical properties involved in the anchors' capacity calculations. 
-Soil classification for clay, sand and rock can be found in [Soil Classification Parameters](#soil-classification-parameters).
->[!NOTE] 
->Some anchor capacity functions require input loads at the anchor lug point. These loads can be sent in to the getAnchorCapacity() method, or the getAnchorCapacity() method will calculate the loads by calling getLugLoads(). 
-The input loads must be maximum or large loads on the anchor.
-
-### Soil Properties
-Introduction to different soil types
-- clay/mud
-	- gamma (submerged soil unit weight) (kN/m^3)
-	- Su (undrained shear strength of soil at mudline) (kPa)
-	
-- sand
-	- gamma (submerged soil unit weight) (kN/m^3)
-	- phi (internal friction angle) (deg)
-	- Dr (relative density) (%)
-	
-- rock (weak rock up to UCS = 5 MPa)
-	- UCS (unconfined compressive strength at failure) (MPa)
-	- Em (rock mass modulus) (MPa)
-		
-### Soil Classification Parameters
-
-The soft, medium, and hard clay soil classes are distinguished by the following parameter ranges: 
-| Soil Type (clay)  | N-Value  |     Eff. Sat. Unit Weight, kN/m3  | Void Ratio | Natural Water Content in Sat. State, % | Undrained Shear Strength, kN/m2 |
-|:-----------------:|:--------:|:---------------------------------:|:----------:|:--------------------------------------:|:-------------------------------:|
-|     Very Soft     |  0 - 2   |             5.5 - 8.5             |  0.9 - 1.4 |                30 - 50                 |            0 - 12.5             |
-|       Soft        |  2 - 4   |             5.5 - 8.5             |  0.9 - 1.4 |                30 - 50                 |            12.5 - 25            |
-|       Medium      |  4 - 8   |             5.5 - 8.5             |  0.9 - 1.4 |                30 - 50                 |             25 - 50             |
-|       Stiff       |  8 - 15  |             8.5 - 12              |    ~ 0.6   |                20 - 30                 |            50 - 100             |
-|     Very Stiff    | 15 - 30  |             8.5 - 12              |    ~ 0.6   |                20 - 30                 |            100 - 200            |
-|        Hard       |   < 30   |             8.5 - 12              |    ~ 0.6   |                20 - 30                 |              > 200              |
-
-
-Sand can also be classified ranging from soft to hard, however only a single sand class is supported at this time. In the future, sand classes will follow the parameter ranges in the following table:
-
-| Soil Type (sand) |  N-Value | Eff. Sat. Unit Weight, kN/m3 | Void Ratio | Natural Water Content in Sat. State, % | Eff. friction Angle | Relative density (%) |
-|:----------------:|:--------:|:----------------------------:|:----------:|:--------------------------------------:|:-------------------:|:--------------------:|
-|   Very   Loose   |    > 4   |            7 - 9.5           |    ~ 0.8   |                 25 - 30                |        < 30         |         < 15         |
-|       Loose      |  4 - 10  |            7 - 9.5           |    ~ 0.8   |                 25 - 30                |       30 - 35       |        15 - 35       |
-|     Compact      | 10 - 30  |          9.5 - 11.5          |   ~ 0.45   |                 12 - 16                |       35 - 40       |        35 - 65       |
-|      Dense       | 30 - 50  |          9.5 - 11.5          |   ~ 0.45   |                 12 - 16                |       40 - 45       |       65 - 85        |
-|    Very Dense    |   < 50   |          9.5 - 11.5          |   ~ 0.45   |                 12 - 16                |        > 45         |         > 85         |
-
-Conversion Units
-
-Z0 explanaition on the pile head reference and how for zlug > z0 mooring line is embedded and below the mudline elevation
-
-### Loads
-- Loads at mudline elevation
-	- Tm, thetam (Tension and angle of the load on mudline)
-	- Hm, Vm (Horizontal and vertical loads on mudline)
-- Loads at mudline elevation
-	- Ta, thetaa (Tension and angle of the load on padeye of anchor)
-	- Ha, Va (Horizontal and vertical loads on padeye of anchor)
-- Transfer functions: soil properties (profile)  mooring line properties (line_type, d and w), loads and zlug 
-
-> [!NOTE] check getLugForces for more details on this transfer function from mudline to lug elevation (below the seabed)
-The getTransferLoad function requires **maximum** mudline forces as an input. These forces can be sent in as a dictionary, or anchor.loads dictionary will be searched for 'Hm' and 'Vm' values with additional 
-key-value pair 'mudline_force_type':'max' to indicate these mudline forces are maximums.
- 
-If there are no max mudline forces in the anchor.loads dictionary, getMudlineForces(max_force=True) will be called. Stores results in loads dictionary. 
-If lug is at mudline or no lug provided, equates mudline forces with lug forces. 
->[!NOTE]
->The getTransferFunction function called by getLugForces() is tuned to work with maximum loads on the anchor. Some anchor configuration, load, and soil condition combinations may produce invalid results in getTransferFunction. 
-For example, the output Va may show as negative. In that case, getLugForces() will warn the user of the invalidity of the result and assign the anchor lug forces = mudline forces.
-
--------------------------------------------------------------------------------
-> [!IMPORTANT] 
-> A positive zlug denotes a lug/padeye/bridle below the mudline, while a negative zlug denotes a lug/padeye/bridle above the mudline. Anchors in rock should have a zlug >= 0.
-
-> [!NOTE] 
-> Load inputs to the capacity functions (with the exception of driven & drilled and grouted anchors) are in kN, while the anchor loads dictionary is in N. This conversion is automatically completed in the getAnchorCapacity() 
-function so no manual load conversion is required. Load outputs are automatically converted in the getAnchorCapacity function where necessary. 
-
------------------------------------------------------------------------------
-	
-### Anchor Types
-The supported anchor types are below, with the associated FAModel name in italics.
-- Plate anchors 
-  - *DEA* (drag-embedment anchors)
-  - *SEPLA* (suction embedded plate anchors)
-  - *DEPLA* (dynamically embedded plate anchors)
-  - *VLA* (vertically loaded anchors)
-  - *plate* (unspecified plate anchor)
-- *suction_pile* (Suction caisson/ suction bucket anchors)
-- *torpedo_pile* (Torpedo pile anchors)
-- *helical_pile* (Helical pile anchors)
-- *driven_pile*  (Driven pile anchors)
-- *dandg_pile* (Drilled and grouted piles)
-
-### Anchor geometrical properties
-#### DEA/SEPLA/DEPLA/VLA/plate
-- soil condition: clay 
-- geometry
-   - A (area of plate) (m^2)
-   - zlug (embedded depth of bridle/padeye below mudline - positive is below mudline, negative is above mudline) (m)
-   - beta (OPTIONAL - angle of plate with horizontal plane) (deg)
-- loads
-  - Ha, Va (horizontal and vertical loads on padeye of anchor)
-  
-#### suction_pile (Suction caisson/ suction bucket anchors)
-- soil condition: clay and sand
-- geometry
-   - L (length of pile) (m)
-   - D (diameter of pile) (m)
-   - zlug (embedded depth of padeye below mudline) (m)
-- loads
-  - Ha, Va (horizontal and vertical loads on padeye of anchor)
-  
-#### torpedo_pile (Torpedo pile anchors)
-- soil condition: clay
-- geometry
-   - D1 (wing diameter) (m)
-   - D2 (shaft diameter) (m)
-   - L1 (wing length) (m)
-   - L2 (shaft length) (m)
-   - zlug (embedded depth of padeye below mudline) (m)
-- loads
-  - Ha, Va (horizontal and vertical loads on padeye of anchor)
-
-#### helical_pile (Helical pile anchors)
-- soil condition: clay and sand 
-- geometry
-  - D (helix diameter) (m)
-  - L (shaft length) (m)
-  - d (shaft diameter) (m)
-  - zlug (embedded depth of padeye below mudline) (m)
-- loads
-  - Ha, Va (horizontal and vertical loads on padeye of anchor)
-  
-#### driven_pile (Driven pile anchors)
-- soil condition: clay, sand and (weak) rock
-- geometry
-  - L (length of pile) (m)
-  - D (diameter of pile) (m)
-  - zlug (embedded depth of padeye below mudline) (m)
-- loads
-  - Ha, Va (horizontal and vertical loads on padeye of anchor)
-  
-#### Output notes 
- The general output is a lateral and rotational displacement or bending moment. In getCapacityAnchor, the driven pile capacity function is called in a while loop with incremented horizontal 
- input forces until one of the displacements goes past set failure criteria, thus providing a horizontal force capacity output [N]. Vertical capacity [N] is already calculated within the driven pile capacity function.
-  
- For non-rock soil, the hinge (bending moment) is also considered as a failure mode along with the lateral and rotational displacement 
- 
-#### dandg_pile (Drilled and grouted piles)
-- soil condition: rock
-- geometry
-   - L (length of pile) (m)
-   - D (diameter of pile) (m)
-   - zlug (lug location) (m)
-- loads
-  - Ha, Va (horizontal and vertical loads on padeye of anchor)
-  
-#### Output notes
- The general output is a lateral and rotational displacement. In getAnchorCapacity, the drilled and grouted pile function is called in a while loop with incremented horizontal input forces 
- until one of the displacements goes past set failure criteria, thus providing a horizontal force capacity output [N]. Vertical capacity [N] is already calculated within the driven pile capacity function. 
- 
-
-### Model Fidelity
-
-There are two levels of fidelity in these models:
-
-- Level 1 basic models are soil-dependent capacity curves for a 
-  range of anchor types based on performing curve fits to 
-  published information in anchor manuals and standards. 
-- Level 2 intermediate models are quantitative calculations for
-  suction caissons and plate anchors that account for quantitative 
-  soil properties as well as their variation with embedment depth.
-
-This plot gives an example of the capacity curves that can be 
-produced by the intermediate model (holding capacity for a suction
-embedded plate anchor) as a function of surface shear strength:
-
-![Capacities](images/SEPLA_curves_small.PNG)
-
-### Implemented level-1 model anchor and soil types
-
-|             | DEA       | Suction | VLA | SEPLA |
-|-------------|-----------|---------|-----|-------|
-| Soft clay   | X         | X       | X   | X     |
-| Medium clay | X         | X       | X   | X     |
-| Hard clay   | X         |         |     |       |
-| Sand        | X         |         |     |       |
-
-### Parameters needed for level-2 anchor capacity models
-
-|        **Anchor type** | **Suction** | **Suction** | **VLA**  | **SEPLA** |
-|------------------------|-------------|-------------|----------|-----------|
-|        **Soil type**   | **Clay**    | **Sand**    | **Clay** | **Clay**  |
-| **Anchor parameters**  |             |             |          |           |
-|        Diameter        | x           | x           |          |           |
-|        Length          | x           | x           |          |           |
-|        Area            |             |             | X        | X         |
-|        Thickness       | ratio       | ratio       | ratio    | ratio     |
-|       Embedment depth  |             |             | X        | X         |
-| **Soil parameters**    |             |             |          |           |
-|        gamma           | X           | X           | X        | X         |
-|        Su0             | X           |             | X        | X         |
-|        k               | X           |             | X        | X         |
-|        alpha           | X           |             |          |           |
-|        phi             |             | X           |          |           |
-
-
-These models will continue to be expanded as data sources and time permit.
-
diff --git a/famodel/anchors/anchor.py b/famodel/anchors/anchor.py
index 66c17943..f0399135 100644
--- a/famodel/anchors/anchor.py
+++ b/famodel/anchors/anchor.py
@@ -3,71 +3,78 @@
 """
 import moorpy as mp
 import numpy as np
+from scipy.optimize import minimize
 from famodel.famodel_base import Node
 from famodel.mooring.mooring import Mooring
+import matplotlib.pyplot as plt
+from collections import defaultdict
 import famodel.platform.platform 
 import shapely as sh
 
-
 class Anchor(Node):
     
-    def __init__(self, dd=None, ms=None, r=[0,0,0], aNum=None, id=None, 
-                 g=9.81, rho=1025):
+    def __init__(self, dd=None, ms=None, r=[0,0,0], aNum=None, id=None,
+                 g=9.81, rho=1025, profile_map=None, display=0):
         '''
+        Initialize an Anchor object.
+
         Parameters
         ----------
-        dd: dictionary
-            Design dictionary that contains all information on an anchor for a mooring line/shared mooring
-            {
-                type:   # anchor type (plate,suction_pile,torpedo_pile,helical_pile,driven_pile,dandg_pile)
-                design: # all geometric info from yaml file, only need to include info relevant to your anchor type
-                     A    plate anchor area
-                     D    anchor diameter (or helix diameter for helical piles)
-                     D1   torpedo anchor wing diameter
-                     D2   torpedo anchor shaft diameter
-                     d    helical pile shaft diameter 
-                     L    pile anchor length
-                     L1   torpedo anchor wing length 
-                     L2   torpedo anchor shaft length
-                     zlug padeye z elevation (+ down into the soil)
-                     beta angle of plate anchor after keying (optional)
-                cost:
-                    matCost: # material cost
-                    instCost: # installation cost
-                    decomCost: # decomissioning cost                          
-            }
-        ms: system object
-            MoorPy system object the anchor is in
-            
-        r: list
-            Location of anchor in x,y,z
-            
-        aNum: int
-            entry number in project.anchorList dictionary (may remove...)
-        id: str/int
-            unique id of this object
-        g: float
-            acceleration due to gravity in m/s^2
-        rho: float
-            density of water in kg/m^3
+        dd : dict
+            Design dictionary containing all information on the anchor.
+        ms : MoorPy system object
+            MoorPy system instance.
+        r : list of float
+            Anchor position coordinates (x, y, z) (m)
+        aNum : int, optional
+            Index in anchor list.
+        id : str or int, optional
+            Unique anchor identifier.
+        g : float, optional
+            Gravity.
+        rho : float, optional
+            Water density.
+        profile_map : list of dict, optional
+            Full soil profile map for selecting local soil layers.
         '''
+
         # Initialize as a node
-        Node.__init__(self,id)
-        
+        Node.__init__(self, id)
+
         # Design description dictionary for this Anchor
         self.dd = dd
-        
         # MoorPy system this anchor is in
         self.ms = ms
-        
         # x,y,z location of anchor
         self.r = r
-        
-        # anchor index in array mooring list (only used for shared moorings/anchors)
+        # anchor index in array mooring list 
         self.aNum = aNum
-               
-        # MoorPy anchor object
+        
+        self.g = g
+        self.rho = rho
+
+        if dd and 'type' in dd:
+            self.anchType = dd['type']
+        else:
+            self.anchType = 'suction'
+            print(f"[Anchor] No type provided. Defaulting to 'suction'.")
+        
+        # raise errors/warnings if the anchor type is not what it needs to be
+        anchor_type_options = ['suction', 'sepla', 'dea', 'depla', 'vla', 'plate', 'torpedo', 'helical', 'driven', 'drilled']
+        if self.anchType.lower() not in anchor_type_options:
+            raise ValueError(f"The anchor 'type' {self.anchType} needs to explicitly be one of {anchor_type_options} (Case not sensitive)")
+        # if self.anchType not in ['drag-embedment', 'gravity', 'suction', 'SEPLA', 'VLA', 'driven']:
+        #     print('Warning: The anchor type provided does not have any cost coefficients. This will default to a suction pile')
+
+        self.soil_type = None
+        self.soil_profile = None
+        self.profile_name = None
+        self.soil_type_list = []
+
         self.mpAnchor = None
+        self.capacity_format = None
+        self.mass = dd.get('design', {}).get('mass', None) if dd else None
+        self.point_num = 0  # initialize point number
         
         # get environment info
         self.g = g # acceleration due to gravity (m/s^2)
@@ -101,530 +108,1058 @@ def __init__(self, dd=None, ms=None, r=[0,0,0], aNum=None, id=None,
             }
         '''
         self.soilProps = {}
+        self.loads = {}
+        self.anchorCapacity = {}
+        self.cost = {}
         self.failure_probability = {}
-
-        # environmental impact
         self.env_impact = {}
-        
 
-        # self.cost = {}
+        # Assign soil profile if map is provided
+        if profile_map is not None:
+            if len(profile_map) == 1:
+                self.setSoilProfile(profile_map)
+            elif len(profile_map) >= 4:
+                self.interpolateSoilProfile(profile_map)
+            else:
+                raise ValueError("profile_map must contain either 1 or ≥4 CPTs for soil assignment.")
         
+        self.display = display
+
+    def setSoilProfile(self, profile_map):
+        '''
+        Assign a soil profile directly from a single CPT.
+        Assumes profile_map is a list with only one entry.
+        '''
+        if len(profile_map) != 1:
+            raise ValueError("setSoilProfile expects a profile_map with exactly one CPT.")
+
+        cpt = profile_map[0]
+        self.soil_profile = profile_map               
+        self.profile_name = cpt.get('name', 'CPT_Assigned')
+    
+        # Extract soil types from layers
+        layers = cpt['layers']
+        soil_types = [layer['soil_type'] for layer in layers]
+        self.soil_type_list = list(set(soil_types))
+        self.soil_type = soil_types[0] if len(self.soil_type_list) == 1 else 'mixed'
+    
+        # Group layers by soil type
+        soilProps = defaultdict(list)
+        for layer in layers:
+            layer_copy = layer.copy()
+            soil_type = layer_copy.pop('soil_type')
+            soilProps[soil_type].append(layer_copy)
+        self.soilProps = dict(soilProps)
+
+        if self.display > 0: print(f"[Anchor] Assigned soil profile from {self.profile_name} with soil types {self.soil_type_list}")
+
+    def interpolateSoilProfile(self, profile_map):
+        '''
+        Interpolate a soil profile from the 4 nearest CPTs in profile_map.
+        '''
+        if len(profile_map) < 4:
+            raise ValueError("interpolateSoilProfile requires at least 4 CPTs.")
+
+        x_anchor, y_anchor = self.r[0], self.r[1]
+
+        # Sort CPTs by distance
+        distances = [np.hypot(p['x'] - x_anchor, p['y'] - y_anchor) for p in profile_map]
+        idx_sorted = np.argsort(distances)
+        CPTs = [profile_map[i] for i in idx_sorted[:4]]
+
+        # Inverse distance weighting
+        x = np.array([cpt['x'] for cpt in CPTs])
+        y = np.array([cpt['y'] for cpt in CPTs])
+        d = np.hypot(x - x_anchor, y - y_anchor)
+        w = 1 / np.maximum(d, 1e-3)**2
+        w /= np.sum(w)
+
+        # Interpolate layer-by-layer (assumes same layer structure)
+        layers_list = [cpt['layers'] for cpt in CPTs]
+        n_layers = len(layers_list[0])
+        interpolated_layers = []
+
+        for i in range(n_layers):
+            base_layer = layers_list[0][i]
+            layer = {'soil_type': base_layer['soil_type']}
+
+            for key in base_layer:
+                if key == 'soil_type':
+                    continue
+                if all(key in l[i] for l in layers_list):
+                    vals = [l[i][key] for l in layers_list]
+                    layer[key] = np.dot(w, vals)
+
+            interpolated_layers.append(layer)
+
+        self.soil_profile = [{
+            'name': 'Interpolated_2D',
+            'x': x_anchor,
+            'y': y_anchor,
+            'layers': interpolated_layers}]
+        self.profile_name = "Interpolated_2D"
+
+        # Extract soil types
+        layers = self.soil_profile[0]['layers']
+        soil_types = [layer['soil_type'] for layer in layers]
+        self.soil_type_list = list(set(soil_types))
+        self.soil_type = soil_types[0] if len(self.soil_type_list) == 1 else 'mixed'
+
+        # Group interpolated layers by soil type
+        soilProps = defaultdict(list)
+        for layer in self.soil_profile[0]['layers']:
+            layer_copy = layer.copy()
+            soil_type = layer_copy.pop('soil_type')
+            soilProps[soil_type].append(layer_copy)
+        self.soilProps = dict(soilProps)
+
+        if self.display > 0: print(f"[Anchor] Interpolated soil profile: {self.profile_name} with soil types {self.soil_type_list}")
         
     def makeMoorPyAnchor(self, ms):
-        '''Create a MoorPy anchor object in a moorpy system
+        '''
+        Create a MoorPy anchor object in a MoorPy system.
+
         Parameters
         ----------
-        ms : class instance
-            MoorPy system
-        
+        ms : MoorPy system instance
+            The MoorPy system to add the anchor to.
+
         Returns
         -------
-        ms : class instance
-            MoorPy system 
+        ms : MoorPy system instance
+            The updated MoorPy system with the anchor added.
+        '''       
+        anchType = self.anchType or 'suction'
 
         '''
+        # Create anchor as a fixed point in MoorPy system
+        ms.addPoint(1, self.r)
+
+        # Assign this point as mpAnchor in the anchor class instance
+        self.mpAnchor = ms.pointList[-1]
+        '''
+
         # create anchor as a fixed body in MoorPy system and assign to mpAnchor property
         # r6 = [self.r[0],self.r[1],self.r[2],0,0,0]
         # self.mpAnchor = ms.addBody(1,r6)
         self.mpAnchor = ms.addPoint(1,self.r)
 
-        # add mass if available
-        if 'm' in self.dd['design'] and self.dd['design']['m']:
-            self.mpAnchor.m = self.dd['design']['m']
-        # set anchor diameter
-        if 'd' in self.dd['design'] and self.dd['design']['d']:
+        # Set mass if available
+        if 'mass' in self.dd.get('design', {}):
+            self.mpAnchor.m = self.dd['design']['mass']
+
+        # Set diameter if available
+        if 'd' in self.dd.get('design', {}):
             self.mpAnchor.d = self.dd['design']['d']
-        # set the point as an anchor entity
-        self.mpAnchor.entity= {'type': 'anchor'}
-        if 'type' in self.dd:
-            self.mpAnchor.entity['anchor_type']=self.dd['type']
-        
-        return(ms)
-    
-    
-    def getAnchorCapacity(self,ground_cons=None,installAdj=1,profile=None,loads=None,plot=True):
-        '''
-        Calls anchor capacity functions developed by Felipe Moreno for the correct anchor type 
+            
+        # Set dummy design to get PointType from MoorPy
+        if anchType not in list(ms.pointProps['AnchorProps'].keys()):
+            anchType = 'suction'    # default to a suction pile just to get the MoorPy pointProps working
+        design = {f"num_a_{anchType}": 1}
+        pointType = ms.setPointType(design, source=None)
+        self.mpAnchor.entity = pointType
 
-        Parameters
-        ----------
-        ground_conds : dict, optional
-            Ground conditions dictionary with the key as the soil type name, values as soil info such as UCS,Em,phi,gamma,effective stress,etc. The default is None.
-            If no dict provided, the ground conds will be pulled from the anchor soilProps property
-        installAdj : float, optional
-            Adjustment to the capacity based on installation (dummy variable for now, but future installation functions
-                                                              will dictate this value)
-        profile : 2D array,  optional
-            2d array of depths (m) and corresponding undrained shear strength (Pa). Su must not be zero 
-            (change to small value such as .001), but z must always start at 0. Ex: array([z1,Su1],[z2,Su2],...)
-            Used only for driven pile and drilled and grouted pile anchors.
-        loads : dict, optional
-            Dictionary of loads on the anchor at the lug point in [N]. If not provided, will use the loads dictionary property 
-            of the anchor. If this is empty and it is needed for the capacity function (i.e. driven piles) then 
-            the anchor.getLugForces() function will be called.
+        return ms
+       
+    def getLineProperties(self):
+        '''
+        Retrieve line_type, diameter and unit weight from attached mooring.
 
         Returns
         -------
-        results : dict
-            Dictionary of capacity of the anchor (generally a max force [N] in H and V, but can be a max displacement (driven, dandg piles))
-
+        line_type : str
+            Type of mooring line ('chain' or 'wire')
+        d : float
+            Nominal diameter (m)
+        w : float
+            Unit weight (N/m)
         '''
-        # - - - - set details - - - -
-        anchType = self.dd['type'] 
-        geom = self.dd['design']# geometric anchor information
-
-        if not ground_cons:
-            soil = next(iter(self.soilProps.keys()), None) # soil type
-            ground_conds = self.soilProps[soil]
-        else:
-            soil = next(iter(ground_cons.keys()))
-            ground_conds = ground_cons[soil]
-         
-        for key,prop in ground_conds.items():
-            if isinstance(prop,list) or isinstance(prop,np.ndarray):
-                if len(prop)>1:
-                    print('Warning: Only homogeneous soils are supported at this time. Only the first item in a property list will be used.')
-                    break 
-                else:
-                    ground_conds[key] = prop[0]
-        
-        
-        if loads:
-            # find out if mudline loads or anchor loads
-            if not 'Ha' in loads:
-                # get loads at lug
-                loads = self.getLugForces(mudloads=loads,plot=plot)
-        else:
-            loads = self.loads
-        
-        
-       
-        # logic to determine what functions to call based on anchor type and soil type...
-        
-        # - - - - plate anchors - - - - 
-        if anchType == 'SEPLA' or anchType == 'DEA' or anchType == 'DEPLA' or anchType == 'VLA' or anchType == 'plate':
-            from .anchors_famodel.capacity_plate import getCapacityPlate
-            if 'clay' in soil or 'mud' in soil:
-                # write or overwrite beta in geom dictionary from loads function
-                if anchType != 'DEA':
-                    if not 'beta' in geom:
-                        if not 'thetaa' in loads:
-                            # calculate thetaa from Ha and Va
-                            loads['thetaa'] = np.arctan2(loads['Va'],loads['Ha'])
-                            # loads = self.getLugForces(plot=plot)
-                        geom['beta'] = 90 - loads['thetaa']
-                else:
-                    geom['beta'] = 0
-                if 'Su0' in ground_conds and 'k' in ground_conds and 'gamma' in ground_conds:             
-                    results = getCapacityPlate(geom['A'], geom['beta'], geom['zlug'], 'clay', ground_conds['gamma'],
-                                               Su0=ground_conds['Su0'], k=ground_conds['k'])
-                else:
-                    raise Exception('Ground conditions dictionary needs Su0, k, gamma information for clay plate anchors')
-            else:
-                print(f'Warning: Soil type {soil} is not compatible with plate anchors (SEPLA/DEPLA/DEA/VLA)')
-         
-        # - - - - suction buckets - - - -                       
-        elif 'suction' in anchType:
-            from .anchors_famodel.capacity_suction import getCapacitySuction
-            # check loads have been calculated (needed for capacity function in this case)
-            if not 'Ha' in loads:
-                # call getMPForces function 
-                loads = self.getLugForces(plot=plot)
-            if 'sand' in soil:
-                if 'phi' in ground_conds and 'Dr' in ground_conds:
-                    results = getCapacitySuction(geom['D'], geom['L'], geom['zlug'],
-                                                 loads['Ha']/1000, loads['Va']/1000,
-                                                 'sand', ground_conds['gamma'],
-                                                 phi=ground_conds['phi'],
-                                                 Dr=ground_conds['Dr'], plot=plot)
-                else:
-                    raise Exception('Ground conditions dictionary needs phi and relative density information for sand suction pile anchor')
-            elif 'clay' in soil or 'mud' in soil:
-                if 'Su0' in ground_conds and 'k' in ground_conds and 'alpha' in ground_conds:# and 'gamma_sub' in ground_conds:
-                    results = getCapacitySuction(geom['D'],geom['L'], geom['zlug'],
-                                                 loads['Ha']/1000, loads['Va']/1000,
-                                                 'clay', ground_conds['gamma'],
-                                                 Su0=ground_conds['Su0'],
-                                                 k=ground_conds['k'], plot=plot)
-                    results['Horizontal max.'] = results['Horizontal max.']
-                    results['Vertical max.'] = results['Vertical max.']
-                    
-                else:
-                    raise Exception('Ground conditions dictionary needs Su0, k, and alpha information for clay suction pile anchor')
-            else:
-                print(f'Warning: Soil type {soil} is not compatible with suction pile anchor')
-                
-        # - - - - helical piles - - - -
-        elif 'helical' in anchType:
-            from .anchors_famodel.capacity_helical import getCapacityHelical
-            if 'sand' in soil:
-                if 'phi' in ground_conds and 'gamma' in ground_conds:
-                    results = getCapacityHelical(geom['D'], geom['L'], geom['d'],
-                                                 geom['zlug'], 'sand', 
-                                                 ground_conds['gamma'],
-                                                 phi=ground_conds['phi'], 
-                                                 Dr=ground_conds['Dr'])
-                    results['Vertical max.'] = results['Capacity']
-                else:
-                    raise Exception('Ground conditions dictionary needs phi, gamma and relative density information for clay helical pile anchor')
-            elif 'clay' in soil or 'mud' in soil:
-                if not 'alpha_star' in ground_conds:
-                    ground_conds['alpha_star'] = ground_conds['alpha']
-                if 'Su0' in ground_conds and 'k' in ground_conds and 'gamma' in ground_conds:
-                    results = getCapacityHelical(geom['D'], geom['L'], geom['d'],
-                                                 geom['zlug'], 'clay', 
-                                                 ground_conds['gamma'],
-                                                 Su0=ground_conds['Su0'], 
-                                                 k=ground_conds['k'])
-                    results['Vertical max.'] = results['Capacity']
-                else:
-                    raise Exception('Ground conditions dictionary needs Su0, k, gamma, and alpha_star information for clay helical pile anchor')
-            else:
-                print(f'Warning: Soil type {soil} is not compatible with helical pile anchor')
-        
-        # - - - - torpedo piles - - - - 
-        elif 'torpedo' in anchType:
-            from .anchors_famodel.capacity_torpedo import getCapacityTorpedo
-            if 'clay' in soil or 'mud' in soil:
-                if 'Su0' in ground_conds and 'k' in ground_conds and 'alpha' in ground_conds:
-                    results = getCapacityTorpedo(geom['D1'], geom['D2'], 
-                                                 geom['L1'], geom['L2'], 
-                                                 geom['zlug'], 'clay', 
-                                                 ground_conds['Su0'],
-                                                 ground_conds['k'], 
-                                                 ground_conds['alpha'])
-                    results['Horizontal max.'] = results['Horizontal max.']
-                    results['Vertical max.'] = results['Vertical max.']
-                else:
-                    raise Exception('Ground conditions dictionary needs Su0, k, and alpha information')
-            else:
-                print('Warning: Soil type {soil} is not compatible with torpedo pile anchor')
-        
-        # - - - - driven piles - - - - 
-        elif 'driven' in anchType: # driven pile anchor
-            # check loads have been calculated (needed for capacity function in this case)
-            if not 'Ha' in loads:
-                # call getLugForces function 
-                loads = self.getLugForces(plot=plot)
-            H_inc = loads['Ha']*0.1 # increment H by 10% of Ha load in the while loops to back-calc max H from displacements
-            H = 0
-            # check soil
-            if 'weak_rock' in soil:
-                from .anchors_famodel.capacity_drivenrock import getCapacityDrivenRock
-                
-                if not profile:
-                    if 'UCS' in ground_conds and 'Em' in ground_conds:
-                        profile = [[0,ground_conds['UCS'],ground_conds['Em']], 
-                                   [75,ground_conds['UCS'],ground_conds['Em']]] #profile = [list(x) for x in list(zip(ground_conds['depth'],ground_conds['UCS'],ground_conds['Em']))]
-                    else:
-                        raise Exception('Ground conditions dictionary needs UCS, Em, and depth information for weak rock driven pile anchor')
-                
-                y, z, results = getCapacityDrivenRock(profile, geom['L'], geom['D'], 
-                                                      geom['zlug'], loads['Va'], 
-                                                      loads['Ha'], plot=plot)
-                
-                # loop through, calling capacity with larger H values until a displacement value goes above limit
-                while results['Lateral displacement']< 0.05*geom['D'] and results['Rotational displacement'] < 0.25:
-                    # increment H 
-                    H += H_inc
-                    # call capacity function       
-                    y, z, results = getCapacityDrivenRock(profile, geom['L'], 
-                                                          geom['D'], geom['zlug'], 
-                                                          loads['Va'], H=H, plot=plot)
-                    
-                   
-            elif 'sand' in soil:
-                from .anchors_famodel.capacity_drivensoil import getCapacityDrivenSoil
-                if profile or ('gamma' in ground_conds and 'Dr' in ground_conds and 'phi' in ground_conds):
-                    if not profile:
-                        profile = [[0,ground_conds['phi'],ground_conds['gamma'],ground_conds['Dr']], 
-                                   [75,ground_conds['phi'],ground_conds['gamma'],ground_conds['Dr']]] #profile = [list(x) for x in list(zip(ground_conds['depth'],ground_conds['phi'],ground_conds['gamma']))]
-
-                    y, z, results = getCapacityDrivenSoil(profile, 'sand', 
-                                                          geom['L'], geom['D'], 
-                                                          geom['zlug'], loads['Va'], 
-                                                          loads['Ha'], plot=plot)
-                    if geom['zlug'] > 0:
-                        # need to check bending moment if lug is below mudline (+ zlug)
-                        # loop through, calling capacity with larger H values until a displacement value goes above limit
-                        while results['Lateral displacement']<= 0.05*geom['D'] and results['Bending moment'] <= results['Plastic moment']:
-                            # increment H by 10% of load
-                            H += H_inc
-                            # call capacity function     
-                            y, z, results = getCapacityDrivenSoil(profile,'clay', 
-                                                                  geom['L'], geom['D'],
-                                                                  geom['zlug'], loads['Va'], 
-                                                                  H=H, plot=plot)
-                            
-                    else:
-                        while results['Lateral displacement']<= 0.05*geom['D'] and results['Rotational displacement'] <= 0.25:
-                            # increment H by 10% of load
-                            H += H_inc  
-                            # call capacity function
-                            y, z, results = getCapacityDrivenSoil(profile, 'clay', 
-                                                                  geom['L'], geom['D'], 
-                                                                  geom['zlug'], loads['Va'],
-                                                                  H=H, plot=plot)
+        for att in self.attachments.values():
+            if isinstance(att['obj'], Mooring):
+                mtype = att['obj'].sections()[0]['type']['material'].lower()
+                if 'chain' not in mtype:
+                    print('No chain below seafloor, setting Ta=Tm (no load transfer).')
+                    return mtype, None, None, True
                 else:
-                    raise Exception('Ground conditions dictionary needs phi, gamma, and depth information for sand driven pile anchor')
-            elif 'clay' in soil or 'mud' in soil:
-                from .anchors_famodel.capacity_drivensoil import getCapacityDrivenSoil
-                #if profile or ('Su' in ground_conds and 'gamma' in ground_conds and 'depth' in ground_conds) or ('Su0' in ground_conds and 'k' in ground_conds):
-                if not profile:
-                    if 'Su' in ground_conds and 'depth' in ground_conds and 'gamma' in ground_conds:
-                        profile = [list(x) for x in list(zip(ground_conds['depth'],ground_conds['Su'],ground_conds['gamma']))]
-                    elif 'Su0' in ground_conds and 'k' in ground_conds and 'gamma' in ground_conds:
-                        Su = ground_conds['Su0']+ground_conds['k']*75
-                        profile = [[0,ground_conds['Su0'],ground_conds['gamma']],[75,Su,ground_conds['gamma']]]
-                    else:
-                        raise Exception('Ground conditions dictionary needs information for clay driven pile anchor')
+                    d_nom = att['obj'].sections()[0]['type']['d_nom']
+                    w_nom = att['obj'].sections()[0]['type']['w']
+                    return 'chain', d_nom, w_nom, False
+        raise ValueError('No mooring line attachment found for anchor.')
 
-                y, z, results = getCapacityDrivenSoil(profile,'clay',geom['L'],geom['D'],geom['zlug'],loads['Va'],loads['Ha'], plot=plot)
-                
-                if geom['zlug'] > 0:
-                    # need to check bending moment if lug is below mudline (+ zlug)
-                    # loop through, calling capacity with larger H values until a displacement value goes above limit
-                    while results['Lateral displacement']<= 0.05*geom['D'] and results['Bending moment'] <= results['Plastic moment']:
-                        # increment H by 10% of load
-                        H += H_inc
-                        # call capacity function     
-                        y, z, results = getCapacityDrivenSoil(profile,'clay',geom['L'],geom['D'],geom['zlug'],loads['Va'], H=H, plot=plot)
-                
-                else:
-                    while results['Lateral displacement']<= 0.05*geom['D'] and results['Rotational displacement'] <= 0.25:
-                        # increment H by 10% of load
-                        H += H_inc  
-                        # call capacity function
-                        y, z, results = getCapacityDrivenSoil(profile,'clay',geom['L'],geom['D'],geom['zlug'],loads['Va'], H=H, plot=plot)
-                        
-                    
-            else:
-                print(f'Warning: Soil type {soil} is not compatible with driven pile anchors')
-                
-        # - - - - drilled and grouted piles - - - -                
-        elif 'dandg' in anchType:  # drill and grout pile
-            from .anchors_famodel.capacity_dandg import getCapacityDandG
-            # check for correct soil
-            if 'rock' in soil:
-                # check loads have been calculated (needed for capacity function in this case)
-                if not 'Ha' in loads:
-                    # call getMPForces function 
-                    loads = self.getLugForces(plot=plot)
-                # check for correct ground properties
-                if profile or ('UCS' in ground_conds and 'Em' in ground_conds):
-                    if not profile:
-                        profile = [[0,ground_conds['UCS'],ground_conds['Em']],[75,ground_conds['UCS'],ground_conds['Em']]] #[list(x) for x in list(zip(ground_conds['depth'],ground_conds['UCS'],ground_conds['Em']))]
-
-                    # call capacity function once to get displacement values
-                    y, z, results = getCapacityDandG(profile,geom['L'],geom['D'], 
-                                                     geom['zlug'], loads['Va'], 
-                                                     loads['Ha'], plot=plot)
-                    H_inc = loads['Ha']*0.1 # increment H by 10% of Ha load
-                    H = H_inc # start H at 10% of Ha load
-                    # loop through, calling capacity with larger H values until a displacement value goes above limit
-                    while results['Lateral displacement']< 0.05*geom['D'] and results['Rotational displacement'] < 0.25:
-                        # call capacity function       
-                        y, z, results = getCapacityDandG(profile, geom['L'], geom['D'], 
-                                                         geom['zlug'], loads['Va'], 
-                                                         H=H, plot=plot)
-                        # increment H 
-                        H += H_inc
-                else:
-                    raise Exception('Ground conditions dictionary need UCS and Em information for drill and grout pile')
-            else:
-                print(f'Warning: soil type {soil} is not compatible with drill and grout pile')
-                
-        # - - - - anchor type not recognized or supported - - - - 
-        else:
-            raise Exception(f'Anchor type {anchType} is not supported at this time')
-            
-        # - - - - save relevant results in dictionary using common terms - - - - 
-        # capacity = cap*installAdj ??? OR is installAdj an input to the capacity functions?
-        # save capacity 
-        if 'dandg' in anchType or 'driven' in anchType: # will take in dandg, dandg_pile, driven, driven_pile
-            self.anchorCapacity['Lat_max'] = results['Lateral displacement'] # [deg]
-            if 'Rotational displacement' in results:
-                self.anchorCapacity['Rot_max'] = results['Rotational displacement'] # [deg]
-            elif 'Bending moment' in results:
-                self.anchorCapacity['Mbend_max'] = results['Bending moment']
-            self.anchorCapacity['Va_max'] = results['Axial capacity'] # [N]
-            self.anchorCapacity['Ha_max'] = H
+    def getMudlineForces(self, max_force=False, lines_only=False, seabed=True, xyz=False, project=None):
+        '''
+        Find forces on anchor at mudline using the platform.getWatchCircle method
+        or the MoorPy Point.getForces method. Optionally computes the maximum force 
+        based on platform excursion using the project's arrayWatchCircle method or
+        the attached platform's getWatchCircle method.
 
-        else:
-            if 'Horizontal max.' in results:
-                self.anchorCapacity['Ha_max'] = results['Horizontal max.']*1000 # [N]
-            self.anchorCapacity['Va_max'] = results['Vertical max.']*1000 # [N]
-        self.mass = results['Weight']*1000/self.g # mass in [kg]
-            
-        # add on extra for drag-embedment anchors (flukes)
-        if 'DEA' in anchType:
-            self.mass *= 1.75
-        
-            
-        return(results)
-            
-    def getMudlineForces(self, max_force=False,lines_only=False, seabed=True, xyz=False,project=None):   
-        '''Find forces on anchor at mudline using the platform.getWatchCircle method or MoorPy Point.getForces method. 
-        Optionally, get forces at anchor lug location with getTransferLoad function in capacity_loads.py.
-        Stores in loads dictionary
         Parameters
         ----------
-        max_force : boolean, optional
-            Find and save the maximum force on the anchor (True) or just get force at the current MoorPy system state (False)           
-        lines_only : boolean, optional
-            Calculate forces from just mooring lines (True) or not (False). Default is false
-        seabed : boolean, optional
-            Include effect of seabed pushing up the anchor (True) or not (False). Default is true
-        xyz : boolean, optional
-            Return forces in x,y,z DOFs (True) or only the enabled DOFs (False). Default is false
-            
+        max_force : bool, optional
+            If True, computes the maximum expected force on the anchor 
+            using platform excursion. Default is False.
+        lines_only : bool, optional
+            Calculate forces from just mooring lines (True) or not (False). Default is False.
+        seabed : bool, optional
+            Include effect of seabed pushing up the anchor (True) or not (False). Default is True.
+        xyz : bool, optional
+            Return forces in x, y, z DOFs (True) or only the enabled DOFs (False). Default is False.
+        project : object, optional
+            Project object that can run arrayWatchCircle(). Used only if max_force is True.
+
+        Returns
+        -------
+        dict
+            Dictionary containing mudline forces.
         '''
         Platform = famodel.platform.platform.Platform
+
         if max_force:
             if project:
-                # get watch circle of platform(s)
                 project.arrayWatchCircle()
             else:
-                # find platform associated with this anchor
                 for att in self.attachments.values():
-                    if isinstance(att['obj'],Mooring):
+                    if isinstance(att['obj'], Mooring):
                         for attM in att['obj'].attached_to:
-                            if isinstance(attM,Platform):
-                                locx,locy,maxVals = attM.getWatchCircle()
-        # call getForces method from moorpy point object
+                            if isinstance(attM, Platform):
+                                locx, locy, maxVals = attM.getWatchCircle()
+                                Hm = np.sqrt(maxVals[0]**2 + maxVals[1]**2)
+                                Vm = maxVals[2]
+                                thetam = np.degrees(np.arctan2(Vm, Hm))
+                                self.loads['Hm'] = Hm
+                                self.loads['Vm'] = Vm
+                                self.loads['thetam'] = thetam
+                                self.loads['mudline_load_type'] = 'max_force'
+                                break
         else:
-            loads = self.mpAnchor.getForces(lines_only=lines_only, seabed=seabed, xyz=xyz)
-            self.loads['Hm'] = np.sqrt(loads[0]**2+loads[1]**2) # mudline forces in [N]
-            self.loads['Vm'] = loads[2] # [N]
-            self.loads['thetam'] = np.degrees(np.arctan(self.loads['Vm']/self.loads['Hm'])) # [deg]
+            # loads = self.mpAnchor.getForces(lines_only=lines_only, seabed=seabed, xyz=xyz)
+            # MoorPy Body.getForces does not accept seabed/lines_only in current API.
+            # Get forces (total), optionally post-process seabed if needed.
+            loads = self.mpAnchor.getForces()
+            Hm = np.sqrt(loads[0]**2 + loads[1]**2)
+            Vm = loads[2]
+            thetam = np.degrees(np.arctan2(Vm, Hm))
+            self.loads['Hm'] = Hm
+            self.loads['Vm'] = Vm
+            self.loads['thetam'] = thetam
             self.loads['mudline_load_type'] = 'current_state'
-        
-        # loads determined from moorpy are static
+
         self.loads['method'] = 'static'
-        
-        return(self.loads)
-    
-    def getLugForces(self, mudloads=None, max_force=True, plot=False):
+        return self.loads
+       
+    def getLugForces(self, Hm, Vm, zlug, line_type=None, d=None, w=None, plot=False, display=0):
         '''
-        Find forces on an anchor at the lug point based on the mudline forces and angles. Calls getTransferFunction script
+        Calculate the lug forces Ha and Va based on mudline loads using local soil profile.
 
         Parameters
         ----------
-        mudloads : dict, optional
-            Dictionary of max mudline forces. The default is None.
+        Hm : float
+            Horizontal mudline load (N)
+        Vm : float
+            Vertical mudline load (N)
+        zlug : float
+            Padeye embedment depth (m)
+        line_type : str, optional
+            Type of mooring line ('chain' or 'wire')
+        d : float, optional
+            Mooring line diameter (m)
+        w : float, optional
+            Mooring line unit weight (N/m)
+        plot : bool, optional
+            Whether to plot the load transfer profile
 
         Returns
         -------
-        loads: dict
-            Dictionary of loads at the lug point [N]
-
+        Ha : float
+            Horizontal load at lug (N).
+        Va : float
+            Vertical load at lug (N).
         '''
         from .anchors_famodel.capacity_load import getTransferLoad
+        from .anchors_famodel.support_plots import plot_load
+
+        # Ensure soil profile is available
+        if self.soil_profile is None or self.soil_type is None:
+            raise ValueError("Anchor soil profile or soil type is not assigned. Use setSoilProfile first.")
+
+        soil_profile = self.soil_profile
+        soil_type = self.soil_type
+
+        # Determine mudline depth
+        z0 = soil_profile[0]['layers'][0]['top']
+        
+        # Load transfer if padeye is embedded
+        if zlug > z0:
+            # Check if padeye is embedded in rock
+            if any(layer.get('soil_type') == 'rock' for layer in self.soil_profile[0]['layers']):
+                raise ValueError('[Warning] Padeye depth is embedded in rock. Embedded line in rock is not possible.')
+             
+
+            if line_type is None or d is None or w is None:
+                try:
+                    line_type, d, w = self.getLineProperties()
+                except ValueError:
+                    print('[Warning] No mooring attachment found. Trying anchor-level line properties...')
+                    line_type = getattr(self, 'line_type', None)
+                    d = getattr(self, 'd', None)
+                    w = getattr(self, 'w', None)
+
+                    if any(v is None for v in [line_type, d, w]):
+                        print('[Fallback] Using default chain properties.')
+                        line_type = 'chain'
+                        d = 0.16
+                        w = 5500.0
+
+            layers, loads = getTransferLoad(
+                profile_map=self.soil_profile,
+                Tm=np.sqrt(Hm**2 + Vm**2),
+                thetam=np.degrees(np.arctan2(Vm, Hm)),
+                zlug=zlug,
+                line_type=line_type,
+                d=d,
+                w=w,
+                plot=plot, display=display)
+
+            Ta = loads['Ta']
+            thetaa = loads['thetaa']
+            Ha = Ta*np.cos(np.deg2rad(thetaa))
+            Va = Ta*np.sin(np.deg2rad(thetaa))
+
+        else:
+            Ha = Hm
+            Va = Vm
+            layers = self.soil_profile[0]['layers']  
+
+            
+        if plot == True:
+            plot_load(layers, loads['drag_values'], loads['depth_values'], 
+                      loads['Tm'], loads['thetam'], loads['Ta'], 
+                      loads['thetaa'], zlug=zlug)
+
+        return layers, Ha, Va
+
+    def getCapacityAnchor(self, Hm, Vm, zlug, line_type=None, d=None, w=None, mass_update=False, plot=False, display=0):
+        '''
+        Calculate anchor capacity based on anchor type and local soil profile.
+    
+        Parameters
+        ----------
+        Hm : float
+            Horizontal mudline load (N)
+        Vm : float
+            Vertical mudline load (N)
+        zlug : float
+            Padeye embedment depth (m)
+        line_type : str, optional
+            Type of mooring line ('chain' or 'wire')
+        d : float, optional
+            Mooring line diameter (m)
+        w : float, optional
+            Mooring line unit weight (N/m)
+        mass_update : bool, optional
+            Whether to update the mass when is not assigned
+        plot : bool, optional
+            Whether to plot the load transfer and pile geometry
+    
+        Returns
+        -------
+        results : dict
+            Capacity results dictionary from the selected capacity function.
+        '''
+
+        from .anchors_famodel.capacity_plate import getCapacityPlate
+        from .anchors_famodel.capacity_suction import getCapacitySuction
+        from .anchors_famodel.capacity_torpedo import getCapacityTorpedo
+        from .anchors_famodel.capacity_helical import getCapacityHelical
+        from .anchors_famodel.capacity_driven import getCapacityDriven
+        from .anchors_famodel.capacity_drilled import getCapacityDrilled
+           
+        capacity_dispatch = {
+            'suction': getCapacitySuction,
+            'sepla': getCapacityPlate,
+            'dea': getCapacityPlate,
+            'depla': getCapacityPlate,
+            'vla': getCapacityPlate,
+            'plate': getCapacityPlate,
+            'torpedo': getCapacityTorpedo,
+            'helical': getCapacityHelical,
+            'driven': getCapacityDriven,
+            'drilled': getCapacityDrilled}
+        
+        if self.display > 0: print('[DEBUG] profile_name:', self.profile_name)
+        if self.display > 0: print('[DEBUG] soil_profile passed as profile_map:')
+        for entry in self.soil_profile:
+            if self.display > 0: print(entry.get('name'), list(entry.keys()))
+
+
+        if self.display > 1: print(f'[Debug] mass_update = {mass_update}')
+        anchType_clean = self.dd['type'].lower().replace(' ', '')
+        capacity_func = capacity_dispatch.get(anchType_clean)
+        if capacity_func is None:
+            raise ValueError(f"Unknown anchor type '{self.anchType}' for anchor capacity calculation.")
+    
+        if self.soil_profile is None or self.soil_type is None:
+            raise ValueError("Soil profile or soil type not set for this anchor.")
+    
+        soil_profile = self.soil_profile
+        soil_type = self.soil_type
+        z0 = soil_profile[0]['layers'][0]['top']  
+    
+        if line_type is None or d is None or w is None:
+            try:
+                line_type, d, w = self.getLineProperties()
+            except ValueError:
+                if self.display > 0: print('[Warning] No mooring attachment found. Trying anchor-level line properties...')
+                line_type = getattr(self, 'line_type', None)
+                d = getattr(self, 'd', None)
+                w = getattr(self, 'w', None)
+
+                if any(v is None for v in [line_type, d, w]):
+                    if self.display > 0: print('[Fallback] Using default chain properties.')
+                    line_type = 'chain'
+                    d = 0.16
+                    w = 5500.0
+    
+        # Load transfer if padeye is embedded below mudline
+        if zlug > z0:
+            layers, Ha, Va = self.getLugForces(
+                Hm, Vm,
+                zlug=zlug,
+                line_type=line_type,
+                d=d,
+                w=w,
+                plot=False, display=display)
+
+            Ta = np.sqrt(Ha**2 + Va**2)
+            thetaa = np.degrees(np.arctan2(Va, Ha))
+            
+            if self.display > 0: print(f"[Branch Check] Entered {'zlug>z0' if zlug>z0 else 'else'} for anchor {self.anchType}")
+
+        else:
+            Ha = Hm
+            Va = Vm
+            Ta = np.sqrt(Ha**2 + Va**2)
+            thetaa = np.degrees(np.arctan2(Va, Ha))
+
+            if self.display > 0: print(f"[Branch Check] Entered {'zlug>z0' if zlug>z0 else 'else'} for anchor {self.anchType}")
+
+        # --- Call the appropriate capacity function ---
+        if anchType_clean in ['sepla', 'dea', 'depla', 'vla', 'plate']:
+            self.capacity_format = 'plate'
+            B = self.dd['design']['B']
+            L = self.dd['design']['L']
+            if self.display > 1: print(f"[Final Check] Ha = {Ha}, Va = {Va}, anchor = {self.anchType}")
+            beta = 90.0 - np.degrees(np.arctan2(Va, Ha))
+            self.dd['design']['beta'] = beta 
+            layers, results = capacity_func(
+                profile_map=self.soil_profile,
+                location_name=self.profile_name,
+                B=B, L=L, zlug=zlug,
+                beta=beta,
+                Ha=Ha, Va=Va,
+                plot=plot, display=display)
+            
+        elif anchType_clean == 'suction':
+            self.capacity_format = 'envelope'
+            D = self.dd['design']['D']
+            L = self.dd['design']['L']
+            zlug = self.dd['design']['zlug']
+            layers, results = capacity_func(
+                profile_map=self.soil_profile,
+                location_name=self.profile_name,
+                D=D, L=L, zlug=zlug,
+                Ha=Ha, Va=Va,
+                thetalug=5, psilug=7.5,
+                plot=plot, display=display)
+            
+        elif anchType_clean == 'torpedo':
+            self.capacity_format = 'envelope'
+            D1 = self.dd['design']['D1']
+            D2 = self.dd['design']['D2']
+            L1 = self.dd['design']['L1']
+            L2 = self.dd['design']['L2']
+            ballast = self.dd['design'].get('ballast', 0.0)
+            layers, results = capacity_func(
+                profile_map=self.soil_profile,
+                location_name=self.profile_name,
+                D1=D1, D2=D2, L1=L1, L2=L2,
+                zlug=zlug,
+                ballast=ballast,
+                Ha=Ha, Va=Va,
+                plot=plot, display=display)
+
+        elif anchType_clean == 'helical':
+            self.capacity_format = 'component'
+            D = self.dd['design']['D']     
+            L = self.dd['design']['L']     
+            d = self.dd['design']['d']     
+            zlug = self.dd['design']['zlug']
+            layers, results = capacity_func(
+                profile_map=self.soil_profile,
+                location_name=self.profile_name,
+                D=D, L=L, d=d,
+                zlug=zlug,
+                Ha=Ha, Va=Va,
+                plot=plot, display=display)
+
+        elif anchType_clean == 'driven':
+            self.capacity_format = 'component'
+            L = self.dd['design']['L']
+            D = self.dd['design']['D']
+            zlug = self.dd['design']['zlug']
+            layers, y, z, results = capacity_func(
+                profile_map=self.soil_profile,
+                location_name=self.profile_name,
+                L=L, D=D, zlug=zlug,
+                Ha=Ha, Va=Va,
+                plot=plot, display=display)
+        
+        elif anchType_clean == 'drilled':
+            self.capacity_format = 'component'           
+            L = self.dd['design']['L']
+            D = self.dd['design']['D']
+            zlug = self.dd['design']['zlug']
+            layers, y, z, results = capacity_func(
+                profile_map=self.soil_profile,
+                location_name=self.profile_name,
+                L=L, D=D, zlug=zlug,
+                Ha=Ha, Va=Va,
+                plot=plot, display=display)
+
+        else:
+            raise ValueError(f"Anchor type '{self.anchType}' not supported.")
+    
+        # --- Store results ---
+        self.anchorCapacity = {
+            'Hmax': results.get('Horizontal max.', np.nan),
+            'Vmax': results.get('Vertical max.', np.nan),
+            'Ha': Ha,
+            'Va': Va,
+            'zlug': zlug,
+            'z0': z0}
+        
+        # Correct UC format
+        if anchType_clean in ['suction', 'torpedo', 'plate', 'sepla', 'dea', 'depla', 'vla']:
+            self.anchorCapacity['UC'] = results.get('Unity check', np.nan)
         
-        nolugload = False
+        elif anchType_clean in ['helical', 'driven', 'drilled']:
+            self.anchorCapacity['Unity check (horizontal)'] = results.get('Unity check (horizontal)', np.nan)
+            self.anchorCapacity['Unity check (vertical)'] = results.get('Unity check (vertical)', np.nan)
         
-        if not mudloads:  
-            if not self.loads:
-                # get max mudline forces first
-                self.getMudlineForces(max_force=max_force)
-            elif not 'mudline_load_type' in self.loads:
-                raise KeyError("Loads dictionary must specify 'mudline_load_type'='current_state' or 'mudline_load_type'='max', where 'max' indicates the loads are maximum loads.")
-            elif max_force and self.loads['mudline_load_type'] != 'max':
-                # need max forces, not current state
-                self.getMudlineForces(max_force=True)
-            mudloads = self.loads
+        # Copy over lateral and rotational displacements
+        if 'Lateral displacement' in results:
+            self.anchorCapacity['Lateral displacement'] = results['Lateral displacement']
+        if 'Rotational displacement' in results:
+            self.anchorCapacity['Rotational displacement'] = results['Rotational displacement']
+        
+        # Weight calculated via dimensions
+        if not mass_update:
+            if 'Weight pile' in results:
+                self.anchorCapacity['Weight pile'] = results['Weight pile']
+            if 'Weight plate' in results:
+                self.anchorCapacity['Weight plate'] = results['Weight plate']
         else:
-            # check syntax
-            if not 'Hm' in mudloads or not 'Vm' in mudloads:
-                raise KeyError('Mudline load dictionary must have Hm and Vm for horizontal load and vertical load (in [N]) at the mudline')
-            if not 'thetam' in mudloads:
-                mudloads['thetam'] = np.degrees(np.arctan(mudloads['Vm']/mudloads['Hm']))
+            if 'Weight pile' in results:
+                self.mass = results['Weight pile']/self.g
+                self.anchorCapacity['Weight pile'] = results['Weight pile']
+            if 'Weight plate' in results:
+                self.mass = results['Weight plate']/self.g
+                self.anchorCapacity['Weight plate'] = results['Weight plate']
                 
-        def makeEqual_TaTm(mudloads):
-            mudloads['Ha'] = mudloads['Hm'] # [N]
-            mudloads['Va'] = mudloads['Vm'] # [N]
-            mudloads['thetaa'] = mudloads['thetam'] # [deg]
+        # print(f"[DEBUG] Stored Lateral displacement in anchorCapacity: {self.anchorCapacity['Lateral displacement']:.6f}")
+         
+    def getSizeAnchor(self, geom, geomKeys, geomBounds=None, loads=None, lambdap_con=[4, 8],
+                       zlug_fix=True, safety_factor={}, plot=False, display=0):
+        '''
+        Generalized optimization method for all anchor types, using dictionary-based safety factors.
+        '''
+        self.display = display
+    
+        anchType_clean = self.dd['type'].strip().lower()
+        print(f"[Debug] Anchor type parsed: '{anchType_clean}'")
+    
+        if loads is None:
+            loads = self.loads
         
-        if 'zlug' in self.dd['design']:
-            if self.dd['design']['zlug'] > 0:
-                # get line type
-                for att in self.attachments.values():
-                    if isinstance(att['obj'],Mooring):
-                        mtype = att['obj'].sections()[0]['type']['material']
-                        if not 'chain' in mtype:
-                            print('No chain on seafloor, setting Ta=Tm')
-                            nolugload = True
-                            break
-                        else:
-                            md = att['obj'].sections()[0]['type']['d_nom']
-                            mw = att['obj'].sections()[0]['type']['w']
-                soil = next(iter(self.soilProps.keys()), None)
-                ground_conds = self.soilProps[soil]
-                # update soil conds as needed to be homogeneous
-                for key,prop in ground_conds.items():
-                    if isinstance(prop,list) or isinstance(prop,np.ndarray):
-                        if len(prop)>1:
-                            print('Warning: Only homogeneous soils are supported at this time. Only the first item in a property list will be used.')
-                            break 
-                        else:
-                            ground_conds[key] = prop[0]
-                            
-                Tm =  np.sqrt(mudloads['Hm']**2+mudloads['Vm']**2) # [N]
-                if 'clay' in soil or 'mud' in soil and not nolugload:
-                    # Tm, thetam, zlug, line_type, d, soil_type, Su0=None, k=None, w=None
-                    try:
-                        loadresults = getTransferLoad(Tm/1000,mudloads['thetam'],
-                                                      self.dd['design']['zlug'],mtype,md,
-                                                      'clay',Su0=ground_conds['Su0'],
-                                                      k=ground_conds['k'],w=mw/1000,
-                                                      plot=plot) # output Ha and Va    (convert weight to kN/m)   
-                    except Exception as e:
-                        print(e)
-                        print('Unable to get loads at anchor lug location. Setting Ta = Tm')
-                        nolugload = True
-                elif 'sand' in soil and not nolugload:
-                        soil = 'sand'
-                        try:
-                            loadresults = getTransferLoad(Tm/1000, self.loads['thetam'], 
-                                                        self.dd['design']['zlug'],
-                                                        mtype, md, soil,
-                                                        gamma=ground_conds['gamma'], 
-                                                        phi=ground_conds['phi'],
-                                                        delta=ground_conds['delta'], 
-                                                        w=mw/1000,plot=plot) # output Ha and Va  (convert weight to kN/m)
-                        except Exception as e:
-                            print(e)
-                            print('Unable to get loads at anchor lug location. Setting Ta = Tm')
-                            nolugload = True
-                elif 'rock' in soil and not nolugload:
-                    raise ValueError('zlug should be <= 0 for rock.')
-                    
-                # if loadresults['V']<0:
-                #     # results are invalid
-                #     print('Warning: invalid results for the combination of anchor ',self.dd['type'],' soil ',soil,' and loads ',mudloads,'. Setting Ha=Hm, Va=Vm, thetaa=thetam')
-                #     makeEqual_TaTm(mudloads)
-                if nolugload:
-                    makeEqual_TaTm(mudloads)
+        sf_Hm = safety_factor.get('Hm', safety_factor.get('SF_horizontal', 1.0))
+        sf_Vm = safety_factor.get('Vm', safety_factor.get('SF_vertical', 1.0))
+        sf_uc = safety_factor.get('SF_combined', max(sf_Hm, sf_Vm))  # conservative by default
+
+        Hm = loads['Hm']*sf_Hm
+        Vm = loads['Vm']*sf_Vm
+    
+        line_type = getattr(self, 'line_type', 'chain')
+        d = getattr(self, 'd', 0.16)
+        w = getattr(self, 'w', 5000.0)
+    
+        def update_zlug():
+            if 'suction' in anchType_clean and not zlug_fix and 'zlug' not in geomKeys:
+                self.dd['design']['zlug'] = (2/3)*self.dd['design']['L']
+            elif np.any([name in anchType_clean for name in ['driven', 'helical']]) and not zlug_fix:    
+                ratio = self.dd['design'].get('zlug_ratio', self.dd['design']['zlug']/self.dd['design']['L'])
+                self.dd['design']['zlug_ratio'] = ratio
+                self.dd['design']['zlug'] = ratio*self.dd['design']['L']
+            elif 'drilled' in anchType_clean:
+                self.dd['design']['zlug'] = 0
+    
+        def get_lambda():
+            if 'torpedo' in anchType_clean:
+                L = self.dd['design']['L1'] + self.dd['design']['L2']
+                A_wing = (self.dd['design']['D1'] - self.dd['design']['D2']) * self.dd['design']['L1']
+                A_shaft = self.dd['design']['D2'] * L
+                D = (A_wing + A_shaft) / L
+            elif np.any([name in anchType_clean for name in ['driven', 'drilled', 'helical', 'suction']]):
+                L = self.dd['design']['L']
+                D = self.dd['design']['D']
+            elif np.any([name in anchType_clean for name in ['plate', 'sepla', 'dea', 'depla', 'vla']]):
+                L = self.dd['design']['L']
+                D = self.dd['design']['B']
+            else:
+                raise ValueError(f'lambda not defined for anchor type: {anchType_clean}')
+            return L/D
+    
+        def constraint_lambda_min(vars):
+            for i, key in enumerate(geomKeys):
+                self.dd['design'][key] = vars[i]
+            update_zlug()
+            self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                    line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+            return get_lambda() - lambdap_con[0]
+    
+        def constraint_lambda_max(vars):
+            return lambdap_con[1] - get_lambda()
+        
+        def constraint_bounds(vars):
+            con_bound_return = np.zeros(len(geomKeys)*2)
+            for i,var in enumerate(geomKeys):
+                con_bound_return[2*i] = self.dd['design'][var] - geomBounds[i][0]
+                con_bound_return[2*i+1] = geomBounds[i][1] - self.dd['design'][var]
+            return con_bound_return
+    
+        if np.any([name in anchType_clean for name in ['suction', 'torpedo', 'plate', 'sepla', 'dea', 'depla', 'vla']]):
+            target_UC = 1.0/sf_uc
+    
+            def objective_uc(vars):
+                '''
+                for i, key in enumerate(geomKeys):
+                    self.dd['design'][key] = vars[i]
+                update_zlug()
+                self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                       line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+                '''
+                #UC = self.anchorCapacity.get('UC', 2.0)
+                #return (UC - target_UC)**2
+                #return self.anchorCapacity.get('Weight pile')
+                if any(name in anchType_clean for name in ['plate', 'sepla', 'dea', 'depla', 'vla']):
+                    return self.anchorCapacity.get('Weight plate')
                 else:
-                    mudloads['Ha'] = loadresults['H']*1000 # [N]
-                    mudloads['Va'] = loadresults['V']*1000 # [N]
-                    mudloads['thetaa'] = loadresults['angle'] # [deg]
+                    return self.anchorCapacity.get('Weight pile')
+    
+            def constraint_uc_envelope(vars):
+                return self.anchorCapacity.get('UC', 0.0) - target_UC
+    
+            constraints_uc = [
+                {'type': 'ineq', 'fun': constraint_lambda_min},
+                {'type': 'ineq', 'fun': constraint_lambda_max},
+                {'type': 'ineq', 'fun': constraint_uc_envelope},
+                {'type': 'ineq', 'fun': constraint_bounds},
+            ]
+    
+            result_uc = minimize(
+                objective_uc,
+                geom,
+                method='COBYLA',
+                constraints=constraints_uc,
+                options={'rhobeg': 0.1, 'catol': 0.01, 'maxiter': 500}
+            )
+    
+            endGeom = dict(zip(geomKeys, result_uc.x))
+            self.dd['design'].update(endGeom)
+            update_zlug()
+            self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                   line_type=line_type, d=d, w=w, mass_update=True, plot=plot, display=display)
+    
+            print('\nFinal Optimized Anchor (UC-based):')
+            print('Design:', self.dd['design'])
+            print('Capacity Results:', self.anchorCapacity)
+            return
+        
+        def near_border():
+            UC_h = self.anchorCapacity['Ha']/self.anchorCapacity['Hmax']
+            UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+            disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+            disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+            limit_lat = 0.05*self.dd['design']['D']  # 10% of the pile diameter
+            limit_rot = 10.0                         # 10 deg
+        
+            near_UC_h = 0.95 <= UC_h <= 1.0
+            near_UC_v = 0.95 <= UC_v <= 1.0
+            near_disp_lat = 0.95*limit_lat <= disp_lat <= limit_lat
+            near_disp_rot = 4.75 <= disp_rot <= limit_rot
+        
+            return near_UC_h or near_UC_v or near_disp_lat or near_disp_rot
+
+        def termination_condition():
+            UC_h = self.anchorCapacity['Ha']/self.anchorCapacity['Hmax']
+            UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+            disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+            disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+            limit_lat = 0.05*self.dd['design']['D']  # 10% of the pile diameter
+            limit_rot = 10.0                         # 10 deg
+        
+            all_satisfied = (UC_h <= 1.0 and UC_v <= 1.0 and disp_lat <= limit_lat and disp_rot <= limit_rot)
+        
+            if all_satisfied:
+                if near_border():
+                    if self.display > 0: print('[Termination] All criteria satisfied and near border.')
+                    return 'terminate'
+                else:
+                    if self.display > 0: print('[Safe but not near border] Continue shrinking...')
+                    return 'continue'
+            return 'continue'
+        
+        def termination_condition_drilled():
+            UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+            disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+            disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+            limit_lat = 0.05*self.dd['design']['D']  # 10% of the pile diameter
+            limit_rot = 10.0                         # 10 deg
+        
+            all_satisfied = (UC_v <= 1.0 and disp_lat <= limit_lat and disp_rot <= limit_rot)
+        
+            if all_satisfied:
+                if near_border():
+                    if self.display > 0: print('[Termination] All criteria satisfied and near border.')
+                    return 'terminate'
+                else:
+                    if self.display > 0: print('[Safe but not near border] Continue shrinking...')
+                    return 'continue'
+            return 'continue'
+           
+        def is_valid(value):
+            return np.isfinite(value) and not np.isnan(value) and abs(value) < 1e6
+        
+        if anchType_clean in ['helical', 'driven']:
+            L0, D0 = geom if len(geom) == 2 else [5.0, 1.0]
+            self.dd['design']['L'] = L0
+            self.dd['design']['D'] = D0
+            Lmin, Lmax = geomBounds[0]
+            Dmin, Dmax = geomBounds[1]
+            update_zlug()
+            self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                   line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+        
+            UC_h = self.anchorCapacity['Ha']/self.anchorCapacity['Hmax']
+            UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+            disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+            disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+            limit_disp = 0.10*D0    # 10% of the pile diameter
+            limit_rot = 10.0        # 10 deg 
+            direction = 'shrink' if (UC_h <= 1.0 and UC_v <= 1.0 and disp_lat <= limit_disp and disp_rot <= limit_rot) else 'grow'
+    
+            max_iter = 200
+            iter_count = 0
+    
+            if direction == 'shrink':
+                for L in np.arange(L0, Lmin - 1e-6, -0.25):
+                    self.dd['design']['L'] = L
+                    for D in np.arange(Dmax, Dmin - 1e-6, -0.05):
+                        if L/D > lambdap_con[1] or L/D < lambdap_con[0]:
+                            continue
+                        self.dd['design']['L'] = L
+                        update_zlug()
+                        self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                               line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+                        UC_h = self.anchorCapacity['Ha']/self.anchorCapacity['Hmax']
+                        UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+                        disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+                        disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+                        if self.display > 0: print(f'[Iter {iter_count}] L={L:.2f}, D={D:.2f}, UC_h={UC_h:.3f}, UC_v={UC_v:.3f}, lat={disp_lat:.3f} m, rot={disp_rot:.3f} deg')
+                        iter_count += 1
+                        if not all(is_valid(v) for v in [UC_h, UC_v, disp_lat, disp_rot]):
+                            continue
+                        if termination_condition():
+                            print(f'\nTermination criteria met.')
+                            print('Design:', self.dd['design'])
+                            print('Capacity Results:', self.anchorCapacity)
+                            return
+            elif direction == 'grow':
+                for L in np.arange(L0, Lmax + 1e-6, 0.25):
+                    self.dd['design']['L'] = L
+                    for D in np.arange(Dmin, Dmax + 1e-6, 0.05):   
+                        if L/D > lambdap_con[1] or L/D < lambdap_con[0]:
+                            continue
+                        self.dd['design']['L'] = L
+                        update_zlug()
+                        self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                               line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+                        UC_h = self.anchorCapacity['Ha']/self.anchorCapacity['Hmax']
+                        UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+                        disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+                        disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+                        if self.display > 0: print(f'[Iter {iter_count}] L={L:.2f}, D={D:.2f}, UC_h={UC_h:.3f}, UC_v={UC_v:.3f}, lat={disp_lat:.3f} m, rot={disp_rot:.3f} deg')
+                        iter_count += 1
+                        status = termination_condition()
+                        if status == 'terminate':
+                            print(f'Termination criteria met.')
+                            print('Design:', self.dd['design'])
+                            print('Capacity Results:', self.anchorCapacity)
+                            return
+                        elif status == 'continue':
+                            continue
+                    status = termination_condition()
+                    if status == 'terminate':
+                        print(f'\nTermination criteria met.')
+                        print('Design:', self.dd['design'])
+                        print('Capacity Results:', self.anchorCapacity)
+                        return
+            else:
+                raise ValueError(f"Unknown optimization direction: {direction}")
+                
+            if self.display > 0: print('[Warning] While-loop search reached bounds without meeting criteria.')
+                    
+        if 'drilled' in anchType_clean:
+            L0, D0 = geom if len(geom) == 2 else [5.0, 1.0]
+            self.dd['design']['L'] = L0
+            self.dd['design']['D'] = D0
+            Lmin, Lmax = geomBounds[0]
+            Dmin, Dmax = geomBounds[1]
+            update_zlug()
+            self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                   line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+        
+            UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+            disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+            disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+            limit_disp = 0.10*D0   # 10% of the pile diameter
+            limit_rot = 10.0        # 10 deg 
+            direction = 'shrink' if (UC_v <= 1.0 and disp_lat <= limit_disp and disp_rot <= limit_rot) else 'grow'
+    
+            max_iter = 200
+            iter_count = 0
+    
+            if direction == 'shrink':
+                for L in np.arange(L0, Lmin - 1e-6, -0.25):
+                    self.dd['design']['L'] = L
+                    for D in np.arange(Dmax, Dmin - 1e-6, -0.05):
+                        if L/D > lambdap_con[1] or L/D < lambdap_con[0]:
+                            continue
+                        self.dd['design']['L'] = L
+                        update_zlug()
+                        self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                               line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+                        UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+                        disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+                        disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+                        if self.display > 0: print(f'[Iter {iter_count}] L={L:.2f}, D={D:.2f}, UC_v={UC_v:.3f}, lat={disp_lat:.3f} m, rot={disp_rot:.3f} deg')
+                        iter_count += 1
+                        if not all(is_valid(v) for v in [UC_v, disp_lat, disp_rot]):
+                            continue
+                        if termination_condition_drilled():
+                            print(f'\nTermination criteria met.')
+                            print('Design:', self.dd['design'])
+                            print('Capacity Results:', self.anchorCapacity)
+                            return
+            elif direction == 'grow':
+                for L in np.arange(L0, Lmax + 1e-6, 0.25):
+                    self.dd['design']['L'] = L
+                    for D in np.arange(Dmin, Dmax + 1e-6, 0.05):
+                        if L/D > lambdap_con[1] or L/D < lambdap_con[0]:
+                            continue
+                        self.dd['design']['L'] = L
+                        update_zlug()
+                        self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'],
+                                               line_type=line_type, d=d, w=w, mass_update=True, plot=False, display=display)
+                        UC_v = self.anchorCapacity['Va']/self.anchorCapacity['Vmax']
+                        disp_lat = abs(self.anchorCapacity.get('Lateral displacement', 0.0))
+                        disp_rot = abs(self.anchorCapacity.get('Rotational displacement', 0.0))
+                        if self.display > 0: print(f'[Iter {iter_count}] L={L:.2f}, D={D:.2f}, UC_v={UC_v:.3f}, lat={disp_lat:.3f} m, rot={disp_rot:.3f} deg')
+                        iter_count += 1
+                        status = termination_condition_drilled()
+                        if status == 'terminate':
+                            print(f'Termination criteria met.')
+                            print('Design:', self.dd['design'])
+                            print('Capacity Results:', self.anchorCapacity)
+                            return
+                        elif status == 'continue':
+                            continue
+                    status = termination_condition_drilled()
+                    if status == 'terminate':
+                        print(f'\nTermination criteria met.')
+                        print('Design:', self.dd['design'])
+                        print('Capacity Results:', self.anchorCapacity)
+                        return
             else:
-                # Ha = Hm because zlug is at mudline or above
-                makeEqual_TaTm(mudloads)
+                raise ValueError(f"Unknown optimization direction: {direction}")
+    
+            if self.display > 0: print('[Warning] While-loop search reached bounds without meeting criteria.')
+    
         else:
-            print('No zlug given, assuming loads at mudline = loads at anchor lug')
-            makeEqual_TaTm(mudloads)
-            
-        if not 'method' in mudloads:
-            # assume mudloads are static unless told otherwise
-            # loads determined from moorpy are static
-            mudloads['method'] = 'static'
+            raise ValueError(f"Anchor type '{anchType_clean}' not supported for safety factor input.")
+                   
+   
+    def getSafetyFactor(self):
+        '''
+        Calculate the safety factor based on the unity checks stored in capacity results.
+
+        Returns
+        -------
+        dict
+            Dictionary containing safety factors.
+        '''
+
+        anchType_clean = self.anchType.lower().replace(' ', '')
+
+        if anchType_clean in ['helical', 'driven', 'drilled']:
+            UC_v = self.anchorCapacity.get('Unity check (vertical)', None)
+            UC_h = self.anchorCapacity.get('Unity check (horizontal)', None)
+
+            if UC_v is None or UC_h is None:
+                print("Warning: Vertical or horizontal unity check (UC) not found in capacity results. Returning NaN.")
+                return {'SF_vertical': np.nan, 'SF_horizontal': np.nan}
+
+            SF_v = 1.0/UC_v if UC_v != 0 else np.inf
+            SF_h = 1.0/UC_h if UC_h != 0 else np.inf
+
+            return {'SF_vertical': SF_v, 'SF_horizontal': SF_h}
+
         else:
-            mudloads['method'] = mudloads['method']
+            UC = self.anchorCapacity.get('UC', None)
+
+            if UC is None:
+                print("Warning: Unity check (UC) not found in capacity results. Returning NaN.")
+                return {'SF_combined': np.nan}
+
+            SF = 1.0/UC if UC != 0 else np.inf
+
+            return {'SF_combined': SF} 
+                            
+    def getCost(self, ms=None, mass_update=True):
+        '''
+        Assign material cost using a Point object and getCost_and_MBL().
         
-        return mudloads
+        Parameters
+        ----------
+        ms : MoorPy System, optional
+            The mooring system to which the anchor point belongs. If None, a new one is created.
+        mass_update : bool, optional
+            If True, update mpAnchor mass from self.mass.
+            If False, preserve existing mpAnchor.m if already set.
+        '''
+
+        # Create or use existing MoorPy system
+        if ms is None:
+            ms = mp.System()
+
+            # Create MoorPy Point using makeMoorPyAnchor
+            self.makeMoorPyAnchor(ms)
+
+        # Assign self.mass if missing
+        if self.mass is None or mass_update:
+            if 'Weight pile' in self.anchorCapacity:
+                self.mass = self.anchorCapacity['Weight pile']/self.g
+            elif 'Weight plate' in self.anchorCapacity:
+                self.mass = self.anchorCapacity['Weight plate']/self.g
+            else:
+                raise KeyError("Missing 'Weight pile' or 'Weight plate' in anchorCapacity. \
+                Run getCapacityAnchor() before getCostAnchor(), or define self.mass explicitly.")
+        
+        # Assign mass to MoorPy point
+        self.mpAnchor.m = self.mass
+
+        cost, MBL, info = self.mpAnchor.getCost_and_MBL()
+
+        # Store results
+        self.cost = {
+            'Material cost': cost,
+            #'MBL': MBL,
+            #'unit_cost': cost/self.mpAnchor.m 
+            }
+
+        return self.cost
+
+    def getCombinedPlot(self):
+        '''
+        Create a plot showing the suction pile and the inverse catenary overlay in the same coordinate system.
+        '''
+        from anchors_famodel.capacity_load  import getTransferLoad
+        from anchors_famodel.capacity_plots import plot_suction
+
+        if self.anchType.lower() != 'suction':
+            raise NotImplementedError("getCombinedPlot only supports suction piles.")
+
+        # Extract design inputs
+        design = self.dd['design']
+        D = design['D']
+        L = design['L']
+        zlug = design['zlug']
+
+        if self.soil_profile is None or self.soil_type is None:
+            raise ValueError("Soil profile or type not assigned. Use setSoilProfile first.")
+
+        soil_profile = self.soil_profile
+        soil_type = self.soil_type
+        z0 = soil_profile[0]['top']
+
+        Hm = self.loads['Hm']
+        Vm = self.loads['Vm']
+        thetam = self.loads.get('thetam', np.degrees(np.arctan2(Vm, Hm)))
+
+        line_type = getattr(self, 'line_type', 'chain')
+        d = getattr(self, 'd', 0.16)
+        w = getattr(self, 'w', 5000.0)
+
+        # Get inverse catenary path
+        layers, result = getTransferLoad(
+            profile_map=[{'layers': self.soil_profile}],
+            Tm=np.sqrt(Hm**2 + Vm**2),
+            thetam=thetam,
+            zlug=zlug,
+            line_type=line_type,
+            d=d,
+            w=w,
+            plot=False
+        )
+
+        drag_values  = np.array(result['drag_values'])
+        depth_values = -np.array(result['depth_values'])[::-1]
+
+        x_start = D/2 + drag_values[0]
+        z_start = zlug
+        drag_transformed  = x_start - drag_values
+        depth_transformed = z_start + (depth_values- depth_values[0])
+
+        # Plot suction pile
+        plot_suction(soil_profile, L, D, z0=z0, zlug=zlug, title='Suction Pile and Mooring Line Load Path')
+
+
+        # Overlay inverse catenary path
+        plt.plot(drag_transformed, depth_transformed, color='b', lw=2.0, label='Inverse catenary')
+        plt.plot(drag_transformed[-1], depth_transformed[-1], 'ro', label='Mudline end')
+        plt.plot( drag_transformed[0],  depth_transformed[0], 'go', label='Embedded end')
+
+        n = 2e6
+        Tm = result['Tm']
+        Ta = result['Ta']
+        thetaa = result['thetaa']
+
+        plt.arrow(drag_transformed[-1], depth_transformed[-1],
+                  Tm*np.cos(np.deg2rad(thetam))/n, -Tm*np.sin(np.deg2rad(thetam))/n,
+                  head_width=0.25, head_length=0.5, color='r', label='Mudline load')
     
+        plt.arrow(drag_transformed[0], depth_transformed[0],
+                  Ta*np.cos(np.deg2rad(thetaa))/n, -Ta*np.sin(np.deg2rad(thetaa))/n,
+                  head_width=0.25, head_length=0.5, color='g', label='Padeye load')
+
+        xmax = max(drag_transformed[-1] + D, 2*D)
+        plt.xlim(-D, xmax)
+        plt.legend()
+        plt.grid(True)
+        plt.tight_layout()
+        plt.show()
+
+
+
     def getFS(self, loads=None, acceptance_crit=None):
         '''
         Compute safety factor for loads on the anchor
@@ -683,53 +1218,9 @@ def makeBuffer(self, buff_rad=50):
         point = sh.Point(self.r[:2])
         buff = point.buffer(buff_rad)
         return buff
-               
-    def getCost(self,costDict='default'):
-        '''find costs of anchor and store in design dictionary
-        
-        Parameters
-        ----------
-        costDict : dictionary or yaml, optional
-            Dictionary of various costs for anchors. Sub costs that can be included are: 
-            material : material costs
-            
-        '''
-        if isinstance(costDict,str) and costDict != 'default':
-            import yaml
-            costDict = yaml.load(costDict, Loader=yaml.FullLoader)
-        anchType = self.dd['type']
-        if costDict == 'default':
-            matCostDict = {'DEA':5.705,'suction_pile':4.435,'gravity':1.905} # mean values from Task 49 Design Basis ranges
-            instCostDict = {}
-            decomCostDict = {}
-        else:
-            matCostDict = costDict['material']
-            if 'install' in costDict:
-                instCostDict = costDict['install']
-            if 'decom' in costDict:
-                decomCostDict = costDict['decom']
-        keyFail = True
-        # check if mass info is available
-        if not self.mass:
-            if self.soilProps:               
-                # need mass - call capacity functions
-                self.getAnchorCapacity(plot=False)
-            else:
-                print('Soil properties needed to calculate anchor mass for cost. Setting cost to 0.')
-                self.mass = 0
-            
-        # sort by type of anchor
-        for Ckey,Cval in matCostDict.items():
-            if anchType in Ckey:
-                self.cost['materials'] = matCostDict[Ckey]*self.mass
-                # self.cost['install'] = instCostDict[Ckey]
-                # self.cost['decom'] = decomCostDict[Ckey]
-                keyFail = False
-        # raise error if anchType not found in cost dictionary
-        if keyFail:
-            raise KeyError(f'anchor type {anchType} not found in material cost dictionary')
-            
-        return(sum(self.cost.values()))
+
+
+
 
            
         
@@ -890,7 +1381,7 @@ def conFun_Suction(vars, geomKeys, input_loads, fix_zlug, LD_con, geomBounds, mi
             # convalB = 1 - results['UC'] 
             return(conval)
         
-        def conFun_DandG(vars, geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs):
+        def conFun_Drilled(vars, geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs):
 
             newGeom = dict(zip(geomKeys, vars))
             self.dd['design'].update(newGeom)
@@ -992,10 +1483,8 @@ def conBounds(vars, geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs):
             input_loads = {'Hm':loads['Hm']*minfs['Hm'], 'Vm':loads['Vm']*minfs['Vm']}
         else:
             input_loads = {'Ha':loads['Ha']*minfs['Ha'],'Va':loads['Va']*minfs['Va']}
-
-           
-
-        
+            
+            
         # Initial guess for geometry
         initial_guess = geom  # [val for val in startGeom.values()]       # Input values for geometry
         # geomKeys = [key for key in startGeom.keys()]
@@ -1011,9 +1500,9 @@ def conBounds(vars, geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs):
                            {'type':'ineq','fun':conFunV,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)},
                            {'type':'ineq','fun':conBounds,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)}]
         
-        elif 'dandg' in anchType:
+        elif 'drilled' in anchType:
             constraints = [{'type':'ineq','fun':conFun_LD,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)},
-                           {'type':'ineq','fun':conFun_DandG,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)},
+                           {'type':'ineq','fun':conFun_Drilled,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)},
                            {'type':'ineq','fun':conFunH,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)},
                            {'type':'ineq','fun':conFunV,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)},
                            {'type':'ineq','fun':conBounds,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)}]
@@ -1025,7 +1514,7 @@ def conBounds(vars, geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs):
         # Run the optimization to find sizing that satisfy UC close to 1
         print('optimizing anchor size')
         
-        if 'suction' in anchType or 'dandg' in anchType:
+        if 'suction' in anchType or 'drilled' in anchType:
             solution = minimize(objective, initial_guess, args=dict(geomKeys=geomKeys, input_loads=input_loads, fix_zlug=fix_zlug, LD_con=LD_con, geomBounds=geomBounds, minfs=minfs),
                                 method="COBYLA", constraints=constraints, options={'rhobeg':0.1, 'catol':0.001})
         else:
@@ -1058,7 +1547,7 @@ def conBounds(vars, geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs):
 
                 print('new initial guess',initial_guess)
                 # re-run optimization
-                if 'suction' in anchType or 'dandg' in anchType:
+                if 'suction' in anchType or 'drilled' in anchType:
                     solution = minimize(objective, initial_guess, args=dict(geomKeys=geomKeys, input_loads=input_loads, fix_zlug=fix_zlug, LD_con=LD_con, geomBounds=geomBounds, minfs=minfs),
                                         method="COBYLA", constraints=constraints, options={'rhobeg':0.1, 'catol':0.001})
                 else:
diff --git a/famodel/anchors/anchor_capacity.py b/famodel/anchors/anchor_capacity.py
deleted file mode 100644
index e3acb56b..00000000
--- a/famodel/anchors/anchor_capacity.py
+++ /dev/null
@@ -1,153 +0,0 @@
-"""The anchor capacity calculation 'switchboard' that holds generic
-anchor capacity functions and calls the specific calculation functions
-from other modules depending on the soil and anchor information."""
-
-import matplotlib.pyplot as plt
-import numpy as np
-
-import moorpy.MoorProps as mprop 
-
-from .capacity_plate import getCapacityPlate
-from .capacity_suction import getCapacitySuction
-from .capacity_dandg import *
-
-
-
-
-
-def anchorCapacity(anchor, soil, display=0):
-    '''Calculate anchor holding capacity based on specified anchor and soil
-    information.
-    
-    Parameters
-    ----------
-    anchor : dictionary
-        anchor description
-    soil : dictionary 
-        soil description. Can be a keyword ([_/soft/medium/hard] clay, or sand)
-        for the level 1 model, or a soilProps dict for the level 2 model.
-    model_level : int
-        1 or 2.
-
-    Returns
-    -------
-    UHC: float
-        required anchor ultimate holding capacity [kN]
-    info: dict
-        dictionary with additional information depending on the model.
-    '''
-
-    
-    if model_level == 1:   # soil keyword indicates level 1 models
-    
-    
-        # calls level 1 anchor capacity function, with anchor/soil types and default assumptions
-        uhc, mass, info = mprop.getAnchorMass(uhc_mode=True, mass_int=anchor['mass'], 
-                                              anchor=anchor['type'], soil_type=soil['class'], 
-                                              method='static', display=0)
-        
-        #fx, fz = anchor_curves.anchorCapacity(0, 0, 0, anchor=anchor['type'],
-        #                                      soil_type=soil['class'], display=display)
-
-
-    elif model_level==2:  # dict indicates a soilProps dictionary
-    
-        # >>> we probably need anchor details too then ...
-        
-        
-        # For now the anchor properties get checked in this function 
-        # but in the future they coudl be moved to the individual functions.
-        
-        if anchor['type'] == 'DEA':
-            # make curves from 
-            pass
-        
-        elif anchor['type'] == 'SCA':
-        
-            L     = getFromDict(anchor, 'length')
-            D     = getFromDict(anchor, 'diameter', default=L/6)
-            thick = getFromDict(anchor, 'thickness', default=L/100)
-            F_ang = np.degrees(np.atan2(Fz, Fx))  # load inclination angle [deg]
-            
-            if soil['class'] == 'clay':
-            
-                gamma = getFromDict(soil, 'gamma', default=4.7)
-                Su0   = getFromDict(soil, 'So0'  , default=2.39)
-                k     = getFromDict(soil, 'k'    , default=1.41)
-                alpha = getFromDict(soil, 'alpha', default=0.7)
-                SF = 2
-            
-                results = getCapacitySuction(L, L_D_aspect=L/D, D_t_aspect=D/thick, 
-                                    A_angle=F_ang, Su0=Su0, k=k, 
-                                    Alpha=alpha, gamma=gamma, J=1/SF)
-            
-            elif soil['class'] == 'sand':
-            
-                gamma = getFromDict(soil, 'gamma', default=9.0)
-                phi   = getFromDict(soil, 'phi'  , default=30)            
-                results = getCapacitySuction(L, L_D_aspect=L/D, D_t_aspect=D/thick, 
-                                    A_angle=F_ang, gamma=gamma, Phi=phi)
-            
-            else:
-                #raise Exception(f"soil class '{soil.class}' is not supported.")
-                pass
-                
-            
-        elif anchor['type'] == 'VLA':
-        
-            # same plate capacity calc as SEPLA for now - will in future consider angle
-        
-            A     = getFromDict(anchor, 'area')
-            thick = getFromDict(anchor, 'thickness', default=np.sqrt(L)/40)
-            H     = getFromDict(anchor, 'embedment')  # embedment depth [m]
-            
-            if soil['class'] == 'clay':
-            
-                gamma = getFromDict(soil, 'gamma', default=4.7)
-                Su0   = getFromDict(soil, 'So0'  , default=2.39)
-                k     = getFromDict(soil, 'k'    , default=1.41)
-                
-                results = getCapacityPlate(A, B_t_aspect=np.sqrt(L)/thick, 
-                                           Hs=H, Bita=30, Los=0.05,
-                                           gamma=gamma, So0=So0, k=k)
-            else:
-                raise Exception("Only clay soil is supported for this anchor type.")
-         
-        
-        elif anchor['type'] == 'SEPLA':
-            
-            A     = getFromDict(anchor, 'area')
-            thick = getFromDict(anchor, 'thickness', default=np.sqrt(L)/40)
-            H     = getFromDict(anchor, 'embedment')  # embedment depth [m]
-            
-            if soil['class'] == 'clay':
-            
-                gamma = getFromDict(soil, 'gamma', default=4.7)
-                Su0   = getFromDict(soil, 'So0'  , default=2.39)
-                k     = getFromDict(soil, 'k'    , default=1.41)
-                
-                results = getCapacityPlate(A, B_t_aspect=np.sqrt(L)/thick, 
-                                           Hs=H, Bita=30, Los=0.05,
-                                           gamma=gamma, So0=So0, k=k)
-            else:
-                raise Exception("Only clay soil is supported for this anchor type.")
-
-        else:
-            raise Exception(f"Anchor type '{anchor.type}' is not yet supported in hte intermediate anchor model set")
-    
-
-        
-        print(f"UHC input: fx:{fx} fz:{fz} -- Mass: {mass}, Cost: {cost}")
-        info["UHC input"] = fx,fz           #[kN]
-        info["Capacity_sf"] = capacity_sf   #[kN]
-        info["Mass"] = mass                 #[mT]
-        info["Cost"] = cost                 #[$/mT]
-        #info["Length"] = L
-        info["Area"] = area    
-
-    else:
-        raise Exception("Model level must be 1 or 2")
-
-
-    return capacity, info
-
diff --git a/famodel/anchors/anchor_conflict_backup.py b/famodel/anchors/anchor_conflict_backup.py
new file mode 100644
index 00000000..ff882af2
--- /dev/null
+++ b/famodel/anchors/anchor_conflict_backup.py
@@ -0,0 +1,1153 @@
+"""Anchor class for FAModel, containing information and key methods for anchors of mooring lines
+    Work in progress
+"""
+import moorpy as mp
+import numpy as np
+from famodel.famodel_base import Node
+from famodel.mooring.mooring import Mooring
+import famodel.platform.platform 
+from collections import defaultdict
+import shapely as sh
+
+
+class Anchor(Node):
+    
+    def __init__(self, dd=None, ms=None, r=[0,0,0], aNum=None, id=None, 
+                 g=9.81, rho=1025):
+        '''
+        Parameters
+        ----------
+        dd: dictionary
+            Design dictionary that contains all information on an anchor for a mooring line/shared mooring
+            {
+                type:   # anchor type (plate,suction_pile,torpedo_pile,helical_pile,driven_pile,dandg_pile)
+                design: # all geometric info from yaml file, only need to include info relevant to your anchor type
+                     A    plate anchor area
+                     D    anchor diameter (or helix diameter for helical piles)
+                     D1   torpedo anchor wing diameter
+                     D2   torpedo anchor shaft diameter
+                     d    helical pile shaft diameter 
+                     L    pile anchor length
+                     L1   torpedo anchor wing length 
+                     L2   torpedo anchor shaft length
+                     zlug padeye z elevation (+ down into the soil)
+                     beta angle of plate anchor after keying (optional)
+                cost:
+                    matCost: # material cost
+                    instCost: # installation cost
+                    decomCost: # decomissioning cost                          
+            }
+        ms: system object
+            MoorPy system object the anchor is in
+            
+        r: list
+            Location of anchor in x,y,z
+            
+        aNum: int
+            entry number in project.anchorList dictionary (may remove...)
+        id: str/int
+            unique id of this object
+        g: float
+            acceleration due to gravity in m/s^2
+        rho: float
+            density of water in kg/m^3
+        '''
+        # Initialize as a node
+        Node.__init__(self,id)
+        
+        # Design description dictionary for this Anchor
+        self.dd = dd
+        
+        # MoorPy system this anchor is in
+        self.ms = ms
+        
+        # x,y,z location of anchor
+        self.r = r
+        
+        # anchor index in array mooring list (only used for shared moorings/anchors)
+        self.aNum = aNum
+               
+        # MoorPy anchor object
+        self.mpAnchor = None
+        
+        # get environment info
+        self.g = g # acceleration due to gravity (m/s^2)
+        self.rho = rho # density of fluid (kg/m^3)
+        
+        # anchor mass
+        if 'mass' in self.dd['design']:
+            self.mass = self.dd['design']['mass']
+        else:
+            self.mass = None
+        
+        # Dictionaries for additional information
+        # anchor capacity
+        self.anchorCapacity = {}
+        self.safety_factors = {} # calculated safety factor
+        self.safety_factors_required = {} # minimum allowable safety factor
+        
+        # anchor costs
+        self.cost = {}
+        
+        self.loads = {}
+        '''
+        {
+           Hm:      # horizontal maximum anchor loads at mudline [N]
+           Vm:      # vertical maximum anchor loads at mudline [N]
+           thetam: # angle of load at the mudline [rad]
+           Ha:      # horizontal maximum loads at lug
+           Va:      # vertical maximum loads at lug
+           thetaa:  # angle of load at lug
+           method:  # dynamic or static method of calculation
+            }
+        '''
+        self.soilProps = {}
+        self.failure_probability = {}
+
+        # environmental impact
+        self.env_impact = {}
+        
+
+        # self.cost = {}
+        
+    def setSoilProfile(self, profile_map):
+        '''
+        Assign a soil profile directly from a single CPT.
+        Assumes profile_map is a list with only one entry.
+        '''
+        if len(profile_map) != 1:
+            raise ValueError("setSoilProfile expects a profile_map with exactly one CPT.")
+
+        cpt = profile_map[0]
+        self.soil_profile = cpt['layers']
+        self.profile_name = cpt.get('name', 'CPT_Assigned')
+
+        # Extract soil types from layers
+        soil_types = [layer['soil_type'] for layer in self.soil_profile]
+        self.soil_type_list = list(set(soil_types))
+        self.soil_type = soil_types[0] if len(self.soil_type_list) == 1 else 'mixed'
+
+        # Group layers by soil type
+        soilProps = defaultdict(list)
+        for layer in self.soil_profile:
+            layer_copy = layer.copy()
+            soil_type = layer_copy.pop('soil_type')
+            soilProps[soil_type].append(layer_copy)
+        self.soilProps = dict(soilProps)
+
+        print(f"[Anchor] Assigned soil profile from {self.profile_name} with soil types {self.soil_type_list}")
+
+    
+    def makeMoorPyAnchor(self, ms):
+        '''Create a MoorPy anchor object in a moorpy system
+        Parameters
+        ----------
+        ms : class instance
+            MoorPy system
+        
+        Returns
+        -------
+        ms : class instance
+            MoorPy system 
+
+        '''
+        # create anchor as a fixed point in MoorPy system
+        ms.addPoint(1,self.r)
+        # assign this point as mpAnchor in the anchor class instance
+        self.mpAnchor = ms.pointList[-1]
+
+        # add mass if available
+        if 'm' in self.dd['design'] and self.dd['design']['m']:
+            self.mpAnchor.m = self.dd['design']['m']
+        # set anchor diameter
+        if 'd' in self.dd['design'] and self.dd['design']['d']:
+            self.mpAnchor.d = self.dd['design']['d']
+        # set the point as an anchor entity
+        self.mpAnchor.entity= {'type': 'anchor'}
+        if 'type' in self.dd:
+            self.mpAnchor.entity['anchor_type']=self.dd['type']
+        
+        return(ms)
+    
+    
+    def getAnchorCapacity(self,ground_cons=None,installAdj=1,profile=None,loads=None,plot=True):
+        '''
+        Calls anchor capacity functions developed by Felipe Moreno for the correct anchor type 
+
+        Parameters
+        ----------
+        ground_conds : dict, optional
+            Ground conditions dictionary with the key as the soil type name, values as soil info such as UCS,Em,phi,gamma,effective stress,etc. The default is None.
+            If no dict provided, the ground conds will be pulled from the anchor soilProps property
+        installAdj : float, optional
+            Adjustment to the capacity based on installation (dummy variable for now, but future installation functions
+                                                              will dictate this value)
+        profile : 2D array,  optional
+            2d array of depths (m) and corresponding undrained shear strength (Pa). Su must not be zero 
+            (change to small value such as .001), but z must always start at 0. Ex: array([z1,Su1],[z2,Su2],...)
+            Used only for driven pile and drilled and grouted pile anchors.
+        loads : dict, optional
+            Dictionary of loads on the anchor at the lug point in [N]. If not provided, will use the loads dictionary property 
+            of the anchor. If this is empty and it is needed for the capacity function (i.e. driven piles) then 
+            the anchor.getLugForces() function will be called.
+
+        Returns
+        -------
+        results : dict
+            Dictionary of capacity of the anchor (generally a max force [N] in H and V, but can be a max displacement (driven, dandg piles))
+
+        '''
+        # - - - - set details - - - -
+        anchType = self.dd['type'] 
+        geom = self.dd['design']# geometric anchor information
+
+        if not ground_cons:
+            soil = next(iter(self.soilProps.keys()), None) # soil type
+            ground_conds = self.soilProps[soil]
+        else:
+            soil = next(iter(ground_cons.keys()))
+            ground_conds = ground_cons[soil]
+         
+        for key,prop in ground_conds.items():
+            if isinstance(prop,list) or isinstance(prop,np.ndarray):
+                if len(prop)>1:
+                    print('Warning: Only homogeneous soils are supported at this time. Only the first item in a property list will be used.')
+                    break 
+                else:
+                    ground_conds[key] = prop[0]
+        
+        
+        if loads:
+            # find out if mudline loads or anchor loads
+            if not 'Ha' in loads:
+                # get loads at lug
+                loads = self.getLugForces(mudloads=loads,plot=plot)
+        else:
+            loads = self.loads
+        
+        
+       
+        # logic to determine what functions to call based on anchor type and soil type...
+        
+        # - - - - plate anchors - - - - 
+        if anchType == 'SEPLA' or anchType == 'DEA' or anchType == 'DEPLA' or anchType == 'VLA' or anchType == 'plate':
+            from .anchors_famodel.capacity_plate import getCapacityPlate
+            if 'clay' in soil or 'mud' in soil:
+                # write or overwrite beta in geom dictionary from loads function
+                if anchType != 'DEA':
+                    if not 'beta' in geom:
+                        if not 'thetaa' in loads:
+                            # calculate thetaa from Ha and Va
+                            loads['thetaa'] = np.arctan2(loads['Va'],loads['Ha'])
+                            # loads = self.getLugForces(plot=plot)
+                        geom['beta'] = 90 - loads['thetaa']
+                else:
+                    geom['beta'] = 0
+                if 'Su0' in ground_conds and 'k' in ground_conds and 'gamma' in ground_conds:             
+                    results = getCapacityPlate(geom['A'], geom['beta'], geom['zlug'], 'clay', ground_conds['gamma'],
+                                               Su0=ground_conds['Su0'], k=ground_conds['k'])
+                else:
+                    raise Exception('Ground conditions dictionary needs Su0, k, gamma information for clay plate anchors')
+            else:
+                print(f'Warning: Soil type {soil} is not compatible with plate anchors (SEPLA/DEPLA/DEA/VLA)')
+         
+        # - - - - suction buckets - - - -                       
+        elif 'suction' in anchType:
+            from .anchors_famodel.capacity_suction import getCapacitySuction
+            # check loads have been calculated (needed for capacity function in this case)
+            if not 'Ha' in loads:
+                # call getMPForces function 
+                loads = self.getLugForces(plot=plot)
+            if 'sand' in soil:
+                if 'phi' in ground_conds and 'Dr' in ground_conds:
+                    results = getCapacitySuction(geom['D'], geom['L'], geom['zlug'],
+                                                 loads['Ha']/1000, loads['Va']/1000,
+                                                 'sand', ground_conds['gamma'],
+                                                 phi=ground_conds['phi'],
+                                                 Dr=ground_conds['Dr'], plot=plot)
+                else:
+                    raise Exception('Ground conditions dictionary needs phi and relative density information for sand suction pile anchor')
+            elif 'clay' in soil or 'mud' in soil:
+                if 'Su0' in ground_conds and 'k' in ground_conds and 'alpha' in ground_conds:# and 'gamma_sub' in ground_conds:
+                    results = getCapacitySuction(geom['D'],geom['L'], geom['zlug'],
+                                                 loads['Ha']/1000, loads['Va']/1000,
+                                                 'clay', ground_conds['gamma'],
+                                                 Su0=ground_conds['Su0'],
+                                                 k=ground_conds['k'], plot=plot)
+                    results['Horizontal max.'] = results['Horizontal max.']
+                    results['Vertical max.'] = results['Vertical max.']
+                    
+                else:
+                    raise Exception('Ground conditions dictionary needs Su0, k, and alpha information for clay suction pile anchor')
+            else:
+                print(f'Warning: Soil type {soil} is not compatible with suction pile anchor')
+                
+        # - - - - helical piles - - - -
+        elif 'helical' in anchType:
+            from .anchors_famodel.capacity_helical import getCapacityHelical
+            if 'sand' in soil:
+                if 'phi' in ground_conds and 'gamma' in ground_conds:
+                    results = getCapacityHelical(geom['D'], geom['L'], geom['d'],
+                                                 geom['zlug'], 'sand', 
+                                                 ground_conds['gamma'],
+                                                 phi=ground_conds['phi'], 
+                                                 Dr=ground_conds['Dr'])
+                    results['Vertical max.'] = results['Capacity']
+                else:
+                    raise Exception('Ground conditions dictionary needs phi, gamma and relative density information for clay helical pile anchor')
+            elif 'clay' in soil or 'mud' in soil:
+                if not 'alpha_star' in ground_conds:
+                    ground_conds['alpha_star'] = ground_conds['alpha']
+                if 'Su0' in ground_conds and 'k' in ground_conds and 'gamma' in ground_conds:
+                    results = getCapacityHelical(geom['D'], geom['L'], geom['d'],
+                                                 geom['zlug'], 'clay', 
+                                                 ground_conds['gamma'],
+                                                 Su0=ground_conds['Su0'], 
+                                                 k=ground_conds['k'])
+                    results['Vertical max.'] = results['Capacity']
+                else:
+                    raise Exception('Ground conditions dictionary needs Su0, k, gamma, and alpha_star information for clay helical pile anchor')
+            else:
+                print(f'Warning: Soil type {soil} is not compatible with helical pile anchor')
+        
+        # - - - - torpedo piles - - - - 
+        elif 'torpedo' in anchType:
+            from .anchors_famodel.capacity_torpedo import getCapacityTorpedo
+            if 'clay' in soil or 'mud' in soil:
+                if 'Su0' in ground_conds and 'k' in ground_conds and 'alpha' in ground_conds:
+                    results = getCapacityTorpedo(geom['D1'], geom['D2'], 
+                                                 geom['L1'], geom['L2'], 
+                                                 geom['zlug'], 'clay', 
+                                                 ground_conds['Su0'],
+                                                 ground_conds['k'], 
+                                                 ground_conds['alpha'])
+                    results['Horizontal max.'] = results['Horizontal max.']
+                    results['Vertical max.'] = results['Vertical max.']
+                else:
+                    raise Exception('Ground conditions dictionary needs Su0, k, and alpha information')
+            else:
+                print('Warning: Soil type {soil} is not compatible with torpedo pile anchor')
+        
+        # - - - - driven piles - - - - 
+        elif 'driven' in anchType: # driven pile anchor
+            # check loads have been calculated (needed for capacity function in this case)
+            if not 'Ha' in loads:
+                # call getLugForces function 
+                loads = self.getLugForces(plot=plot)
+            H_inc = loads['Ha']*0.1 # increment H by 10% of Ha load in the while loops to back-calc max H from displacements
+            H = 0
+            # check soil
+            if 'weak_rock' in soil:
+                from .anchors_famodel.capacity_drivenrock import getCapacityDrivenRock
+                
+                if not profile:
+                    if 'UCS' in ground_conds and 'Em' in ground_conds:
+                        profile = [[0,ground_conds['UCS'],ground_conds['Em']], 
+                                   [75,ground_conds['UCS'],ground_conds['Em']]] #profile = [list(x) for x in list(zip(ground_conds['depth'],ground_conds['UCS'],ground_conds['Em']))]
+                    else:
+                        raise Exception('Ground conditions dictionary needs UCS, Em, and depth information for weak rock driven pile anchor')
+                
+                y, z, results = getCapacityDrivenRock(profile, geom['L'], geom['D'], 
+                                                      geom['zlug'], loads['Va'], 
+                                                      loads['Ha'], plot=plot)
+                
+                # loop through, calling capacity with larger H values until a displacement value goes above limit
+                while results['Lateral displacement']< 0.05*geom['D'] and results['Rotational displacement'] < 0.25:
+                    # increment H 
+                    H += H_inc
+                    # call capacity function       
+                    y, z, results = getCapacityDrivenRock(profile, geom['L'], 
+                                                          geom['D'], geom['zlug'], 
+                                                          loads['Va'], H=H, plot=plot)
+                    
+                   
+            elif 'sand' in soil:
+                from .anchors_famodel.capacity_drivensoil import getCapacityDrivenSoil
+                if profile or ('gamma' in ground_conds and 'Dr' in ground_conds and 'phi' in ground_conds):
+                    if not profile:
+                        profile = [[0,ground_conds['phi'],ground_conds['gamma'],ground_conds['Dr']], 
+                                   [75,ground_conds['phi'],ground_conds['gamma'],ground_conds['Dr']]] #profile = [list(x) for x in list(zip(ground_conds['depth'],ground_conds['phi'],ground_conds['gamma']))]
+
+                    y, z, results = getCapacityDrivenSoil(profile, 'sand', 
+                                                          geom['L'], geom['D'], 
+                                                          geom['zlug'], loads['Va'], 
+                                                          loads['Ha'], plot=plot)
+                    if geom['zlug'] > 0:
+                        # need to check bending moment if lug is below mudline (+ zlug)
+                        # loop through, calling capacity with larger H values until a displacement value goes above limit
+                        while results['Lateral displacement']<= 0.05*geom['D'] and results['Bending moment'] <= results['Plastic moment']:
+                            # increment H by 10% of load
+                            H += H_inc
+                            # call capacity function     
+                            y, z, results = getCapacityDrivenSoil(profile,'clay', 
+                                                                  geom['L'], geom['D'],
+                                                                  geom['zlug'], loads['Va'], 
+                                                                  H=H, plot=plot)
+                            
+                    else:
+                        while results['Lateral displacement']<= 0.05*geom['D'] and results['Rotational displacement'] <= 0.25:
+                            # increment H by 10% of load
+                            H += H_inc  
+                            # call capacity function
+                            y, z, results = getCapacityDrivenSoil(profile, 'clay', 
+                                                                  geom['L'], geom['D'], 
+                                                                  geom['zlug'], loads['Va'],
+                                                                  H=H, plot=plot)
+                else:
+                    raise Exception('Ground conditions dictionary needs phi, gamma, and depth information for sand driven pile anchor')
+            elif 'clay' in soil or 'mud' in soil:
+                from .anchors_famodel.capacity_drivensoil import getCapacityDrivenSoil
+                #if profile or ('Su' in ground_conds and 'gamma' in ground_conds and 'depth' in ground_conds) or ('Su0' in ground_conds and 'k' in ground_conds):
+                if not profile:
+                    if 'Su' in ground_conds and 'depth' in ground_conds and 'gamma' in ground_conds:
+                        profile = [list(x) for x in list(zip(ground_conds['depth'],ground_conds['Su'],ground_conds['gamma']))]
+                    elif 'Su0' in ground_conds and 'k' in ground_conds and 'gamma' in ground_conds:
+                        Su = ground_conds['Su0']+ground_conds['k']*75
+                        profile = [[0,ground_conds['Su0'],ground_conds['gamma']],[75,Su,ground_conds['gamma']]]
+                    else:
+                        raise Exception('Ground conditions dictionary needs information for clay driven pile anchor')
+
+                y, z, results = getCapacityDrivenSoil(profile,'clay',geom['L'],geom['D'],geom['zlug'],loads['Va'],loads['Ha'], plot=plot)
+                
+                if geom['zlug'] > 0:
+                    # need to check bending moment if lug is below mudline (+ zlug)
+                    # loop through, calling capacity with larger H values until a displacement value goes above limit
+                    while results['Lateral displacement']<= 0.05*geom['D'] and results['Bending moment'] <= results['Plastic moment']:
+                        # increment H by 10% of load
+                        H += H_inc
+                        # call capacity function     
+                        y, z, results = getCapacityDrivenSoil(profile,'clay',geom['L'],geom['D'],geom['zlug'],loads['Va'], H=H, plot=plot)
+                
+                else:
+                    while results['Lateral displacement']<= 0.05*geom['D'] and results['Rotational displacement'] <= 0.25:
+                        # increment H by 10% of load
+                        H += H_inc  
+                        # call capacity function
+                        y, z, results = getCapacityDrivenSoil(profile,'clay',geom['L'],geom['D'],geom['zlug'],loads['Va'], H=H, plot=plot)
+                        
+                    
+            else:
+                print(f'Warning: Soil type {soil} is not compatible with driven pile anchors')
+                
+        # - - - - drilled and grouted piles - - - -                
+        elif 'dandg' in anchType:  # drill and grout pile
+            from .anchors_famodel.capacity_dandg import getCapacityDandG
+            # check for correct soil
+            if 'rock' in soil:
+                # check loads have been calculated (needed for capacity function in this case)
+                if not 'Ha' in loads:
+                    # call getMPForces function 
+                    loads = self.getLugForces(plot=plot)
+                # check for correct ground properties
+                if profile or ('UCS' in ground_conds and 'Em' in ground_conds):
+                    if not profile:
+                        profile = [[0,ground_conds['UCS'],ground_conds['Em']],[75,ground_conds['UCS'],ground_conds['Em']]] #[list(x) for x in list(zip(ground_conds['depth'],ground_conds['UCS'],ground_conds['Em']))]
+
+                    # call capacity function once to get displacement values
+                    y, z, results = getCapacityDandG(profile,geom['L'],geom['D'], 
+                                                     geom['zlug'], loads['Va'], 
+                                                     loads['Ha'], plot=plot)
+                    H_inc = loads['Ha']*0.1 # increment H by 10% of Ha load
+                    H = H_inc # start H at 10% of Ha load
+                    # loop through, calling capacity with larger H values until a displacement value goes above limit
+                    while results['Lateral displacement']< 0.05*geom['D'] and results['Rotational displacement'] < 0.25:
+                        # call capacity function       
+                        y, z, results = getCapacityDandG(profile, geom['L'], geom['D'], 
+                                                         geom['zlug'], loads['Va'], 
+                                                         H=H, plot=plot)
+                        # increment H 
+                        H += H_inc
+                else:
+                    raise Exception('Ground conditions dictionary need UCS and Em information for drill and grout pile')
+            else:
+                print(f'Warning: soil type {soil} is not compatible with drill and grout pile')
+                
+        # - - - - anchor type not recognized or supported - - - - 
+        else:
+            raise Exception(f'Anchor type {anchType} is not supported at this time')
+            
+        # - - - - save relevant results in dictionary using common terms - - - - 
+        # capacity = cap*installAdj ??? OR is installAdj an input to the capacity functions?
+        # save capacity 
+        if 'dandg' in anchType or 'driven' in anchType: # will take in dandg, dandg_pile, driven, driven_pile
+            self.anchorCapacity['Lat_max'] = results['Lateral displacement'] # [deg]
+            if 'Rotational displacement' in results:
+                self.anchorCapacity['Rot_max'] = results['Rotational displacement'] # [deg]
+            elif 'Bending moment' in results:
+                self.anchorCapacity['Mbend_max'] = results['Bending moment']
+            self.anchorCapacity['Va_max'] = results['Axial capacity'] # [N]
+            self.anchorCapacity['Ha_max'] = H
+
+        else:
+            if 'Horizontal max.' in results:
+                self.anchorCapacity['Ha_max'] = results['Horizontal max.']*1000 # [N]
+            self.anchorCapacity['Va_max'] = results['Vertical max.']*1000 # [N]
+        self.mass = results['Weight']*1000/self.g # mass in [kg]
+            
+        # add on extra for drag-embedment anchors (flukes)
+        if 'DEA' in anchType:
+            self.mass *= 1.75
+        
+            
+        return(results)
+            
+    def getMudlineForces(self, max_force=False,lines_only=False, seabed=True, xyz=False,project=None):   
+        '''Find forces on anchor at mudline using the platform.getWatchCircle method or MoorPy Point.getForces method. 
+        Optionally, get forces at anchor lug location with getTransferLoad function in capacity_loads.py.
+        Stores in loads dictionary
+        Parameters
+        ----------
+        max_force : boolean, optional
+            Find and save the maximum force on the anchor (True) or just get force at the current MoorPy system state (False)           
+        lines_only : boolean, optional
+            Calculate forces from just mooring lines (True) or not (False). Default is false
+        seabed : boolean, optional
+            Include effect of seabed pushing up the anchor (True) or not (False). Default is true
+        xyz : boolean, optional
+            Return forces in x,y,z DOFs (True) or only the enabled DOFs (False). Default is false
+            
+        '''
+        Platform = famodel.platform.platform.Platform
+        if max_force:
+            if project:
+                # get watch circle of platform(s)
+                project.arrayWatchCircle()
+            else:
+                # find platform associated with this anchor
+                for att in self.attachments.values():
+                    if isinstance(att['obj'],Mooring):
+                        for attM in att['obj'].attached_to:
+                            if isinstance(attM,Platform):
+                                locx,locy,maxVals = attM.getWatchCircle()
+        # call getForces method from moorpy point object
+        else:
+            loads = self.mpAnchor.getForces(lines_only=lines_only, seabed=seabed, xyz=xyz)
+            self.loads['Hm'] = np.sqrt(loads[0]**2+loads[1]**2) # mudline forces in [N]
+            self.loads['Vm'] = loads[2] # [N]
+            self.loads['thetam'] = np.degrees(np.arctan(self.loads['Vm']/self.loads['Hm'])) # [deg]
+            self.loads['mudline_load_type'] = 'current_state'
+        
+        # loads determined from moorpy are static
+        self.loads['method'] = 'static'
+        
+        return(self.loads)
+    
+    def getLugForces(self, mudloads=None, max_force=True, plot=False):
+        '''
+        Find forces on an anchor at the lug point based on the mudline forces and angles. Calls getTransferFunction script
+
+        Parameters
+        ----------
+        mudloads : dict, optional
+            Dictionary of max mudline forces. The default is None.
+
+        Returns
+        -------
+        loads: dict
+            Dictionary of loads at the lug point [N]
+
+        '''
+        from .anchors_famodel.capacity_load import getTransferLoad
+        
+        nolugload = False
+        
+        if not mudloads:  
+            if not self.loads:
+                # get max mudline forces first
+                self.getMudlineForces(max_force=max_force)
+            elif not 'mudline_load_type' in self.loads:
+                raise KeyError("Loads dictionary must specify 'mudline_load_type'='current_state' or 'mudline_load_type'='max', where 'max' indicates the loads are maximum loads.")
+            elif max_force and self.loads['mudline_load_type'] != 'max':
+                # need max forces, not current state
+                self.getMudlineForces(max_force=True)
+            mudloads = self.loads
+        else:
+            # check syntax
+            if not 'Hm' in mudloads or not 'Vm' in mudloads:
+                raise KeyError('Mudline load dictionary must have Hm and Vm for horizontal load and vertical load (in [N]) at the mudline')
+            if not 'thetam' in mudloads:
+                mudloads['thetam'] = np.degrees(np.arctan(mudloads['Vm']/mudloads['Hm']))
+                
+        def makeEqual_TaTm(mudloads):
+            mudloads['Ha'] = mudloads['Hm'] # [N]
+            mudloads['Va'] = mudloads['Vm'] # [N]
+            mudloads['thetaa'] = mudloads['thetam'] # [deg]
+        
+        if 'zlug' in self.dd['design']:
+            if self.dd['design']['zlug'] > 0:
+                # get line type
+                for att in self.attachments.values():
+                    if isinstance(att['obj'],Mooring):
+                        mtype = att['obj'].dd['sections'][0]['type']['material']
+                        if not 'chain' in mtype:
+                            print('No chain on seafloor, setting Ta=Tm')
+                            nolugload = True
+                            break
+                        else:
+                            md = att['obj'].dd['sections'][0]['type']['d_nom']
+                            mw = att['obj'].dd['sections'][0]['type']['w']
+                soil = next(iter(self.soilProps.keys()), None)
+                ground_conds = self.soilProps[soil]
+                # update soil conds as needed to be homogeneous
+                for key,prop in ground_conds.items():
+                    if isinstance(prop,list) or isinstance(prop,np.ndarray):
+                        if len(prop)>1:
+                            print('Warning: Only homogeneous soils are supported at this time. Only the first item in a property list will be used.')
+                            break 
+                        else:
+                            ground_conds[key] = prop[0]
+                            
+                Tm =  np.sqrt(mudloads['Hm']**2+mudloads['Vm']**2) # [N]
+                if 'clay' in soil or 'mud' in soil and not nolugload:
+                    # Tm, thetam, zlug, line_type, d, soil_type, Su0=None, k=None, w=None
+                    try:
+                        loadresults = getTransferLoad(Tm/1000,mudloads['thetam'],
+                                                      self.dd['design']['zlug'],mtype,md,
+                                                      'clay',Su0=ground_conds['Su0'],
+                                                      k=ground_conds['k'],w=mw/1000,
+                                                      plot=plot) # output Ha and Va    (convert weight to kN/m)   
+                    except Exception as e:
+                        print(e)
+                        print('Unable to get loads at anchor lug location. Setting Ta = Tm')
+                        nolugload = True
+                elif 'sand' in soil and not nolugload:
+                        soil = 'sand'
+                        try:
+                            loadresults = getTransferLoad(Tm/1000, self.loads['thetam'], 
+                                                        self.dd['design']['zlug'],
+                                                        mtype, md, soil,
+                                                        gamma=ground_conds['gamma'], 
+                                                        phi=ground_conds['phi'],
+                                                        delta=ground_conds['delta'], 
+                                                        w=mw/1000,plot=plot) # output Ha and Va  (convert weight to kN/m)
+                        except Exception as e:
+                            print(e)
+                            print('Unable to get loads at anchor lug location. Setting Ta = Tm')
+                            nolugload = True
+                elif 'rock' in soil and not nolugload:
+                    raise ValueError('zlug should be <= 0 for rock.')
+                    
+                # if loadresults['V']<0:
+                #     # results are invalid
+                #     print('Warning: invalid results for the combination of anchor ',self.dd['type'],' soil ',soil,' and loads ',mudloads,'. Setting Ha=Hm, Va=Vm, thetaa=thetam')
+                #     makeEqual_TaTm(mudloads)
+                if nolugload:
+                    makeEqual_TaTm(mudloads)
+                else:
+                    mudloads['Ha'] = loadresults['H']*1000 # [N]
+                    mudloads['Va'] = loadresults['V']*1000 # [N]
+                    mudloads['thetaa'] = loadresults['angle'] # [deg]
+            else:
+                # Ha = Hm because zlug is at mudline or above
+                makeEqual_TaTm(mudloads)
+        else:
+            print('No zlug given, assuming loads at mudline = loads at anchor lug')
+            makeEqual_TaTm(mudloads)
+            
+        if not 'method' in mudloads:
+            # assume mudloads are static unless told otherwise
+            # loads determined from moorpy are static
+            mudloads['method'] = 'static'
+        else:
+            mudloads['method'] = mudloads['method']
+        
+        return mudloads
+    
+    def getFS(self, loads=None, acceptance_crit=None):
+        '''
+        Compute safety factor for loads on the anchor
+        
+        Parameters
+        ----------
+        loads : dict, optional
+            Dictionary of loads on the anchor. 
+        acceptance_crit : dict, optional
+            Dictionary of acceptable factors of safety for each load type.
+            Key is the load type, and value is the minimum acceptable safety factor.
+            Default is None (in which case no comparison between FS and acceptance criteria is calculated)
+
+        Returns
+        -------
+        FS : dict
+            Dictionary of safety factors (often horizontal and vertical load SFs, but could be displacement SFs (drilled and grouted/driven piles))
+        acceptance : dict
+            Dictionary of bools that state whether the FS>=acceptance_crit for each load
+        acceptance_margin : dict
+            Dictionary of difference between FS and acceptance criteria for each load type
+        
+
+        '''
+        if not loads:
+            if not 'Ha' in self.loads:
+                self.getLugForces()
+            loads = self.loads
+        if not self.anchorCapacity:
+            self.getAnchorCapacity()
+         
+        # look for load dictionary key in capacity dictionary
+        FS = {}
+        acceptance = {}
+        acceptance_margin = {}
+        for Lkey,Lval in loads.items():
+            for Ckey,Cval in self.anchorCapacity.items():
+                if Lkey in Ckey:
+                    if Lval == 0:
+                        FS[Lkey] = float('inf')
+                    else:
+                        FS[Lkey] = Cval/Lval
+                    if acceptance_crit and Lkey in acceptance_crit:
+                        if Lval == 0 or acceptance_crit[Lkey] == 0:
+                            acceptance[Lkey] = True
+                        else:
+                            acceptance[Lkey] = acceptance_crit[Lkey]<=FS[Lkey]
+                            acceptance_margin[Lkey] = FS[Lkey] - acceptance_crit[Lkey]
+                    
+        if acceptance_crit:
+            return(FS,acceptance,acceptance_margin)
+        else:
+            return(FS)
+            
+    def makeBuffer(self, buff_rad=50):
+        point = sh.Point(self.r[:2])
+        buff = point.buffer(buff_rad)
+        return buff
+               
+    def getCost(self,costDict='default'):
+        '''find costs of anchor and store in design dictionary
+        
+        Parameters
+        ----------
+        costDict : dictionary or yaml, optional
+            Dictionary of various costs for anchors. Sub costs that can be included are: 
+            material : material costs
+            
+        '''
+        if isinstance(costDict,str) and costDict != 'default':
+            import yaml
+            costDict = yaml.load(costDict, Loader=yaml.FullLoader)
+        anchType = self.dd['type']
+        if costDict == 'default':
+            matCostDict = {'DEA':5.705,'suction_pile':4.435,'gravity':1.905} # mean values from Task 49 Design Basis ranges
+            instCostDict = {}
+            decomCostDict = {}
+        else:
+            matCostDict = costDict['material']
+            if 'install' in costDict:
+                instCostDict = costDict['install']
+            if 'decom' in costDict:
+                decomCostDict = costDict['decom']
+        keyFail = True
+        # check if mass info is available
+        if not self.mass:
+            if 'soil_properties' in self.dd:               
+                # need mass - call capacity functions
+                self.getAnchorCapacity(plot=False)
+            else:
+                print('Soil properties needed to calculate anchor mass for cost. Setting cost to 0.')
+                self.mass = 0
+            
+        # sort by type of anchor
+        for Ckey,Cval in matCostDict.items():
+            if anchType in Ckey:
+                self.cost['materials'] = matCostDict[Ckey]*self.mass
+                # self.cost['install'] = instCostDict[Ckey]
+                # self.cost['decom'] = decomCostDict[Ckey]
+                keyFail = False
+        # raise error if anchType not found in cost dictionary
+        if keyFail:
+            raise KeyError(f'anchor type {anchType} not found in material cost dictionary')
+            
+        return(sum(self.cost.values()))
+
+           
+        
+    # def getSuctionSize(self,D,L,loads=None,minfs={'Ha':1.6,'Va':2},LD_con=[4,8]):
+    #     '''
+        
+
+    #     Parameters
+    #     ----------
+    #     D : float
+    #         Diameter of suction bucket
+    #     L : float
+    #         Length of suction bucket
+    #     loads : dict, optional
+    #         Dictionary of maximum anchor loads in horizontal and vertical directions. The default is None.
+    #     minfs : dict,optoinal
+    #         Minimum factors of safety in horizontal and vertical directions
+    #     LD_con : float
+    #         Constraint for L/D parameter
+
+    #     Returns
+    #     -------
+    #     None.
+
+    #     '''
+    #     from scipy.optimize import minimize
+    #     anchType = self.dd['type']
+    #     if not loads:
+    #         loads = self.loads
+            
+    #     if not 'Ha' in loads:
+    #         loads = self.getLugForces(mudloads=loads)
+           
+    #     loads['Ha'] = minfs['Ha']*loads['Ha']
+    #     loads['Va'] = minfs['Va']*loads['Va']
+                   
+    #     if not 'zlug' in self.dd['design']:
+    #         self.dd['design']['zlug'] = (2/3)*L
+            
+    #     # Define the objective function: Minimize |UC - 1| (aim for UC to be 1)
+    #     def objective(vars):
+    #         D, L = vars
+    #         self.dd['design']['D'] = D
+    #         self.dd['design']['L'] = L
+    #         self.dd['design']['zlug'] = (2/3)*L
+    #         results = self.getAnchorCapacity(plot=False)
+    #         return abs(results['UC'] - 1)  
+        
+    #     def conFun(vars,LD_con):
+    #         D, L = vars
+    #         if L/D >= LD_con[0] and L/D <= LD_con[1]:
+    #             conval = 1 
+    #         else:
+    #             conval = -1 
+            
+    #         return(conval)
+        
+    #     # Initial guess for D and L
+    #     initial_guess = [D, L]       # Input values for D and L
+        
+    #     # Bounds for D and L (adjust as needed)
+    #     bounds = [(1, 5), (5, 50)]   # Bounds for D and L
+        
+    #     # constraints
+    #     constraints = [{'type':'ineq','fun':conFun,'args':(LD_con,)}]
+        
+    #     # Run the optimization to find D and L that satisfy UC close to 1
+    #     solution = minimize(objective, initial_guess, bounds=bounds,method="COBYLA",
+    #                         constraints=constraints,options={'rhobeg':0.1, 'catol':0.001})
+        
+    #     # Extract the optimized values of D and L
+    #     self.dd['design']['D'], self.dd['design']['L'] = solution.x
+    #     self.dd['design']['zlug'] = (2/3)*self.dd['design']['L'] 
+    #     results = self.getAnchorCapacity(plot=False)    
+   
+
+    def getSize(self, geom, geomKeys, geomBounds=None, loads=None, minfs={'Ha':1.6,'Va':2}, 
+                LD_con=[4,8], fix_zlug=False, FSdiff_max=None, plot=False):
+        '''
+        
+    
+        Parameters
+        ----------
+        geom: list
+            starting guess geometry values
+        geomKeys : list
+            List of keys that match the geom list values i.e. 'L','D','zlug'
+        geomBounds : list,optional
+            List of upper and lower bounds for each geometry value. 
+            Each entry should be a tuple of upper and lower bounds for each geometry i.e. [(5,10),(10,20)]
+        loads : dict, optional
+            Dictionary of maximum anchor loads in horizontal and vertical directions (not including factor of safety). The default is None.
+        minfs : dict,optional
+            Minimum factors of safety in horizontal and vertical directions
+        LD_con : float
+            Constraint for L/D parameter
+        fix_zlug : bool
+            Boolean to decide if zlug should be altered as geometric values are altered. 
+            True = fixed zlug, False = zlug may be changed
+        plot : bool
+            Boolean controls if capacity plots are generated or not for the final configuration
+    
+        Returns
+        -------
+        None.
+    
+        '''
+        # - - - - Objective and Constraint Functions 
+        
+        # Define the objective function: Minimize weight of anchor (cost is dependent on weight)
+        def objective(vars, args):
+
+            geomKeys = args['geomKeys']
+            input_loads = args['input_loads']
+            fix_zlug = args['fix_zlug']
+
+            newGeom = dict(zip(geomKeys,vars))
+            self.dd['design'].update(newGeom)
+            if 'suction' in self.dd['type'] and not fix_zlug:
+                self.dd['design']['zlug'] = (2/3)*newGeom['L']
+            
+            if 'Hm' in input_loads or 'Vm' in input_loads:
+                anchor_loads = self.getLugForces(mudloads=input_loads)
+                input_loads = dict(Ha=anchor_loads['Ha'], Va=anchor_loads['Va'])    # overwrite the input_loads dictionary
+            # get results
+            results = self.getAnchorCapacity(loads=input_loads, plot=False)
+                
+            return(results['Weight'])
+        
+        # constraint for suction bucket sizing only. May add more constraints for other anchors in the future...
+        def conFun_LD(vars, geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs):
+            newGeom = dict(zip(geomKeys, vars))
+            self.dd['design'].update(newGeom)
+
+            if 'Hm' in input_loads or 'Vm' in input_loads:
+                anchor_loads = self.getLugForces(mudloads=input_loads)
+                input_loads = dict(Ha=anchor_loads['Ha'], Va=anchor_loads['Va'])    # overwrite the input_loads dictionary
+
+            results = self.getAnchorCapacity(loads=input_loads, plot=False)
+            
+            convalA = newGeom['L']/newGeom['D'] - LD_con[0]
+            convalB = LD_con[1] - newGeom['L']/newGeom['D']
+            conval = min([convalA,convalB])
+            # if newGeom['L']/newGeom['D'] >= LD_con[0] and newGeom['L']/newGeom['D'] <= LD_con[1]:
+            #     conval = 1 
+            # else:
+            #     conval = -1 
+            
+            return(conval)
+        # constraint to ensure unity check > 1 for suction buckets
+        def conFun_Suction(vars, geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs):
+            if 'Hm' in input_loads or 'Vm' in input_loads:
+                anchor_loads = self.getLugForces(mudloads=input_loads)
+                input_loads = dict(Ha=anchor_loads['Ha'], Va=anchor_loads['Va'])    # overwrite the input_loads dictionary
+            results = self.getAnchorCapacity(loads=input_loads, plot=False)
+            #conval = results['UC'] - 1
+            conval = 1 - results['UC']
+            # convalB = 1 - results['UC'] 
+            return(conval)
+        
+        def conFun_DandG(vars, geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs):
+
+            newGeom = dict(zip(geomKeys, vars))
+            self.dd['design'].update(newGeom)
+            if 'Hm' in input_loads or 'Vm' in input_loads:
+                anchor_loads = self.getLugForces(mudloads=input_loads)
+                input_loads = dict(Ha=anchor_loads['Ha'], Va=anchor_loads['Va'])    # overwrite the input_loads dictionary
+            results = self.getAnchorCapacity(loads=input_loads, plot=False)
+
+            return np.array([0.05*newGeom['D'] - results['Lateral displacement'] , 0.25 - results['Rotational displacement']])
+            
+        def conFunH(vars, geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs):
+            # if 'suction' in self.dd['type']:
+            #     results = self.getAnchorCapacity(plot=False)
+            #     conval = results['UC'] - 1
+            #     # if results['UC'] < 1:
+            #     #     conval = -1*(results['UC'])
+            # else:
+            if 'Hm' in input_loads or 'Vm' in input_loads:
+                anchor_loads = self.getLugForces(mudloads=input_loads)
+                input_loads = dict(Ha=anchor_loads['Ha'], Va=anchor_loads['Va'])    # overwrite the input_loads dictionary
+                minfs = dict(Ha=minfs['Hm'], Va=minfs['Vm'])
+            FS, _, _ = self.getFS(loads=input_loads, acceptance_crit=minfs)
+            conval = FS['Ha'] - 1
+                # for key,val in FS.items():
+                    
+                #     if val/minfs[key]<1:
+                #         if -1*(1-val/minfs[key]) < conval:
+                #             conval = -1*(1-val/minfs[key])
+            return(conval)
+        
+        def conFunV(vars, geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs):
+            if 'Hm' in input_loads or 'Vm' in input_loads:
+                anchor_loads = self.getLugForces(mudloads=input_loads)
+                input_loads = dict(Ha=anchor_loads['Ha'], Va=anchor_loads['Va'])    # overwrite the input_loads dictionary
+                minfs = dict(Ha=minfs['Hm'], Va=minfs['Vm'])
+            FS, _, _ = self.getFS(loads=input_loads, acceptance_crit=minfs)
+            # special case for DEAs
+            if minfs['Va'] == 0:
+                 conval = 1
+            else:
+                conval = FS['Va'] - 1
+                
+            # print('FS_V',FS['Va'])
+            return(conval)
+        
+        def conBounds(vars, geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs):
+
+            newGeom = dict(zip(geomKeys, vars))
+            self.dd['design'].update(newGeom)
+
+            if 'Hm' in input_loads or 'Vm' in input_loads:
+                anchor_loads = self.getLugForces(mudloads=input_loads)
+                input_loads = dict(Ha=anchor_loads['Ha'], Va=anchor_loads['Va'])    # overwrite the input_loads dictionary
+            results = self.getAnchorCapacity(loads=input_loads, plot=False)
+
+            bound_L_lower = newGeom['L'] - geomBounds[0][0]
+            bound_L_upper = geomBounds[0][1] - newGeom['L']
+            bound_D_lower = newGeom['D'] - geomBounds[1][0]
+            bound_D_upper = geomBounds[1][1] - newGeom['D']
+
+            return np.array([bound_L_lower, bound_L_upper, bound_D_lower, bound_D_upper])
+        
+        # - - - - - Setup & Optimization
+        from scipy.optimize import minimize
+        from copy import deepcopy
+
+        anchType = self.dd['type']
+
+        # loads['Ha'] = minfs['Ha']*loads['Ha']
+        # loads['Va'] = minfs['Va']*loads['Va']
+        startGeom = dict(zip(geomKeys,geom))
+        print('start geometry: ',startGeom)
+        # apply initial guess geometry
+        self.dd['design'].update(startGeom)
+                   
+        if not 'zlug' in self.dd['design']:
+            if 'suction' in anchType and not fix_zlug:
+                self.dd['design']['zlug'] = (2/3)*startGeom['L']
+            else:
+                self.dd['design']['zlug'] = 0
+        
+        # if zlug is fixed, remove it from design variables
+        if fix_zlug and 'zlug' in geomKeys:
+            zlug_loc = geomKeys.index('zlug')
+            startGeom.pop('zlug')
+            geomKeys.remove('zlug')
+            geom.pop(zlug_loc)
+            if geomBounds:
+                geomBounds.pop(zlug_loc)
+
+        if not loads:
+            loads = self.loads
+            
+        if not 'Ha' in loads:
+            loads = self.getLugForces(mudloads=loads)
+            
+        # suction bucket needs to be loads*FS because of capacity envelope calculations in capacity function
+        if ('Hm' in loads and 'Vm' in loads) and ('Hm' in minfs and 'Vm' in minfs):
+            input_loads = {'Hm':loads['Hm']*minfs['Hm'], 'Vm':loads['Vm']*minfs['Vm']}
+        else:
+            input_loads = {'Ha':loads['Ha']*minfs['Ha'],'Va':loads['Va']*minfs['Va']}
+
+           
+
+        
+        # Initial guess for geometry
+        initial_guess = geom  # [val for val in startGeom.values()]       # Input values for geometry
+        # geomKeys = [key for key in startGeom.keys()]
+        
+        # Bounds and constraints
+        if 'suction' in anchType:
+            # bounds = [(1, 7), (5, 50),()]   # Bounds for D and L
+            # constraints
+            
+            constraints = [{'type':'ineq','fun':conFun_LD,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)},
+                           {'type':'ineq','fun':conFun_Suction,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)},
+                           {'type':'ineq','fun':conFunH,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)},
+                           {'type':'ineq','fun':conFunV,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)},
+                           {'type':'ineq','fun':conBounds,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)}]
+        
+        elif 'dandg' in anchType:
+            constraints = [{'type':'ineq','fun':conFun_LD,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)},
+                           {'type':'ineq','fun':conFun_DandG,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)},
+                           {'type':'ineq','fun':conFunH,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)},
+                           {'type':'ineq','fun':conFunV,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)},
+                           {'type':'ineq','fun':conBounds,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)}]
+        
+        else:
+            constraints = [{'type':'ineq','fun':conFunH,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)},
+                           {'type':'ineq','fun':conFunV,'args':(geomKeys, input_loads, fix_zlug, LD_con, geomBounds, minfs)}]
+        
+        # Run the optimization to find sizing that satisfy UC close to 1
+        print('optimizing anchor size')
+        
+        if 'suction' in anchType or 'dandg' in anchType:
+            solution = minimize(objective, initial_guess, args=dict(geomKeys=geomKeys, input_loads=input_loads, fix_zlug=fix_zlug, LD_con=LD_con, geomBounds=geomBounds, minfs=minfs),
+                                method="COBYLA", constraints=constraints, options={'rhobeg':0.1, 'catol':0.001})
+        else:
+            solution = minimize(objective, initial_guess, args=dict(geomKeys=geomKeys, input_loads=input_loads, fix_zlug=fix_zlug, LD_con=LD_con, geomBounds=geomBounds, minfs=minfs),
+                                method="COBYLA", constraints=constraints, options={'rhobeg':0.1, 'catol':0.001})
+        
+        FS, acceptance, FSdiff = self.getFS(loads=input_loads, acceptance_crit=minfs)
+        
+        # adjust starting value if you're far off from the acceptance criteria (in either direction)
+        if FSdiff_max:
+            count = 0
+            while count<10 and (np.any([abs(FSdiff[key])>FSdiff_max[key] for key in FSdiff.keys()]) or np.any([diff<0 for diff in FSdiff.values()])):
+                if np.any([diff<.02 for key,diff in FSdiff.items() if minfs[key]>0]) and np.all([diff>=0 for diff in FSdiff.values()]):
+                    # exit loop if you're as close as can be on one of the FS even if other is above diff requirements UNLESS an FS is below minimum reqiured FS
+                    break
+                print('Factor of Safety not close enough to minimum factor of safety, trying again with adjusted initial guess.')
+                print(FS)
+                # calculate new percent difference of FS from min fs
+                diffPCT = [FSdiff[key]/FS[key] for key in FSdiff]
+                # create adjustment coefficient based on this or .25, whichever is lower
+                adjust_coeff = np.min([np.min(diffPCT),0.25])
+                # adjust initial guess values by adjustment coefficient
+                for i,val in enumerate(initial_guess):
+                    initial_guess[i] = val - val*adjust_coeff
+                # update zlug for suction buckets as needed to be 2/3L
+                if 'suction' in anchType and not fix_zlug:
+                    zlug_loc = geomKeys.index('zlug')
+                    L_loc = geomKeys.index('L')
+                    initial_guess[zlug_loc] = (2/3)*initial_guess[L_loc]
+
+                print('new initial guess',initial_guess)
+                # re-run optimization
+                if 'suction' in anchType or 'dandg' in anchType:
+                    solution = minimize(objective, initial_guess, args=dict(geomKeys=geomKeys, input_loads=input_loads, fix_zlug=fix_zlug, LD_con=LD_con, geomBounds=geomBounds, minfs=minfs),
+                                        method="COBYLA", constraints=constraints, options={'rhobeg':0.1, 'catol':0.001})
+                else:
+                    solution = minimize(objective, initial_guess, args=dict(geomKeys=geomKeys, input_loads=input_loads, fix_zlug=fix_zlug, LD_con=LD_con, geomBounds=geomBounds, minfs=minfs),
+                                        method="COBYLA", constraints=constraints, options={'rhobeg':0.1, 'catol':0.001})
+                # re-determine FS and diff from minFS
+                FS, acceptance, FSdiff = self.getFS(loads=input_loads, acceptance_crit=minfs)  
+                count += 1
+        
+        # Extract the optimized values of geometry
+        endGeom = dict(zip(geomKeys,solution.x))
+        print('End geometry: ',endGeom)
+        self.dd['design'].update(endGeom)
+        if 'suction' in anchType and not fix_zlug:
+            self.dd['design']['zlug'] = (2/3)*self.dd['design']['L'] 
+        results = self.getAnchorCapacity(loads=input_loads,plot=plot)            
+            
+        # # check if anchor loads are available
+        # if not self.loads:
+        #     # if not, check if theres a moorpy anchor object and calculate loads from that
+        #     if self.mpAnchor:
+        #         print("Need anchor loads to obtain cost, using getMPForces to determine loads in MoorPy")
+        #         self.getLugForces()
+        #     elif self.ms:
+        #         print('Need anchor loads to obtain cost, creating a MoorPy anchor object and using getMPForces to determine loads in MoorPy')
+        #         self.makeMoorPyAnchor(self.ms)
+        #         self.getLugForces()
+        #     else:
+        #         raise Exception("Need anchor loads to obtain cost")
+        # # check again if there are loads
+        # if self.loads:
+        #     c = self.dd['cost'] # set location for clarity
+        #     # calculate individual costs and total cost for the anchor
+        #     c['matCost'], c['instCost'], c['decomCost'] = mp.Point.getcost(self.mpAnchor)
+        #     c['totCost'] = c['matCost'] + c['instCost'] + c['decomCost']
+
+    
+    # def getMass(self,uhc_mode):
+    #     '''find mass and/or UHC of anchor from MoorProps and store in design dictionary
+    #     Parameters
+    #     ----------
+    #     uhc_mode : boolean
+    #         True : obtain UHC from mass
+    #         False : obtain Masss and UHC from loads
+    #     '''
+    #     if uhc_mode: # if looking for UHC given mass
+    #         if self.dd['design']['m']: # check anchor mass is given
+    #             self.dd['design']['UHC'], self.dd['design']['m'], info = mp.MoorProps.getAnchorMass(uhc_mode=1, mass_int=self.dd['design']['m'], anchor=self.dd['type'], soil_type=self.anchorProps['soil_type'])
+    #         else:
+    #             raise Exception("Need anchor mass to calculate UHC when uhc_mode = 1")
+    #     else: # if looking for mass and UHC given loads
+    #         if self.loads: # check the loads section exists
+    #             self.dd['design']['UHC'], self.dd['design']['m'], info = mp.MoorProps.getAnchorMass(uhc_mode=0, fx=self.loads['ff'], fz=self.loads['fz'], anchor=self.dd['type'],soil_type=self.dd['soil_type'],method=self.loads['method'])
+    #         elif self.mpAnchor:
+    #             print("Need anchor loads to obtain mass, using getMPForces to determine loads in MoorPy")
+    #             self.getLugForces()
+    #             self.dd['design']['UHC'], self.dd['design']['m'], info = mp.MoorProps.getAnchorMass(uhc_mode=0, fx=self.loads['ff'], fz=self.loads['fz'], anchor=self.dd['type'],soil_type=self.dd['soil_type'],method=self.loads['method'])
+    #         elif self.ms:
+    #             print('Need anchor loads to obtain mass, creating a MoorPy anchor object and using getMPForces to determine loads in MoorPy')
+    #             self.makeMoorPyAnchor(self.ms)
+    #             self.getLugForces()
+    #             self.dd['design']['UHC'], self.dd['design']['m'], info = mp.MoorProps.getAnchorMass(uhc_mode=0, fx=self.loads['ff'], fz=self.loads['fz'], anchor=self.dd['type'],soil_type=self.dd['soil_type'],method=self.loads['method'])
+    #         else:
+    #             raise Exception("Need anchor loads to obtain mass")
\ No newline at end of file
diff --git a/famodel/anchors/anchor_map.py b/famodel/anchors/anchor_map.py
deleted file mode 100644
index 525d569f..00000000
--- a/famodel/anchors/anchor_map.py
+++ /dev/null
@@ -1,889 +0,0 @@
-"""Anchor class for FAModel, containing information and key methods for anchors of mooring lines
-    Work in progress
-"""
-import moorpy as mp
-import numpy as np
-from scipy.optimize import minimize
-from famodel.famodel_base import Node
-from famodel.mooring.mooring import Mooring
-import famodel.platform.platform 
-import matplotlib.pyplot as plt
-
-class Anchor(Node):
-    
-    def __init__(self, dd=None, ms=None, r=[0,0,0], aNum=None, id=None,
-                 g=9.81, rho=1025, profile_map=None):
-        '''
-        Initialize an Anchor object.
-
-        Parameters
-        ----------
-        dd : dict
-            Design dictionary containing all information on the anchor.
-        ms : MoorPy system object
-            MoorPy system instance.
-        r : list of float
-            Anchor position coordinates (x, y, z) (m)
-        aNum : int, optional
-            Index in anchor list.
-        id : str or int, optional
-            Unique anchor identifier.
-        g : float, optional
-            Gravity.
-        rho : float, optional
-            Water density.
-        profile_map : list of dict, optional
-            Full soil profile map for selecting local soil layers.
-        '''
-
-        from famodel.famodel_base import Node
-        Node.__init__(self, id)
-
-        self.dd = dd
-        self.ms = ms
-        self.r = r
-        self.aNum = aNum
-        self.g = g
-        self.rho = rho
-
-        self.anchType = dd.get('type') if dd else None
-        self.soil_type = None
-        self.soil_profile = None
-        self.profile_name = None
-        self.soil_type_list = []
-
-        self.mpAnchor = None
-        self.capacity_format = None
-        self.mass = dd.get('design', {}).get('mass', None) if dd else None
-
-        self.anchorCapacity = {}
-        self.cost = {}
-        self.loads = {}
-        self.soilProps = {}
-        self.failure_probability = {}
-        self.env_impact = {}
-
-        # --- Assign soil profile if map is provided ---
-        if profile_map is not None:
-            self.setSoilProfile(profile_map)
-
-    def setSoilProfile(self, profile_map):
-        '''
-        Assign a bilinearly interpolated soil profile from the 4 nearest CPTs.
-    
-        Parameters
-        ----------
-        profile_map : list of dict
-            Each CPT must have keys: 'x', 'y', and 'layers'
-    
-        Returns
-        -------
-        None
-        '''
-        import numpy as np
-    
-        x_anchor, y_anchor = self.r[0], self.r[1]
-    
-        # Sort all CPTs by distance
-        distances = [np.hypot(p['x'] - x_anchor, p['y'] - y_anchor) for p in profile_map]
-        idx_sorted = np.argsort(distances)
-        CPTs = [profile_map[i] for i in idx_sorted[:4]]
-       
-        # Extract positions and weights (inverse distance squared)
-        x = np.array([cpt['x'] for cpt in CPTs])
-        y = np.array([cpt['y'] for cpt in CPTs])
-        dx = x - x_anchor
-        dy = y - y_anchor
-        d = np.hypot(dx, dy)
-        w = 1/np.maximum(d, 1e-3)**2
-        w /= np.sum(w)
-    
-        # Interpolate layer-by-layer
-        layers_list = [cpt['layers'] for cpt in CPTs]
-        n_layers = len(layers_list[0])
-        interpolated_layers = []
-    
-        for i in range(n_layers):
-            layer = {'soil_type': layers_list[0][i]['soil_type']}
-            keys = layers_list[0][i].keys()
-    
-            for key in keys:
-                if key == 'soil_type':
-                    continue
-                if all(key in l[i] for l in layers_list):
-                    vals = [l[i][key] for l in layers_list]
-                    layer[key] = np.dot(w, vals)
-    
-            interpolated_layers.append(layer)
-    
-        self.soil_profile = interpolated_layers
-        self.profile_name = f'Interpolated_2D'
-    
-        # Assign soil type
-        soil_types = [layer['soil_type'] for layer in self.soil_profile]
-        self.soil_type_list = list(set(soil_types))
-        self.soil_type = soil_types[0] if len(self.soil_type_list) == 1 else 'mixed'
-    
-        print(f"[Anchor] Assigned interpolated soil profile: {self.profile_name} weighting with soil types {self.soil_type_list}")
-
-    def makeMoorPyAnchor(self, ms):
-        '''
-        Create a MoorPy anchor object in a MoorPy system.
-
-        Parameters
-        ----------
-        ms : MoorPy system instance
-            The MoorPy system to add the anchor to.
-
-        Returns
-        -------
-        ms : MoorPy system instance
-            The updated MoorPy system with the anchor added.
-        '''
-        import moorpy as mp
-
-        # Create anchor as a fixed point in MoorPy system
-        ms.addPoint(1, self.r)
-
-        # Assign this point as mpAnchor in the anchor class instance
-        self.mpAnchor = ms.pointList[-1]
-
-        # Set mass if available
-        if 'mass' in self.dd.get('design', {}):
-            self.mpAnchor.m = self.dd['design']['mass']
-
-        # Set diameter if available
-        if 'd' in self.dd.get('design', {}):
-            self.mpAnchor.d = self.dd['design']['d']
-
-        # Set the point as an anchor entity
-        self.mpAnchor.entity = {'type': 'anchor'}
-        if 'type' in self.dd:
-            self.mpAnchor.entity['anchor_type'] = self.dd['type']
-
-        return ms
-       
-    def getLineProperties(self):
-        '''
-        Retrieve line_type, diameter and unit weight from attached mooring.
-
-        Returns
-        -------
-        line_type : str
-            Type of mooring line ('chain' or 'wire')
-        d : float
-            Nominal diameter (m)
-        w : float
-            Unit weight (N/m)
-        '''
-        for att in self.attachments.values():
-            if isinstance(att['obj'], Mooring):
-                mtype = att['obj'].dd['sections'][0]['type']['material'].lower()
-                if 'chain' not in mtype:
-                    print('No chain below seafloor, setting Ta=Tm (no load transfer).')
-                    return mtype, None, None, True
-                else:
-                    d_nom = att['obj'].dd['sections'][0]['type']['d_nom']
-                    w_nom = att['obj'].dd['sections'][0]['type']['w']
-                    return 'chain', d_nom, w_nom, False
-        raise ValueError('No mooring line attachment found for anchor.')
-
-    def getMudlineForces(self, lines_only=False, seabed=True, xyz=False):
-        '''
-        Find forces on anchor at mudline using the platform.getWatchCircle method or MoorPy Point.getForces method.
-
-        Parameters
-        ----------
-        lines_only : boolean, optional
-            Calculate forces from just mooring lines (True) or not (False). Default is False.
-        seabed : boolean, optional
-            Include effect of seabed pushing up the anchor (True) or not (False). Default is True.
-        xyz : boolean, optional
-            Return forces in x,y,z DOFs (True) or only the enabled DOFs (False). Default is False.
-
-        Returns
-        -------
-        dict
-            Dictionary containing mudline forces.
-        '''
-        loads = self.mpAnchor.getForces(lines_only=lines_only, seabed=seabed, xyz=xyz)
-
-        self.loads = {
-            'Hm': np.sqrt(loads[0]**2 + loads[1]**2),
-            'Vm': loads[2],
-            'thetam': np.degrees(np.arctan2(loads[2], np.sqrt(loads[0]**2 + loads[1]**2))),
-            'method': 'static',
-            'mudline_load_type': 'current_state'
-        }
-
-        return self.loads
-       
-    def getLugForces(self, Hm, Vm, zlug, line_type=None, d=None, w=None, plot=False):
-        '''
-        Calculate the lug forces Ha and Va based on mudline loads using local soil profile.
-
-        Parameters
-        ----------
-        Hm : float
-            Horizontal mudline load (N)
-        Vm : float
-            Vertical mudline load (N)
-        zlug : float
-            Padeye embedment depth (m)
-        line_type : str, optional
-            Type of mooring line ('chain' or 'wire')
-        d : float, optional
-            Mooring line diameter (m)
-        w : float, optional
-            Mooring line unit weight (N/m)
-        plot : bool, optional
-            Whether to plot the load transfer profile
-
-        Returns
-        -------
-        Ha : float
-            Horizontal load at lug (N).
-        Va : float
-            Vertical load at lug (N).
-        '''
-        from famodel.anchors.anchors_famodel_map.capacity_load_map import getTransferLoad
-
-        # Ensure soil profile is available
-        if self.soil_profile is None or self.soil_type is None:
-            raise ValueError("Anchor soil profile or soil type is not assigned. Use setSoilProfile first.")
-
-        soil_profile = self.soil_profile
-        soil_type = self.soil_type
-
-        # Determine mudline depth
-        z0 = soil_profile[0]['top']
-
-        # Load transfer if padeye is embedded
-        if zlug > z0:
-            if line_type is None or d is None or w is None:
-                try:
-                    line_type, d, w = self.getLineProperties()
-                except ValueError:
-                    print('[Warning] No mooring attachment found. Trying anchor-level line properties...')
-                    line_type = getattr(self, 'line_type', None)
-                    d = getattr(self, 'd', None)
-                    w = getattr(self, 'w', None)
-
-                    if any(v is None for v in [line_type, d, w]):
-                        print('[Fallback] Using default chain properties.')
-                        line_type = 'chain'
-                        d = 0.16
-                        w = 5000.0
-
-            layers, loads = getTransferLoad(
-                profile_map=[{'layers': self.soil_profile}],
-                Tm=np.sqrt(Hm**2 + Vm**2),
-                thetam=np.degrees(np.arctan2(Vm, Hm)),
-                zlug=zlug,
-                line_type=line_type,
-                d=d,
-                w=w,
-                plot=plot
-            )
-
-            Ta = loads['Ta']
-            thetaa = loads['thetaa']
-            Ha = Ta*np.cos(np.deg2rad(thetaa))
-            Va = Ta*np.sin(np.deg2rad(thetaa))
-
-        else:
-            Ha = Hm
-            Va = Vm
-
-        return layers, Ha, Va
-
-    def getCapacityAnchor(self, Hm, Vm, zlug, line_type=None, d=None, w=None, plot=False):
-        '''
-        Calculate anchor capacity based on anchor type and local soil profile.
-    
-        Parameters
-        ----------
-        Hm : float
-            Horizontal mudline load (N)
-        Vm : float
-            Vertical mudline load (N)
-        zlug : float
-            Padeye embedment depth (m)
-        line_type : str, optional
-            Type of mooring line ('chain' or 'wire')
-        d : float, optional
-            Mooring line diameter (m)
-        w : float, optional
-            Mooring line unit weight (N/m)
-        plot : bool, optional
-            Whether to plot the load transfer and pile geometry
-    
-        Returns
-        -------
-        results : dict
-            Capacity results dictionary from the selected capacity function.
-        '''
-        from famodel.anchors.anchors_famodel_map.capacity_plate_map import getCapacityPlate
-        from famodel.anchors.anchors_famodel_map.capacity_suction_map import getCapacitySuction
-        from famodel.anchors.anchors_famodel_map.capacity_torpedo_map import getCapacityTorpedo
-        from famodel.anchors.anchors_famodel_map.capacity_helical_map import getCapacityHelical
-        from famodel.anchors.anchors_famodel_map.capacity_driven_map import getCapacityDriven
-        from famodel.anchors.anchors_famodel_map.capacity_dandg_map import getCapacityDandG
-        from famodel.anchors.anchors_famodel_map.capacity_load_map import getTransferLoad
-        from famodel.anchors.anchors_famodel_map.capacity_plots_map import plot_load
-        # import numpy as np
-    
-        capacity_dispatch = {
-            'suction': getCapacitySuction,
-            'sepla': getCapacityPlate,
-            'dea': getCapacityPlate,
-            'depla': getCapacityPlate,
-            'vla': getCapacityPlate,
-            'plate': getCapacityPlate,
-            'torpedo': getCapacityTorpedo,
-            'helical': getCapacityHelical,
-            'driven': getCapacityDriven,
-            'dandg': getCapacityDandG
-        }
-    
-        anchType_clean = self.anchType.lower().replace(' ', '')
-        capacity_func = capacity_dispatch.get(anchType_clean)
-        if capacity_func is None:
-            raise ValueError(f"Unknown anchor type '{self.anchType}' for anchor capacity calculation.")
-    
-        if self.soil_profile is None or self.soil_type is None:
-            raise ValueError("Soil profile or soil type not set for this anchor.")
-    
-        soil_profile = self.soil_profile
-        soil_type = self.soil_type
-        z0 = soil_profile[0]['top']
-    
-        # Load transfer if padeye is embedded below mudline
-        if zlug > z0:
-            if line_type is None or d is None or w is None:
-                try:
-                    line_type, d, w = self.getLineProperties()
-                except ValueError:
-                    print('[Warning] No mooring attachment found. Trying anchor-level line properties...')
-                    line_type = getattr(self, 'line_type', None)
-                    d = getattr(self, 'd', None)
-                    w = getattr(self, 'w', None)
-    
-                    if any(v is None for v in [line_type, d, w]):
-                        print('[Fallback] Using default chain properties.')
-                        line_type = 'chain'
-                        d = 0.16
-                        w = 5000.0
-    
-            else:
-                layers, resultsLoad = getTransferLoad(
-                    profile_map=[{'layers': soil_profile}],
-                    Tm=np.sqrt(Hm**2 + Vm**2),
-                    thetam=np.degrees(np.arctan2(Vm, Hm)),
-                    zlug=zlug,
-                    line_type=line_type,
-                    d=d,
-                    w=w,
-                    plot=False
-                )
-                if plot:
-                    plot_load(
-                        layers,
-                        resultsLoad['drag_values'],
-                        resultsLoad['depth_values'],
-                        resultsLoad['Tm'],
-                        resultsLoad['thetam'],
-                        resultsLoad['Ta'],
-                        resultsLoad['thetaa'],
-                        zlug=zlug
-                    )
-    
-                Ta = resultsLoad['Ta']
-                thetaa = resultsLoad['thetaa']
-                Ha = Ta*np.cos(np.deg2rad(thetaa))
-                Va = Ta*np.sin(np.deg2rad(thetaa))
-                
-                print(f'Input Hm = {Hm}, Vm = {Vm}, zlug = {zlug}')
-                print(f'Input Ha = {Ha}, Va = {Va}, zlug = {zlug}')
-                print(f'Input Ta = {Ta}, thetaa = {(thetaa)}')
-        else:
-            Ha = Hm
-            Va = Vm
-    
-        # --- Call the appropriate capacity function ---
-        if anchType_clean in ['sepla', 'dea', 'depla', 'vla', 'plate']:
-            self.capacity_format = 'plate'
-            B = self.dd['design']['B']
-            L = self.dd['design']['L']
-            beta = self.dd['design'].get('beta', 0.0)
-            layers, results = capacity_func(
-                profile_map=[{'name': self.profile_name, 'layers': self.soil_profile}],
-                location_name=self.profile_name,
-                B=B, L=L, zlug=zlug,
-                beta=beta,
-                Ha=Ha, Va=Va,
-                plot=plot
-            )
-            
-        elif anchType_clean == 'suction':
-            self.capacity_format = 'envelope'
-            D = self.dd['design']['D']
-            L = self.dd['design']['L']
-            zlug = self.dd['design']['zlug']
-            layers, results = capacity_func(
-                profile_map=[{'name': self.profile_name, 'layers': self.soil_profile}],
-                location_name=self.profile_name,
-                D=D, L=L, zlug=zlug,
-                Ha=Ha, Va=Va,
-                thetalug=5, psilug=7.5,
-                plot=plot
-            )
-            
-        elif anchType_clean == 'torpedo':
-            self.capacity_format = 'envelope'
-            D1 = self.dd['design']['D1']
-            D2 = self.dd['design']['D2']
-            L1 = self.dd['design']['L1']
-            L2 = self.dd['design']['L2']
-            ballast = self.dd['design'].get('ballast', 0.0)
-            layers, results = capacity_func(
-                profile_map=[{'name': self.profile_name, 'layers': self.soil_profile}],
-                location_name=self.profile_name,
-                D1=D1, D2=D2, L1=L1, L2=L2,
-                zlug=zlug,
-                ballast=ballast,
-                Ha=Ha, Va=Va,
-                plot=plot
-            )
-
-        elif anchType_clean == 'helical':
-            self.capacity_format = 'component'
-            D = self.dd['design']['D']     
-            L = self.dd['design']['L']     
-            d = self.dd['design']['d']     
-            zlug = self.dd['design']['zlug']
-            layers, results = capacity_func(
-                profile_map=[{'name': self.profile_name, 'layers': self.soil_profile}],
-                location_name=self.profile_name,
-                D=D, L=L, d=d,
-                zlug=zlug,
-                Ha=Ha, Va=Va,
-                plot=plot
-            )
-
-        elif anchType_clean in ['driven', 'dandg']:
-            self.capacity_format = 'component'
-            L = self.dd['design']['L']
-            D = self.dd['design']['D']
-            zlug = self.dd['design']['zlug']
-            layers, y, z, results = capacity_func(
-                profile_map=[{'name': self.profile_name, 'layers': self.soil_profile}],
-                location_name=self.profile_name,
-                L=L, D=D, zlug=zlug,
-                Ha=Ha, Va=Va,
-                plot=plot
-            )
-    
-        else:
-            raise ValueError(f"Anchor type '{self.anchType}' not supported.")
-    
-        # --- Store results ---
-        self.capacity_results = {
-            'Hmax': results.get('Horizontal max.', np.nan),
-            'Vmax': results.get('Vertical max.', np.nan),
-            'UC': results.get('Unity check', np.nan),
-            'Ha': Ha,
-            'Va': Va,
-            'zlug': zlug,
-            'z0': z0
-        }
-    
-        if 'Weight pile' in results:
-            self.capacity_results['Weight pile'] = results['Weight pile']
-        if 'Weight plate' in results:
-            self.capacity_results['Weight plate'] = results['Weight plate']
-    
-        if anchType_clean in ['driven', 'dandg']:
-            self.capacity_results['Lateral displacement'] = results.get('Lateral displacement', np.nan)
-            self.capacity_results['Rotational displacement'] = results.get('Rotational displacement', np.nan)
-    
-        return results
-                   
-    def getSafetyFactor(self):
-        '''
-        Calculate the safety factor based on the unity checks stored in capacity results.
-
-        Returns
-        -------
-        dict
-            Dictionary containing safety factors.
-        '''
-        anchType_clean = self.anchType.lower().replace(' ', '')
-
-        if anchType_clean in ['helical', 'driven', 'dandg']:
-            UC_v = self.capacity_results.get('Unity check (vertical)', None)
-            UC_h = self.capacity_results.get('Unity check (horizontal)', None)
-
-            if UC_v is None or UC_h is None:
-                print("Warning: Vertical or horizontal unity check (UC) not found in capacity results. Returning NaN.")
-                return {'SF_vertical': np.nan, 'SF_horizontal': np.nan}
-
-            SF_v = 1.0/UC_v if UC_v != 0 else np.inf
-            SF_h = 1.0/UC_h if UC_h != 0 else np.inf
-
-            return {'SF_vertical': SF_v, 'SF_horizontal': SF_h}
-
-        else:
-            UC = self.capacity_results.get('UC', None)
-
-            if UC is None:
-                print("Warning: Unity check (UC) not found in capacity results. Returning NaN.")
-                return {'SF_combined': np.nan}
-
-            SF = 1.0/UC if UC != 0 else np.inf
-
-            return {'SF_combined': SF} 
-
-    def getCostAnchor(self, costDict='default'):
-        '''
-        Calculate the cost of the anchor based on material, installation, and decommissioning costs.
-
-        Parameters
-        ----------
-        costDict : str or dict, optional
-            If 'default', uses mean values from Task 49 Design Basis ranges.
-            If dict or yaml path, loads user-defined cost dictionaries.
-
-        Returns
-        -------
-        float
-            Total cost of the anchor.
-        '''
-        if isinstance(costDict, str) and costDict != 'default':
-            import yaml
-            costDict = yaml.load(costDict, Loader=yaml.FullLoader)
-
-        anchType = self.dd['type']
-
-        if costDict == 'default':
-            matCostDict = {
-                'suction_pile': 4.435,
-                'DEA': 5.705,
-                'SEPLA': 5.705,
-                'DEPLA': 5.705,
-                'VLA': 5.705,
-                'torpedo_pile': 5.0,
-                'helical_pile': 6.0,
-                'driven_pile': 4.0,
-                'dandg_pile': 5.5
-            }
-            instCostDict = {
-                'suction_pile': 2.0,
-                'DEA': 1.5,
-                'SEPLA': 1.5,
-                'DEPLA': 1.5,
-                'VLA': 1.5,
-                'torpedo_pile': 2.5,
-                'helical_pile': 3.0,
-                'driven_pile': 2.0,
-                'dandg_pile': 2.2
-            }
-            decomCostDict = {
-                'suction_pile': 1.0,
-                'DEA': 0.8,
-                'SEPLA': 0.8,
-                'DEPLA': 0.8,
-                'VLA': 0.8,
-                'torpedo_pile': 1.2,
-                'helical_pile': 1.5,
-                'driven_pile': 1.0,
-                'dandg_pile': 1.1
-            }
-        else:
-            matCostDict = costDict.get('material', {})
-            instCostDict = costDict.get('install', {})
-            decomCostDict = costDict.get('decom', {})
-
-        keyFail = True
-
-        # Ensure mass is available
-        if self.mass is None or self.mass == 0:
-            # Try to extract from capacity_results if already available
-            if 'Weight pile' in self.capacity_results:
-                self.mass = self.capacity_results['Weight pile']/self.g
-            elif 'Weight plate' in self.capacity_results:
-                self.mass = self.capacity_results['Weight plate']/self.g
-            else:
-                # If capacity_results missing, attempt to calculate capacity to retrieve weight
-                if 'soil_properties' in self.dd:
-                    self.getAnchorCapacity(plot=False)
-                    if 'Weight pile' in self.capacity_results:
-                        self.mass = self.capacity_results['Weight pile']/self.g
-                    elif 'Weight plate' in self.capacity_results:
-                        self.mass = self.capacity_results['Weight plate']/self.g
-                    else:
-                        print('Warning: Weight not found after capacity calculation, setting mass to 0.')
-                        self.mass = 0
-                else:
-                    print('Soil properties needed to calculate anchor mass for cost. Setting mass to 0.')
-                    self.mass = 0
-
-        # Calculate material cost based on mass
-        if anchType in matCostDict:
-            self.cost['Material Cost'] = matCostDict[anchType]*self.mass
-            keyFail = False
-        else:
-            raise KeyError(f'Anchor type {anchType} not found in material cost dictionary.')
-
-        # Install and decom costs if available
-        self.cost['Installation Cost'] = instCostDict.get(anchType, 0.0)
-        self.cost['Decommissioning Cost'] = decomCostDict.get(anchType, 0.0)
-
-        # Total cost
-        self.cost['Total Cost'] = (self.cost['Material Cost'] +
-                                   self.cost['Installation Cost'] +
-                                   self.cost['Decommissioning Cost'])
-
-        return sum(self.cost.values())
-        
-    def getSizeAnchor(self, geom, geomKeys, geomBounds=None, loads=None,
-                      minfs={'Ha': 1.6, 'Va': 2.0}, lambdap_con=[4, 8], zlug_fix=False, plot=False):
-        '''
-        Generalized optimization method for all anchor types.
-        '''
-        
-        anchType_clean = self.dd['type'].lower().replace(' ', '')
-        
-        if loads is None:
-            loads = self.loads
-    
-        Hm = loads['Hm']
-        Vm = loads['Vm']
-    
-        line_type = getattr(self, 'line_type', 'chain')
-        d = getattr(self, 'd', 0.16)
-        w = getattr(self, 'w', 5000.0)
-        
-        def update_zlug_if_suction():
-            if anchType_clean == 'suction' and not zlug_fix and 'zlug' not in geomKeys:
-                self.dd['design']['zlug'] = (2/3)*self.dd['design']['L']   
-
-        # --- Stage 1: Safety Optimization to reach UC <= 1 ---
-        def safety_objective(vars):
-            for i, key in enumerate(geomKeys):
-                self.dd['design'][key] = vars[i]
-            update_zlug_if_suction()
-    
-            _, Ha, Va = self.getLugForces(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'], line_type=line_type, d=d, w=w, plot=False)
-            
-            self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'], line_type=line_type, d=d, w=w, plot=False)
-    
-            if self.capacity_format == 'envelope':
-                UC = self.capacity_results.get('UC', 2.0)
-            elif self.capacity_format == 'component':
-                UC = max(
-                    self.capacity_results.get('Unity check (horizontal)', 2.0),
-                    self.capacity_results.get('Unity check (vertical)', 2.0)
-                )
-            elif self.capacity_format == 'plate':
-                UC = self.capacity_results.get('UC', 2.0)
-            else:
-                UC = 2.0
-            return (UC - 1.0)**2
-    
-        minimize(
-            safety_objective,
-            geom,
-            method='COBYLA',
-            bounds=geomBounds if geomBounds else None,
-            options={'rhobeg': 0.02, 'catol': 0.001, 'maxiter': 1500}
-        )
-    
-        # --- Stage 2: Weight Minimization with constraints ---
-        if anchType_clean != 'torpedo':    
-            def weight_objective(vars):
-                for i, key in enumerate(geomKeys):
-                    self.dd['design'][key] = vars[i]
-                update_zlug_if_suction()
-    
-                _, Ha, Va = self.getLugForces(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'], line_type=line_type, d=d, w=w, plot=False)
-        
-                self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'], line_type=line_type, d=d, w=w, plot=False)
-        
-                return self.capacity_results.get('Weight pile',
-                       self.capacity_results.get('Weight plate',
-                       self.capacity_results.get('Weight', 1e9)))
-        
-            def constraint_uc_envelope(vars):
-                return 1.0 - self.capacity_results.get('UC', 2.0)
-        
-            def constraint_uc_component(vars):
-                return 1.0 - max(
-                    self.capacity_results.get('Unity check (horizontal)', 2.0),
-                    self.capacity_results.get('Unity check (vertical)', 2.0)
-                )
-        
-            def constraint_fs_horizontal(vars):
-                return (self.capacity_results.get('Horizontal max.', 0)/self.capacity_results.get('Ha', 1)) - minfs['Ha']
-        
-            def constraint_fs_vertical(vars):
-                return (self.capacity_results.get('Vertical max.', 0)/self.capacity_results.get('Va', 1)) - minfs['Va']
-        
-            def constraint_lambda_min(vars):
-                anchType_clean = self.dd['type'].lower().replace(' ', '')
-                
-                if anchType_clean == 'torpedo':
-                    L = self.dd['design']['L1'] + self.dd['design']['L2']
-                    A_wing = (self.dd['design']['D1'] - self.dd['design']['D2'])*self.dd['design']['L1']
-                    A_shaft = self.dd['design']['D2']*L
-                    D = (A_wing + A_shaft)/L
-                elif anchType_clean in ['driven', 'dandg', 'helical', 'suction']:
-                    L = self.dd['design']['L']
-                    D = self.dd['design']['D']
-                elif anchType_clean in ['plate', 'sepla', 'dea', 'depla', 'vla']:
-                    L = self.dd['design']['L']
-                    D = self.dd['design']['B']  
-                else:
-                    raise ValueError(f'lambda constraints not defined for anchor type: {anchType_clean}')
-                return (L/D) - lambdap_con[0]
-        
-            def constraint_lambda_max(vars):
-                anchType_clean = self.dd['type'].lower().replace(' ', '')
-                
-                if anchType_clean == 'torpedo':
-                    L = self.dd['design']['L1'] + self.dd['design']['L2']
-                    A_wing = (self.dd['design']['D1'] - self.dd['design']['D2'])*self.dd['design']['L1']
-                    A_shaft = self.dd['design']['D2']*L
-                    D = (A_wing + A_shaft)/L
-                elif anchType_clean in ['driven', 'dandg', 'helical', 'suction']:
-                    L = self.dd['design']['L']
-                    D = self.dd['design']['D']
-                elif anchType_clean in ['plate', 'sepla', 'dea', 'depla', 'vla']:
-                    L = self.dd['design']['L']
-                    D = self.dd['design']['B']  # use plate width
-                else:
-                    raise ValueError(f'lambda constraints not defined for anchor type: {anchType_clean}')
-                return lambdap_con[1] - (L/D)
-        
-            if self.capacity_format == 'envelope':
-                constraints = [
-                    {'type': 'ineq', 'fun': constraint_uc_envelope},
-                    {'type': 'ineq', 'fun': constraint_fs_horizontal},
-                    {'type': 'ineq', 'fun': constraint_fs_vertical},
-                    {'type': 'ineq', 'fun': constraint_lambda_min},
-                    {'type': 'ineq', 'fun': constraint_lambda_max},
-                ]
-            elif self.capacity_format == 'component':
-                constraints = [
-                    {'type': 'ineq', 'fun': constraint_uc_component},
-                    {'type': 'ineq', 'fun': constraint_lambda_min},
-                    {'type': 'ineq', 'fun': constraint_lambda_max},
-                ]
-            elif self.capacity_format == 'plate':
-                constraints = [
-                    {'type': 'ineq', 'fun': constraint_uc_envelope}
-                ]
-            else:
-                raise ValueError(f"Unknown capacity_format: {self.capacity_format}")
-        
-            result = minimize(
-                weight_objective,
-                [self.dd['design'][key] for key in geomKeys],
-                method='COBYLA',
-                constraints=constraints,
-                bounds=geomBounds if geomBounds else None,
-                options={'rhobeg': 0.5, 'catol': 0.01, 'maxiter': 100}
-            )
-        
-            endGeom = dict(zip(geomKeys, result.x))
-            print('Optimized geometry:', endGeom)
-            self.dd['design'].update(endGeom)
-        
-            update_zlug_if_suction()
-        
-            self.getCapacityAnchor(Hm=Hm, Vm=Vm, zlug=self.dd['design']['zlug'], line_type=line_type, d=d, w=w, plot=plot)
-        
-            print('\nFinal Optimized Anchor:')
-            print('Design:', self.dd['design'])
-            print('Capacity Results:', self.capacity_results)
-
-
-    def getCombinedPlot(self):
-        '''
-        Create a plot showing the suction pile and the inverse catenary overlay in the same coordinate system.
-        '''
-        from famodel.anchors.anchors_famodel_map.capacity_load_map import getTransferLoad
-        from famodel.anchors.anchors_famodel_map.capacity_plots_map import plot_suction
-
-        if self.anchType.lower() != 'suction':
-            raise NotImplementedError("getCombinedPlot only supports suction piles.")
-
-        # Extract design inputs
-        design = self.dd['design']
-        D = design['D']
-        L = design['L']
-        zlug = design['zlug']
-
-        if self.soil_profile is None or self.soil_type is None:
-            raise ValueError("Soil profile or type not assigned. Use setSoilProfile first.")
-
-        soil_profile = self.soil_profile
-        soil_type = self.soil_type
-        z0 = soil_profile[0]['top']
-
-        Hm = self.loads['Hm']
-        Vm = self.loads['Vm']
-        thetam = self.loads.get('thetam', np.degrees(np.arctan2(Vm, Hm)))
-
-        line_type = getattr(self, 'line_type', 'chain')
-        d = getattr(self, 'd', 0.16)
-        w = getattr(self, 'w', 5000.0)
-
-        # Get inverse catenary path
-        layers, result = getTransferLoad(
-            profile_map=[{'layers': self.soil_profile}],
-            Tm=np.sqrt(Hm**2 + Vm**2),
-            thetam=thetam,
-            zlug=zlug,
-            line_type=line_type,
-            d=d,
-            w=w,
-            plot=False
-        )
-
-        drag_values  = np.array(result['drag_values'])
-        depth_values = -np.array(result['depth_values'])[::-1]
-
-        x_start = D/2 + drag_values[0]
-        z_start = zlug
-        drag_transformed  = x_start - drag_values
-        depth_transformed = z_start + (depth_values- depth_values[0])
-
-        # Plot suction pile
-        plot_suction(soil_profile, L, D, z0=z0, zlug=zlug, title='Suction Pile and Mooring Line Load Path')
-
-
-        # Overlay inverse catenary path
-        plt.plot(drag_transformed, depth_transformed, color='b', lw=2.0, label='Inverse catenary')
-        plt.plot(drag_transformed[-1], depth_transformed[-1], 'ro', label='Mudline end')
-        plt.plot( drag_transformed[0],  depth_transformed[0], 'go', label='Embedded end')
-
-        n = 2e6
-        Tm = result['Tm']
-        Ta = result['Ta']
-        thetaa = result['thetaa']
-
-        plt.arrow(drag_transformed[-1], depth_transformed[-1],
-                  Tm*np.cos(np.deg2rad(thetam))/n, -Tm*np.sin(np.deg2rad(thetam))/n,
-                  head_width=0.25, head_length=0.5, color='r', label='Mudline load')
-    
-        plt.arrow(drag_transformed[0], depth_transformed[0],
-                  Ta*np.cos(np.deg2rad(thetaa))/n, -Ta*np.sin(np.deg2rad(thetaa))/n,
-                  head_width=0.25, head_length=0.5, color='g', label='Padeye load')
-
-        xmax = max(drag_transformed[-1] + D, 2*D)
-        plt.xlim(-D, xmax)
-        plt.legend()
-        plt.grid(True)
-        plt.tight_layout()
-        plt.show()
diff --git a/famodel/anchors/anchor_profile.py b/famodel/anchors/anchor_profile.py
deleted file mode 100644
index 611c5b0a..00000000
--- a/famodel/anchors/anchor_profile.py
+++ /dev/null
@@ -1,915 +0,0 @@
-"""Anchor class for FAModel, containing information and key methods for anchors of mooring lines
-    Work in progress
-"""
-import moorpy as mp
-import numpy as np
-from scipy.optimize import minimize
-from famodel.famodel_base import Node
-from famodel.mooring.mooring import Mooring
-import famodel.platform.platform 
-
-class Anchor(Node):
-    
-    def __init__(self, dd=None, ms=None, r=[0,0,0], aNum=None, id=None, g=9.81, rho=1025):
-        '''
-        Initialize an Anchor object.
-
-        Parameters
-        ----------
-        dd : dict
-            Design dictionary containing all information on the anchor:
-            {
-                type : str
-                    Anchor type ('plate', 'suction_pile', 'torpedo_pile', 'helical_pile', 'driven_pile', 'dandg_pile')
-                design : dict
-                    Geometric properties (e.g., A, D, D1, D2, d, L, L1, L2, zlug, beta)
-                cost : dict
-                    Cost breakdown (matCost, instCost, decomCost)
-            }
-        ms : MoorPy system object
-            The MoorPy system instance the anchor is added to.
-        r : list of float
-            Location of the anchor in (x, y, z) coordinates (m).
-        aNum : int, optional
-            Entry number for anchor within the project anchorList dictionary.
-        id : str or int, optional
-            Unique identifier for the anchor object.
-        g : float, optional
-            Gravitational acceleration (m/s²). Default is 9.81.
-        rho : float, optional
-            Water density (kg/m³). Default is 1025.
-        '''
-
-        from famodel.famodel_base import Node
-        Node.__init__(self, id)
-
-        self.dd = dd
-        self.ms = ms
-        self.r = r
-        self.aNum = aNum
-        self.g = g
-        self.rho = rho
-
-        # Initialize anchor type and soil type
-        self.anchType = dd.get('type') if dd else None
-        self.soil_type = None
-
-        # Initialize MoorPy anchor object
-        self.mpAnchor = None
-
-        # Extract mass if available
-        self.mass = dd.get('design', {}).get('mass', None) if dd else None
-
-        # Initialize other dictionaries
-        self.anchorCapacity = {}
-        self.cost = {}
-        self.loads = {}
-        self.soilProps = {}
-        self.failure_probability = {}
-        self.env_impact = {}
-        
-    def makeMoorPyAnchor(self, ms):
-        '''
-        Create a MoorPy anchor object in a MoorPy system.
-
-        Parameters
-        ----------
-        ms : MoorPy system instance
-            The MoorPy system to add the anchor to.
-
-        Returns
-        -------
-        ms : MoorPy system instance
-            The updated MoorPy system with the anchor added.
-        '''
-        import moorpy as mp
-
-        # Create anchor as a fixed point in MoorPy system
-        ms.addPoint(1, self.r)
-
-        # Assign this point as mpAnchor in the anchor class instance
-        self.mpAnchor = ms.pointList[-1]
-
-        # Set mass if available
-        if 'mass' in self.dd.get('design', {}):
-            self.mpAnchor.m = self.dd['design']['mass']
-
-        # Set diameter if available
-        if 'd' in self.dd.get('design', {}):
-            self.mpAnchor.d = self.dd['design']['d']
-
-        # Set the point as an anchor entity
-        self.mpAnchor.entity = {'type': 'anchor'}
-        if 'type' in self.dd:
-            self.mpAnchor.entity['anchor_type'] = self.dd['type']
-
-        return ms
-       
-    def getLineProperties(self):
-        '''
-        Retrieve line_type, diameter and unit weight from attached mooring.
-
-        Returns
-        -------
-        line_type : str
-            Type of mooring line ('chain' or 'wire').
-        d : float
-            Nominal diameter (m).
-        w : float
-            Unit weight (N/m).
-        nolugload : bool
-            True if no lug load transfer should be applied.
-        '''
-        for att in self.attachments.values():
-            if isinstance(att['obj'], Mooring):
-                mtype = att['obj'].dd['sections'][0]['type']['material'].lower()
-                if 'chain' not in mtype:
-                    print('No chain on seafloor, setting Ta=Tm (no load transfer).')
-                    return mtype, None, None, True
-                else:
-                    d_nom = att['obj'].dd['sections'][0]['type']['d_nom']
-                    w_nom = att['obj'].dd['sections'][0]['type']['w']
-                    return 'chain', d_nom, w_nom, False
-        raise ValueError('No mooring line attachment found for anchor.')
-
-    def getMudlineForces(self, lines_only=False, seabed=True, xyz=False):
-        '''
-        Find forces on anchor at mudline using the platform.getWatchCircle method or MoorPy Point.getForces method.
-
-        Parameters
-        ----------
-        lines_only : boolean, optional
-            Calculate forces from just mooring lines (True) or not (False). Default is False.
-        seabed : boolean, optional
-            Include effect of seabed pushing up the anchor (True) or not (False). Default is True.
-        xyz : boolean, optional
-            Return forces in x,y,z DOFs (True) or only the enabled DOFs (False). Default is False.
-
-        Returns
-        -------
-        dict
-            Dictionary containing mudline forces.
-        '''
-        loads = self.mpAnchor.getForces(lines_only=lines_only, seabed=seabed, xyz=xyz)
-
-        self.loads = {
-            'Hm': np.sqrt(loads[0]**2 + loads[1]**2),
-            'Vm': loads[2],
-            'thetam': np.degrees(np.arctan2(loads[2], np.sqrt(loads[0]**2 + loads[1]**2))),
-            'method': 'static',
-            'mudline_load_type': 'current_state'
-        }
-
-        return self.loads
-       
-    def getLugForces(self, ground_conds, Hm, Vm, thetam, zlug, line_type=None, d=None, w=None, plot=False):
-        '''
-        Calculate the lug forces Ha and Va based on mudline loads.
-
-        Parameters
-        ----------
-        ground_conds : dict
-            Dictionary of ground conditions where keys are soil types.
-        Hm : float
-            Horizontal mudline load (N).
-        Vm : float
-            Vertical mudline load (N).
-        thetam : float
-            Mudline load angle (deg).
-        zlug : float
-            Padeye embedment depth (m).
-        line_type : str, optional
-            Type of mooring line ('chain' or 'wire').
-        d : float, optional
-            Mooring line diameter (m).
-        w : float, optional
-            Mooring line unit weight (N/m).
-        plot : bool, optional
-            Whether to plot the load transfer profile.
-
-        Returns
-        -------
-        Ha : float
-            Horizontal load at lug (N).
-        Va : float
-            Vertical load at lug (N).
-        '''
-        from famodel.anchors.anchors_famodel_profile.capacity_load import getTransferLoad
-
-        if self.soil_type is None:
-            self.soil_type = self.dd.get('design', {}).get('soil_type')
-        
-        soil_profile = self.dd.get('soil_properties', {}).get(self.soil_type)
-
-        # Determine mudline depth
-        z0 = soil_profile[0][0]
-
-        # Load transfer if padeye is embedded
-        if zlug > z0:
-            # Fallback mechanism for line properties
-            if line_type is None or d is None or w is None:
-                try:
-                    line_type, d, w, _ = self.getLineProperties()
-                except ValueError:
-                    print('[Warning] No mooring attachment found. Trying anchor-level line properties...')
-                    line_type = getattr(self, 'line_type', None)
-                    d = getattr(self, 'd', None)
-                    w = getattr(self, 'w', None)
-        
-                    if any(v is None for v in [line_type, d, w]):
-                        print('[Fallback] Using default chain properties.')
-                        line_type = 'chain'
-                        d = 0.16
-                        w = 5000.0
-        
-            loads = getTransferLoad(
-                soil_profile, self.soil_type, np.sqrt(Hm**2 + Vm**2),
-                thetam, zlug, line_type, d, w, plot=plot
-            )
-            Ta = loads['Ta']
-            thetaa = loads['thetaa']
-            Ha = Ta*np.cos(thetaa)
-            Va = Ta*np.sin(thetaa)
-        
-        else:
-            Ha = Hm
-            Va = Vm
-        
-        return Ha, Va
-
-
-    def getCapacityAnchor(self, ground_conds, Hm, Vm, thetam, zlug, line_type=None, d=None, w=None, plot=False):
-        '''
-        Calculate anchor capacity based on anchor type and ground conditions.
-
-        Parameters
-        ----------
-        ground_conds : dict
-            Dictionary of ground conditions where keys are soil types.
-        Hm : float
-            Horizontal mudline load (N).
-        Vm : float
-            Vertical mudline load (N).
-        thetam : float
-            Mudline load angle (deg).
-        zlug : float
-            Padeye embedment depth (m).
-        line_type : str, optional
-            Type of mooring line ('chain' or 'wire').
-        d : float, optional
-            Mooring line diameter (m).
-        w : float, optional
-            Mooring line unit weight (N/m).
-        plot : bool, optional
-            Whether to plot the results.
-
-        Returns
-        -------
-        None
-            Updates anchor object with capacity results.
-        '''
-        from famodel.anchors.anchors_famodel_profile.capacity_plate import getCapacityPlate
-        from famodel.anchors.anchors_famodel_profile.capacity_suction import getCapacitySuction
-        from famodel.anchors.anchors_famodel_profile.capacity_torpedo import getCapacityTorpedo
-        from famodel.anchors.anchors_famodel_profile.capacity_helical import getCapacityHelical
-        from famodel.anchors.anchors_famodel_profile.capacity_driven import getCapacityDriven
-        from famodel.anchors.anchors_famodel_profile.capacity_dandg import getCapacityDandG
-        from famodel.anchors.anchors_famodel_profile.capacity_load import getTransferLoad
-        import numpy as np
-
-        # --- Dispatch dictionary ---
-        capacity_dispatch = {
-            'suction': getCapacitySuction,
-            'sepla': getCapacityPlate,
-            'dea': getCapacityPlate,
-            'depla': getCapacityPlate,
-            'vla': getCapacityPlate,
-            'plate': getCapacityPlate,
-            'torpedo': getCapacityTorpedo,
-            'helical': getCapacityHelical,
-            'driven': getCapacityDriven,
-            'dandg': getCapacityDandG
-        }
-
-        # Normalize anchor type
-        anchType_clean = self.anchType.lower().replace(' ', '')
-
-        # Find function
-        capacity_func = capacity_dispatch.get(anchType_clean)
-        if capacity_func is None:
-            raise ValueError(f"Unknown anchor type '{self.anchType}' for anchor capacity calculation.")
-
-        # Get ground conditions
-        soil_profile = ground_conds.get(self.soil_type)
-        if soil_profile is None:
-            raise ValueError(f"Ground condition '{self.soil_type}' not found in provided ground_conds.")
-
-        # Determine if load transfer is needed
-        z0 = soil_profile[0][0]
-        
-        # Load transfer if padeye is embedded
-        if zlug > z0:
-            if line_type is None or d is None or w is None:
-                try:
-                    line_type, d, w, nolugload = self.getLineProperties()
-                except ValueError:
-                    print('[Warning] No mooring attachment found. Trying anchor-level line properties...')
-                    line_type = getattr(self, 'line_type', None)
-                    d = getattr(self, 'd', None)
-                    w = getattr(self, 'w', None)
-                    nolugload = False
-                
-                    if line_type is None or d is None or w is None:
-                        print('[Fallback] Using default chain properties.')
-                        line_type = 'chain'
-                        d = 0.16
-                        w = 5000.0
-
-                if nolugload:
-                    Ha, Va = Hm, Vm
-                else:
-                    loads = getTransferLoad(soil_profile, self.soil_type, Tm=np.sqrt(Hm**2 + Vm**2), thetam=thetam, zlug=zlug, line_type=line_type, d=d, w=w, plot=plot)
-                    Ta = loads['Ta']
-                    thetaa = loads['thetaa']
-                    Ha = Ta*np.cos(thetaa)
-                    Va = Ta*np.sin(thetaa)
-            else:
-                loads = getTransferLoad(soil_profile, self.soil_type, Tm=np.sqrt(Hm**2 + Vm**2), thetam=thetam, zlug=zlug, line_type=line_type, d=d, w=w, plot=plot)
-                Ta = loads['Ta']
-                thetaa = loads['thetaa']
-                Ha = Ta*np.cos(thetaa)
-                Va = Ta*np.sin(thetaa)
-        else:
-            Ha = Hm
-            Va = Vm
-            
-        # Call the capacity function based on anchor type
-        if anchType_clean == 'suction':
-            D = self.dd['design']['D']
-            L = self.dd['design']['L']
-            zlug = self.dd['design']['zlug']
-            
-            results = capacity_func(soil_profile, self.soil_type, D, L, zlug, Ha, Va, plot=plot)
-
-        elif anchType_clean in ['sepla', 'dea', 'depla', 'vla', 'plate']:
-            results = capacity_func(soil_profile, self.soil_type, self.B, self.L, zlug, self.beta, Ha, Va, plot=plot)
-
-        elif anchType_clean == 'torpedo':
-            results = capacity_func(soil_profile, self.soil_type, self.D1, self.D2, self.L1, self.L2, zlug, self.ballast, Ha, Va, plot=plot)
-
-        elif anchType_clean == 'helical':
-            results = capacity_func(soil_profile, self.soil_type, self.D, self.L, self.d, zlug, Ha, Va, plot=plot)
-
-        elif anchType_clean == 'driven':
-            y, z, results = capacity_func(soil_profile, self.soil_type, self.L, self.D, zlug, Ha, Va, plot=plot)
-
-        elif anchType_clean == 'dandg':
-            y, z, results = capacity_func(soil_profile, self.soil_type, self.L, self.D, zlug, Ha, Va, plot=plot)
-
-        else:
-            raise ValueError(f"Anchor type '{self.anchType}' not supported.")
-
-        # --- Standardize and store capacity results ---
-        self.capacity_results = {
-            'Hmax': results.get('Horizontal max.', np.nan),
-            'Vmax': results.get('Vertical max.', np.nan),
-            'UC': results.get('Unity check', np.nan),
-            'Ha': Ha,
-            'Va': Va,
-            'zlug': zlug,
-            'z0': z0
-        }
-
-        # Add mass if weight is available
-        if 'Weight pile' in results:
-            self.capacity_results['Weight pile'] = results['Weight pile']
-        if 'Weight plate' in results:
-            self.capacity_results['Weight plate'] = results['Weight plate']
-
-        # Special cases for displacement-based anchors
-        if anchType_clean in ['driven_pile', 'dandg_pile']:
-            self.capacity_results['Lateral displacement'] = results.get('Lateral displacement', np.nan)
-            self.capacity_results['Rotational displacement'] = results.get('Rotational displacement', np.nan)
-
-        return results
-                    
-    def getSafetyFactor(self):
-        '''
-        Calculate the safety factor based on the unity checks stored in capacity results.
-
-        Returns
-        -------
-        dict
-            Dictionary containing safety factors.
-        '''
-        anchType_clean = self.anchType.lower().replace(' ', '')
-
-        if anchType_clean in ['helical', 'driven', 'dandg']:
-            UCv = self.capacity_results.get('Unity check (vertical)', None)
-            UCh = self.capacity_results.get('Unity check (horizontal)', None)
-
-            if UCv is None or UCh is None:
-                print("Warning: Vertical or Horizontal Unity Check not found in capacity results. Returning NaN.")
-                return {'SF_vertical': np.nan, 'SF_horizontal': np.nan}
-
-            SFv = 1.0/UCv if UCv != 0 else np.inf
-            SFh = 1.0/UCh if UCh != 0 else np.inf
-
-            return {'SF_vertical': SFv, 'SF_horizontal': SFh}
-
-        else:
-            UC = self.capacity_results.get('UC', None)
-
-            if UC is None:
-                print("Warning: Unity Check (UC) not found in capacity results. Returning NaN.")
-                return {'SF_combined': np.nan}
-
-            SF = 1.0/UC if UC != 0 else np.inf
-
-            return {'SF_combined': SF} 
-
-    def getCost(self, costDict='default'):
-        '''
-        Calculate the cost of the anchor based on material, installation, and decommissioning costs.
-
-        Parameters
-        ----------
-        costDict : str or dict, optional
-            If 'default', uses mean values from Task 49 Design Basis ranges.
-            If dict or yaml path, loads user-defined cost dictionaries.
-
-        Returns
-        -------
-        float
-            Total cost of the anchor.
-        '''
-        if isinstance(costDict, str) and costDict != 'default':
-            import yaml
-            costDict = yaml.load(costDict, Loader=yaml.FullLoader)
-
-        anchType = self.dd['type']
-
-        if costDict == 'default':
-            matCostDict = {
-                'suction_pile': 4.435,
-                'DEA': 5.705,
-                'SEPLA': 5.705,
-                'DEPLA': 5.705,
-                'VLA': 5.705,
-                'torpedo_pile': 5.0,
-                'helical_pile': 6.0,
-                'driven_pile': 4.0,
-                'dandg_pile': 5.5
-            }
-            instCostDict = {
-                'suction_pile': 2.0,
-                'DEA': 1.5,
-                'SEPLA': 1.5,
-                'DEPLA': 1.5,
-                'VLA': 1.5,
-                'torpedo_pile': 2.5,
-                'helical_pile': 3.0,
-                'driven_pile': 2.0,
-                'dandg_pile': 2.2
-            }
-            decomCostDict = {
-                'suction_pile': 1.0,
-                'DEA': 0.8,
-                'SEPLA': 0.8,
-                'DEPLA': 0.8,
-                'VLA': 0.8,
-                'torpedo_pile': 1.2,
-                'helical_pile': 1.5,
-                'driven_pile': 1.0,
-                'dandg_pile': 1.1
-            }
-        else:
-            matCostDict = costDict.get('material', {})
-            instCostDict = costDict.get('install', {})
-            decomCostDict = costDict.get('decom', {})
-
-        keyFail = True
-
-        # Ensure mass is available
-        if self.mass is None or self.mass == 0:
-            # Try to extract from capacity_results if already available
-            if 'Weight pile' in self.capacity_results:
-                self.mass = self.capacity_results['Weight pile']/self.g
-            elif 'Weight plate' in self.capacity_results:
-                self.mass = self.capacity_results['Weight plate']/self.g
-            else:
-                # If capacity_results missing, attempt to calculate capacity to retrieve weight
-                if 'soil_properties' in self.dd:
-                    self.getAnchorCapacity(plot=False)
-                    if 'Weight pile' in self.capacity_results:
-                        self.mass = self.capacity_results['Weight pile']/self.g
-                    elif 'Weight plate' in self.capacity_results:
-                        self.mass = self.capacity_results['Weight plate']/self.g
-                    else:
-                        print('Warning: Weight not found after capacity calculation, setting mass to 0.')
-                        self.mass = 0
-                else:
-                    print('Soil properties needed to calculate anchor mass for cost. Setting mass to 0.')
-                    self.mass = 0
-
-        # Calculate material cost based on mass
-        if anchType in matCostDict:
-            self.cost['Material Cost'] = matCostDict[anchType]*self.mass
-            keyFail = False
-        else:
-            raise KeyError(f'Anchor type {anchType} not found in material cost dictionary.')
-
-        # Install and decom costs if available
-        self.cost['Installation Cost'] = instCostDict.get(anchType, 0.0)
-        self.cost['Decommissioning Cost'] = decomCostDict.get(anchType, 0.0)
-
-        # Total cost
-        self.cost['Total Cost'] = (self.cost['Material Cost'] +
-                                   self.cost['Installation Cost'] +
-                                   self.cost['Decommissioning Cost'])
-
-        return sum(self.cost.values())
-
-
-    def getSize(self, geom, geomKeys, geomBounds=None, loads=None, minfs={'Ha':1.0,'Va':1.0}, 
-                 lambdap_con=[4,6], zlug_fix=False, FSdiff_max=None, plot=False):
-        '''
-        Resize the anchor dimensions to meet the target safety factor and geometric constraints.
-    
-        Parameters
-        ----------
-        geom : list
-            Starting guess geometry values.
-        geomKeys : list
-            List of keys matching the geom list values (e.g., 'L', 'D', 'zlug').
-        geomBounds : list, optional
-            List of tuples of upper and lower bounds for each geometry value.
-        loads : dict, optional
-            Dictionary of maximum anchor loads.
-        minfs : dict, optional
-            Minimum factors of safety in horizontal and vertical directions.
-        lambdap_con : list, optional
-            Constraint for L/D parameter as [min, max].
-        zlug_fix : bool, optional
-            Whether zlug should be fixed (True) or updated (False).
-        FSdiff_max : dict, optional
-            Maximum allowable difference between achieved FS and target FS.
-        plot : bool, optional
-            Whether to plot results.
-    
-        Returns
-        -------
-        None
-        '''
-        from scipy.optimize import minimize
-        import numpy as np
-    
-        anchType = self.dd['type']
-    
-        if loads is None:
-            loads = self.loads
-    
-        # Compute thetam internally from Hm and Vm
-        Hm = loads['Hm']
-        Vm = loads['Vm']
-        thetam = np.degrees(np.arctan2(Vm, Hm))
-        zlug = loads['zlug']
-        
-        # Read mooring properties from anchor attributes
-        line_type = self.line_type
-        d = self.d
-        w = self.w
-    
-        Ha, Va = self.getLugForces(
-            ground_conds=self.dd.get('soil_properties'),
-            Hm=Hm,
-            Vm=Vm,
-            thetam=thetam,
-            zlug=zlug,
-            line_type=line_type,
-            d=d,
-            w=w,
-            plot=plot
-        )
-    
-        ground_conds = self.dd.get('soil_properties')
-    
-        input_loads = {'Ha': Ha*minfs['Ha'], 'Va': Va*minfs['Va']}
-    
-        # Objective: minimize weight
-        def objective_(vars, geomKeys, Ha, Va, ground_conds, thetam, zlug, plot):
-            newGeom = dict(zip(geomKeys, vars))
-            self.dd['design'].update(newGeom)
-            if 'suction' in self.dd['type'] and not zlug_fix:
-                self.dd['design']['zlug'] = (2/3)*newGeom['L']
-            results = self.getCapacityAnchor(ground_conds, Ha, Va, thetam, zlug, plot=plot)
-            return results.get('Weight pile', results.get('Weight plate', 1e6))
-    
-        # Constraints
-        def conFun_lambdap_(vars, lambdap_con, geomKeys):
-            newGeom = dict(zip(geomKeys, vars))
-            lambdap = newGeom['L']/newGeom['D']
-            return min(lambdap - lambdap_con[0], lambdap_con[1] - lambdap)
-    
-        def conFun_UC_(vars, Ha, Va, ground_conds, thetam, zlug, plot):
-            results = self.getCapacityAnchor(ground_conds, Ha, Va, thetam, zlug, plot=plot)
-            return results.get('Unity check', 0) - 1
-    
-        def conFun_H_(vars, Ha, Va, ground_conds, thetam, zlug, plot):
-            results = self.getCapacityAnchor(ground_conds, Ha, Va, thetam, zlug, plot=plot)
-            FS = self.getFS()
-            return FS.get('SF_horizontal', FS.get('SF_combined', 0)) - 1
-    
-        def conFun_V_(vars, minfs, Ha, Va, ground_conds, thetam, zlug, plot):
-            results = self.getCapacityAnchor(ground_conds, Ha, Va, thetam, zlug, plot=plot)
-            FS = self.getFS()
-            if minfs['Va'] == 0:
-                return 1
-            return FS.get('SF_vertical', FS.get('SF_combined', 0)) - 1
-    
-        # Initial geometry setup
-        startGeom = dict(zip(geomKeys, geom))
-        self.dd['design'].update(startGeom)
-    
-        if not 'zlug' in self.dd['design']:
-            if 'suction' in anchType and not zlug_fix:
-                self.dd['design']['zlug'] = (2/3)*startGeom['L']
-            else:
-                self.dd['design']['zlug'] = 0
-    
-        if zlug_fix and 'zlug' in geomKeys:
-            zlug_loc = geomKeys.index('zlug')
-            geomKeys.pop(zlug_loc)
-            geom.pop(zlug_loc)
-            if geomBounds:
-                geomBounds.pop(zlug_loc)
-    
-        initial_guess = geom
-    
-        # Setup constraints
-        constraints = []
-    
-        if 'suction' in anchType:
-            constraints.append({'type': 'ineq', 'fun': conFun_lambdap_, 'args': (lambdap_con, geomKeys)})
-    
-        if 'torpedo' in anchType or 'suction' in anchType:
-            constraints.append({'type': 'ineq', 'fun': conFun_UC_, 'args': (Ha, Va, ground_conds, thetam, zlug, plot)})
-        else:
-            constraints.append({'type': 'ineq', 'fun': conFun_H_, 'args': (Ha, Va, ground_conds, thetam, zlug, plot)})
-            constraints.append({'type': 'ineq', 'fun': conFun_V_, 'args': (minfs, Ha, Va, ground_conds, thetam, zlug, plot)})
-    
-        print('Starting optimization of anchor size')
-    
-        if geomBounds is None:
-            solution = minimize(objective_, initial_guess, args=(geomKeys, Ha, Va, ground_conds, thetam, zlug, plot),
-                                 method='COBYLA', constraints=constraints,
-                                 options={'rhobeg': 0.1, 'catol': 0.001})
-        else:
-            solution = minimize(objective_, initial_guess, args=(geomKeys, Ha, Va, ground_conds, thetam, zlug, plot),
-                                 method='COBYLA', constraints=constraints, bounds=geomBounds,
-                                 options={'rhobeg': 0.1, 'catol': 0.001})
-    
-        # Update final geometry
-        endGeom = dict(zip(geomKeys, solution.x))
-        print('Optimized geometry: ', endGeom)
-        self.dd['design'].update(endGeom)
-    
-        if 'suction' in anchType and not zlug_fix:
-            self.dd['design']['zlug'] = (2/3)*self.dd['design']['L']
-            zlug = self.dd['design']['zlug']  # update local zlug
-    
-        self.getCapacityAnchor(ground_conds, Ha, Va, thetam, zlug, plot=plot)
-        
-    def getSizeSuction(self, geom, geomKeys, geomBounds=None, loads=None, minfs={'Ha':1.6,'Va':2}, 
-                 lambdap_con=[4,8], zlug_fix=False, plot=False):
-        '''
-        Two-stage optimization:
-        Stage 1 - Grow anchor to satisfy UC <= 1.
-        Stage 2 - Minimize weight while keeping UC <= 1 and satisfying L/D constraints.
-        '''
-    
-        anchType = self.dd['type']
-    
-        if loads is None:
-            loads = self.loads
-    
-        Hm = loads['Hm']
-        Vm = loads['Vm']
-        zlug = self.dd['design']['zlug']
-        thetam = np.degrees(np.arctan2(Vm, Hm))
-    
-        line_type = self.line_type
-        d = self.d
-        w = self.w
-    
-        initial_guess = [self.dd['design']['L'], self.dd['design']['D']]
-        bounds = geomBounds if geomBounds else [(5.0, 30.0), (2.0, 5.0)]
-
-        ground_conds = self.dd.get('soil_properties')
-    
-        # --- Stage 1: Safety First ---
-        def safety_objective(vars):
-            L, D = vars
-            self.dd['design']['L'] = L
-            self.dd['design']['D'] = D
-            self.dd['design']['zlug'] = (2/3) * L
-    
-            Ha, Va = self.getLugForces(
-                ground_conds=ground_conds,
-                Hm=Hm,
-                Vm=Vm,
-                thetam=thetam,
-                zlug=self.dd['design']['zlug'],
-                line_type=line_type,
-                d=d,
-                w=w,
-                plot=False
-            )
-    
-            self.getCapacityAnchor(
-                ground_conds=ground_conds,
-                Hm=Hm,
-                Vm=Vm,
-                thetam=thetam,
-                zlug=self.dd['design']['zlug'],
-                line_type=line_type,
-                d=d,
-                w=w,
-                plot=False
-            )
-    
-            UC = self.capacity_results.get('UC', 2.0)
-            return max(0.0, UC - 1.0)**2
-    
-        minimize(
-            safety_objective,
-            initial_guess,
-            method='COBYLA',
-            bounds=bounds,
-            options={'rhobeg': 0.1, 'catol': 0.001, 'maxiter': 300}
-        )
-    
-        # --- Stage 2: Weight Minimization ---
-        def weight_objective(vars):
-            L, D = vars
-            self.dd['design']['L'] = L
-            self.dd['design']['D'] = D
-            self.dd['design']['zlug'] = (2/3) * L
-    
-            Ha, Va = self.getLugForces(
-                ground_conds=ground_conds,
-                Hm=Hm,
-                Vm=Vm,
-                thetam=thetam,
-                zlug=self.dd['design']['zlug'],
-                line_type=line_type,
-                d=d,
-                w=w,
-                plot=False
-            )
-    
-            self.getCapacityAnchor(
-                ground_conds=ground_conds,
-                Hm=Hm,
-                Vm=Vm,
-                thetam=thetam,
-                zlug=self.dd['design']['zlug'],
-                line_type=line_type,
-                d=d,
-                w=w,
-                plot=False
-            )
-    
-            return self.capacity_results.get('Weight pile', 1e9)
-    
-        def constraint_uc(vars):
-            L, D = vars
-            return 1.0 - self.capacity_results.get('UC', 2.0)
-        
-        def constraint_fs_horizontal(vars):
-            L, D = vars
-            return (self.capacity_results.get('Hmax', 0) / self.capacity_results.get('Ha', 1)) - minfs['Ha']
-        
-        def constraint_fs_vertical(vars):
-            L, D = vars
-            return (self.capacity_results.get('Vmax', 0) / self.capacity_results.get('Va', 1)) - minfs['Va']
-
-        def constraint_lambda_min(vars):
-            L, D = vars
-            return (L/D) - lambdap_con[0]
-    
-        def constraint_lambda_max(vars):
-            L, D = vars
-            return lambdap_con[1] - (L/D)
-    
-        result = minimize(
-            weight_objective,
-            [self.dd['design']['L'], self.dd['design']['D']],
-            method='COBYLA',
-            constraints=[
-                {'type': 'ineq', 'fun': constraint_fs_horizontal},
-                {'type': 'ineq', 'fun': constraint_fs_vertical},
-                {'type': 'ineq', 'fun': constraint_lambda_min},
-                {'type': 'ineq', 'fun': constraint_lambda_max}
-            ],
-            bounds=bounds,
-            options={'rhobeg': 0.5, 'catol': 0.01, 'maxiter': 100}
-        )
-    
-        # Update final geometry
-        endGeom = dict(zip(geomKeys, result.x))
-        print('Optimized geometry:', endGeom)
-        self.dd['design'].update(endGeom)
-    
-        if 'suction' in anchType and not zlug_fix:
-            self.dd['design']['zlug'] = (2/3) * self.dd['design']['L']
-    
-        self.getCapacityAnchor(
-            ground_conds=ground_conds,
-            Hm=Hm,
-            Vm=Vm,
-            thetam=thetam,
-            zlug=self.dd['design']['zlug'],
-            line_type=line_type,
-            d=d,
-            w=w,
-            plot=plot
-        )
-    
-        print('\nFinal Optimized Anchor:')
-        print('Design:', self.dd['design'])
-        print('Capacity Results:', self.capacity_results)
-
-    def getCombinedPlot(self):
-        '''
-        Create a single plot showing the suction pile and the inverse catenary overlay in the same coordinate system.
-        '''
-        from famodel.anchors.anchors_famodel_profile.capacity_load import getTransferLoad
-        from famodel.anchors.anchors_famodel_profile.capacity_plots import plot_suction
-        import numpy as np
-        import matplotlib.pyplot as plt
-    
-        if self.anchType.lower() != 'suction':
-            raise NotImplementedError("getCombinedPlot only supports suction piles for now.")
-    
-        # Extract key parameters
-        design = self.dd['design']
-        D = design['D']
-        L = design['L']
-        zlug = design['zlug']
-        soil_type = self.soil_type
-        soil_profile = self.dd['soil_properties'][soil_type]
-        z0 = soil_profile[0][0]
-    
-        Hm = self.loads['Hm']
-        Vm = self.loads['Vm']
-        thetam = self.loads.get('thetam', np.degrees(np.arctan2(Vm, Hm)))
-    
-        line_type = getattr(self, 'line_type', 'chain')
-        d = getattr(self, 'd', 0.16)
-        w = getattr(self, 'w', 5000.0)
-    
-        # Get inverse catenary path
-        result = getTransferLoad(
-            soil_profile, soil_type, np.sqrt(Hm**2 + Vm**2), thetam, zlug, line_type, d, w, plot=False
-        )
-        drag_values  = np.array(result['drag_values'])
-        depth_values = np.array(result['depth_values'])
-        depth_values = -depth_values[::-1]
-        Tm = result['Tm']; thetam = result['thetam']
-        Ta = result['Ta']; thetaa = result['thetaa']        
-    
-        # Transform to suction pile coordinate system
-        x_start = D/2 + drag_values[0]
-        z_start = zlug
-        drag_transformed  = x_start - drag_values
-        depth_transformed = z_start + (depth_values - depth_values[0])
-    
-        # Set up plot
-        fig, ax = plt.subplots(figsize=(5, 5))
-    
-        # Plot suction pile
-        plot_suction(soil_profile, soil_type, L, D, zlug=zlug, title='', ax=ax)
-    
-        # Overlay inverse catenary
-        ax.plot(drag_transformed, depth_transformed, color='b', lw=2.0, label='Inverse Catenary')
-    
-        # Annotate ends
-        ax.plot(drag_transformed[-1], depth_transformed[-1], 'ro', label='Mudline End')
-        ax.plot(drag_transformed[0], depth_transformed[0], 'go', label='Embedded End')
-        
-        n = 2e6
-        # Add load vectors
-        ax.arrow(drag_transformed[-1], depth_transformed[-1], Tm*np.cos(np.deg2rad(thetam))/n, -Tm*np.sin(np.deg2rad(thetam))/n,
-                 head_width=0.25, head_length=0.5, color='r', label='Mudline Load')
-        ax.arrow(drag_transformed[0], depth_transformed[0], Ta*np.cos(thetaa)/n, -Ta*np.sin(thetaa)/n,
-                 head_width=0.25, head_length=0.5, color='g', label='Padeye Load')
-    
-        # Finalize plot
-        xmax = max(drag_transformed[-1] + D, 2*D)
-        ax.set_xlim(-D, xmax)
-        ax.set_title('Suction Pile with Inverse Catenary')
-        ax.legend()
-        ax.grid(True)
-        plt.tight_layout()
-        plt.show()
diff --git a/famodel/anchors/anchors_famodel/__init__.py b/famodel/anchors/anchors_famodel/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/famodel/anchors/anchors_famodel/capacity_dandg.py b/famodel/anchors/anchors_famodel/capacity_dandg.py
deleted file mode 100644
index 284c4339..00000000
--- a/famodel/anchors/anchors_famodel/capacity_dandg.py
+++ /dev/null
@@ -1,373 +0,0 @@
-
-import numpy as np
-import matplotlib.pyplot as plt
-from scipy.interpolate import interp1d
-from scipy import linalg
-import inspect
-
-###################################
-#### Pile Geometry and Loading ####
-###################################
-
-def getCapacityDandG(profile, L, D, zlug, V, H, plot=True):
-    '''
-    Models a laterally loaded pile using the p-y method. The solution for
-    lateral displacements is obtained by solving the 4th order ODE, 
-    EI*d4y/dz4 - V*d2y/dz2 + ky = 0 using the finite difference method.
-    EI*d4y/dz4 - V*d2y/dz2 + K*z*dy/dz + ky = 0 using the finite difference method.
-
-    Assumes that EI remains constant with respect to curvature i.e. pile
-    material remains in the elastic region.
-
-    Input:
-    -----
-    profile     - A 2D array of depths (m) and corresponding undrained shear strength(Pa)
-                  Eg: array([[z1,UCS1],[z2,UCS2],[z3,UCS3]...])
-                  Use small values for Su (eg: 0.001) instead of zeros to avoid divisions 
-                  by zero but always start z at 0.0
-                  Example of a valid data point at the mudline is [0.0, 0.001]
-    L           - Length of pile (m)
-    D           - Outer diameter of pile (m)
-    V           - Axial force at pile head (N)
-    H           - Force at pile head (N)
-    M           - Moment at pile head (N*m)
-    n           - Number of elements (50 by default)
-    iterations  - Number of iterations to repeat calculation in order obtain convergence of 'y'
-                  (A better approach is to iterate until a predefined tolerance is achieved)
-
-    Output:
-    ------
-    y           - Lateral displacement at each node, length = n + 5, (n+1) real nodes and 4 imaginary nodes
-    z           - Vector of node locations along pile
-    resultsDandG- Dictionary with results
-    '''
-    
-    # Extract optional keyword arguments
-    # ls = 'x'
-
-    n = 50; iterations = 10; loc = 2
-
-    # Resistance factor
-    nhuc = 1; nhu = 0.3
-    delta_r = 0.08               # Mean roughness height [m]
-    
-    # Convert L and D to floating point numbers to avoid rounding errors
-    L = float(L)
-    D = float(D)
-    t = (6.35 + D*20)/1e3        # Pile wall thickness (m), API RP2A-WSD
-    E = 200e9                    # Elastic modulus of pile material (Pa)
-    rhows = 66.90e3              # Submerged steel specific weight (N/m3)
-    rhow = 10e3                  # Water specific weight (N/m3) 
-    
-    # Pile geometry
-    I = (np.pi/64.0)*(D**4 - (D - 2*t)**4)
-    EI = E*I
-    h = L/n                      # Element size
-    N = (n + 1) + 4              # (n+1) Real + 4 Imaginary nodes
-    
-    # Dry and wet mass of the pile    
-    def PileWeight(Len, Dia, tw, rho):
-        Wp = ((np.pi/4)*(Dia**2 - (Dia - 2*tw)**2)*Len)*rho
-        return Wp 
-
-    # Array for displacements at nodes, including imaginary nodes.
-    y = np.ones(N)*(0.01*D)      # An initial value of 0.01D was arbitrarily chosen
-
-    # Initialize and assemble array/list of p-y curves at each real node
-    z = np.zeros(N)
-    py_funs = []
-    k_secant = np.zeros(N)
-    DQ = []
-
-    for i in [0,1]:              # Top two imaginary nodes
-        z[i] = (i - 2)*h
-        py_funs.append(0)
-        k_secant[i] = 0.0
-   
-    for i in range(2,n+3):       # Real nodes
-        z[i] = (i - 2)*h
-        # Extract rock profile data
-        zlug, f_UCS, f_Em = rock_profile(profile)
-        UCS, Em = f_UCS(z[i]), f_Em(z[i])
-        py_funs.append(py_Reese(z[i], D, zlug, UCS, Em, plot=plot))
-        k_secant[i] = py_funs[i](y[i])/y[i]
-        SCR = nhuc*Em/(UCS*(1 + nhu))*delta_r/D
-        alpha = 0.36*SCR - 0.0005
-        fs = alpha*UCS
-        Dq = np.pi*D*fs*z[i]
-        DQ.append(Dq)
-
-    for i in [n+3, n+4]:         # Bottom two imaginary nodes
-        z[i] = (i - 2)*h
-        py_funs.append(0)
-        k_secant[i] = 0.0
-
-    # Track k_secant and current displacements
-
-    y1 = np.linspace(-2.*D, 2.*D, 500)
-    if plot:
-        plt.plot(y1, py_funs[loc](y1))
-        plt.xlabel('y (m)'), plt.ylabel('p (N/m)')
-        plt.grid(True)
-
-    for j in range(iterations):
-        # if j == 0: print 'FD Solver started!'
-        y = fd_solver(n, N, h, EI, V, H, zlug, k_secant)
-        if plot:
-            plt.plot(y[loc], k_secant[loc]*y[loc])
-
-        for i in range(2, n+3):
-            k_secant[i] = py_funs[i](y[i])/y[i]
-
-    # print(f'y_max = {max(y):.3f} m')
-    # print(f'rot_max = {np.rad2deg((y[2] - y[3])/h):.3f} deg')
-
-    resultsDandG = {}
-    resultsDandG['Lateral displacement'] = y[2]
-    resultsDandG['Rotational displacement'] = np.rad2deg((y[2] - y[3])/h)
-    resultsDandG['Axial capacity'] = DQ[-1]
-    resultsDandG['Weight'] = PileWeight(L, D, t, (rhows + rhow))
-    
-    return y[2:-2], z[2:-2], resultsDandG
-
-#################
-#### Solvers ####
-#################
-
-def fd_solver(n, N, h, EI, V, H, zlug, k_secant):
-    '''
-    Solves the finite difference equations from 'py_analysis_1'. This function should be run iteratively for
-    non-linear p-y curves by updating 'k_secant' using 'y'. A single iteration is sufficient if the p-y curves
-    are linear.
-
-    Input:
-    -----
-    n        - Number of elements
-    N        - Total number of nodes
-    h        - Element size
-    EI       - Flexural rigidity of pile
-    V        - Axial force at pile head
-    H        - Shear at pile head/tip
-    M        - Moment at pile head/tip
-    k_secant - Secant stiffness from p-y curves
-
-    Output:
-    ------
-    y        - Lateral displacement at each node
-    '''
-    M = H*zlug
-    
-    # Initialize and assemble matrix
-    X = np.zeros((N,N))
-
-    # (n+1) finite difference equations for (n+1) real nodes
-    for i in range(0,n+1):
-        X[i,i]   =  1.0
-        X[i,i+1] = -4.0 + V*h**2/EI
-        X[i,i+2] =  6.0 - 2*V*h**2/EI + k_secant[i+2]*h**4/EI
-        X[i,i+3] = -4.0 + V*h**2/EI
-        X[i,i+4] =  1.0
-
-    # Curvature at pile head
-    X[n+1,1] =  1.0
-    X[n+1,2] = -2.0
-    X[n+1,3] =  1.0
-
-    # Shear at pile head
-    X[n+2,0] = -1.0
-    X[n+2,1] =  2.0 - V*h**2/EI
-    X[n+2,2] =  0.0
-    X[n+2,3] = -2.0 + V*h**2/EI
-    X[n+2,4] =  1.0
-
-    # Curvature at pile tip
-    X[n+3,-2] =  1.0
-    X[n+3,-3] = -2.0
-    X[n+3,-4] =  1.0
-
-    # Shear at pile tip
-    X[n+4,-1] =  1.0
-    X[n+4,-2] = -2.0 + V*h**2/EI
-    X[n+4,-3] =  0.0
-    X[n+4,-4] =  2.0 - V*h**2/EI
-    X[n+4,-5] = -1.0
-
-    # Initialize vector q
-    q = np.zeros(N)
-
-    # Populate q with boundary conditions
-    q[-3] = 2*H*h**3      # Shear at pile head
-    # q[-4] = M*h**2        # Moment at pile head
-
-    y = linalg.solve(EI*X, q)
-
-    return y
-
-###############################
-#### P-Y Curve Definitions ####
-###############################
-
-
-def py_Reese(z, D, zlug, UCS, Em, plot=True):
-
-    '''
-    Returns an interp1d interpolation function which represents the Reese (1997) p-y curve at the depth of interest.
-
-    Important: Make sure to import the interp1 function by running 'from scipy.interpolate import interp1d' in the main program.
-
-    Input:
-    -----
-    z      - Depth relative to pile head (m)
-    D      - Pile diameter (m)
-    zlug   - Load eccentricity above the mudline or depth to mudline relative to the pile head (m)
-    UCS    - Undrained shear strength (Pa)
-    Em     - Effectve vertical stress (Pa)
-    RQD    - Rock quality designation, measures the quality of the rock core taken from a borehole.
-             Typically ranges from 25% (very weathered rock) to 100% (fresh rock).
-
-    Output:
-    ------
-    Returns an interp1d interpolation function which represents the p-y curve at the depth of interest.
-    'p' (N/m) and 'y' (m).
-    '''
-    z0 = 0
-    
-    #from scipy.interpolate import interp1d
-    #global var_Reese
-    
-    RQD = 69                     # Assumed good rock quality (hard rock)  
-    Dref = 0.305; nhu = 0.3; E = 200e9
-    t = (6.35 + D*20)/1e3        # Pile wall thickness (m), API RP2A-WSD
-    I  = np.pi*(D**4 - (D - 2*t)**4)/64.0
-    EI = E*I
-    alpha = -0.00667*RQD + 1
-    krm = 0.0005
-    
-    if (z - z0) < 0:
-        p_ur = 0
-    else:
-        if z < 3*D:
-            p_ur = alpha*UCS*D*(1 + 1.4*z/D)
-            #kir = (100 +400*z/(3*D))
-        else:
-            p_ur = 5.2*alpha*UCS*D
-            #kir = 500
-        
-    kir = (D/Dref)*2**(-2*nhu)*(EI/(Em*D**4))**0.284
-    Kir = kir*Em     
-    y_rm = krm*D
-    y_a = (p_ur/(2*y_rm**0.25*Kir))**1.333    
-   
-    # Normalized lateral displacement
-    N = 20
-    y = np.concatenate((-np.logspace(5,-3,N),[0],np.logspace(-3,5,N)))
-    
-    p=[]; P=[];
-    for i in range (len(y)):
-        if abs(y[i]) < y_a: 
-            P = np.sign(y[i])*Kir*y[i]
-        elif abs(y[i]) > y_a:
-            P = min((p_ur/2)*(abs(y[i])/y_rm)**0.25,p_ur)
-        p.append(P)    
-   
-    p = np.array(p).squeeze()     
-    for j in range(len(y)):
-        if y[j] < 0:
-            p[j] = -1*p[j]
-        elif y[j] > 0:
-            p[j] = p[j]                            
- 
-    #var_Reese = inspect.currentframe().f_locals          
-    
-    f = interp1d(y, p)   # Interpolation function for p-y curve
-    if plot:    
-        plt.plot(y, p) 
-        plt.xlabel('y (m)') 
-        plt.ylabel('p (N/m)'),
-        plt.title('PY Curves - Reese (1997)')
-        plt.grid(True)
-        plt.xlim([-0.03*D, 0.03*D])
-        plt.ylim([min(p), max(p)])     
-        
-    return f      # This is f (linear interpolation of y-p)
-   
-#######################
-#### Rock Profile #####
-#######################
-
-def rock_profile(profile):
-    '''
-    Define the (weak) rock profile used by the p-y analyzer. Outputs 'interp1d' functions containing 
-    UCS and Em profiles to be used by the p-y curve functions.
-
-    Input:
-    -----
-    profile - A 2D tuple in the following format: ([depth (m), UCS (MPa), Em (MPa), py-model])
-              The soil profile should be defined relative to the pile/tower head (i.e. point of lateral load application)
-              so that any load eccentricities can be taken into account. An example soil profile is shown below.
-              Eg: array([[z0,UCS0,Em0, 'Reese'],
-                         [z1,UCS1,Em1, 'Reese'],
-                         [z2,UCS2,Em2, 'Reese'],
-                          ...])
-              *The current program cannot define layers with different p-y models. But it will added in the future.
-
-    Output:
-    ------
-    z0       - Depth of mudline relative to the pile head (m)
-    f_UCS    - 'interp1d' function containing undrained shear strength profile (Pa)
-    f_Em     - 'interp1d' function containing effective vertical stress profile (Pa)
-    '''
-
-    # Depth of mudline relative to pile head
-    z0 = float(profile[0][0])
-
-    # Extract data from soil_profile array and zero strength virtual soil layer
-    # from the pile head down to the mudline
-    depth = np.concatenate([np.array([z0]),np.array([row[0] for row in profile],dtype=float)])  # m  
-    UCS   = np.concatenate([np.array([0]), np.array([row[1] for row in profile],dtype=float)])  # MPa
-    Em    = np.concatenate([np.array([0]), np.array([row[2] for row in profile],dtype=float)])  # MPa
-
-    # Define interpolation functions
-    f_UCS = interp1d(depth, UCS*1e6, kind='linear')  # Pa
-    f_Em  = interp1d(depth, Em*1e6, kind='linear')   # Pa
-    
-    #var_rock_profile = inspect.currentframe().f_locals
-
-    return z0, f_UCS, f_Em
-
-if __name__ == '__main__':
-
-    profile = np.array([[0.0,  5, 7, 'Name of p-y model'],
-                        [25.0, 5, 7, 'Name of p-y model']])
-    
-    L = 15
-    D = 1
-    zlug = 0
-    H0 = 318763.5
-    V0 = 297554.3 
-    
-    H = 1e4; V = 1e4
-
-    values_H =[]; values_V =[]      
-    
-    y, z, results = getCapacityDandG(profile, L=L, D=D, zlug=zlug, V=V0, H=H0)
-
-    while results['Lateral displacement']< 0.05*D and results['Rotational displacement'] < 0.25:
-               
-        y, z, results = getCapacityDandG(profile, L=L, D=D, zlug=zlug, V=V, H=H)
-        
-        H += 10000
-                   
-    values_H.append(H); H_ratio = np.array(values_H)/H0
-          
-    y0 = np.zeros(len(z))
-    #Plot deflection profile of pile
-    fig, ax = plt.subplots(figsize=(3,5))    
-    ax.plot(y0,z,'black')
-    ax.plot(y,z,'r')
-    ax.set_xlabel('Displacement [m]')
-    ax.set_ylabel('Depth below pile head [m]')
-    ax.set_ylim([L + 2, -2])
-    ax.set_xlim([-0.1*D, 0.1*D])
-    ax.grid(ls='--')
-    fig.show()
\ No newline at end of file
diff --git a/famodel/anchors/anchors_famodel_map/capacity_dandg_map.py b/famodel/anchors/anchors_famodel/capacity_drilled.py
similarity index 85%
rename from famodel/anchors/anchors_famodel_map/capacity_dandg_map.py
rename to famodel/anchors/anchors_famodel/capacity_drilled.py
index aafc2af4..929e2af5 100644
--- a/famodel/anchors/anchors_famodel_map/capacity_dandg_map.py
+++ b/famodel/anchors/anchors_famodel/capacity_drilled.py
@@ -1,12 +1,12 @@
 
 import numpy as np
 import matplotlib.pyplot as plt
-from .capacity_soils_map import rock_profile
-from .capacity_solvers import fd_solver
-from .capacity_pycurves_map import py_Lovera
-from .capacity_plots_map import plot_pile, plot_pycurve
+from .support_soils import rock_profile
+from .support_solvers import fd_solver
+from .support_pycurves import py_Lovera
+from .support_plots import plot_pile, plot_pycurve
 
-def getCapacityDandG(profile_map, location_name, L, D, zlug, Ha, Va, plot=True):
+def getCapacityDrilled(profile_map, location_name, L, D, zlug, Ha, Va, plot=False, display=0):
     '''Models a laterally loaded pile using the p-y method. The solution for
     lateral displacements is obtained by solving the 4th order ODE, 
     EI*d4y/dz4 - V*d2y/dz2 + ky = 0 using the finite difference method.
@@ -96,7 +96,7 @@ def PileWeight(Len, Dia, tw, rho):
             DQ.append(0.0)
             continue
         
-        profile = [[matched_layer['top'], matched_layer['UCS_top'], matched_layer['Em_top']],
+        profile = [[matched_layer['top'],    matched_layer['UCS_top'], matched_layer['Em_top']],
                    [matched_layer['bottom'], matched_layer['UCS_bot'], matched_layer['Em_bot']]]
         z0_local, f_UCS, f_Em = rock_profile(profile)
         
@@ -108,7 +108,7 @@ def PileWeight(Len, Dia, tw, rho):
 
         UCS = f_UCS(z_depth)
         Em = f_Em(z_depth)
-        py_f, (y_vals, p_vals) = py_Lovera(z_depth, D, f_UCS, f_Em, zlug, z0, return_curve=True)
+        py_f, (y_vals, p_vals) = py_Lovera(z_depth, D, UCS, Em, zlug, z0, return_curve=True)
         py_funs.append(py_f)
         pycurve_data.append((y_vals, p_vals, z_depth, 'rock'))
         # print(f"z_depth = {z_depth:.2f} m, UCS = {f_UCS(z_depth):.2e} Pa, Em = {f_Em(z_depth):.2e} Pa")
@@ -141,10 +141,10 @@ def PileWeight(Len, Dia, tw, rho):
     
         # Check convergence
         if np.linalg.norm(y - y_old, ord=2) < tol:
-            print(f'[Converged in {j+1} iterations]')
+            if display > 0: print(f'[Converged in {j+1} iterations]')
             break
     else:
-        print('[Warning: Solver did not converge]')
+        if display > 0: print('[Warning: Solver did not converge]')
 
 
     if plot:
@@ -164,22 +164,23 @@ def PileWeight(Len, Dia, tw, rho):
         ax.legend() 
             
     # Relevant index of nodes
-    zlug_index = int(zlug/h); print(zlug_index)
-    ymax_index = np.argmax(y); print(ymax_index)    
+    zlug_index = int(zlug/h)
+    if display > 0: print(zlug_index)
+    ymax_index = np.argmax(y)
+    if display > 0: print(ymax_index)    
     
     resultsDandG = {
-        'Weight pile': PileWeight(L, D, t, rhows + rhow),
         'Vertical max.': Vmax,
         'Lateral displacement': y[ymax_index],
         'Rotational displacement': np.rad2deg(abs(y[ymax_index - 1] - y[ymax_index])/h),
-        'Unity check (vertical)': Va/Vmax if Vmax != 0 else np.inf,
-        'Unity check (horizontal)': 0.0,  # Placeholder; no Mp or Mi in current model
         'Bending moment': None,
         'Plastic moment': None,
         'Plastic hinge': None,
-        'Hinge location': None,
-        'p-y model': 'Lovera (2023)',
-        }
+        'Hinge location': None,      
+        'Unity check (vertical)': Va/Vmax if Vmax != 0 else np.inf,
+        'Unity check (horizontal)': 0.0,  # Placeholder; no Mp or Mi in current model
+        'Weight pile': PileWeight(L, D, t, rhows + rhow),
+        'p-y model': 'Lovera (2023)'}
     
     return layers, y[2:-2], z[2:-2], resultsDandG
    
@@ -194,19 +195,19 @@ def PileWeight(Len, Dia, tw, rho):
                 {
                     'top': 2.0, 'bottom': 5.0,
                     'soil_type': 'rock',
-                    'UCS_top': 1.0, 'UCS_bot': 2.0,    # MPa
+                    'UCS_top': 8.0, 'UCS_bot': 8.0,    # MPa
                     'Em_top': 100, 'Em_bot': 200       # MPa
                 },
                 {
                     'top': 5.0, 'bottom': 9.0,
                     'soil_type': 'rock',
-                    'UCS_top': 2.0, 'UCS_bot': 3.0,    # MPa
+                    'UCS_top': 10.0, 'UCS_bot': 10.0,  # MPa
                     'Em_top': 200, 'Em_bot': 300       # MPa
                 },
                 {
                     'top': 9.0, 'bottom': 30.0,
                     'soil_type': 'rock',
-                    'UCS_top': 3.0, 'UCS_bot': 6.0,    # MPa
+                    'UCS_top': 20.0, 'UCS_bot': 20.0,  # MPa
                     'Em_top': 300, 'Em_bot': 400       # MPa
                 }
             ]
@@ -216,12 +217,12 @@ def PileWeight(Len, Dia, tw, rho):
     D = 3.0           # Diameter (m)
     L = 10.0          # Length (m)
     zlug = 1          # Padeye elevation (m)
-    Ha = 8.0e6        # Horizontal load (N)
-    Va = 3.0e6        # Vertical load (N)
+    Ha = 5.0e6        # Horizontal load (N)
+    Va = 3.0e5        # Vertical load (N)
 
-    layers, y, z, results = getCapacityDandG(profile_map, 'CPT_rock_1', L, D, zlug, Ha, Va, plot=True)
+    layers, y, z, results = getCapacityDrilled(profile_map, 'CPT_rock_1', L, D, zlug, Ha, Va, plot=True, display=0)
 
-    print('\n--- Results for DandG Pile in Layered Rock ---')
+    print('\n--- Results for Drilled Pile in Layered Rock ---')
     for key, val in results.items():
         print(f'{key}: {val:.3f}' if isinstance(val, float) else f'{key}: {val}')
         
diff --git a/famodel/anchors/anchors_famodel_map/capacity_driven_map.py b/famodel/anchors/anchors_famodel/capacity_driven.py
similarity index 79%
rename from famodel/anchors/anchors_famodel_map/capacity_driven_map.py
rename to famodel/anchors/anchors_famodel/capacity_driven.py
index cd7c58ee..83961540 100644
--- a/famodel/anchors/anchors_famodel_map/capacity_driven_map.py
+++ b/famodel/anchors/anchors_famodel/capacity_driven.py
@@ -1,12 +1,12 @@
 
 import numpy as np
 import matplotlib.pyplot as plt
-from .capacity_soils_map import clay_profile, sand_profile, rock_profile
-from .capacity_solvers import fd_solver
-from .capacity_pycurves_map import py_Matlock, py_API, py_Reese
-from .capacity_plots_map import plot_pile, plot_pycurve
+from .support_soils import clay_profile, sand_profile, rock_profile
+from .support_solvers import fd_solver
+from .support_pycurves import py_Matlock, py_API, py_Reese
+from .support_plots import plot_pile, plot_pycurve
 
-def getCapacityDriven(profile_map, location_name, D, L, zlug, Ha, Va, plot=True):
+def getCapacityDriven(profile_map, location_name, D, L, zlug, Ha, Va, plot=False, display=0):
     '''Models a laterally loaded pile using the p-y method. The solution for
     lateral displacements is obtained by solving the 4th order ODE, EI*d4y/dz4
     EI*d4y/dz4 - V*d2y/dz2 + ky = 0 using the finite difference method.
@@ -51,7 +51,7 @@ def getCapacityDriven(profile_map, location_name, D, L, zlug, Ha, Va, plot=True)
     layers = profile_entry['layers']
 
     n = 50; loc = 2              # Number of nodes (-)
-    tol = 1e-16; max_iter = 50   # Iteration parameters (-)
+    tol = 1e-16; max_iter = 100  # Iteration parameters (-)
     nhuc = 1; nhu = 0.3          # Resistance factor (-)
     delta_r = 0.08               # Mean roughness height (m)
     
@@ -101,9 +101,9 @@ def SoilWeight(Len, Dia, tw, gamma_soil):
             continue
 
         soil_type = matched_layer['soil_type']
-
+        
         if soil_type == 'clay':
-            profile = [[matched_layer['top'], matched_layer['Su_top'], matched_layer['gamma_top']],
+            profile = [[matched_layer['top'],    matched_layer['Su_top'], matched_layer['gamma_top']],
                        [matched_layer['bottom'], matched_layer['Su_bot'], matched_layer['gamma_bot']]]
             z0_local, f_Su, f_sigma_v_eff, f_gamma, f_alpha = clay_profile(profile)
             if z_depth < z0_local:
@@ -115,7 +115,7 @@ def SoilWeight(Len, Dia, tw, gamma_soil):
             sigma_v_eff = f_sigma_v_eff(z_depth)
             gamma = f_gamma(z_depth)
             alpha = f_alpha(z_depth)
-            py_f, (y_vals, p_vals) = py_Matlock(z_depth, D, zlug, f_Su, f_sigma_v_eff, f_gamma, z0=z0_local, return_curve=True)
+            py_f, (y_vals, p_vals) = py_Matlock(z_depth, D, gamma, Su, sigma_v_eff, z0=z0_local, return_curve=True)
             py_funs.append(py_f)
             pycurve_data.append((y_vals, p_vals, z_depth, 'clay'))
             Vo = np.pi*D*alpha*Su*z_depth**2
@@ -124,7 +124,7 @@ def SoilWeight(Len, Dia, tw, gamma_soil):
             k_secant[i] = k_val/y[i] if y[i] != 0 else 0.0
 
         elif soil_type == 'sand':
-            profile = [[matched_layer['top'], matched_layer['phi_top'], matched_layer['gamma_top'], matched_layer['Dr_top']],
+            profile = [[matched_layer['top'],    matched_layer['phi_top'], matched_layer['gamma_top'], matched_layer['Dr_top']],
                        [matched_layer['bottom'], matched_layer['phi_bot'], matched_layer['gamma_bot'], matched_layer['Dr_bot']]]
             z0_local, f_phi, f_sigma_v_eff, f_gamma, f_Dr, f_delta = sand_profile(profile)
             if z_depth < z0_local:
@@ -132,9 +132,11 @@ def SoilWeight(Len, Dia, tw, gamma_soil):
                 k_secant[i] = 0.0
                 PileShaft.append(0.0)
                 continue
+            phi = f_phi(z_depth)
             sigma_v_eff = f_sigma_v_eff(z_depth)
+            Dr = f_Dr(z_depth)
             delta = f_delta(z_depth)
-            py_f, (y_vals, p_vals) = py_API(z_depth, D, zlug, f_phi, f_sigma_v_eff, f_Dr, z0=z0_local, return_curve=True)
+            py_f, (y_vals, p_vals) = py_API(z_depth, D, phi, sigma_v_eff, Dr, z0=z0_local, return_curve=True)
             py_funs.append(py_f)
             pycurve_data.append((y_vals, p_vals, z_depth, 'sand'))
             fs = delta * sigma_v_eff
@@ -144,7 +146,7 @@ def SoilWeight(Len, Dia, tw, gamma_soil):
             k_secant[i] = k_val/y[i] if y[i] != 0 else 0.0
 
         elif soil_type in ['rock', 'weak_rock']:
-            profile = [[matched_layer['top'], matched_layer['UCS_top'], matched_layer['Em_top']],
+            profile = [[matched_layer['top'],    matched_layer['UCS_top'], matched_layer['Em_top']],
                        [matched_layer['bottom'], matched_layer['UCS_bot'], matched_layer['Em_bot']]]
             z0_local, f_UCS, f_Em = rock_profile(profile)
             if z_depth < z0_local:
@@ -154,7 +156,7 @@ def SoilWeight(Len, Dia, tw, gamma_soil):
                 continue
             UCS = f_UCS(z_depth)
             Em = f_Em(z_depth)
-            py_f, (y_vals, p_vals) = py_Reese(z_depth, D, zlug, f_UCS, f_Em, z0=z0_local, return_curve=True)
+            py_f, (y_vals, p_vals) = py_Reese(z_depth, D, UCS, Em, z0=z0_local, return_curve=True)
             py_funs.append(py_f)
             pycurve_data.append((y_vals, p_vals, z_depth, 'rock'))
             SCR = nhuc*Em/(UCS*(1 + nhu))*delta_r/D
@@ -166,7 +168,7 @@ def SoilWeight(Len, Dia, tw, gamma_soil):
             k_secant[i] = k_val/y[i] if y[i] != 0 else 0.0
             
         else:
-            raise ValueError(f"Unsupported soil type: {matched_layer['soil_type']}")
+            raise ValueError(f"Unsupported soil type: {matched_layer.get('soil_type')} at depth z = {z_depth:.2f} m")
 
     for i in [n+3, n+4]:
         z[i] = (i - 2)*h
@@ -194,10 +196,10 @@ def SoilWeight(Len, Dia, tw, gamma_soil):
     
         # Check convergence
         if np.linalg.norm(y - y_old, ord=2) < tol:
-            print(f'[Converged in {j+1} iterations]')
+            if display > 0: print(f'[Converged in {j+1} iterations]')
             break
     else:
-        print('[Warning: Solver did not converge]')
+        if display > 0: print('[Warning: Solver did not converge]')
 
     if plot:
         plot_pycurve(pycurve_data)
@@ -216,22 +218,25 @@ def SoilWeight(Len, Dia, tw, gamma_soil):
         ax.legend()
 
     # Relevant index of nodes
-    zlug_index = int(zlug/h)
-    ymax_index = np.argmax(y)
+    y_pile = y[2:-2]
+    z_pile = z[2:-2]
+    ymax_index = np.argmax(np.abs(y_pile))
 
     resultsDriven = {
-        'Weight': PileWeight(L, D, t, rhows + rhow),
+        'Horizontal max.': abs(Mi)/abs(zlug) if zlug != 0 else 1e-6,
         'Vertical max.': Vmax,
-        'Lateral displacement': y[ymax_index],
-        'Rotational displacement': np.rad2deg(abs(y[ymax_index - 1] - y[ymax_index])/h),
+        'Lateral displacement': y_pile[ymax_index],
+        'Rotational displacement': np.rad2deg(abs(y_pile[ymax_index - 1] - y_pile[ymax_index])/h),
         'Bending moment': abs(Mi),
         'Plastic moment': Mp,
         'Plastic hinge': hinge_formed,
-        'Hinge location': hinge_location,
-        'Horizontal max.': abs(Mi)/abs(zlug) if zlug != 0 else 1e-6,
+        'Hinge location': hinge_location,         
         'Unity check (vertical)': Va/Vmax if Vmax != 0 else np.inf,
-        'Unity check (horizontal)': Ha/(abs(Mi)/abs(zlug)) if zlug != 0 else np.inf
-    }
+        'Unity check (horizontal)': Ha/(abs(Mi)/abs(zlug)) if zlug != 0 else np.inf,
+        'Weight pile': PileWeight(L, D, t, rhows + rhow)}
+    
+    if display > 0: print(f"Max lateral displacement: {y_pile[ymax_index]:.6f} m at z = {z_pile[ymax_index]:.2f} m")
+    if display > 0: print(f"Deflected tip: {y_pile[-1]:.6f} m at z = {z_pile[-1]:.2f} m")
 
     return layers, y[2:-2], z[2:-2], resultsDriven
 
@@ -246,28 +251,33 @@ def SoilWeight(Len, Dia, tw, gamma_soil):
                     'top': 1.0, 'bottom': 6.0,
                     'soil_type': 'clay',
                     'gamma_top': 8.0, 'gamma_bot': 8.0,
-                    'Su_top': 60, 'Su_bot': 200},
-                # {
-                #     'top': 6.0, 'bottom': 15.0,
-                #     'soil_type': 'clay',
-                #     'gamma_top': 8.0, 'gamma_bot': 8.0,
-                #     'Su_top': 200, 'Su_bot': 400},
+                    'Su_top': 60, 'Su_bot': 80},
                 {
                     'top': 6.0, 'bottom': 15.0,
-                    'soil_type': 'sand',
+                    'soil_type': 'clay',
                     'gamma_top': 8.0, 'gamma_bot': 8.0,
-                    'phi_top': 32, 'phi_bot': 38,
-                    'Dr_top': 70, 'Dr_bot': 75},
+                    'Su_top': 80, 'Su_bot': 400},
+                # {
+                #     'top': 6.0, 'bottom': 15.0,
+                #     'soil_type': 'sand',
+                #     'gamma_top': 8.0, 'gamma_bot': 8.0,
+                #     'phi_top': 32, 'phi_bot': 38,
+                #     'Dr_top': 70, 'Dr_bot': 75},
                 {
                     'top': 15.0, 'bottom': 30.0,
                     'soil_type': 'clay',
-                    'gamma_top': 8.0, 'gamma_bot': 9.0,
+                    'gamma_top': 8.0, 'gamma_bot': 8.0,
                     'Su_top': 200, 'Su_bot': 400}]
+                # {
+                #     'top': 0.0, 'bottom': 30.0,
+                #     'soil_type': 'rock',
+                #     'UCS_top': 5.0, 'UCS_bot': 5.0,
+                #     'Em_top': 7.0, 'Em_bot': 7.0}]
         }
     ]
 
     D = 2.5           # Diameter (m)
-    L = 25.0          # Length (m)
+    L = 15.0          # Length (m)
     zlug = 3          # Padeye depth (m)
     Ha = 5.0e5        # Horizontal load (N)
     Va = 1.5e5        # Vertical load (N)
diff --git a/famodel/anchors/anchors_famodel/capacity_drivenrock.py b/famodel/anchors/anchors_famodel/capacity_drivenrock.py
deleted file mode 100644
index d44f6e2f..00000000
--- a/famodel/anchors/anchors_famodel/capacity_drivenrock.py
+++ /dev/null
@@ -1,373 +0,0 @@
-
-import numpy as np
-import matplotlib.pyplot as plt
-from scipy.interpolate import interp1d
-from scipy import linalg
-import inspect
-
-###################################
-#### Pile Geometry and Loading ####
-###################################
-
-def getCapacityDrivenRock(profile, L, D, zlug, V, H, plot=True):
-    '''
-    Models a laterally loaded pile using the p-y method. The solution for
-    lateral displacements is obtained by solving the 4th order ODE, 
-    EI*d4y/dz4 - V*d2y/dz2 + ky = 0 using the finite difference method.
-    EI*d4y/dz4 - V*d2y/dz2 + K*z*dy/dz + ky = 0 using the finite difference method.
-
-    Assumes that EI remains constant with respect to curvature i.e. pile
-    material remains in the elastic region.
-
-    Input:
-    -----
-    profile     - A 2D array of depths (m) and corresponding undrained shear strength(Pa)
-                  Eg: array([[z1,UCS1],[z2,UCS2],[z3,UCS3]...])
-                  Use small values for Su (eg: 0.001) instead of zeros to avoid divisions 
-                  by zero but always start z at 0.0
-                  Example of a valid data point at the mudline is [0.0, 0.001]
-    L           - Length of pile (m)
-    D           - Outer diameter of pile (m)
-    V           - Axial force at pile head (N)
-    H           - Force at pile head (N)
-    M           - Moment at pile head (N*m)
-    n           - Number of elements (50 by default)
-    iterations  - Number of iterations to repeat calculation in order obtain convergence of 'y'
-                  (A better approach is to iterate until a predefined tolerance is achieved)
-
-    Output:
-    ------
-    y           - Lateral displacement at each node, length = n + 5, (n+1) real nodes and 4 imaginary nodes
-    z           - Vector of node locations along pile
-    resultsDrivenRock - Dictionary with results
-    '''
-    
-    # Extract optional keyword arguments
-    # ls = 'x'
-    n = 50; iterations = 10; loc = 2
-
-    # Resistance factor
-    nhuc = 1; nhu = 0.3 
-    delta_r = 0.08               # Mean roughness height [m]
-    
-    # Convert L and D to floating point numbers to avoid rounding errors
-    L = float(L)
-    D = float(D)
-    t = (6.35 + D*20)/1e3        # Pile wall thickness (m), API RP2A-WSD
-    E = 200e9                    # Elastic modulus of pile material (Pa)
-    rhows = 66.90e3              # Submerged steel specific weight (N/m3)
-    rhow = 10e3                  # Water specific weight (N/m3) 
-    
-    # Pile geometry
-    I = (np.pi/64.0)*(D**4 - (D - 2*t)**4)
-    EI = E*I
-    h = L/n                      # Element size
-    N = (n + 1) + 4              # (n+1) Real + 4 Imaginary nodes
-    
-    # Dry and wet mass of the pile    
-    def PileWeight(Len, Dia, tw, rho):
-        Wp = ((np.pi/4)*(Dia**2 - (Dia - 2*tw)**2)*Len)*rho
-        return Wp 
-
-    # Array for displacements at nodes, including imaginary nodes.
-    y = np.ones(N)*(0.01*D)      # An initial value of 0.01D was arbitrarily chosen
-
-    # Initialize and assemble array/list of p-y curves at each real node
-    z = np.zeros(N)
-    py_funs = []
-    k_secant = np.zeros(N)
-    DQ = []
-
-    for i in [0,1]:              # Top two imaginary nodes
-        z[i] = (i - 2)*h
-        py_funs.append(0)
-        k_secant[i] = 0.0
-   
-    for i in range(2,n+3):       # Real nodes
-        z[i] = (i - 2)*h
-        # Extract rock profile data
-        zlug, f_UCS, f_Em = rock_profile(profile)
-        UCS, Em = f_UCS(z[i]), f_Em(z[i])
-        py_funs.append(py_Reese(z[i], D, zlug, UCS, Em))
-        k_secant[i] = py_funs[i](y[i])/y[i]
-        SCR = nhuc*Em/(UCS*(1 + nhu))*delta_r/D
-        alpha = 0.36*SCR - 0.0005
-        fs = alpha*UCS
-        Dq = np.pi*D*fs*z[i]
-        DQ.append(Dq)
-
-    for i in [n+3, n+4]:         # Bottom two imaginary nodes
-        z[i] = (i - 2)*h
-        py_funs.append(0)
-        k_secant[i] = 0.0
-
-    # Track k_secant and current displacements
-
-    y1 = np.linspace(-2.*D, 2.*D, 500)
-    if plot:
-        plt.plot(y1, py_funs[loc](y1))
-        plt.xlabel('y (m)'), plt.ylabel('p (N/m)')
-        plt.grid(True)
-
-    for j in range(iterations):
-        # if j == 0: print 'FD Solver started!'
-        y = fd_solver(n, N, h, EI, V, H, zlug, k_secant)
-        
-        if plot:
-            plt.plot(y[loc], k_secant[loc]*y[loc])
-
-        for i in range(2, n+3):
-            k_secant[i] = py_funs[i](y[i])/y[i]
-
-    # print(f'y_max = {y[2]:.3f} m')
-    # print(f'rot_max = {np.rad2deg((y[2] - y[3])/h):.3f} deg')
-
-    resultsDrivenRock = {}
-    resultsDrivenRock['Lateral displacement'] = y[2]
-    resultsDrivenRock['Rotational displacement'] = np.rad2deg((y[2] - y[3])/h)
-    resultsDrivenRock['Axial capacity'] = DQ[-1]
-    resultsDrivenRock['Weight'] = PileWeight(L, D, t, (rhows + rhow))
-    
-    return y[2:-2], z[2:-2], resultsDrivenRock
-
-#################
-#### Solvers ####
-#################
-
-def fd_solver(n, N, h, EI, V, H, zlug, k_secant):
-    '''
-    Solves the finite difference equations from 'py_analysis_1'. This function should be run iteratively for
-    non-linear p-y curves by updating 'k_secant' using 'y'. A single iteration is sufficient if the p-y curves
-    are linear.
-
-    Input:
-    -----
-    n        - Number of elements
-    N        - Total number of nodes
-    h        - Element size
-    EI       - Flexural rigidity of pile
-    V        - Axial force at pile head
-    H        - Shear at pile head/tip
-    M        - Moment at pile head/tip
-    k_secant - Secant stiffness from p-y curves
-
-    Output:
-    ------
-    y        - Lateral displacement at each node
-    '''
-    M = H*zlug
-    
-    # Initialize and assemble matrix
-    X = np.zeros((N,N))
-
-    # (n+1) finite difference equations for (n+1) real nodes
-    for i in range(0,n+1):
-        X[i,i]   =  1.0
-        X[i,i+1] = -4.0 + V*h**2/EI
-        X[i,i+2] =  6.0 - 2*V*h**2/EI + k_secant[i+2]*h**4/EI
-        X[i,i+3] = -4.0 + V*h**2/EI
-        X[i,i+4] =  1.0
-
-    # Curvature at pile head
-    X[n+1,1] =  1.0
-    X[n+1,2] = -2.0
-    X[n+1,3] =  1.0
-
-    # Shear at pile head
-    X[n+2,0] = -1.0
-    X[n+2,1] =  2.0 - V*h**2/EI
-    X[n+2,2] =  0.0
-    X[n+2,3] = -2.0 + V*h**2/EI
-    X[n+2,4] =  1.0
-
-    # Curvature at pile tip
-    X[n+3,-2] =  1.0
-    X[n+3,-3] = -2.0
-    X[n+3,-4] =  1.0
-
-    # Shear at pile tip
-    X[n+4,-1] =  1.0
-    X[n+4,-2] = -2.0 + V*h**2/EI
-    X[n+4,-3] =  0.0
-    X[n+4,-4] =  2.0 - V*h**2/EI
-    X[n+4,-5] = -1.0
-
-    # Initialize vector q
-    q = np.zeros(N)
-
-    # Populate q with boundary conditions
-    q[-3] = 2*H*h**3      # Shear at pile head
-    # q[-4] = M*h**2        # Moment at pile head
-
-    y = linalg.solve(EI*X, q)
-
-    return y
-
-###############################
-#### P-Y Curve Definitions ####
-###############################
-
-def py_Reese(z, D, zlug, UCS, Em):
-    '''
-    Returns an interp1d interpolation function which represents the Reese (1997) p-y curve at the depth of interest.
-
-    Important: Make sure to import the interp1 function by running 'from scipy.interpolate import interp1d' in the main program.
-
-    Input:
-    -----
-    z      - Depth relative to pile head (m)
-    D      - Pile diameter (m)
-    zlug   - Load eccentricity above the mudline or depth to mudline relative to the pile head (m)
-    UCS    - Undrained shear strength (Pa)
-    Em     - Effectve vertical stress (Pa)
-    RQD    - Rock quality designation, measures the quality of the rock core taken from a borehole.
-             Typically ranges from 25% (very weathered rock) to 100% (fresh rock).
-
-    Output:
-    ------
-    Returns an interp1d interpolation function which represents the p-y curve at the depth of interest.
-    'p' (N/m) and 'y' (m).
-    '''
-    z0 = 0
-    
-    #from scipy.interpolate import interp1d
-    #global var_Reese
-    
-    RQD = 52                     # Assumed fair rock quality (moderately weathered rocks) 
-    Dref = 0.305; nhu = 0.3; E = 200e9
-    t = (6.35 + D*20)/1e3        # Pile wall thickness (m), API RP2A-WSD
-    I  = np.pi*(D**4 - (D - 2*t)**4)/64.0
-    EI = E*I
-    alpha = -0.00667*RQD + 1
-    krm = 0.0005
-
-    if (z - z0) < 0:
-        p_ur = 0
-    else:    
-        if z < 3*D:
-            p_ur = alpha*UCS*D*(1 + 1.4*z/D)
-            #kir = (100 +400*z/(3*D))
-        else:
-            p_ur = 5.2*alpha*UCS*D
-            #kir = 500
-        
-    kir = (D/Dref)*2**(-2*nhu)*(EI/(Em*D**4))**0.284
-    Kir = kir*Em     
-    y_rm = krm*D
-    y_a = (p_ur/(2*y_rm**0.25*Kir))**1.333    
-   
-    # Normalized lateral displacement
-    N = 20
-    y = np.concatenate((-np.logspace(5,-3,N),[0],np.logspace(-3,5,N)))
-    
-    p=[]; P=[];
-    for i in range (len(y)):
-        if abs(y[i]) < y_a: 
-            P = np.sign(y[i])*Kir*y[i]
-        elif abs(y[i]) > y_a:
-            P = min((p_ur/2)*(abs(y[i])/y_rm)**0.25,p_ur)
-        p.append(P)    
-   
-    p = np.array(p).squeeze()     
-    for j in range(len(y)):
-        if y[j] < 0:
-            p[j] = -1*p[j]
-        elif y[j] > 0:
-            p[j] = p[j]                            
- 
-    #var_Reese = inspect.currentframe().f_locals          
-    
-    f = interp1d(y, p)   # Interpolation function for p-y curve
-         
-    plt.plot(y, p) 
-    plt.xlabel('y (m)') 
-    plt.ylabel('p (N/m)'),
-    plt.title('PY Curves - Reese (1997)')
-    plt.grid(True)
-    plt.xlim([-0.03*D, 0.03*D])
-    plt.ylim([min(p), max(p)])     
-        
-    return f      # This is f (linear interpolation of y-p)
-   
-#######################
-#### Rock Profile #####
-#######################
-
-def rock_profile(profile):
-    '''
-    Define the (weak) rock profile used by the p-y analyzer. Outputs 'interp1d' functions containing 
-    UCS and Em profiles to be used by the p-y curve functions.
-
-    Input:
-    -----
-    profile - A 2D tuple in the following format: ([depth (m), UCS (MPa), Em (MPa), py-model])
-              The soil profile should be defined relative to the pile/tower head (i.e. point of lateral load application)
-              so that any load eccentricities can be taken into account. An example soil profile is shown below.
-              Eg: array([[z0,UCS0,Em0, 'Reese'],
-                         [z1,UCS1,Em1, 'Reese'],
-                         [z2,UCS2,Em2, 'Reese'],
-                          ...])
-              *The current program cannot define layers with different p-y models. But it will added in the future.
-
-    plot_profile - Plot Su vs depth profile. Choose 'Yes' to plot.
-
-    Output:
-    ------
-    z0       - Depth of mudline relative to the pile head (m)
-    f_UCS    - 'interp1d' function containing undrained shear strength profile (Pa)
-    f_Em     - 'interp1d' function containing effective vertical stress profile (Pa)
-    '''
-
-    # Depth of mudline relative to pile head
-    z0 = float(profile[0][0])
-
-    # Extract data from soil_profile array and zero strength virtual soil layer
-    # from the pile head down to the mudline
-    depth = np.concatenate([np.array([z0]),np.array([row[0] for row in profile],dtype=float)])  # m  
-    UCS   = np.concatenate([np.array([0]), np.array([row[1] for row in profile],dtype=float)])  # MPa
-    Em    = np.concatenate([np.array([0]), np.array([row[2] for row in profile],dtype=float)])  # MPa
-
-    # Define interpolation functions
-    f_UCS = interp1d(depth, UCS*1e6, kind='linear') # Pa
-    f_Em  = interp1d(depth, Em*1e6, kind='linear')  # Pa
-    
-    #var_rock_profile = inspect.currentframe().f_locals
-
-    return z0, f_UCS, f_Em
-
-if __name__ == '__main__':
-
-    profile = np.array([[0.0,  5, 7, 'Name of p-y model'],
-                        [25.0, 5, 7, 'Name of p-y model']])
-    
-    L = 20
-    D = 1.5
-    zlug = 2*D
-    H0 = 3187635
-    V0 = 2975543 
-
-    H = 1e4; V = 1e4    
-
-    values_H =[]; values_V =[]      
-
-    y, z, results = getCapacityDrivenRock(profile, L=L, D=D, zlug=zlug, V=V0, H=H0)
-    
-    while results['Lateral displacement']< 0.05*D and results['Rotational displacement'] < 0.25:
-           
-        y, z, results = getCapacityDrivenRock(profile, L=L, D=D, zlug=zlug, V=V, H=H)
-    
-        H += 10000
-               
-    values_H.append(H); H_ratio = np.array(values_H)/H0
-          
-    y0 = np.zeros(len(z))
-    #Plot deflection profile of pile
-    fig, ax = plt.subplots(figsize=(3,5))    
-    ax.plot(y0,z,'black')
-    ax.plot(y,z,'r')
-    ax.set_xlabel('Displacement [m]')
-    ax.set_ylabel('Depth below pile head [m]')
-    ax.set_ylim([L + 2,-2])
-    ax.set_xlim([-0.1*D, 0.1*D])
-    ax.grid(ls='--')
-    fig.show()
\ No newline at end of file
diff --git a/famodel/anchors/anchors_famodel/capacity_drivensoil.py b/famodel/anchors/anchors_famodel/capacity_drivensoil.py
deleted file mode 100644
index b4cee31c..00000000
--- a/famodel/anchors/anchors_famodel/capacity_drivensoil.py
+++ /dev/null
@@ -1,628 +0,0 @@
-
-import numpy as np
-import matplotlib.pyplot as plt
-
-###################################
-#### Pile Geometry and Loading ####
-###################################
-
-def getCapacityDrivenSoil(profile, soil_type, L, D, zlug, V, H, plot=True):
-    
-    '''Models a laterally loaded pile using the p-y method. The solution for
-    lateral displacements is obtained by solving the 4th order ODE, EI*d4y/dz4
-    - F*d2y/dz2 + ky = 0 using the finite difference method.
-
-    Assumes that EI remains constant with respect to curvature i.e. pile
-    material remains in the elastic region.
-
-    Input:
-    -----
-    profile     - A 2D array of depths (m) and corresponding undrained shear strength(Pa)
-                  Eg: array([[z1,Su1],[z2,Su2],[z3,Su3]...])
-                  Use small values for Su (eg: 0.001) instead of zeros to avoid divisions by zero but always start z at 0.0
-                  Example of a valid data point at the mudline is [0.0, 0.001]
-    soil_type   - Select soil condition, 'clay' or 'sand'
-                  Assigns which p-y model to use, 'Matlock' or 'API'.
-    L           - Length of pile (m)
-    D           - Outer diameter of pile (m)
-    zlug        - Load eccentricity above the mudline or depth to mudline relative to the pile head (m)
-    V           - Axial force at pile head (N), vertically downwards is postive.
-    H           - Force at pile head (N), shear causing clockwise rotation of pile is positive.
-    M           - Moment at pile head (N*m), moments causing tension on left side of pile is positive.
-    n           - Number of elements (50 by default)
-    iterations  - Number of iterations to repeat calculation in order obtain convergence of 'y'
-                  (A better approach is to iterate until a predefined tolerance is achieved but this requires additional
-                  coding so, I will implement this later.)
-
-    Output:
-    ------
-    y           - Lateral displacement at each node, length = n + 5, (n+1) real nodes and 4 imaginary nodes
-    z           - Vector of node locations along pile
-    '''
-
-    # Extract optional keyword arguments
-
-    ls = 'x'
-    n = 25; iterations = 10; loc=2
-    
-    # Convert L and D to floating point numbers to avoid rounding errors
-    L = float(L)
-    D = float(D)
-    t = (6.35 + D*20)/1e3       # Pile wall thickness (m), API RP2A-WSD
-    E = 200e9                   # Elastic modulus of pile material (Pa)
-    fy = 350e6                  # Yield strength of pile material (Pa)
-    rhows = 66.90e3             # Submerged steel specific weight (N/m3)
-    rhow = 10e3                 # Water specific weight (N/m3) 
-    
-    # Pile geometry
-    I = (np.pi/64.0)*(D**4 - (D - 2*t)**4)
-    EI = E*I
-    h  = L/n                    # Element size
-    N  = (n + 1) + 4            # (n+1) Real + 4 Imaginary nodes
-    
-    # Outer and inner surface of the pile skirt
-    def PileSurface(Len, Dia):
-        Sp = np.pi*Dia*Len
-        return Sp    
-    # Dry and wet mass of the pile    
-    def PileWeight(Len, Dia, tw, rho):
-        Wp = ((np.pi/4)*(Dia**2 - (Dia - 2*tw)**2)*Len)*rho 
-        return Wp 
-    # Mass of the soil plug      
-    def SoilWeight(Len, Dia, tw, gamma_soil): 
-        Wsoil =(np.pi/4)*(Dia - 2*tw)**2*Len*gamma_soil
-        return Wsoil
-
-    # Array for displacements at nodes, including imaginary nodes.
-    y = np.ones(N)*(0.01*D)     # An initial value of 0.01D was arbitrarily chosen
-
-    # Initialize and assemble array/list of p-y curves at each real node
-    z = np.zeros(N)
-    py_funs  = []; PileShaft =[]
-    k_secant = np.zeros(N)
-
-    for i in [0, 1]:            # Top two imaginary nodes
-        z[i] = (i - 2)*h
-        py_funs.append(0)
-        k_secant[i] = 0.0
-
-    # Extract soil profile data
-    if soil_type == 'clay':
-        z0, f_Su, f_sigma_v_eff, f_gamma, f_alpha = clay_profile(profile)
-
-    elif soil_type == 'sand':
-        z0, f_phi, f_sigma_v_eff, f_gamma, f_Dr, f_delta = sand_profile(profile)
-
-    for i in range(2, n+3):    # Real nodes
-        z[i] = (i - 2)*h      
-        if soil_type == 'clay':
-            Su, sigma_v_eff, gamma, alpha = f_Su(z[i]), f_sigma_v_eff(z[i]), f_gamma(z[i]), f_alpha(z[i])
-            py_funs.append(py_Matlock(z[i], D, zlug, Su, sigma_v_eff, gamma, plot=plot))
-            Vo = np.pi*D*alpha*Su*z[i]**2
-            PileShaft.append(Vo)
-            Vmax = PileWeight(L, D, t, rhows) + SoilWeight(L, D, t, gamma) + PileShaft[-1]
-            
-        elif soil_type == 'sand':
-            phi, sigma_v_eff, gamma, Dr, delta = f_phi(z[i]), f_sigma_v_eff(z[i]), f_gamma(z[i]), f_Dr(z[i]), f_delta(z[i])
-            py_funs.append(py_API(z[i], D, zlug, phi, sigma_v_eff, Dr, plot=plot))
-            fs = delta*sigma_v_eff
-            Vo = np.pi*D*fs*z[i]
-            PileShaft.append(Vo)
-            Vmax = PileWeight(L, D, t, rhows) + SoilWeight(L, D, t, gamma) + PileShaft[-1]
-        
-        k_secant[i] = py_funs[i](y[i])/y[i]
-
-    for i in [n+3, n+4]:        # Bottom two imaginary nodes
-        z[i] = (i - 2)*h
-        py_funs.append(0)
-        k_secant[i] = 0.0
-
-    y1 = np.linspace(-2.*D, 2.*D, 500)
-    if plot:
-        plt.plot(y1, py_funs[loc](y1))
-        plt.xlabel('y (m)'), plt.ylabel('p (N/m)')
-        plt.grid(True)
-
-    for j in range(iterations):
-        # if j == 0: print 'FD Solver started!'
-        y, Mi, Mp, hinge_formed, hinge_location = fd_solver(n, N, h, D, t, fy, EI, V, H, zlug, k_secant)
-
-        for i in range(2, n+3):
-            k_secant[i] = py_funs[i](y[i])/y[i]
-
-
-    resultsDrivenSoil = {}
-    # Populate q with boundary conditions
-    if zlug <= 0:      
-        # print(f'y_max = {max(y):.3f} m')
-        # print(f'rot_max = {np.rad2deg((y[2] - y[3])/h):.3f} deg')
-               
-        resultsDrivenSoil['Lateral displacement'] = max(y)
-        resultsDrivenSoil['Rotational displacement'] = np.rad2deg((y[2] - y[3])/h)
-        resultsDrivenSoil['Axial capacity'] = Vmax
-        resultsDrivenSoil['Pile weight'] = PileWeight(L, D, t, (rhows + rhow))
-   
-    else:
-        # print(f'y_max = {max(y):.3f} m')
-        # print(f'Mi = {Mi:.3f} Nm')
-        
-        resultsDrivenSoil['Lateral displacement'] = max(y)
-        resultsDrivenSoil['Bending moment'] = Mi
-        resultsDrivenSoil['Plastic moment'] = Mp
-        resultsDrivenSoil['Plastic hinge'] = hinge_formed
-        resultsDrivenSoil['Hinge location'] = hinge_location
-        resultsDrivenSoil['Axial capacity'] = Vmax
-        resultsDrivenSoil['Weight'] = PileWeight(L, D, t, (rhows + rhow))
-    
-    return y[2:-2], z[2:-2], resultsDrivenSoil
-
-#################
-#### Solvers ####
-#################
-
-def fd_solver(n, N, h, D, t, fy, EI, V, H, zlug, k_secant):
-    '''Solves the finite difference equations from 'py_analysis_1'. This function should be run iteratively for
-    non-linear p-y curves by updating 'k_secant' using 'y'. A single iteration is sufficient if the p-y curves
-    are linear.
-
-    Input:
-    -----
-    n         - Number of elements
-    N         - Total number of nodes
-    h         - Element size
-    EI        - Flexural rigidity of pile
-    V         - Axial force at pile head/zlug depth
-    H         - Shear at pile head/zlug depth
-    M         - Moment at pile head/zlug depth
-    zlug      - Load eccentricity above the mudline or depth to mudline relative to the pile head (m)
-    k_secant  - Secant stiffness from p-y curves
-
-    Output:
-    ------
-    y_updated - Lateral displacement at each node
-    '''
-    
-    from scipy import linalg
-    
-    # Identify the node corresponding to zlug
-    zlug_index = int(zlug/h)  # Index for the node corresponding to zlug
-
-    # Initialize and assemble matrix
-    X = np.zeros((N, N))
-
-    # (n+1) finite difference equations for (n+1) real nodes
-    for i in range(0, n+1):
-        X[i,i]   =  1.0
-        X[i,i+1] = -4.0 + V*h**2/EI
-        X[i,i+2] =  6.0 - 2*V*h**2/EI + k_secant[i+2]*h**4/EI
-        X[i,i+3] = -4.0 + V*h**2/EI
-        X[i,i+4] =  1.0
-
-    # Curvature at pile head
-    X[n+1,1]   =  1.0
-    X[n+1,2]   = -2.0
-    X[n+1,3]   =  1.0
-
-    # Shear at pile head
-    X[n+2,0]   = -1.0
-    X[n+2,1]   =  2.0 - V*h**2/EI
-    X[n+2,2]   =  0.0
-    X[n+2,3]   = -2.0 + V*h**2/EI
-    X[n+2,4]   =  1.0
-
-    # Curvature at pile tip
-    X[n+3,-2]   =  1.0
-    X[n+3,-3]   = -2.0
-    X[n+3,-4]   =  1.0
-
-    # Shear at pile tip
-    X[n+4,-1]   =   1.0
-    X[n+4,-2]   =  -2.0 + V*h**2/EI
-    X[n+4,-3]   =   0.0
-    X[n+4,-4]   =   2.0 - V*h**2/EI
-    X[n+4,-5]   =  -1.0
-
-    # Initialize vector q
-    q = np.zeros(N)
-    #M = H*abs(zlug)
-
-    # Populate q with boundary conditions
-    if zlug <= 0:
-        q[-3] = 2*H*h**3      # Shear at pile head
-        #q[-4] = M*h**2        # Moment at pile head
-    else:
-        q[zlug_index]      = 2*H*h**3     # Shear at pile head
-        #q[zlug_index + 1]  = M*h**2      # Moment at pile head
-               
-    y = linalg.solve(EI*X, q)
-
-    # Compute the plastic moment capacity Mp
-    Zp = (1/6)*(D**3 - (D - 2*t)**3)  # Plastic section modulus for hollow pile (m3)
-    Mp = Zp*fy                        # Plastic moment capacity (N/m)
-
-    # Check for plastic hinge formation
-    Mi, Mp, hinge_formed, hinge_location = plastic_hinge(y, h, EI, Mp)
-    
-    return y, Mi, Mp, hinge_formed, hinge_location
-
-###############################
-#### P-Y Curve Definitions ####
-###############################
-
-def py_Matlock(z, D, zlug, Su, sigma_v_eff, gamma, plot=True):
-    
-    '''Returns an interp1d interpolation function which represents the Matlock (1970) p-y curve at the depth of interest.
-    Important: Make sure to import the interp1 function by running 'from scipy.interpolate import interp1d' in the main program.
-
-    Input:
-    -----
-    z            - Depth relative to pile head (m)
-    D            - Pile diameter (m)
-    zlug         - Load eccentricity above the mudline or depth to mudline relative to the pile head (m)
-    Su           - Undrained shear strength (Pa)
-    sigma_v_eff  - Effective vertical stress (Pa)
-    gamma        - Effective unit weight of the soil (kN/m3)
-
-    Output:
-    ------
-    Returns an interp1d interpolation function which represents the p-y curve at the depth of interest.
-    'p' (N/m) and 'y' (m).
-    '''
-
-    from scipy.interpolate import interp1d
-    
-    z0 = 0
-    
-    # Strain at half the strength as defined by Matlock (1970). 
-    # Typically ranges from 0.005 (stiff clay) to 0.02 (soft clay).
-    epsilon_50 = 0.02          
-    # p-y curve properties
-    J = 0.5
-    
-    if zlug < 0:
-        # Scenario 1: zlug is negative (above mudline)
-        if (z - z0) < 0:
-            # No p-y curve between z = 0 and zlug
-            Nc = 0.0
-            z_cr = 1.0  # Dummy value to avoid crashing
-        else:
-            # Calculate p-y curve below zlug
-            Nc = 3.0 + sigma_v_eff/Su + J*(z - abs(zlug))/D
-            if Nc > 9.0: 
-                Nc = 9.0
-            z_cr = 6.0*D/(gamma*D/Su + J)
-
-    else:
-        # Scenario 2: zlug is positive (below mudline)
-        # Calculate p-y curve for the entire pile (all depths)
-        Nc = 3.0 + sigma_v_eff/Su + J*(z - zlug)/D
-        if Nc > 9.0: 
-            Nc = 9.0
-        z_cr = 6.0 * D/(gamma*D/Su + J)
-
-    p_ult = Su*Nc*D
-    y_50 = 2.5*epsilon_50*D
-
-    # Normalized lateral displacement
-    Y = np.concatenate((-np.logspace(3,-4,100),[0],np.logspace(-4,3,100)))
-
-    # Normalized p-y curves
-    P = 0.5*np.sign(Y)*abs(Y)**(1.0/3.0)  # sign(Y) and abs(Y) used since negative numbers cannot be raised to fractional powers
-                                          # Expression equivalent to P = 0.5*Y**(1.0/3.0) for Y>=0
-    for i in range(0,len(Y)):
-        if P[i] > 1.0:    P[i] = 1.0
-        elif P[i] < -1.0: P[i] = -1.0
-
-    # Un-normallized p-y curves
-    p = P*p_ult
-    y = Y*y_50
-
-    f = interp1d(y, p, kind='linear')   # Interpolation function for p-y curve
-
-    # Plot of p-y curve and check if 'k' is calculated correctly
-    if plot:
-        plt.plot(y, p,'-')
-        plt.xlabel('y (m)') 
-        plt.ylabel('p (N/m)')
-        plt.title('PY Curves - Matlock (1970)')
-        plt.grid(True)
-        plt.xlim([-2*D, 2*D])
-
-    return f   # This is f (linear interpolation of y-p)
-       
-def py_API(z, D, zlug, phi, sigma_v_eff, Dr, plot=True):
-    
-    '''Returns an interp1d interpolation function which represents the Matlock (1970) p-y curve at the depth of interest.
-
-    Important: Make sure to import the interp1 function by running 'from scipy.interpolate import interp1d' in the main program.
-
-    Input:
-    -----
-    z            - Depth relative to pile head (m)
-    D            - Pile diameter (m)
-    zlug         - Load eccentricity above the mudline or depth to mudline relative to the pile head (m)
-    phi          - Internal friction angle (deg)
-    sigma_v_eff  - Effectve vertical stress (Pa)
-
-    Output:
-    ------
-    Returns an interp1d interpolation function which represents the p-y curve at the depth of interest.
-    'p' (N/m) and 'y' (m).
-    '''
-    
-    from scipy.interpolate import interp1d
-       
-    # Interpolate coefficients depending on the effective friction angle
-    phi_ref = [  20,   25,   30,   35,   40]
-    C1_ref  = [0.80, 1.25, 1.90, 3.00, 4.50]
-    C2_ref  = [1.60, 2.10, 2.60, 3.40, 4.30]
-    C3_ref  = [  10,   15,   30,   55,  105]
-    
-    C1 = np.interp(phi, phi_ref, C1_ref)
-    C2 = np.interp(phi, phi_ref, C2_ref)
-    C3 = np.interp(phi, phi_ref, C3_ref)
-    
-    if (z - zlug) < 0:
-        # p-y curves for the virtual soil layer between the pile head and the mudline should have p=0
-        p_ult = 0.0
-    else:
-        try:
-            p_ult = min(C1*z + C2*D, C3*D)*sigma_v_eff
-        except ZeroDivisionError:
-            print("Division by zero! phi = 0.0 so z_cr cannot be calculated.")
-    
-    # Dr = 0.75     # Relative density of the soil (assumed)
-    k = (54.6*Dr**2 + 0.8*Dr + 1.8)*1e3
-    
-    # Normalized lateral displacement
-    N = 20
-    y = np.concatenate((-np.logspace(3,-4,N),[0],np.logspace(-4,3,N)))
-    A = max(3 - 0.8*z/D, 0.9)
-    ε = 1e-6
-    p = A*p_ult*np.tanh(k*z*y/(A*p_ult + ε))
-
-    f = interp1d(y, p, kind='linear')   # Interpolation function for p-y curve
-    
-    if plot:
-        # Plot of p-y curve and check if 'k' is calculated correctly
-        plt.plot(y, p,'-') 
-        plt.xlabel('y (m)') 
-        plt.ylabel('p (N/m)')
-        plt.title('PY Curves - API (1993)')
-        plt.grid(True)
-        plt.xlim([-0.10*D, 0.10*D])
-    # plt.ylim([min(y), max(y)])  # Adjust x-axis limits to match y values
-        
-    return f  # This is f (linear interpolation of y-p)
-
-########################
-#### Plastic Hinge #####
-########################
-
-def plastic_hinge(y, h, EI, Mp):
-    '''
-    Check for plastic hinge formation along the pile.
-    
-    Parameters:
-    ----------
-    y : ndarray
-        Lateral displacements at each node.
-    h : float
-        Element size (distance between nodes).
-    EI : float
-        Flexural rigidity of the pile (N*m²).
-    Mp : float
-        Plastic moment capacity of the pile section.
-    
-    Returns:
-    -------
-    Mp : float
-        Plastic moment of the pile section (Nm)
-    hinge_formed : bool
-        True if a plastic hinge forms, False otherwise.
-    hinge_location : int
-        Index of the node where the plastic hinge forms (if any).
-    '''
-    
-    hinge_formed = False
-    hinge_location = -1
-    Mi = []
-        
-    # Loop through each internal node and compute the bending moment
-    for i in range(1, len(y)-1):
-        # Approximate the bending moment at node i
-        Mint = EI*(y[i+1] - 2*y[i] + y[i-1])/h**2
-        Mi.append(Mint)
-        
-        # Check if the moment exceeds the plastic moment capacity
-        if Mint >= Mp:
-            hinge_formed = True
-            hinge_location = i
-            break  # Stop at the first plastic hinge formation
-    
-    return max(Mi), Mp, hinge_formed, hinge_location
-
-
-########################
-#### Soil Profiles #####
-########################
-
-def clay_profile(profile):
-    '''Define the clay profile used by the p-y analyzer. Outputs 'interp1d' functions containing Su and sigma'_v
-    profiles to be used by the p-y curve functions.
-
-    Input:
-    -----
-    profile      - A 2D tuple in the following format: ([Depth (m), Su (kPa), gamma (kN/m^3), py-model, model parameter])
-                   The soil profile should be defined relative to the pile/tower head (i.e. point of lateral load application)
-                   so that any load eccentricities can be taken into account. An example soil profile is shown below.
-                   Eg: array([[z0, Su0, gamma0, 'Matlock', 0.02],
-                              ...])
-
-                   *The current program cannot define layers with different p-y models. But it will added in the future.
-
-    Output:
-    ------
-    z0            - Depth of mudline relative to the pile head (m)
-    f_Su          - 'interp1d' function containing undrained shear strength profile (Pa)
-    f_sigma_v_eff - 'interp1d' function containing effective vertical stress profile (Pa)
-    f_gamma       - 'interp1d' function containing effective unit weight (kN/m3)
-    f_alpha       - Adhesion factor for clays
-    '''
-
-    from scipy.interpolate import interp1d
-
-    # Depth of mudline relative to pile head
-    z0 = float(profile[0][0])
-
-    # Extract data from profile array and zero strength virtual soil layer
-    # from the pile head down to the mudline
-    depth = np.concatenate([np.array([z0]),np.array([row[0] for row in profile],dtype=float)]) # m
-    Su    = np.concatenate([np.array([0]), np.array([row[1] for row in profile],dtype=float)]) # kPa
-    gamma = np.concatenate([np.array([0]), np.array([row[2] for row in profile],dtype=float)]) # kN/m3
-
-    # Calculate sigma_v_eff at each depth
-    sigma_v_eff = np.zeros(len(depth))
-
-    for i in range(1, len(depth)):
-        sigma_v_eff[i] = sigma_v_eff[i-1] + gamma[i-1]*(depth[i] - depth[i-1])
-
-    # Define interpolation functions
-    f_Su          = interp1d(depth, Su*1000, kind='linear')           # Pa
-    f_sigma_v_eff = interp1d(depth, sigma_v_eff*1000, kind='linear')  # Pa
-    f_gamma       = interp1d(depth, gamma*1000, kind='linear')        # N/m3
-    
-    # Calculate f_psi and f_alpha at each depth (not as a scalar)
-    f_psi = lambda z: f_Su(z) / f_sigma_v_eff(z)
-    
-    def calc_alpha(z):
-        psi_val = f_psi(z)
-        if psi_val <= 1.0:
-            return min(0.5*psi_val**-0.50, 1)
-        else:
-            return min(0.5*psi_val**-0.25, 1)
-
-    # Create an interpolated adhesion factor function
-    f_alpha = lambda z: calc_alpha(z)
-
-    return z0, f_Su, f_sigma_v_eff, f_gamma, f_alpha
-
-def sand_profile(profile):
-    '''Define the sand profile used by the p-y analyzer. Outputs 'interp1d' functions containing Su and sigma'_v
-    profiles to be used by the p-y curve functions.
-
-    Input:
-    -----
-    profile      - A 2D tuple in the following format: ([Depth (m), Su (kPa), gamma (kN/m^3), py-model, model parameter])
-                   The soil profile should be defined relative to the pile/tower head (i.e. point of lateral load application)
-                   so that any load eccentricities can be taken into account. An example soil profile is shown below.
-                   Eg: array([[z0, phi, gamma0, Dr, 'API', 0.02],
-                              ...])
-
-                   *The current program cannot define layers with different p-y models. But it will added in the future.
-
-    Output:
-    ------
-    z0            - Depth of mudline relative to the pile head (m)
-    f_phi         - 'interp1d' function containing effective friction angle (deg)
-    f_sigma_v_eff - 'interp1d' function containing effective vertical stress profile (Pa)
-    f_gamma       - 'interp1d' function containing effective unit weight (N/m3)
-    f_Dr          - Relative density of the soil (%)
-    f_delta       - Skin friction factor (sand/steel)
-    '''
-
-    from scipy.interpolate import interp1d
-
-    # Depth of mudline relative to pile head
-    z0 = float(profile[0][0])
-
-    # Extract data from profile array and zero strength virtual soil layer
-    # from the pile head down to the mudline
-    depth = np.concatenate([np.array([z0]),np.array([row[0] for row in profile],dtype=float)]) # m
-    phi   = np.concatenate([np.array([0]), np.array([row[1] for row in profile],dtype=float)]) # deg
-    gamma = np.concatenate([np.array([0]), np.array([row[2] for row in profile],dtype=float)]) # kN/m3
-    Dr    = np.concatenate([np.array([0]), np.array([row[3] for row in profile],dtype=float)]) # %
-   
-    # Calculate sigma_v_eff and static loading factor at each depth
-    sigma_v_eff = np.zeros(len(depth))
-
-    for i in range(1, len(depth)):  
-        sigma_v_eff[i] = sigma_v_eff[i-1] + gamma[i-1]*(depth[i] - depth[i-1])
-
-    # Define interpolation functions
-    f_phi         = interp1d(depth, phi, kind='linear')                    # deg
-    f_sigma_v_eff = interp1d(depth, sigma_v_eff*1000, kind='linear')       # Pa
-    f_gamma       = interp1d(depth, gamma*1000, kind='linear')             # N/m3
-    f_Dr          = interp1d(depth, Dr, kind='linear')                     # %
-    
-    # Define delta as a function of Dr
-    def calc_delta(Dr_val):
-        if 35 <= Dr_val < 50:
-            return 0.29
-        elif 50 <= Dr_val < 65:
-            return 0.37
-        elif 65 <= Dr_val < 85:
-            return 0.46
-        elif Dr_val >= 85:
-            return 0.56
-        else:
-            return 0  # Default or error value for very low Dr values
-        
-    # Apply delta calculation to Dr profile
-    delta_values = np.array([calc_delta(Dr_val) for Dr_val in Dr])
-    f_delta      = interp1d(depth, delta_values, kind='linear')  # Interpolated delta values
-    
-    return z0, f_phi, f_sigma_v_eff, f_gamma, f_Dr, f_delta
-
-if __name__ == '__main__':
-
-    # CLAY
-    profile = np.array([[ 0.0,  10, 8],
-                        [75.0, 245, 5]])
-    # SAND
-    # profile = np.array([[ 0.0, 32, 8, 75],
-    #                     [75.0, 38, 9, 85]])  
-                       
-    L = 20
-    D = 1.5
-    zlug = 5*D
-    
-    H0 = 4260000
-    V0 = 1590000
-
-    H = 1e6; V = 1e6
-
-    values_H =[]; values_V =[]      
-    
-    y, z, results = getCapacityDrivenSoil(profile, soil_type='clay', L=L, D=D, zlug=zlug, V=V, H=H)
-
-    # while results['Lateral displacement']<= 0.05*D and results['Rotational displacement'] <= 0.25:
-               
-    #     y, z, results = getCapacityDrivenSoil(profile, soil_type='clay', L=L, D=D, zlug=zlug, V=V, H=H)
-        
-    #     H += 10000
-                   
-    # values_H.append(H); H_ratio = np.array(values_H)/H0       
-   
-    while results['Lateral displacement']<= 0.05*D and results['Bending moment'] <= results['Plastic moment']:
-               
-        y, z, results = getCapacityDrivenSoil(profile, soil_type='sand', L=L, D=D, zlug=zlug, V=V, H=H)
-        
-        H += 100000
-                   
-    values_H.append(H); H_ratio = np.array(values_H)/H0
-    
-    # y, z, results = getCapacityDrivenSoil(profile, soil_type='sand', L=L, D=D, zlug=zlug, V=V, H=H)
-    
-        
-    y0 = np.zeros(len(z))
-    #Plot deflection profile of pile
-    fig, ax = plt.subplots(figsize=(3,5))    
-    ax.plot(y0,z,'black')
-    ax.plot(y,z,'r')
-    ax.set_xlabel('Displacement [m]')
-    ax.set_ylabel('Depth below pile head [m]')
-    ax.set_ylim([L + 2,-2])
-    ax.set_xlim([-0.1*D, 0.1*D])
-    ax.grid(ls='--')
-    fig.show()
\ No newline at end of file
diff --git a/famodel/anchors/anchors_famodel/capacity_helical.py b/famodel/anchors/anchors_famodel/capacity_helical.py
index 0ccae2f4..f88fe892 100644
--- a/famodel/anchors/anchors_famodel/capacity_helical.py
+++ b/famodel/anchors/anchors_famodel/capacity_helical.py
@@ -1,93 +1,173 @@
 
 import numpy as np
+from .capacity_driven import getCapacityDriven, plot_pile
+from .support_soils import clay_profile, sand_profile
+from .support_plots import plot_helical
+
+def getCapacityHelical(profile_map, location_name, D, L, d, zlug, Ha, Va, plot=False, display=0):
+    '''Calculate the vertical and horizontal capacity of a helical pile using a soil profile.
+    The calculation is based on the soil profile, anchor geometry and inclined load.
 
-def getCapacityHelical(D, L, d, zlug, soil_type, gamma, Su0=None, k=None, phi=None, Dr=None):
-    
-    '''Calculate the inclined vertical load capacity of a helical pile in clay.
-    The calculation is based on the soil properties and anchor geometry.  
-    
     Parameters
     ----------
+    profile : array
+        Soil profiles (z, parameters)
+            Clay soil profile (z, Su, gamma)
+            Sand soil profile (z, phi, gamma, Dr)
+    soil_type : string
+        Select soil condition, 'clay' or 'sand'
     D : float 
-        Helix diameter [m]
+        Helix diameter (m)
     L : float 
-        Length shaft [m]
+        Shaft length (m)
     d : float 
-        Pile shaft diameter [m]
+        Shaft diameter (m)
     zlug : float
-        Embedded depth of the lug [m]
-    soil_type : string
-        Select soil condition, 'clay' or 'sand' 
-    gamma: float 
-        Effective unit weight of the soil [kN/m3] 
-    Su0 : float 
-        Undrained shear strength at the mudline (clay only) [kPa]
-    k : float 
-        Undrained shear strength gradient (clay only) [kPa/m]
-    phi : float
-        Angle of internal friction (sand only) [deg]
-    Dr : float
-        Relative density of the soil (%) (sand only) [-] 
-    
-    
+        Depth to padeye (m)
+    Ha : float
+        Horizontal load applied at padeye (N)
+    Va : float
+        Vertical load applied at padeye (N)
+    plot : bool
+        Plot the p-y curve and the deflection pile condition if True
+
     Returns
     -------
-    Qu: float
-       Maximum vertical capacity [kN]    
+    y : array
+        Lateral displacement at each node (real nodes only)
+    z : array
+        Node depth positions corresponding to y (m)
+    resultsHelical : dict
+        Dictionary containing displacements, moment capacity, hinge state and vertical capacity
     '''
-    
-    rhos= 78.50                      # Dry steel unit weight (kN/m3)
-    t = (6.35 + D*20)/1e3            # Suction pile wall thickness (m), API RP2A-WSD
-    
-    # Dry and wet mass of the pile    
+
+    profile_entry = next(p for p in profile_map if p['name'] == location_name)
+    layers = profile_entry['layers']
+
+    t = (6.35 + D*20)/1e3            # Helical pile wall thickness (m), API RP2A-WSD
+    rhows = 66.90e3                  # Submerged steel specific weight (kN/m3)
+    rhow = 10e3                      # Water specific weight (kN/m3) 
+
     def PileWeight(Len, Dia1, Dia2, tw, rho):
-        Wp = ((np.pi/4)*((Dia1**2 - (Dia1 - 2*tw)**2)*Len + (np.pi/4)*Dia2**2*tw))*rho
-        return Wp
-    # Define alpha coefficient (clay)
-    if soil_type == 'clay':
-        Su_av_L = Su0 + k*(L - D)        # Undrained shear strength values (average)
-        sigma_v_eff = gamma*zlug         # Effective soil stress (kN/m2)
-        psi_val = Su_av_L/sigma_v_eff    # Su/p0' for point in question (API DP 2A-WSD)   
-        if psi_val <= 1.0:
-            alpha = min(0.5*psi_val**-0.50, 1)
-        else:
-            alpha = min(0.5*psi_val**-0.25, 1)
+        return ((np.pi/4)*((Dia1**2 - (Dia1 - 2*tw)**2)*Len + (np.pi/4)*Dia2**2*tw))*rho
+
+    z_helix = zlug + (L - D)
+    matched_layer = next((layer for layer in layers if layer['top'] <= z_helix <= layer['bottom']), None)
+    if matched_layer is None:
+        raise ValueError(f"No soil layer found at z = {z_helix:.2f} m")
+
+    if matched_layer['soil_type'] == 'clay':
+        profile = [[matched_layer['top'],    matched_layer['Su_top'], matched_layer['gamma_top']],
+                   [matched_layer['bottom'], matched_layer['Su_bot'], matched_layer['gamma_bot']]]
+        z0, f_Su, f_sigma_v_eff, f_gamma, f_alpha = clay_profile(profile)
+
+        z_helix = np.clip(z_helix, matched_layer['top'], matched_layer['bottom'])
+        Su = f_Su(z_helix)
+        sigma_v_eff = max(f_sigma_v_eff(z_helix), 1.0)
+        psi_val = Su/sigma_v_eff
+        alpha = min(0.5*psi_val**-0.50, 1) if psi_val <= 1.0 else min(0.5 * psi_val**-0.25, 1)
+
+        Nc = min(6.0*(1 + 0.2*d/D), 9)
+        Qh = ((np.pi/4)*(D**2 - d**2)*Nc*Su + f_gamma(z_helix)*D)*0.75
+        Qs = np.pi*d*L*alpha*Su
+        Qu = PileWeight(L, D, d, t, rhows) + Qh + Qs
+
+    elif matched_layer['soil_type'] == 'sand':
+        profile = [[matched_layer['top'],    matched_layer['phi_top'], matched_layer['gamma_top'], matched_layer['Dr_top']],
+                   [matched_layer['bottom'], matched_layer['phi_bot'], matched_layer['gamma_bot'], matched_layer['Dr_bot']]]
+        z0, f_phi, f_sigma_v_eff, f_gamma, f_Dr, f_delta = sand_profile(profile)
+
+        z_helix = np.clip(z_helix, matched_layer['top'], matched_layer['bottom'])
+        gamma = f_gamma(z_helix)
+        Dr = f_Dr(z_helix)
+        delta = f_delta(z_helix)
+        phi = f_phi(z_helix)
+
+        Nq = 0.5*(12*phi)**(phi/54)
+        Qh = (np.pi/4)*(D**2 - d**2)*Nq*gamma*z_helix
+        Qs = np.pi*d*L*delta*gamma*z_helix
+        Qu = PileWeight(L, D, d, t, rhows) + Qh + Qs
         
-    # Define delta as a function of Dr (sand)
-    def calc_delta(Dr_val):
-        if 35 <= Dr_val < 50:
-            return 0.29
-        elif 50 <= Dr_val < 65:
-            return 0.37
-        elif 65 <= Dr_val < 85:
-            return 0.46
-        elif Dr_val >= 85:
-            return 0.56
+    
+    Wp = PileWeight(L, D, d, t, (rhows + rhow))    
+
+    # Unity Check based only on vertical capacity
+    UC_vertical = Va/Qu
+
+    # Compute horizontal capacity using p-y method
+    layers, y, z, results_lateral = getCapacityDriven(profile_map, location_name, D, L, zlug, Ha, Va, plot=False)
+    # Plotting
+    if plot:
+        plot_pile(layers, y, z, D, L, z0=layers[0]['top'], zlug=zlug, hinge_location=None)
+
+    Hcap = results_lateral['Horizontal max.']
+    UC_horizontal = Ha/Hcap if Hcap != 0 else np.inf
+
+    resultsHelical = {     
+        'Horizontal max.': Hcap,
+        'Vertical max.': Qu,
+        'Lateral displacement': results_lateral['Lateral displacement'],
+        'Rotational displacement': results_lateral['Rotational displacement'],
+        'Unity check (horizontal)': UC_horizontal,
+        'Unity Check (vertical)': UC_vertical,
+        'Weight pile': Wp,}
+
+    if matched_layer['soil_type'] == 'clay':
+        resultsHelical['Su @ helix'] = Su
+        resultsHelical['alpha'] = alpha
+    elif matched_layer['soil_type'] == 'sand':
+        resultsHelical['Dr @ helix'] = Dr
+        resultsHelical['delta'] = delta
+        resultsHelical['phi'] = phi
+
+    return layers, resultsHelical
+
+if __name__ == '__main__':
+    
+    profile_map = [
+        {
+            'name': 'CPT_1',
+            'x': 498234, 'y': 5725141,
+            'layers': [
+                {
+                    'top': 1.0, 'bottom': 3.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.0, 'gamma_bot': 9.0,
+                    'Su_top': 60, 'Su_bot': 50},
+                # {
+                #     'top': 3.0, 'bottom': 7.0,
+                #     'soil_type': 'clay',
+                #     'gamma_top': 15.0, 'gamma_bot': 25.0,
+                #     'Su_top': 100, 'Su_bot': 150},
+                {
+                    'top': 3.0, 'bottom': 7.0,
+                    'soil_type': 'sand',
+                    'gamma_top': 8.0, 'gamma_bot': 8.0,
+                    'phi_top': 32, 'phi_bot': 38,
+                    'Dr_top': 70, 'Dr_bot': 75},
+                {
+                    'top': 7.0, 'bottom': 15.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 25.0, 'gamma_bot': 50.0,
+                    'Su_top': 200, 'Su_bot': 400}]
+        }
+    ]  
+
+    D = 1.5        # Helix diameter (m)
+    L = 12.0       # Pile length (m)
+    d = 0.5        # Shaft diameter (m)
+    zlug = 3       # Padeye depth (m)
+    Ha = 30e3      # Horizontal load (N)
+    Va = 50e3      # Vertical load (N)
+
+    layers, resultsHelical = getCapacityHelical(profile_map, 'CPT_1', D, L, d, zlug, Ha, Va, plot=True)
+    for key, val in resultsHelical.items():
+        if isinstance(val, float):
+            print(f"{key}: {val:.3f}")
         else:
-            return 0  # Default or error value for very low Dr values        
-        
-    Wp = PileWeight(L, D, d, t, rhos) 
+            print(f"{key}: {val}")
     
-    # ----- Clay case -----
-    if soil_type == 'clay':       
-        Nc = 6.0*(1 + 0.2*d/D); 
-        Nc = np.where(Nc < 9, Nc, 9)
-        # Su is calculated, at the depth of the helix minus one helical plate diameter
-        # A reduction of 25% is applied for a moderately sensitive clay
-        Qh = ((np.pi/4)*(D**2 - d**2)*Nc*(Su0 + k*(L - D)) + gamma*D)*0.75 
-        Qs = np.pi*d*L*alpha*(Su0 + k*(L - D))
-        Qu = Qh + Qs
-                
-    # ----- Sand case -----
-    else:   
-        delta = calc_delta(Dr)
-        Nq = 0.5*(12*phi)**(phi/54) 
-        Qh = (np.pi/4)*(D**2 - d**2)*Nq*gamma*L
-        Qs = np.pi*d*L*delta*gamma*L
-        Qu = Qh + Qs
-                  
-    resultsHelical = {}
-    resultsHelical['Capacity'] = Qu          # Vertical capacity 
-    resultsHelical['Weight'] = Wp       # Dry weight of the helical pile (kN)
-
-    return resultsHelical
\ No newline at end of file
+    plot_helical(layers, D=D, L=L, d=d, z0=layers[0]['top'], zlug=zlug, n_helix=1, spacing=1.0)
+  
+
+
diff --git a/famodel/anchors/anchors_famodel/capacity_load.py b/famodel/anchors/anchors_famodel/capacity_load.py
index 33553bdd..cece7f19 100644
--- a/famodel/anchors/anchors_famodel/capacity_load.py
+++ b/famodel/anchors/anchors_famodel/capacity_load.py
@@ -1,225 +1,210 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Wed May 29 15:53:52 2024
 
-@author: fmoreno
-"""
-
-import yaml      # Allow access to config file for user inputs
 import numpy as np
 import matplotlib.pyplot as plt
-from scipy.optimize import fsolve
+from .support_soils import clay_profile, sand_profile
+from .support_plots import plot_load
 
+def getTransferLoad(profile_map, Tm, thetam, zlug, line_type, d, w=None, plot=False, display=0):
+    '''Calculate the transfer load from mudline to main padeye using a layered soil profile.
 
-def getAnchorLoad(Tm, thetam, zlug, d, soil_type, gamma, Su0, k):
-    
-    '''Calculate the inclined load capacity of a Suction Caisson Anchor in sand or clay.
-    The calculation is based on the soil properties, anchor geometry, and the angle of inclined load.
-    Offshore Geotechnical Engineering (Randolph , page 323)
-    
     Parameters
     ----------
-    Tm : float 
-        Mooring line load at mudlevel [kN]
-    thetam : float 
-        Mooring line angle at mudlevel [deg]
-    zlug : float 
-        Embedded depth of the lug [m]
-    soil_type: string
-        Select soil condition, 'clay' or 'sand'
+    profile_map : list of dicts
+        Soil profile in profile_map format
+    Tm : float
+        Mooring line load at mudlevel (N)
+    thetam : float
+        Mooring line angle at mudlevel (deg)
+    zlug : float
+        Embedment depth of the lug (m)
+    line_type : str
+        'chain' or 'wire'
     d : float
-        Chain diameter [m]
-    Su0 : float 
-        Undrained shear strength at the mudline (clay) [kPa]
-    k : float 
-        Undrained shear strength gradient (clay) [kPa/m]
-  
-    Returns
-    -------
-    Ta : float 
-        Inclined load magnitude at the anchor lug [kN]
-    thetaa : float 
-        Inclined load angle at the anchor lug [deg]
-    '''
-    
-    # Setting bearing capacity values per soil type
-    if soil_type == 'clay':
-        Nc = 8.5; Ab=2.5; nhu=0.40   # Nc    - Bearing capacity factor (9 and 14) DNV-RP-E301 
-    elif soil_type == 'sand':        # Ab    - Effective unit bearing area (2.5 - 2.6 times chain dia)
-        Nc = 9; Ab=2.5; nhu=0.35     # nhu   - Friction coefficient between the mooring line and soil
-        
-    thetam =  np.radians(thetam)
-    
-    if soil_type == 'clay':                           
-        Su_av_lug = Su0*zlug + k*zlug**2/2
-        zaQav = Ab*d*Nc*Su_av_lug
-        
-    elif soil_type == 'sand':
-        zaQav = Ab*d*Nc*gamma*zlug**2/2
-        
-    def LoadTransfer(beta):
-        return(2*zaQav*np.e**(nhu*(beta - thetam)) - Tm*(beta**2 - thetam**2))
-    
-    thetaa = fsolve(LoadTransfer, thetam) 
-    thetaa = thetaa[0] 
-    Ta = Tm/(np.e**(nhu*(thetaa - thetam)))
-    
-    H = Ta*np.cos(thetaa) 
-    V = Ta*np.sin(thetaa)
-       
-    resultsLoad = {}
-    resultsLoad['load'] = Ta                   # Load magnitude @ lug
-    resultsLoad['angle'] = np.rad2deg(thetaa)  # Load angle @ lug
-    resultsLoad['H'] = H                       # Horizontal component @ lug
-    resultsLoad['V'] = V                       # Vertical component @ lug
-    
-    return resultsLoad
-
-def getTransferLoad(Tm, thetam, zlug, line_type, d, soil_type, Su0=None, 
-    k=None, gamma=None, phi= None, delta=None, w=None, plot=False):
-    '''Calculate the transfer load from the mudline to the main padeye 
-    elevation using the DNV standards. The calculation is based on the 
-    mooring line properties, anchor geometry and the load from MoorPy and 
-    RAFT.
-    
-    Parameters
-    ----------
-    Tm : float 
-        Mooring line load at mudlevel [kN]
-    thetam : float 
-        Mooring line angle at mudlevel [deg]
-    zlug : float 
-        Embedded depth of the lug [m]
-    line_type = string
-        Select line type, 'chain' or 'wire'
-    d : float
-        Chain diameter [m]
-    soil_type = string
-        Select soil condition, 'clay' or 'sand'  
-    Su0 : float 
-        Undrained shear strength at the mudline (clay only) [Pa]
-    k : float 
-        Undrained shear strength gradient (clay only) [Pa/m]
-    gamma: float
-        Effective unit weight of the soil (sand only) [N/m3]
-    phi : float
-        Friction angle (sand only) [deg]
-    delta: float
-        Interface friction angle at soil-anchor line (sand only) [deg]
+        Chain diameter (m)
     w : float
-        Mooring line unit weight [N/m]
-    
+        Mooring line unit weight (N/m)
+    plot : bool
+        Show plot
+
     Returns
     -------
-    Ta : float 
-        Inclined load magnitude at the anchor lug [kN]
-    thetaa : float 
-        Inclined load angle at the anchor lug [deg]
+    dict
+        Dictionary with transferred load components and depth.
     '''
-    
-    deltas = 0.2
-      
-    # Include element weight in terms of d and match it with deltas
-    if line_type == 'chain':   
-        Et = 10; En = 2.5;  W = w*deltas; 
+
+    deltas = 0.2  # discretization step
+
+    # Line mechanical properties
+    if line_type == 'chain':
+        Et, En = 10, 2.5
     elif line_type == 'wire':
-        Et = np.pi; En = 1; W = w*deltas;
-    
-    T = Tm; theta = np.deg2rad(thetam);
-    Su = Su0; 
-    drag = 0; depth = 0.1
-         
-    T_values = []; Su_values = [];
-    drag_values = []; depth_values = []; 
+        Et, En = np.pi, 1
+    W = w*deltas
+
+    # Soil layer access
+    layers = profile_map[0]['layers']
+    z0 = min(layer['top'] for layer in layers)
+    Nc = 8.5
+    
+    if all(layer['soil_type'] in ['rock', 'weak_rock'] for layer in layers):
+        if display > 0: print('[Bypass] Skipping load transfer — soil is all rock.')
+        Ha = Tm*np.cos(np.deg2rad(thetam)) 
+        Va = Tm*np.cos(np.deg2rad(thetam))
+        return Ha, Va
+
+    # Initial values
+    z0 = min(layer['top'] for layer in layers)
+    T = Tm
+    theta = np.deg2rad(thetam)
+    drag = 0
+    depth = z0 + 0.01
+
+    # Tracing lists
+    drag_values, depth_values = [], []
     
-    # Setting bearing capacity values per soil type
-    if soil_type == 'clay':
-        Nc = 8.5; alpha = 0.7;
-    elif soil_type == 'sand':
-        nhu = 0.5
-        Nq = np.exp(np.pi*np.tan(np.deg2rad(phi)))*(np.tan(np.deg2rad(45 + phi/2)))**2
-        # print(Nq)
-        
     while (zlug - depth) >= 0:
-        if soil_type =='clay':
-            dtheta = (En*d*Nc*Su - W*np.cos(theta))/T*deltas
-            dT = (Et*d*alpha*Su  + W*np.sin(theta))*deltas
-            
-        elif soil_type =='sand':
-            dtheta  = (En*d*Nq*gamma*depth - W*np.cos(theta))/T*deltas
-            dT = (Et*d*gamma*depth*np.tan(np.rad2deg(delta)) + W*np.sin(theta))*deltas 
+        matched_layer = next((layer for layer in layers if layer['top'] <= depth <= layer['bottom']), None)
+        if matched_layer is None:
+            break
         
-        ddrag  = deltas*np.cos(theta)
-        ddepth = deltas*np.sin(theta)
-        theta += dtheta; T -= dT;
-        
-        drag += ddrag; depth += ddepth
-        if Su:
-            Su = Su0 + k*depth
-                
-        # Ensure consistency in load transfer
-        if abs(Tm - T) > 0.75*Tm:  # More than 75% loss
-            raise Exception(f"Warning: Load transfer is unrealistic. Initial load Tm = {Tm/1e6:.2f} MN and current load T = {T/1e6:.2f} MN differ by more than 75 %")
-            break  # Exit the loop if load transfer is unrealistic
+        if matched_layer['soil_type'] == 'clay':
+            matched_layer = next((layer for layer in layers if layer['soil_type'] == 'clay' and layer['top'] <= depth <= layer['bottom']), None)
+            if matched_layer is None:
+                break
+            profile = [[matched_layer['top'],    matched_layer['gamma_top'], matched_layer['Su_top']],
+                       [matched_layer['bottom'], matched_layer['gamma_bot'], matched_layer['Su_bot']]]
+            z0_local, f_gamma, f_Su, f_sigma_v_eff, f_alpha = clay_profile(profile)
+
+            Su = f_Su(depth)
+            alpha = f_alpha(depth)
+            d_theta = (En*d*Nc*Su - W*np.cos(theta))/T*deltas
+            dT = (Et*d*alpha*Su + W*np.sin(theta))*deltas
+
+        elif matched_layer['soil_type'] == 'sand':
+            matched_layer = next((layer for layer in layers if layer['soil_type'] == 'sand' and layer['top'] <= depth <= layer['bottom']), None)
+            if matched_layer is None:
+                break
             
-        # Check for excessive load angles
-        if not (0 < np.rad2deg(theta) < 90):
-            raise Exception(f"Warning: Load angle is unrealistic: {np.rad2deg(theta):.2f} deg")
-            break  # Exit the loop if the angle becomes unreasonable   
+            profile = [[matched_layer['top'],    matched_layer['gamma_top'], matched_layer['phi_top'], matched_layer['Dr_top']],
+                       [matched_layer['bottom'], matched_layer['gamma_bot'], matched_layer['phi_bot'], matched_layer['Dr_bot']]]
+            z0_local, f_gamma, f_phi, f_Dr, f_sigma_v_eff, f_delta = sand_profile(profile)
+
+            gamma_z = f_gamma(depth)
+            delta_z = f_delta(depth)
+            phi = f_phi(depth)
+            Nq = np.exp(np.pi*np.tan(np.deg2rad(phi)))*(np.tan(np.deg2rad(45 + phi/2)))**2
+            if display > 0: print(f'Nq = {Nq:.2f}, depth = {depth:.2f} m')
+            d_theta = (En*d*Nq*gamma_z*depth - W*np.cos(theta))/T*deltas
+            dT = (Et*d*gamma_z*depth*np.tan(np.deg2rad(delta_z)) + W*np.sin(theta))*deltas
             
-        T_values.append(T); Su_values.append(Su)
-        drag_values.append(drag); depth_values.append(depth); 
-               
-    Ta = T; thetaa = theta 
-    # print(thetaa); print(Ta)
-    H = Ta*np.cos(thetaa); V = Ta*np.sin(thetaa) 
-    length_values = deltas*len(drag_values)
-     
-    resultsLoad = {}
-    resultsLoad['diff'] = (Tm - Ta)/1e6        # Difference
-    resultsLoad['load'] = Ta/1e6               # Load magnitude @ lug
-    resultsLoad['angle'] = np.rad2deg(thetaa)  # Load angle @ lug
-    resultsLoad['H'] = H                       # Horizontal component @ lug
-    resultsLoad['V'] = V                       # Vertical component @ lug
-    resultsLoad['length'] = length_values      # Length of the embedded line
-    
-    # Plot of the line and extreme line tension
-    drag_values = [-1*i for i in drag_values]
-    depth_values = [-1*j for j in depth_values]
-    
-    if plot:
-        fig, ax = plt.subplots(figsize=(20, 5)); n = 2000000
-        ax.scatter(drag_values[-1], depth_values[-1], color='g', zorder=5)
-        ax.scatter(0, 0, color='r', zorder=4)
-        ax.arrow(0, 0, Tm*np.cos(np.deg2rad(thetam))/n, Tm*np.sin(np.deg2rad(thetam))/n,
-              head_width=0.25, head_length=0.5, color='r', zorder=3)
-        ax.arrow(drag_values[-1], depth_values[-1], Ta*np.cos(thetaa)/n, Ta*np.sin(thetaa)/n,
-              head_width=0.25, head_length=0.5, color='g',zorder=2)
-        ax.plot(drag_values, depth_values,color='b', zorder=1)
-         
-        #Set labels and title
-        plt.xlabel('Drag distance [m]')
-        plt.ylabel('Embedded depth [m]')
-        plt.suptitle('Inverse catenary profile in soil DNV')
-        plt.grid(True)
-    
-    return resultsLoad
+        elif matched_layer['soil_type'] in ['rock', 'weak_rock']:
+            raise ValueError(f"Unsupported soil type: {matched_layer['soil_type']}. Mooring line cannot be embedded in rock.")
+
+        d_drag  = deltas*np.cos(theta)
+        d_depth = deltas*np.sin(theta)
+
+        theta += d_theta
+        T -= dT
+        drag += d_drag
+        depth += d_depth
+
+        if not (0 < np.rad2deg(theta) < 90):
+            if display > 0: print(f"[Warning] Line angle reached {np.rad2deg(theta):.2f}°, stopping at drag = {-drag:.2f} m")
+            break
+
+        drag_values.append(-drag); 
+        depth_values.append(-depth); 
+
+    if np.rad2deg(theta) >= 90:
+        if display > 0: print(f"[Correction] Clipping angle to 90° to avoid negative horizontal load (Ha).")
+        theta = np.deg2rad(90)
+    Ta = T; thetaa = theta
+    Hm = Tm*np.cos(np.deg2rad(thetam)); Vm = Tm*np.sin(np.deg2rad(thetam))
+    Ha = Ta*np.cos(thetaa); Va = Ta*np.sin(thetaa)
+    
+    if display > 0: print(f'Input Tm = {Tm} N, thetam = {thetam}°, zlug = {zlug} m')
+    if display > 0: print(f'Output Hm = {Hm} N, Vm = {Vm} N')
+    if display > 0: print(f'Output Ta = {Ta} N, thetaa = {np.rad2deg(thetaa)}°')
+    if display > 0: print(f'Output Ha = {Ha} N, Va = {Va} N')
+
+    resultsLoad = {
+        'Tm': Tm, 'thetam': thetam,
+        'Hm': Hm, 'Vm': Vm,
+        'Ta': Ta, 'thetaa': np.rad2deg(thetaa),
+        'Ha': Hm, 'Va': Va,
+        'length': deltas*len(drag_values),
+        'drag_values': drag_values,
+        'depth_values': depth_values}
+
+    return layers, resultsLoad
 
 
 if __name__ == '__main__':
-    
-    Tm = 1.16e6 
-    thetam = 0
-    zlug = 10
-    line_type ='chain'
-    d = 0.160
-    soil_type ='sand'
-    Su0 = 2.4*1e3
-    k = 1.41*1e3
-    gamma = 9e3
-    phi = 35
-    delta = 27
-    w = 4093
-
-    resultsDNV = getTransferLoad(Tm, thetam, zlug, line_type, d, soil_type, Su0, k, gamma, phi, delta, w)
-    #results = getAnchorLoad(Tm, thetam, zlug, d, soil_type, gamma, Su0, k)
\ No newline at end of file
+
+    # profile_map = [
+    #     {
+    #         'name': 'CPT_1',
+    #         'x': 498234, 'y': 5725141,
+    #         'layers': [
+    #             {
+    #                 'top': 1.0, 'bottom': 2.0,
+    #                 'soil_type': 'clay',
+    #                 'gamma_top': 8.0, 'gamma_bot': 8.0,
+    #                 'Su_top': 10, 'Su_bot': 25},
+    #             {
+    #                 'top': 2.0, 'bottom': 8.0,
+    #                 'soil_type': 'clay',
+    #                 'gamma_top': 8.0, 'gamma_bot': 8.0,
+    #                 'Su_top': 25, 'Su_bot': 50},
+    #             {
+    #                 'top': 8.0, 'bottom': 16.0,
+    #                 'soil_type': 'clay',
+    #                 'gamma_top': 8.0, 'gamma_bot': 8.0,
+    #                 'Su_top': 50, 'Su_bot': 100}
+    #         ]
+    #     }
+    # ]
+    profile_map = [
+        {
+            'name': 'CPT_1',
+            'x': 498234, 'y': 5725141,
+            'layers': [
+                # {
+                #     'top': 0.0, 'bottom': 5.0,
+                #     'soil_type': 'sand',
+                #     'gamma_top': 9.5, 'gamma_bot': 9.5,
+                #     'phi_top': 28, 'phi_bot': 30,
+                #     'Dr_top': 70, 'Dr_bot': 70},
+                {
+                    'top': 0.0, 'bottom': 5.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.0, 'gamma_bot': 8.0,
+                    'Su_top': 25, 'Su_bot': 25},
+                # {
+                #     'top': 0.0, 'bottom': 3.0,
+                #     'soil_type': 'sand',
+                #     'gamma_top': 9.5, 'gamma_bot': 9.5,
+                #     'phi_top': 30, 'phi_bot': 38,
+                #     'Dr_top': 65, 'Dr_bot': 75},
+                {
+                    'top': 5.0, 'bottom': 15.0,
+                    'soil_type': 'sand',
+                    'gamma_top': 9.5, 'gamma_bot': 9.5,
+                    'phi_top': 35, 'phi_bot': 40,
+                    'Dr_top': 77, 'Dr_bot': 85}
+            ]
+        }
+    ]
+
+    Tm = 4978442          # Load at mudline (N)
+    thetam = 30           # Angle at mudline (deg)
+    zlug = 8.5            # Padeye depth (m)
+    line_type = 'chain'
+    d = 0.25              # Chain diameter (m)
+    w = 5000              # Line weight (N/m)
+
+    layers, resultsLoad = getTransferLoad(profile_map, Tm, thetam, zlug, line_type, d, w, plot=True, display=1)
+
+    plot_load(layers, resultsLoad['drag_values'], resultsLoad['depth_values'], 
+              resultsLoad['Tm'], resultsLoad['thetam'], resultsLoad['Ta'], 
+              resultsLoad['thetaa'], zlug=zlug)
\ No newline at end of file
diff --git a/famodel/anchors/anchors_famodel/capacity_plate.py b/famodel/anchors/anchors_famodel/capacity_plate.py
index bc371ff7..59a1f91d 100644
--- a/famodel/anchors/anchors_famodel/capacity_plate.py
+++ b/famodel/anchors/anchors_famodel/capacity_plate.py
@@ -1,102 +1,177 @@
 
 import numpy as np
+import matplotlib.pyplot as plt
+from .support_soils import clay_profile
+from .support_plots import plot_plate
+
+def getCapacityPlate(profile_map, location_name, B, L, zlug, beta, Ha, Va, plot=False, display=0):
+    '''Calculate the plate anchor capacity using clay soil layers from profile_map.
+    The calculation is based on the soil profile, anchor geometry and inclined load.
 
-def getCapacityPlate(A, beta, zlug, soil_type, gamma, Su0=None, k=None):
-    
-    '''Calculate the inclined load capacity of a plate in clay at a given depth.
-    The calculation is based on the soil properties, anchor geometry and the angle of inclined load.
-    The plate is assumed to be inclined perpendicular to the tension at the main padeye depth.     
-    
     Parameters
     ----------
-    A : float 
-        Plate area, assumed to be square so that width B = sqrt(A). [m^2]
+    profile_map : list of dict
+        Soil profile map with coordinates and layers per location.
+    location_name : str
+        Name of the location to select the soil profile.
+    B : float
+        Plate width (m)
+    L : float
+        Plate length (m)
+    zlug : float
+        Embedment depth of the main padeye (m)
     beta : float
-        Angle of the plate after keying process [deg]
-    zlug: float
-        Embedded depth of the main padeye [m]
-    soil_type : string
-        Specify 'sand' or 'clay'. This affects what other soil parameters are used.
-    gamma: float 
-        Effective unit weight of the soil [kN/m3] 
-    Su0 : float 
-        Undrained shear strength at the mudline [kPa]
-    k : float 
-        Undrained shear strength gradient [kPa/m]
-   
+        Inclination angle of the plate (deg)
+    Ha : float
+        Applied horizontal load (N)
+    Va : float
+        Applied vertical load (N)
+    plot : bool
+        Whether to generate plots.
+
     Returns
     -------
-    Tmax: float
-       Maximum capacity [kN] 
+    Dictionary with Capacity, Weight, UC, etc.
     '''
-      
-
-    Los=0.05                   # Key lost fraction due to the keying process, default 0.05 (-)
-    rhos= 78.50                # Dry steel unit weight (kN/m3)
- 
-    B = round(np.sqrt(A),2)    # Anchor width (and length, approximated as square) (m)
-    zlug_B = zlug/B            # Anchor depth range/ width of the plate 
-    B_t = 40                   # Aspect ratio plate width to thickness, default is 40
-    t = round(B/B_t, 2)        # Thickness of the plate, which it depends on the width (m)
+
+    # Extract and filter clay layers from profile_map
+    profile_entry = next(p for p in profile_map if p['name'] == location_name)
+    layers = [layer for layer in profile_entry['layers'] if layer['soil_type'] == 'clay']
+
+    if not layers:
+        raise ValueError('Plate anchor capacity model only supports clay soils.')
+
+    # Build the profile array: [[z, Su, gamma], ...]
+    profile = []
+    for layer in layers:
+        profile.append([layer['top'], layer['gamma_top'], layer['Su_top']])
+        profile.append([layer['bottom'], layer['gamma_bot'], layer['Su_bot']])
+        
+    if display > 0: print("layer gamma_top (raw):", layer['gamma_top'])
+    if display > 0: print("layer gamma_bot (raw):", layer['gamma_bot'])
+
+    profile = np.array(sorted(profile, key=lambda x: x[0]))
+
+    # Parameters and constants
+    Los = 0.05
+    B_t = 40
+    rhows = 66.90e3  # Submerged steel (N/m3)
+    rhow = 10e3      # Seawater (N/m3)
+
+    # Evaluate interpolated Su and gamma
+    z0, f_gamma, f_Su, f_sigma_v_eff, f_alpha = clay_profile(profile)
+    t = round(B/B_t, 2)
+    V_steel = round(B*L*t, 2)
+    zlug_B = zlug/B
+
+    # Profile check points
+    npts = 10
+    z_offsets = np.linspace(-0.5, 0.5, npts)*B*np.sin(np.deg2rad(beta))
+    z_points = zlug + z_offsets; print(z_points)
+
+    Su_vals = [f_Su(z) for z in z_points]
+    gamma_10 = f_gamma(z_points[2]); print(gamma_10)
+    gamma_vals = [f_gamma(z) for z in z_points]; print("gamma_vals:", [f"{val:.2f}" for val in gamma_vals], "N/m3")
+    Su = np.mean(Su_vals); print(f"Su: {Su:.2f} Pa")
+    gamma = np.mean(gamma_vals); print(f"gamma: {gamma:.2f} N/m3")
     
-    #t=np.sqrt(0.006*A)/4  
-    V = round(A*t,2)           # Steel volume (m3)
-    W = V*rhos                 # Plate weight (kg)
-    Su = Su0 + k*zlug          # Undrained shear strength at plate depth
+    if display > 0: print("Profile being sent to clay_profile():")
+    for row in profile:
+        if display > 0: print(f"z = {row[0]:.2f} m, gamma = {row[1]:.2f} kN/m³, Su = {row[2]:.2f} kPa")
 
-    # ----- anchor pullout capacity -----
+    # Shear strength gradient
+    k = np.polyfit(z_points, Su_vals, 1)[0]
+    if display > 0: print(f"k: {k:.2f}")
 
-    # Anchor Pullout capacity factor in weightless clay with breakaway base, soil homogeneous
-    Nco_0_0  = 2.483*np.log(zlug_B) + 1.974  # angle = 0 deg 
-    Nco_90_0 = 2.174*np.log(zlug_B) + 3.391  # angle = 90 deg
+    # Pile weight including auxiliary parts
+    Wp = 1.35*V_steel*(rhows + rhow)
 
-    kBSh = k*B/Su              # Degree of soil non-homogeneity
+    # Capacity factors
+    Nco_0_0  = 2.483*np.log(zlug_B) + 1.974
+    Nco_90_0 = 2.174*np.log(zlug_B) + 3.391
+    kBSh = k*B/Su
+    if display > 0: print(f"kBSh: {kBSh:.2f}")
 
     f0  = np.where(zlug_B < 4, 1.77*(zlug_B**0.3) - 1.289, 0.192*zlug_B + 0.644)
-    f90 = np.where(zlug_B < 4, 0.68*(zlug_B**0.5) - 0.41 , 0.153*zlug_B + 0.341)
+    f90 = np.where(zlug_B < 4, 0.68*(zlug_B**0.5) - 0.410, 0.153*zlug_B + 0.341)
 
-    # Non-homogeneity adjustment factor for anchor ultimate pullout capacity
-    S_kB_0  = 1 - f0 *kBSh
+    S_kB_0  = 1 - f0*kBSh
     S_kB_90 = 1 - f90*kBSh
+    Nco_0  = S_kB_0*Nco_0_0
+    Nco_90 = S_kB_90*Nco_90_0
+    Nco = Nco_0 + (Nco_90 - Nco_0)*(beta/90)**2
 
-    # Anchor Pullout capacity factor in weightless clay with breakaway base, soil nonhomogeneous
-    Nco_0  = S_kB_0*Nco_0_0  
-    Nco_90 = S_kB_90*Nco_90_0 
-
-    # Anchor pullout capacity factor in weightless clay with no breakaway base 
-    Nco = Nco_0 + (Nco_90 - Nco_0)*(beta/90)**2   
-
-    # Uplift bearing capacity factor, soil homogeneous
     Nco_s_0_0  = np.where(2.90*zlug_B + 6.02 <= 11.59, 2.90*zlug_B + 6.02, 11.596)
     Nco_s_90_0 = np.where(2.72*zlug_B + 4.02 <= 11.59, 2.72*zlug_B + 4.02, 11.596)
 
-    # ----- ultimate anchor capacity factor -----
-    
-    # Non-homogeneity factor for anchor ultimate pullout capacity
-    S_s_kB_0 = np.where(zlug_B <= 2, 1 + (0.8 - 0.3*zlug_B)*kBSh - (0.383*kBSh**1.36), 1)  # Angle = 0
-
+    S_s_kB_0 = np.where(zlug_B <= 2, 1 + (0.8 - 0.3*zlug_B)*kBSh - (0.383*kBSh**1.36), 1)
     f90s = np.where(zlug_B <= 3, 0.267*zlug_B, 0.6)
-    S_s_kB_90 = 1 - f90s*kBSh  # Angle = 90
-
-    # Anchor ultimate holding capacity in with breakaway base, soil nonhomogeneous
-    Nco_s_0  = S_s_kB_0 *Nco_s_0_0
+    S_s_kB_90 = 1 - f90s*kBSh
+    Nco_s_0 = S_s_kB_0*Nco_s_0_0
     Nco_s_90 = S_s_kB_90*Nco_s_90_0
-
-    # Anchor ultimate holding capacity in with no breakaway base, soil nonhomogeneous
     Nco_s = Nco_s_90 + (Nco_s_0 - Nco_s_90)*((90 - beta)/90)**2
 
-
-    # ----- final results -----
-    Nc_final = np.minimum(Nco + (gamma*zlug)/Su, Nco_s) # anchor pullout capacity factor [kN]
-    qu = Nc_final*Su  # The bearing pressure capacity of the anchor plate
-    Tmax = round(qu*(1 - Los)*A,2)  # The bearing tension force capacity of the anchor plate
-    Hmax = Tmax*np.cos(np.deg2rad(beta))
-    Vmax = Tmax*np.sin(np.deg2rad(beta))
-
-    resultsPlate = {}
-    resultsPlate['Capacity'] = Tmax                 # Capacity at specified loading angle
-    resultsPlate['Horizontal max.'] = Hmax          # Maximum horizontal capacity in clay
-    resultsPlate['Vertical max.'] = Vmax            # Maximum vertical capacity in clay
-    resultsPlate['Weight'] = W                # Dry weight of the plate (kN)
+    Nc_final = max(Nco + (gamma*zlug)/Su, Nco_s)
+    if display > 0: print(f"Nc_star: {Nco + (gamma*zlug)/Su:.2f}")
+    if display > 0: print(f"Nc_star: {Nco_s:.2f}")
+    qu = Nc_final*Su
+    Tmax = round(qu*(1 - Los)*B*L, 2)
+    Hmax = Tmax*np.cos(np.deg2rad(90 - beta))
+    Vmax = Tmax*np.sin(np.deg2rad(90 - beta))
+
+    Ta = np.sqrt(Ha**2 + Va**2)
+    UC = Ta/Tmax
+
+    resultsPlate = {
+        'Capacity': Tmax,
+        'Horizontal max.': Hmax,
+        'Vertical max.': Vmax,
+        'Unity check': UC,
+        'Weight plate': Wp
+    }
     
-    return resultsPlate
\ No newline at end of file
+    return layers, resultsPlate
+
+if __name__ == '__main__':
+    profile_map = [
+        {
+            'name': 'CPT_1',
+            'x': 498234, 'y': 5725141,
+            'layers': [
+                {
+                    'top': 0.0, 'bottom': 9.5,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.0, 'gamma_bot': 8.5,
+                    'Su_top': 10, 'Su_bot': 25
+                },
+                {
+                    'top': 9.5, 'bottom': 11.5,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.5, 'gamma_bot': 8.5,
+                    'Su_top': 25, 'Su_bot': 45
+                },
+                {
+                    'top': 11.5, 'bottom': 25.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.5, 'gamma_bot': 9.0,
+                    'Su_top': 45, 'Su_bot': 50
+                }
+            ]
+        }
+    ]
+
+    B = 2.0
+    L = 2.0
+    zlug = 10.0
+    Ha = 350e3
+    Va = 400e3
+    alpha = np.rad2deg(np.arctan2(Va, Ha))
+    beta = 90 - alpha
+
+    layers, results = getCapacityPlate(profile_map, 'CPT_1', B, L, zlug, beta, Ha, Va)
+
+    print("\n--- Plate Anchor Capacity Results ---")
+    for key, val in results.items():
+        print(f"{key}: {val:.2f}")
+        
+    plot_plate(layers, B, L, z0 = layers[0]['top'], zlug=zlug, beta=beta, title='Plate Anchor in Layered Soil')
diff --git a/famodel/anchors/anchors_famodel/capacity_suction.py b/famodel/anchors/anchors_famodel/capacity_suction.py
index d16b75a1..328c97ee 100644
--- a/famodel/anchors/anchors_famodel/capacity_suction.py
+++ b/famodel/anchors/anchors_famodel/capacity_suction.py
@@ -1,53 +1,54 @@
 
-import yaml      
 import numpy as np
 import matplotlib.pyplot as plt
-from scipy.optimize import fsolve
-#from famodel.anchors.capacity_load import getAnchorLoad
-#from famodel.anchors.anchors_famodel.capacity_load import getTransferLoad
+import matplotlib.colors as mcolors
+from .support_soils import clay_profile, sand_profile
 
-def getCapacitySuction(D, L, zlug, H, V, soil_type, gamma, Su0=None, k=None, phi=None, Dr=None, plot=True):
-    
+def getCapacitySuction(profile_map, location_name, D, L, zlug, Ha, Va, thetalug=5, psilug=7.5, plot=False, display=0):
     '''Calculate the inclined load capacity of a suction pile in sand or clay following S. Kay methodology.
-    The calculation is based on the soil properties, anchor geometry and inclined load.  
+    The calculation is based on the soil profile, anchor geometry and inclined load.  
     
     Parameters
     ----------
+    profile : array
+        Soil profile as a 2D array: (z, parameters)
+            Clay soil profile (z (m), Su (kPa), gamma (kN/m³))
+            Sand soil profile (z (m), phi (deg), gamma (kN/m³), Dr (%))
+    soil_type : string
+        Select soil condition, 'clay' or 'sand'
     D : float 
-        Suction pile diameter [m]
+        Suction pile diameter (m)
     L : float 
-        Suction anchor length [m]
+        Suction pile length from pile head (m)
     zlug: float
-        Embedded depth of the main padeye [m]
-    soil_type : string
-        Select soil condition, 'clay' or 'sand'              
-    gamma: float 
-        The effective unit weight of the soil. [kN/m3]
-    Su0 : float 
-        Undrained shear strength at the mudline (clay only) [kPa]
-    k : float 
-        Undrained shear strength gradient (clay only) [kPa/m]
-    phi : float
-        Angle of internal friction (sand only) [deg]
-    Dr : float
-        Relative density of the soil (%) (sand only) [-]       
-    
+        Embedded depth of the main padeye (m)
+    thetalug: float
+        Angle of tilt misaligment (deg) (default value: 5.0)
+    psilug: float
+        Angle of twist misaligment (deg) (default value: 7.5)
+    Ha : float       
+        Horizontal load at pile lug elevation (N)
+    Va : float          
+        Vertical load at pile lug elevation (N)
+    plot : bool
+        Plot the capacity envelope if True
+                    
     Returns
     -------
-    Hmax : float 
-        Maximum horizontal capacity [kN]
-    Vmax : float 
-        Maximum vertical capacity [kN]
-    '''  
-            
-    lambdap = L/D; m = 2/3;         # Suction pile slenderness ratio
+    Dictionary with capcity, weigths and UC.
+    ''' 
+    
+    # Retrieve soil layers from map
+    profile_entry = next(p for p in profile_map if p['name'] == location_name)
+    layers = profile_entry['layers']
+    
+    z0 = layers[0]['top']            # Mudline elevation    
+    lambdap = (L - z0)/D             # Suction pile slenderness ratio
     t = (6.35 + D*20)/1e3            # Suction pile wall thickness (m), API RP2A-WSD
     rlug = D/2                       # Radial position of the lug
-    thetalug = 5                     # Angle of tilt misaligment, default is 5. (deg)
-    psilug = 7.5                     # Angle of twist misaligment, default is 7.5. (deg)
-    rhows = 66.90                    # Submerged steel specific weight (kN/m3)
-    rhow = 10                        # Water specific weight (kN/m3) 
-    
+    rhows = 66.90e3                  # Submerged steel specific weight (N/m3)
+    rhow = 10e3                      # Water specific weight (N/m3) 
+      
     # Outer and inner surface of the pile skirt
     def PileSurface(Len, Dia):
         Sp = np.pi*Dia*Len
@@ -67,267 +68,459 @@ def rlugTilt(r, z, theta):
     def zlugTilt(r, z, theta):
         Z = r*np.sin(np.deg2rad(theta)) + z*np.cos(np.deg2rad(theta))
         return Z
-    # Define delta as a function of Dr
-    def calc_delta(Dr_val):
-        if 35 <= Dr_val < 50:
-            return 0.29
-        elif 50 <= Dr_val < 65:
-            return 0.37
-        elif 65 <= Dr_val < 85:
-            return 0.46
-        elif Dr_val >= 85:
-            return 0.56
-        else:
-            return 0  # Default or error value for very low Dr values
-       
-    if soil_type == 'clay':
-        # Definitions for cohesive soils
-        Nc = min (6.2*(1 + 0.34*np.arctan(lambdap)),9)   # End-bearing capacity factor
-        ez = (Su0*L**2/2 + k*L**3/3)/(Su0*L + k*L**2/2)#; print(ez)
-        Np_fixed = 10.25; Np_free = 4                    # From Np vs L/D chart from CAISSON_VHM
-        Su_av_L = Su0 + k*zlug                           # Undrained shear strength values (average) 
-        Su_tip = Su0 + k*L                               # Undrained shear strength values (tip)
-        sigma_v_eff = gamma*zlug                         # Effective soil stress (kN/m2)
-        psi_val = Su_av_L/sigma_v_eff                    # Su/p0' for point in question (API DP 2A-WSD)
-        #zlug = ez                                       # Optimized depth of the lug 
- 
-        if psi_val <= 1.0:
-            alpha = min(0.5*psi_val**-0.50, 1)
-        else:
-            alpha = min(0.5*psi_val**-0.25, 1)
- 
-        Hmax = Np_fixed*L*D*Su_av_L; 
-        H0 = Np_free*L*D*Su_av_L;
-        Mmax = Np_fixed*L*L*D*Su_av_L; 
+    # Ellipse crossing with constant values
+    def horizontal_cross(H, M, M_target):
+        crossings = []
+        for i in range(len(M_rot) - 1):
+            if (M[i] - M_target) * (M[i+1] - M_target) < 0:
+                # Interpolation to get more precise value at crossing
+                H_cross = np.interp(M_target, [M[i], M[i+1]], [H[i], H[i+1]])
+                crossings.append(H_cross)
+        return crossings  
+    def vertical_cross(H, M, H_target):
+        crossings = []
+        for i in range(len(H) - 1):
+            if (H[i] - H_target) * (H[i+1] - H_target) < 0:
+                # Interpolation to get more precise value at crossing
+                M_cross = np.interp(H_target, [H[i], H[i+1]], [M[i], M[i+1]])
+                crossings.append(M_cross)
+        return crossings
+    
+    Np_fixed = 11.65
+    Np_free = 3.5
+    Nc = min(6.2*(1 + 0.34*np.arctan(lambdap)), 9)
+    
+    # Initialize
+    sum_ez_weighted = 0.0
+    Hmax_final = 0.0
+    Vmax_final = 0.0
+    layer_data = []
+
+    # Profile check points
+    npts = 10
+
+    for layer in layers:
+        soil_type = layer['soil_type']
+        z_top = layer['top']
+        z_bot = layer['bottom']
+
+        if soil_type == 'clay':
+            # Prepare soil profile for clay
+            profile = [
+                [z_top, layer['gamma_top'], layer['Su_top']],
+                [z_bot, layer['gamma_bot'], layer['Su_bot']]
+            ]
+    
+            z_ref, f_gamma, f_Su, f_sigma_v_eff, f_alpha = clay_profile(profile)
+    
+            # Clip the layer first
+            z_top_clip = max(z_top, z0)
+            z_bot_clip = min(z_bot, z0 + (L - z0))
+            dz_clip = z_bot_clip - z_top_clip
+            if display > 1: print(f'dz_clip  = {dz_clip:.2f} m')
+    
+            if dz_clip <= 0:
+                continue  # Skip layers fully above or below
+    
+            # Calculate properties over clipped dz
+            z_vals = np.linspace(z_top_clip, z_bot_clip, npts)
+            Su_vals = f_Su(z_vals)
+            Su_total = np.trapz(Su_vals, z_vals)
+            Su_moment = np.trapz(Su_vals*z_vals, z_vals)
+            
+            ez_layer = Su_moment/Su_total
+            Su_av_z = f_Su(ez_layer)
+            
+            if display > 1: print(f'ez_layer = {ez_layer:.2f} m')
+            if display > 1: print(f'Su_av_z (at ez_layer) = {Su_av_z:.2f} Pa')
+            
+            Su_bot = f_Su(z_bot_clip)
+            gamma_vals = f_gamma(z_vals)
+            gamma_av = np.mean(gamma_vals)
+
+            # Calculate Hmax for clay
+            Hmax_layer = Np_fixed*D*dz_clip*Su_av_z
+    
+            layer_data.append({
+                'z_top': z_top_clip,
+                'z_bot': z_bot_clip,
+                'dz': dz_clip,
+                'Hmax_layer': Hmax_layer,
+                'ez_layer': ez_layer
+            })
+    
+            sigma_v_eff = f_sigma_v_eff(np.mean(z_vals))
+            alpha_av = float(f_alpha(np.mean(z_vals)))
+            
+            # Side shear To and Ti
+            To = PileSurface(dz_clip, D)*alpha_av*Su_av_z
+            Ti = PileSurface(dz_clip, D - 2*t)*alpha_av*Su_av_z
+            
+            # Tip resistance
+            if abs(z_bot_clip - (z0 + (L - z0))) < 1e-3:  # tip check
+                Tbase = (np.pi/12)*D**3*Su_bot
+            else:
+                Tbase = 0.0
+            
+            Tmax = min(To + Ti, To + Tbase)
+            
+            # Torque induced by horizontal load
+            T = Ha*rlug*np.sin(np.deg2rad(psilug))
+            
+            nhuT = T/Tmax 
+            nhuV = Ha/To 
+            nhuVstar = np.sqrt(nhuV**2 - nhuT**2) 
+            alphastar = alpha_av*(nhuVstar/nhuV)
+            if display > 1: print(f"alphastar   = {alphastar:.3f}")
+            
+            # Constant weight
+            Pile_Head = PileWeight(z0, D, t, rhows)
+            
+            # Vertical failure modes
+            Vmax1 = None
+            if np.isclose(z_bot_clip, z0 + (L - z0), atol=0.1):
+                Vmax1 = PileWeight(dz_clip, D, t, rhows) + PileSurface(dz_clip, D)*alphastar*Su_av_z + Nc*Su_bot*(np.pi/4)*D**2
+            # else:
+            #     Vmax1 = np.inf  # No tip resistance unless at tip
+            
+            Vmax2 = PileWeight(dz_clip, D, t, rhows) + PileSurface(dz_clip, D)*alphastar*Su_av_z + PileSurface(dz_clip, D - 2*t)*alphastar*Su_av_z
+            Vmax3 = PileWeight(dz_clip, D, t, rhows) + PileSurface(dz_clip, D)*alphastar*Su_av_z + SoilWeight(dz_clip, D, t, gamma_av)
+            
+            Vmax_candidates = [v for v in [Vmax1, Vmax2, Vmax3] if v is not None]
+            Vmax_layer = max(Vmax_candidates)
+
+            # Sum vertical capacities
+            Vmax_final += Vmax_layer
+            
+            # Print layer debug info
+            if display > 0: print(f"Vmax_layer    = {Vmax_layer:.2f} N")
+            if display > 0: print(f"Vmax1   = {Vmax1:.2f} N" if Vmax1 is not None else "Vmax1   = not applicable")
+            if display > 0: print(f"Vmax2   = {Vmax2:.2f} N")
+            if display > 0: print(f"Vmax3   = {Vmax3:.2f} N")
+            
+        elif soil_type == 'sand':
+            # Prepare soil profile for sand
+            profile = [
+                [z_top, layer['gamma_top'], layer['phi_top'], layer['Dr_top']],
+                [z_bot, layer['gamma_bot'], layer['phi_bot'], layer['Dr_bot']]
+            ]
         
-        # M modifies the Hmax capacity
-        M = - V*rlugTilt(rlug,zlug,thetalug) - H*(zlugTilt(rlug,zlug,thetalug) - ez)
-        def f(Hmax):
-             return m*(Hmax/(L*D*(Su0 + k*zlug)) - Np_fixed) + M*(Hmax/(L*D*(Su0 + k*zlug))/(Hmax*L))
-        Hmax = fsolve(f,5)
+            z_ref, f_gamma, f_phi, _, f_sigma_v_eff, f_delta = sand_profile(profile)
         
-        # Torsion capacity
-        Fo = PileSurface(L, D)*alpha*Su_av_L
-        To = Fo
-        Ti = PileSurface(L,(D - 2*t))*alpha*Su_av_L
-        Tbase = np.pi*D**3*Su_tip/12
-        Tmax = min(To + Ti, To + Tbase) 
+            # Clip the layer within pile embedded length
+            z_top_clip = max(z_top, z0)
+            z_bot_clip = min(z_bot, z0 + (L - z0))
+            dz_clip = z_bot_clip - z_top_clip
         
-        # Introduce twist effects due to installation misaligment
-        T = H*rlug*np.sin(np.deg2rad(psilug))
-        nhuT = T/Tmax; nhuV = H/Fo;
-        nhuVstar = np.sqrt(nhuV**2 - nhuT**2)
-        alphastar = alpha*(nhuVstar/nhuV)
+            if dz_clip <= 0:
+                continue  # Skip non-overlapping layers
         
-        # "Plugged" (Reverse end bearing capacity - passive suction) 
-        Vmax1 = (PileWeight(L, D, t, rhows) + PileSurface(L, D)*alphastar*Su_av_L + Nc*Su_tip*(np.pi/4)*D**2)
-        # "Coring"        
-        Vmax2 = (PileWeight(L, D, t, rhows) + PileSurface(L, D)*alphastar*Su_av_L + PileSurface(L,(D - 2*t))*alphastar*Su_av_L)
-        # "Leaking"        
-        Vmax3 = (PileWeight(L, D, t, rhows) + PileSurface(L, D)*alphastar*Su_av_L + SoilWeight(L, D, t, gamma))                  
-        Vmax = min(Vmax1, Vmax2, Vmax3)
-        '''
-        print("\n--- Parameter-Based Version ---")
-        print(f"Su_av_L        = {Su_av_L:.3f} kPa")
-        print(f"sigma'_v(zlug) = {sigma_v_eff:.3f} kPa")
-        print(f"psi_val        = {psi_val:.3f}")
-        print(f"alpha (API)    = {alpha:.3f}")
-        print(f"Hmax           = {Hmax[0]:.2f} kN")
-        print(f"Vmax           = {Vmax:.2f} kN")
-        '''
-               
-    elif soil_type == 'sand':
-        # Definition for non-cohesive soils
-        Nq = np.e**(np.pi*np.tan(np.radians(phi)))*np.tan(np.radians(45) + np.radians(phi)/2)**2 # Lateral-bearing capacity factor
-        sigma_av_L = gamma*L/2                        # Effective stress (average)
-        sigma_tip = gamma*L                           # Effective stress (tip)
-        Hmax = 0.5*D*Nq*gamma*L**2
-
-        M = - V*rlugTilt(rlug,zlug,thetalug) - H*(zlugTilt(rlug,zlug,thetalug) - zlug)
+            # Calculate properties over clipped dz
+            z_vals = np.linspace(z_top_clip, z_bot_clip, npts)
+            phi_vals = f_phi(z_vals)
+            sigma_vals = f_sigma_v_eff(z_vals)
+            delta_vals = f_delta(z_vals)
         
-        # Torsion capacity
-        delta = calc_delta(Dr)
-        To = PileSurface(L, D)*delta*sigma_av_L
-        Ti = PileSurface(L, (D -2*t))*delta*sigma_av_L
-        Tbase = np.pi*D**3*sigma_tip/12
-        Tmax = min(To + Ti, To + Tbase) 
+            phi_av = np.mean(phi_vals)
+            sigma_av = np.mean(sigma_vals)
+            delta_av = np.mean(delta_vals)
         
-        # Introduce twist effects due to installation misaligment
-        T = H*rlug*np.sin(np.deg2rad(psilug))
-        Fo = delta*sigma_av_L*L*np.pi*D
-        nhuT = T/Tmax; nhuV = H/Fo;
-        nhuVstar = np.sqrt(nhuV**2 - nhuT**2)
-        deltastar = delta*(nhuVstar/nhuV)
-    
-        # "Coring"        
-        Vmax2 = PileWeight(L, D, t, rhows) + PileSurface(L, D)*deltastar*sigma_av_L + PileSurface(L,(D - 2*t))*deltastar*sigma_av_L
-        # "Leaking"        
-        Vmax3 = (PileWeight(L, D, t, rhows) + PileSurface(L, D)*deltastar*sigma_av_L + SoilWeight(L, D, t, gamma))
-        Vmax = min(Vmax2, Vmax3)
-        # def y(depth):
-            # return np.e**(-depth) - 1 + depth
-        # Ze = D/(4*7); Zi = D/(4*5)    
-        # Vmax = 7*gamma*Ze**2*y(L/Ze)*PileSurface(L, D)/L + 5*gamma*Zi**2*y(L/Zi)*PileSurface(L,(D - 2*t))/L
-        '''
-        print("\n--- Parameter-Based (Sand) ---")
-        print(f"phi        = {phi:.2f} deg")
-        print(f"gamma      = {gamma:.2f} kN/m3")
-        print(f"deltastar  = {deltastar:.2f} -")
-        print(f"sigma_av_L = {sigma_av_L:.2f} kN")
-        print(f"sigma_tip  = {sigma_tip:.2f} kN")
-        '''
-    # Pile weight (inc. stiffening plus vent) assessed as a factor
-    Wp = 1.10*PileWeight(L, D, t, (rhows + rhow)) 
-    # Submerged weight of the soil plug
-    Ws = SoilWeight(L, D, t, gamma)
-    
-    # Capacity envelope
-    aVH = 0.5 + lambdap; bVH = 4.5 + lambdap/3 
-    #print('Env. exp = ' +str(aVH)+'   '+str(bVH))
-    UC = (H/Hmax)**aVH + (V/Vmax)**bVH      
-    x = np.cos(np.linspace (0, np.pi/2, 100))
-    y = (1 - x**bVH)**(1/aVH)
-    X = Hmax*x; Y = Vmax*y
-    if plot:
-        plt.plot(X, Y, color = 'b')
-        plt.plot(H, V, '*', color = 'r')
+            sigma_tip = f_sigma_v_eff(z_bot_clip)
+            gamma_vals = f_gamma(z_vals)
+            gamma_av = np.mean(gamma_vals)
             
-        # Set labels and title
-        plt.xlabel('Horizontal capacity [kN]')
-        plt.ylabel('Vertical capacity [kN]')
-        plt.suptitle('VH suction pile capacity envelope')
-        plt.axis([0, 1.3*max(X[0], H), 0, 1.3*max(Y[-1], V)]) 
-        plt.grid(True)
-        plt.show()
-    
-    resultsSuction = {}
-    if soil_type == 'clay':
-        resultsSuction['Horizontal max.'] = Hmax[0] # Maximum horizontal capacity in clay
-    elif soil_type == 'sand':   
-        resultsSuction['Horizontal max.'] = Hmax    # Maximum horizontal capacity in sand 
-    resultsSuction['Vertical max.'] = Vmax          # Maximum vertical capacity 
-    if soil_type == 'clay':
-        resultsSuction['UC'] = UC[0]                # Unity check in clay
-    elif soil_type == 'sand':
-        resultsSuction['UC'] = UC                   # Unity check in sand
-    resultsSuction['Weight'] = Wp                   # Dry weight of the suction pile (kN)
-    resultsSuction['Weight Soil'] = Ws              # Submerged weight of the soil plug (kN)
-    resultsSuction['t'] = t                         # Pile thikness in [m]
-    
-    return resultsSuction
+            Nq = np.e**(np.pi*np.tan(np.radians(phi_av)))*(np.tan(np.radians(45) + np.radians(phi_av)/2))**2
+        
+            # Calculate Hmax for sand
+            Hmax_layer = 0.5*Nq*D*gamma_av*dz_clip**2
+        
+            layer_data.append({
+                'z_top': z_top_clip,
+                'z_bot': z_bot_clip,
+                'dz': dz_clip,
+                'Hmax_layer': Hmax_layer,
+                'ez_layer': np.mean(z_vals)
+            })
+        
+            # Side friction
+            To = PileSurface(dz_clip, D)*delta_av*sigma_av
+            Ti = PileSurface(dz_clip, D - 2*t)*delta_av*sigma_av
+        
+            if abs(z_bot_clip - (z0 + (L - z0))) < 1e-3:
+                Tbase = np.pi/4*D**2*sigma_tip
+            else:
+                Tbase = 0.0
+        
+            Tmax = min(To + Ti, To + Tbase)
+        
+            # Torque induced by horizontal load
+            T = Ha*rlug*np.sin(np.deg2rad(psilug))
+            nhuT = T/Tmax 
+            nhuV = Ha/To 
+            nhuVstar = np.sqrt(nhuV**2 - nhuT**2) 
+            deltastar = delta_av*(nhuVstar/nhuV) 
+            
+            # Constant weight
+            Pile_Head = PileWeight(z0, D, t, rhows)
+               
+            # Vertical failure modes
+            Vmax2 = Pile_Head + PileWeight(dz_clip, D, t, rhows) + PileSurface(dz_clip, D)*deltastar*sigma_av + PileSurface(dz_clip, D - 2*t)*deltastar*sigma_av
+            Vmax3 = Pile_Head + PileWeight(dz_clip, D, t, rhows) + PileSurface(dz_clip, D)*deltastar*sigma_av + SoilWeight(dz_clip, D, t, gamma_av)
+        
+            Vmax_layer = min(Vmax2, Vmax3)
+            
+            # Sum vertical capacities
+            Vmax_final += Vmax_layer
         
-def getCapacitySuctionSimp(D, L, zlug, H, V, gamma, Su0, k, alpha):
+            if display > 0: print(f"Vmax_layer (sand) = {Vmax_layer:.2f} N")
+            if display > 0: print(f"Vmax2 (sand) = {Vmax2:.2f} N")
+            if display > 0: print(f"Vmax3 (sand) = {Vmax3:.2f} N")
 
-    '''
-    Parameters
-    ----------
-    D : float 
-        Suction pile diameter [m]
-    L : float 
-        Suction anchor length [m]
-    Tm : float 
-        Mooring line load at mudlevel [kN]
-    thetam : float 
-        Mooring line angle at mudlevel [deg]
-    zlug : float 
-        Embedded depth of the lug [m]
-    gamma: float
-    
-    Su0 : float 
-        Undrained shear strength at the mudline (clay only)[kPa]
-    k : float 
-        Undrained shear strength gradient (clay only) [kPa/m]
-    alpha : float 
-        Skin friction coefficient (outer and inner - clay only) [-] 
-    rhows : float
-        Submerged steel density [t/m3]
+    # Hmax_final and weighted ez
+    for data in layer_data:
+        z_top = data['z_top']
+        z_bot = data['z_bot']
+        Hmax_layer = data['Hmax_layer']
+        ez_layer = data['ez_layer']
+        dz_layer = data['dz']
 
-    Returns
-    -------
-    Hmax : float 
-        Maximum horizontal capacity [kN]
-    Vmax : float 
-        Maximum vertical capacity [kN]
-    UC: float
-        Capacity unity check for given load [-]
-    ''' 
-    
-    lambdap = L/D;                       # Suction pile slenderness ratio   
-    t = 10*D/1e3                         # Thickness of the pile
-    Np_fixed = 10.25;                    # From Np vs L/D chart from CAISSON_VHM
-    rhows=66.90
-    
-    Su_av_L = Su0 + k*zlug;              # Undrained shear strength values (average)
-    Su_tip = Su0 + k*L;                  # Undrained shear strength values (tip)
-    Nc = min (6.2*(1 + 0.34*np.arctan(lambdap)),9)  # End-bearing capacity factor
-    
-    # Outer and inner surface of the pile skirt
-    def PileSurface(Len, Dia):
-        Sp = np.pi*Dia*Len
-        return Sp    
-    # Dry and wet mass of the pile    
-    def PileWeight(Len, Dia, tw, rho):
-        Wp = ((np.pi/4)*((Dia**2 - (Dia - 2*tw)**2)*Len + (np.pi/4)*Dia**2*tw))*rho
-        return Wp 
-    # Weight of the soil plug      
-    def SoilWeight(Len, Dia, tw, gamma_soil): 
-        Wsoil =(np.pi/4)*(Dia - 2*tw)**2*Len*gamma_soil
-        return Wsoil
-    
-    Hmax = Np_fixed*L*D*Su_av_L
-    # "Plugged" (Reverse end bearing capacity - passive suction) 
-    Vmax1 = (PileWeight(L, D, t, rhows) + PileSurface(L, D)*alpha*Su_av_L + Nc*Su_tip*(np.pi/4)*D**2)
-    # "Coring"        
-    Vmax2 = (PileWeight(L, D, t, rhows) + PileSurface(L, D)*alpha*Su_av_L + PileSurface(L,(D - 2*t))*alpha*Su_av_L)
-    # "Leaking"        
-    Vmax3 = (PileWeight(L, D, t, rhows) + PileSurface(L, D)*alpha*Su_av_L + SoilWeight(L, D, t, gamma)) 
-    # print(Vmax1); print(Vmax2); print(Vmax3)                  
-    Vmax = min(Vmax1,Vmax2,Vmax3)
-    
-    # Submerged pile weight (inc. stiffening plus vent) assessed as a factor
-    Wp = 1.00*PileWeight(L, D, t, (rhows)) 
-    # Submerged weight of the soil plug
-    Ws = SoilWeight(L, D, t, gamma) 
+        z_embedded_start = z0
+        z_embedded_end = L - z0
+
+        if z_top >= z_embedded_start and z_bot <= z_embedded_end:
+            sum_ez_weighted += Hmax_layer*ez_layer
+            Hmax_final += Hmax_layer
+            if display > 0: print(f'Hmax_layer  = {Hmax_layer:.2f} m')
+
+        elif z_top < z_embedded_end and z_bot > z_embedded_start:
+            dz_inside = min(z_bot, z_embedded_end) - max(z_top, z_embedded_start)
+            if dz_inside > 0:
+                ratio = dz_inside/dz_layer
+                sum_ez_weighted += Hmax_layer*ratio*ez_layer
+                Hmax_final += Hmax_layer*ratio
+                # print(f'ez_layer (partial) = {ez_layer:.2f} m')
+   
+    ez_global = sum_ez_weighted/Hmax_final 
+    if display > 1: print(f'ez_global   = {ez_global:.2f} m')
+    if display > 0: print(f'Hmax_final  = {Hmax_final:.2f} m')
+
+    # Calculate coupled moment 
+    M  = -Va*rlugTilt(rlug, zlug, thetalug) - Ha*(zlugTilt(rlug, zlug, thetalug) - ez_global)
+    Mv = -Va*rlugTilt(rlug, zlug, thetalug)
+    if display > 1: print(f"rlug_eff = {rlugTilt(rlug, zlug, thetalug):.2f} m")
+    if display > 1: print(f"zlug_eff = {zlugTilt(rlug, zlug, thetalug):.2f} m")
+    if display > 1: print(f"M = {M:.2f} Nm")
     
-    # H = Tm*np.cos(np.deg2rad(thetam)); V = Tm*np.sin(np.deg2rad(thetam))
+    # MH Ellipse Parameters for Clay (Kay 2014)
+    # ΔφMH (piecewise based on L/D)
+    if 0.5 <= lambdap < 1.125:
+        delta_phi = 0.32 + 4.32*lambdap; #print(delta_phi)
+    elif 1.125 <= lambdap < 2.0:
+        delta_phi = 7.13 - 1.71*lambdap; #print(delta_phi)
+    elif 2.0 <= lambdap <= 8.0:
+        delta_phi = 2.25 - 0.25*lambdap; #print(delta_phi)
+    else:
+        raise ValueError('L/D out of bounds for MH ellipse.')
+
+    phi_MH = -np.arctan(ez_global/(L - z0)) - np.deg2rad(delta_phi)
+    a_MH = Np_fixed/np.cos(phi_MH)
+    delta_bMH = 0.45*(lambdap)**(-0.9) if lambdap <= 1.5 else 0
+    b_MH = -Np_free*np.sin(phi_MH) + delta_bMH
+    if display > 1: print(f"delta_phi = {delta_phi:.2f} deg")
+    if display > 1: print(f"phi_MH = {np.rad2deg(phi_MH):.2f} deg")
+    if display > 1: print(f"a_MH = {a_MH:.2f}")
+    if display > 1: print(f"b_MH = {b_MH:.2f}")
+
+    # MH Ellipse Parameters for Clay (Kay 2015)
+    # VH (piecewise based on L/D)
+    if 0.5 <= lambdap < 1.5:
+        a_VH = 9/4 + (5/3)*lambdap; 
+    elif 0.5 <= lambdap < 1.25:
+        b_VH = 23/4 - (13/5)*lambdap; 
+    elif 1.5 <= lambdap < 20.0:     # need to set a maximum of 6 based on installation pump requirements   
+        a_VH = 47/12 - (5/9)*lambdap; 
+        b_VH = 50/19 - (2/19)*lambdap;
+    else:
+        raise ValueError('L/D ratio out of bounds for MH ellipse formulation.')
+    a_VH = 0.5 + lambdap;   b_VH = 4.5 + lambdap/3
+    # a_VH = 4.5 + lambdap/2; b_VH = 4.5 + lambdap/4
+    if display > 0: print(f"a_VH = {a_VH:.2f}")
+    if display > 0: print(f"b_VH = {b_VH:.2f}")
+
+    # Scale VH ellipse based on vertical load ratio (Kay 2015) 
+    shrink_factor = 1 - ((Va/Vmax_final)**b_VH)**(2/a_VH)
+
+    if plot: plt.figure(figsize=(10, 5))
+    theta = np.linspace(0, 2*np.pi, 400)        
+    shrink_factors = np.linspace(0.0, 1.0, 5)  
+    # Define colormap
+    if plot: cmap = plt.colormaps['Greys']  
+    norm = mcolors.Normalize(vmin=min(shrink_factors), vmax=max(shrink_factors))
     
-    # Capacity envelope
-    aVH = 0.5 + lambdap; bVH = 4.5 + lambdap/3 
-    # print('Env. exp =' +str(aVH)+str(bVH))
-    UC = (H/Hmax)**aVH + (V/Vmax)**bVH
+    for s_f in shrink_factors:
+        if plot: color = cmap(norm(s_f))
+        x_ellipse = Hmax_final*s_f*np.cos(theta)
+        y_ellipse = Vmax_final*s_f*np.sin(theta)
+        H_rot = np.cos(phi_MH)*x_ellipse - np.sin(phi_MH)*y_ellipse
+        M_rot = np.sin(phi_MH)*x_ellipse + np.cos(phi_MH)*y_ellipse
+        if plot: plt.plot(H_rot, M_rot, color=color, alpha=0.5)
+
+    x_ellipse_prime = Hmax_final*shrink_factor*np.cos(theta)
+    y_ellipse_prime = Vmax_final*shrink_factor*np.sin(theta)
+    H_rot_prime = np.cos(phi_MH)*x_ellipse_prime - np.sin(phi_MH)*y_ellipse_prime
+    M_rot_prime = np.sin(phi_MH)*x_ellipse_prime + np.cos(phi_MH)*y_ellipse_prime
+    Hlim = 1.2*Hmax_final  
+    if plot: plt.xlim(-Hlim, Hlim)
+    if plot: plt.ylim(-Hlim, Hlim)
+    if plot: plt.grid(True, color='gray', linestyle='--', lw=0.5, alpha=0.8)
 
-    x = np.cos(np.linspace (0,np.pi/2,1000))
-    y = (1 - x**bVH)**(1/aVH)
-    X = Hmax*x; Y = Vmax*y
+    # Highlight the actual one
+    if plot: plt.plot(H_rot_prime, M_rot_prime, 'b', label= f'MH ellipse w/ V/Vmax = {shrink_factor:.3f}')
+    if plot: plt.axhline(0, color='k', linestyle='--', lw=1.0)
+    if plot: plt.axvline(0, color='k', linestyle='--', lw=1.0)
 
-    #H_good = Hmax*np.exp(np.log(0.5)/aVH)
-    #V_good = Vmax*np.exp(np.log(0.5)/bVH)
+    # Plot horizontal line at constant M and Mv
+    H_plot = np.linspace(min(1.3*H_rot), max(1.3*H_rot), 100)
+    M_plot  = np.full_like(H_plot,  M)  # Constant moment
+    Mv_plot = np.full_like(H_plot, Mv)  # Constant moment
+    if plot: plt.plot(H_plot,  M_plot, 'r', lw=1.0, label='Moment line') 
+    if plot: plt.plot(H_plot, Mv_plot, 'r', lw=0.5, label='Vertical moment line') 
+    if plot: plt.legend(loc='lower left', fontsize='small')
    
-    resultsSuctionSimp = {}
-    resultsSuctionSimp['Horizontal max.'] = Hmax    # Capacity at specified loading angle
-    resultsSuctionSimp['Vertical max.'] = Vmax      # Capacity at specified loading angle
-    resultsSuctionSimp['UC'] = UC                   # Unity check
-    resultsSuctionSimp['Weight'] = Wp               # Pile weight in kN
-    resultsSuctionSimp['Weight Soil'] = Ws          # in kN
-    resultsSuctionSimp['t'] = t
-    
-    return resultsSuctionSimp  
+    H_roots = horizontal_cross(H_rot_prime, M_rot_prime, M)
+    Hmax_v = 0.1 
+    if H_roots:
+        Hmax_pos = max([r for r in H_roots if r >= 0], default=None)
+        Hmax_neg = min([r for r in H_roots if r <  0], default=None)
+        if M > 0 and Hmax_neg is not None:
+            Hmax_v = abs(Hmax_neg)
+            if plot: plt.plot(Hmax_neg, M, 'ro', label=f'Hmax,v = {Hmax_neg/1e6:.1f} MN', zorder=20)
+            if plot: plt.legend(loc='lower left')
+        elif M <= 0 and Hmax_pos is not None:
+            Hmax_v = abs(Hmax_pos)
+            if plot: plt.plot(Hmax_pos, M, 'ro', label=f'Hmax,v = {Hmax_pos/1e6:.1f} MN', zorder=20)
+            if plot: plt.legend(loc='lower left')
+        else:
+            if display > 0: print('[WARNING] No valid Hmax crossing found for moment cut.')
+    else:
+        if display > 0: print('[WARNING] No intersection between moment line and ellipse.') 
 
-if __name__ == '__main__':
+    # Find relevant intercept
+    H_v_roots = horizontal_cross(H_rot_prime, M_rot_prime, 0.0)
+    M_v_roots = vertical_cross(H_rot_prime, M_rot_prime, 0.0)
+    idx_maxH = np.argmax(H_rot_prime)
+    H_at_maxH = H_rot_prime[idx_maxH]
+    M_at_maxH = M_rot_prime[idx_maxH]
+    idx_minM = np.argmin(M_rot_prime)
+    H_at_minM = H_rot_prime[idx_minM]
+    M_at_minM = M_rot_prime[idx_minM]
     
-    D = 2.0          # Diameter in meters
-    L = 10.0         # Length in meters
-    zlug = (2/3)*L   # Padeye depth
-    H = 1500.0       # Horizontal load in kN
-    V = 1000.0       # Vertical load in kN
+    # Plotting
+    if plot:
+        plt.scatter(H_v_roots[0], 0.0, s=25, facecolors='white', edgecolors='blue', 
+                    marker='s',label=f'Ho ≈ {H_v_roots[0]/1e6:.1f} MN', zorder=10)
+        plt.legend(loc='lower left', fontsize='small')
+        plt.scatter(0.0, M_v_roots[0], s=25, facecolors='white', edgecolors='blue', 
+                    marker='s', label=f'Mo ≈ {M_v_roots[0]/1e6:.1f} MNm', zorder=10)
+        plt.legend(loc='lower left', fontsize='small')
+        plt.scatter(H_at_maxH, M_at_maxH, s=25, facecolors='white', edgecolors='blue',
+                    marker='D', label=f'Hmax ≈ {H_at_maxH/1e6:.1f} MN', zorder=10)
+        plt.legend(loc='lower left', fontsize='small')
+        plt.scatter(H_at_minM, M_at_minM, s=25, facecolors='white', edgecolors='blue',
+                    marker='D', label=f'Mmax ≈ {M_at_minM/1e6:.1f} MNm', zorder=10)
+        plt.legend(loc='lower left', fontsize='small')
     
-    gamma = 8
-    Su0 = 25
-    k = 0
+    # Constant weight
+    pile_head = PileWeight(z0, D, t, rhows)
+    if display > 0: print(f"pile_head    = {pile_head:.2f} N")
+    Vmax_final += pile_head
+    if display > 0: print(f"Vmax_final   = {Vmax_final:.2f} N")
     
-    phi = 50
-    Dr = 75
+    Wp = 1.10*PileWeight(L, D, t, rhows + rhow) 
     
-    results_clay = getCapacitySuction(D, L, zlug, H, V, 'clay', gamma, Su0=Su0, k=k, phi=phi, Dr=Dr, plot=True) 
+    # Capacity envelope
+    a_VH = 0.5 + lambdap; b_VH = 4.5 + lambdap/3
+    # Unity check
+    UC = (Ha/Hmax_v)**a_VH + (Va/Vmax_final)**b_VH 
+    if plot: plt.figure(figsize=(6, 5))
+    x = np.linspace(0, 1, 100)
+    y = (1 - x**b_VH)**(1/a_VH)
+
+    # Plotting
+    if plot:
+        plt.figure(figsize=(6, 5))
+        plt.plot(Hmax_v*x, Vmax_final*y, 'b', label='VH Envelope')
+        plt.plot(Ha, Va, 'go', label='Applied load')
+        plt.xlabel('Horizontal capacity (N)')
+        plt.ylabel('Vertical capacity (N)')
+        plt.title('VH suction pile capacity envelope')
+        plt.axis([0, 1.3*max(Hmax_v, Ha), 0, 1.3*max(Vmax_final, Va)]) 
+        plt.grid(True)
+        plt.legend()
+        plt.show()
     
-    # results_sand = getCapacitySuction(D, L, zlug, H, V, 'sand', gamma, Su0=Su0, k=k, phi=phi, Dr=Dr, plot=True)   
\ No newline at end of file
+    resultsSuction = {
+        'Horizontal max.': Hmax_v,
+        'Vertical max.': Vmax_final,
+        'Unity check': UC,
+        'Weight pile': Wp}
+
+    return layers, resultsSuction
+
+if __name__ == '__main__':
+
+    profile_map = [
+    {
+        'name': 'CPT_1',
+        'x': 498234, 'y': 5725141,
+        'layers': [
+            {
+                'top': 0.0, 'bottom': 20.0,
+                'soil_type': 'clay',
+                'gamma_top': 8.5, 'gamma_bot': 8.5,
+                'Su_top': 2.4, 'Su_bot': 30.3}]
+            # {
+            #     'top': 10.0, 'bottom': 20.0,
+            #     'soil_type': 'clay',
+            #     'gamma_top': 8.5, 'gamma_bot': 8.5,
+            #     'Su_top': 13.95, 'Su_bot': 30.3}]
+            # {
+            #     'top': 30.0, 'bottom': 36.0,
+            #     'soil_type': 'clay',
+            #     'gamma_top': 9.0, 'gamma_bot': 9.5,
+            #     'Su_top': 75, 'Su_bot': 100},
+            # {
+            #     'top': 36.0, 'bottom': 55.0,
+            #     'soil_type': 'clay',
+            #     'gamma_top': 9.5, 'gamma_bot': 9.5,
+            #     'Su_top': 100, 'Su_bot': 100}]
+        }
+    ]
+
+
+    # Pile and load properties
+    D = 3.34                          # Pile diameter (m)
+    L = 20.0                          # Pile length (m)
+    zlug = (2/3)*L                    # Lug depth (m)
+    theta = 5                         # Tilt misalignment angle (deg)
+    psi = 7.5                         # Twist misalignment angle (deg)
+    Ha = 1e6                          # Applied horizontal load (N)
+    Va = 5.7e6                        # Applied vertical load (N)
+
+    # Calculate
+    layers, resultsSuction = getCapacitySuction(
+        profile_map, 'CPT_1',         # Soil properties and location of the pile
+        D, L, zlug,                   # Pile geometrical properties
+        Ha, Va,                       # Pile loading conditions   
+        thetalug=theta, psilug=psi,   # Pile misaligment tolerances 
+        plot=True,
+        display=1
+    )
+
+    # print('\n--- Suction Pile Capacity Results ---')
+    # print(f"Hmax_final = {resultsSuction['Hmax_final']:.2f} N")
+    # print(f"Vmax_final = {resultsSuction['Vmax_final']:.2f} N")
+    # print(f"Unity check (UC) = {resultsSuction['UnityCheck']:.4f}")
+    # print(f"Total Moment (M_total) = {resultsSuction['M_total']:.2f} Nm")
+
+    # plot_suction(layers, L, D, z0 = layers[0]['top'], zlug=zlug)
diff --git a/famodel/anchors/anchors_famodel/capacity_torpedo.py b/famodel/anchors/anchors_famodel/capacity_torpedo.py
index 1d493f1e..7c7e13aa 100644
--- a/famodel/anchors/anchors_famodel/capacity_torpedo.py
+++ b/famodel/anchors/anchors_famodel/capacity_torpedo.py
@@ -1,95 +1,271 @@
 
-import yaml     
 import numpy as np
 import matplotlib.pyplot as plt
-from scipy.optimize import fsolve
-from matplotlib import cm
-from mpl_toolkits import mplot3d 
-   
-def getCapacityTorpedo(D1, D2, L1, L2, zlug, soil_type, Su0, k, alpha):
-    
+from .support_soils import clay_profile
+from .support_plots import plot_torpedo
+
+def getCapacityTorpedo(profile_map, location_name, D1, D2, L1, L2, zlug, ballast, Ha, Va, plot=False, display=0):
     '''Calculate the inclined load capacity of a torpedo pile in clay following S. Kay methodology.
-    The calculation is based on the holding capacity of the suction pile as if it fully was embedded in soil.  
-    
+    The calculation is based on the soil profile, anchor geometry and inclined load.  
+
     Parameters
     ----------
+    profile : array
+        Clay soil profile (z, Su, gamma)
+            Clay soil profile (z (m), Su (kPa), gamma (kN/m³))
+    soil_type : string
+        Select soil condition, 'clay' 
     D1 : float 
-        Torpedo pile wing diameter. [m]
+        Wing diameter (m)
     D2 : float    
-        Torpedo pile shaft diameter. [m]
+        Shaft diameter (m)
     L1 : float 
-        Torpedo pile wing length. [m]
+        Winged section length (m)
     L2 : float 
-        Torpedo pile shaft length, excluding wing. [m]
+        Shaft section length (m)
     zlug : float 
-        Torpedo pile embedded depth at main padeye elevation. [m]        
-    soil_type : string
-        Select soil condition, 'clay' or 'sand' 
-    gamma: float 
-        The effective unit weight of the soil. [kN/m3] 
-    Su0 : float 
-        The Undrained shear strength at the mudline. [kPa]
-    k : float 
-        The Undrained shear strength gradient. [kPa/m]
-    alpha : float
-        The skin friction coefficient. [-]   
-    
+        Padeye embedment depth (m)       
+    Ha : float       
+        Horizontal load at pile lug elevation (N)
+    Va : float          
+        Vertical load at pile lug elevation (N)
+    plot : bool
+        Plot the capacity envelope if True
+
     Returns
     -------
-    Hmax : float 
-        Maximum horizontal capacity [kN]
-    Vmax : float 
-        Maximum vertical capacity [kN]
+    Dictionary with capcity, weigth and UC.
     '''
 
-    rhos= 78.50                                     # Dry steel unit weight (kN/m3)
-    t = (6.35 + D2*20)/1e3                          # Torpedo pile wall thickness (m), API RP2A-WSD
-    
-    L = L1 + L2;
-    Dstar = (D1*L1 + (D1 + 2*D2)*L2)/L              # Plane 1 (four fins)
-    #Dstar = (D1*L1 + np.sqrt(2)*(D1/2 + D2)*L2)/L  # Plane 2 (four fins)    
-    #rlug = D2/2; zlug = zlug; 
-    lambdap = L/Dstar; print('lambdap = ' +str(lambdap))
-    a = zlug; b = zlug + L1; c = zlug + L1 + L2;
-    Wp = 850                                        # Weight of the pile with ballast [kN]
-    # Dry and wet mass of the pile    
+    # Retrieve soil layers from map
+    profile_entry = next(p for p in profile_map if p['name'] == location_name)
+    layers = profile_entry['layers']
+
+    L = L1 + L2
+    t = (6.35 + D2*20)/1e3
+    rhows = 66.90e3
+    rhow = 10e3
+
     def PileWeight(Len1, Len2, Dia1, Dia2, tw, rho):
-        Wp = ((np.pi/4)*(Dia1**2 - (Dia1 - 2*tw)**2)*(Len1 + Len2) + 4*Len2*Dia2*tw)*rho
-        return(Wp)
-    W = PileWeight(L1, L2, D1, D2, t, rhos)         # Weight of the steel pile [kN]
+        return ((np.pi/4)*(Dia1**2 - (Dia1 - 2*tw)**2)*(Len1 + Len2) + 4*Len2*Dia2*tw)*rho
+
+    def PileWingedSurface(length, diameter):
+        return np.pi*diameter*length
+
+    def PileShaftSurface(length, diameter1, diameter2):
+        return 8*length*(diameter1 - diameter2)
+
+    z_start = zlug
+    z_wing = zlug + L1
+    z_end = zlug + L
+
+    layer_data = []
+    Vmax_total = 0.0
     
-    # Dry and wet mass of the pile
-    def PileSurface(Len1, Len2, Dia1, Dia2):
-        Sp = np.pi*Dia1*(Len1 + Len2) + 8*Len2*Dia2*0.9
-        return(Sp)  
+    # Profile check points
+    npts = 10
+
+    for layer in layers:
+        if layer['soil_type'] != 'clay':
+            raise ValueError('Torpedo pile capacity model only supports clay soils.')
+
+        z_layer_top = layer['top']
+        z_layer_bot = layer['bottom']
+
+        z_clip_top = max(z_layer_top, z_start)
+        z_clip_bot = min(z_layer_bot, z_end)
+
+        if z_clip_bot <= z_clip_top:
+            continue
+
+        segments = []
+        if z_clip_bot <= z_wing:
+            segments.append((z_clip_top, z_clip_bot, D1))
+        elif z_clip_top >= z_wing:
+            segments.append((z_clip_top, z_clip_bot, D2))
+        else:
+            segments.append((z_clip_top, z_wing, D1))
+            segments.append((z_wing, z_clip_bot, D2))
+
+        for z_seg_top, z_seg_bot, D in segments:
+            dz_seg = z_seg_bot - z_seg_top
+            if dz_seg <= 0:
+                continue
+
+            profile = [
+                [z_seg_top, layer['Su_top'], layer['gamma_top']],
+                [z_seg_bot, layer['Su_bot'], layer['gamma_bot']]
+            ]
+            z_ref, f_Su, _, f_gamma, f_alpha = clay_profile(profile)
+
+            z_vals = np.linspace(z_seg_top, z_seg_bot, npts)
+            Su_vals = f_Su(z_vals)
+            alpha_vals = np.array([f_alpha(z) for z in z_vals])
 
+            Su_total = np.trapz(Su_vals, z_vals)
+            Su_moment = np.trapz(z_vals*Su_vals, z_vals)
+            Su_av_z = Su_total/dz_seg
+            if display > 0: print(f"Su_av_z = {Su_av_z:.2f} Pa")
+            ez_layer = Su_moment /Su_total
+            if display > 0: print(f"dz_seg = {dz_seg:.2f} m")
+            if display > 0: print(f"ez_layer = {ez_layer:.2f} m")
+            alpha_av = np.mean(alpha_vals)
+            if display > 0: print(f"alpha_av = {alpha_av:.2f}")
+
+            Np_free = 3.45
+            Hmax_layer = Np_free*dz_seg*D*Su_av_z
+            if display > 0: print(f"Hmax_layer = {Hmax_layer:.2f} N")
+            if display > 0: print(f"D = {D:.2f} m")
+
+            surface_area = PileWingedSurface(dz_seg, D) if D == D1 else PileShaftSurface(dz_seg, D1, D2)
+            Vmax_layer = surface_area*alpha_av*Su_av_z
+            Vmax_total += Vmax_layer
+            if display > 0: print(f"Vmax_layer = {Vmax_layer:.2f} N")
+            
+            layer_data.append({
+                'z_top': z_seg_top,
+                'z_bot': z_seg_bot,
+                'dz': dz_seg,
+                'Hmax_layer': Hmax_layer,
+                'ez_layer': ez_layer,
+                'Su_av_z': Su_av_z,
+                'D_used': D
+            })
+
+    if not layer_data:
+        raise ValueError('No overlapping clay layers within pile depth.')
+
+    sum_Hmax = 0.0
+    sum_ez_weighted = 0.0
+
+    for data in layer_data:
+        z_top = data['z_top']
+        z_bot = data['z_bot']
+        Hmax_layer = data['Hmax_layer']
+        ez_layer = data['ez_layer']
+        dz_layer = data['dz']
+
+        z_embedded_start = zlug
+        z_embedded_end = zlug + L
+
+        if z_top >= z_embedded_start and z_bot <= z_embedded_end:
+            sum_ez_weighted += Hmax_layer*ez_layer
+            sum_Hmax += Hmax_layer
+        elif z_top < z_embedded_end and z_bot > z_embedded_start:
+            dz_inside = min(z_bot, z_embedded_end) - max(z_top, z_embedded_start)
+            if dz_inside > 0:
+                ratio = dz_inside/dz_layer
+                sum_ez_weighted += Hmax_layer*ratio*ez_layer
+                sum_Hmax += Hmax_layer * ratio
+
+    ez_global = sum_ez_weighted/sum_Hmax
+    if display > 0: print(f'ez_global = {ez_global:.2f} m')    
+    if display > 0: print(f'sum_Hmax = {sum_Hmax:.2f} N')
+
+    Vmax_total += PileWeight(L1, L2, D1, D2, t, rhows) + ballast
+    Wp = 1.10 * PileWeight(L1, L2, D1, D2, t, rhows + rhow) + ballast
+
+    ez_ratio = (ez_global - zlug)/L; 
+    if display > 0: print(f"ez_ratio = {ez_ratio:.2f} m")
+    
+    # Average effective width
+    L = L1 + L2
+    A_wing_plane_1 = (D1 - D2)*L1
+    A_wing_plane_2 = (D1 - D2)*np.cos(np.deg2rad(45))/2*L1
+    A_shaft = D2*L
     
-    ez_Su_den = D1*Su0*(b - a) + 0.5*D1*k*(b**2 - a**2) + D2*Su0*(c - b) + 0.5*D2*k*(c**2 - b**2)
-    ez_Su_num = D1*Su0*(a**2 - a*b) + 0.33*D1*k*(b**3 - a**3) + b**2*(0.5*D1*Su0 - 0.5*D1*a*k) - a**2*(0.5*D1*Su0 - 0.5*D1*a*k)\
-        + D2*Su0*(b**2 - b*c) + 0.33*D2*k*(c**3 - b**3) + c**2*(0.5*D2*Su0 - 0.5*D2*b*k) - b**2*(0.5*D2*Su0 - 0.5*D2*b*k)
-    ez_Su = ez_Su_num/ez_Su_den
-    ez_Su_L = ez_Su/L
-    # print('ez_Su = ' +str(ez_Su))
-    Np_free = 3.45     # From Np vs L/D chart from CAISSON_VHM
-                 
-    Hmax = L*Dstar*Np_free*(Su0 + k*(zlug + ez_Su))
-    # print('Hmax = ' +str(Hmax))
-    Vmax = PileSurface(L1, L2, D1, D2)*alpha*(Su0 + k*(zlug + ez_Su)) + Wp
-    # print('Vmax = ' +str(Vmax))
-       
-    #aVH = 0.5 + L/Dstar; bVH = 4.5 - L/(3*Dstar)
-    aVH = 4.5 + L/(2*Dstar); bVH = 3.5 - L/(4*Dstar) 
-    #H = Ta*np.cos(np.deg2rad(resultsLoad['angle'])); V = Ta*np.sin(np.deg2rad(resultsLoad['angle']))
-    #UC = (H/Hmax)**aVH + (V/Vmax)**bVH
+    # Choose based on direction:
+    plane = '1'  # or '2'
     
-    deg = [0, 15, 30, 45, 60, 75, 90]
-    x = np.cos(np.deg2rad(deg))
-    y = (1 - x**bVH)**(1/aVH)
-    X = Hmax*x/1e3; Y = Vmax*y/1e3  # in MN
-       
-    resultsTorpedo = {}
-    resultsTorpedo['Horizontal max.'] = Hmax #Hmax[0]    # Capacity at specified loading angle
-    resultsTorpedo['Vertical max.'] = Vmax               # Capacity at specified loading angle
-    resultsTorpedo['Weight'] = W                    # Dry weight of the helical pile (kN)
-   
-    return resultsTorpedo
\ No newline at end of file
+    if plane == '1':
+        Dstar = (A_wing_plane_1 + A_shaft)/L
+    elif plane == '2':
+        Dstar = (A_wing_plane_2 + A_shaft)/L
+
+    # Assign aVH and bVH based on ez_su/L
+    if np.isclose(ez_ratio, 2/3, atol=0.05):
+        aVH = 0.5 + L/Dstar
+        bVH = 4.5 - L/(3*Dstar)
+        mode = 'deep mobilization (2/3)'
+    elif 0.40 <= ez_ratio <= 0.75:
+        aVH = 4.5 + L/(2*Dstar)
+        bVH = 3.5 - L/(4*Dstar)
+        mode = 'moderate mobilization (1/2 – 3/4)'
+    # else:
+    #     aVH = 4.0
+    #     bVH = 4.0
+    #     mode = 'default exponents (fallback)'
+    if display > 0: print(f'Interaction exponents set to aVH = {aVH:.2f}, bVH = {bVH:.2f} [{mode}]')
+    
+    UC = (Ha/sum_Hmax)**aVH + (Va/Vmax_total)**bVH
+
+    if plot:
+        deg = np.linspace(0, 90, 20)
+        x = np.cos(np.deg2rad(deg))
+        y = (1 - x**bVH)**(1/aVH)
+        X = sum_Hmax*x
+        Y = Vmax_total*y
+
+        plt.figure(figsize=(6, 5))
+        plt.plot(X, Y, color='blue', label='VH Envelope')
+        plt.plot(Ha, Va, 'o', color='red', label='Load Point')
+        plt.xlabel('Horizontal Capacity (N)')
+        plt.ylabel('Vertical Capacity (N)')
+        plt.title('VH torpedo pile capacity envelope')
+        plt.grid(True)
+        plt.legend()
+        plt.tight_layout()
+        plt.show()
+
+    resultsTorpedo = {
+        'Horizontal max.': sum_Hmax,
+        'Vertical max.': Vmax_total,
+        'Unity check': UC,
+        'Weight pile': Wp,
+        'ez_global': ez_global,
+        'layer_data': layer_data}
+
+    return layers, resultsTorpedo
+
+if __name__ == '__main__':
+
+    profile_map = [
+        {
+            'name': 'CPT_1',
+            'x': 498234, 'y': 5725141,
+            'layers': [
+                {
+                    'top': 0.0, 'bottom': 20.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.0, 'gamma_bot': 8.5,
+                    'Su_top': 50, 'Su_bot': 70},
+                {
+                    'top': 20.0, 'bottom': 25.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.5, 'gamma_bot': 8.5,
+                    'Su_top': 80, 'Su_bot': 100},
+                {
+                    'top': 25.0, 'bottom': 50.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.5, 'gamma_bot': 9.0,
+                    'Su_top': 125, 'Su_bot': 150}]
+        }
+    ]
+
+    D1 = 3.0
+    D2 = 1.5
+    L1 = 11.0
+    L2 = 5.0
+    zlug = 15.0
+    ballast = 10000
+    Ha = 6.0e6
+    Va = 8.0e6
+
+    layers, results = getCapacityTorpedo(profile_map, 'CPT_1', D1, D2, L1, L2, zlug, ballast, Ha, Va)
+
+    # print("\n--- Torpedo Pile Capacity Results ---")
+    # for key, val in results.items():
+    #     if key != 'layer_data':
+    #         print(f"{key}: {val:.2f}")
+            
+    plot_torpedo(layers, D1, D2, L1, L2, z0 = layers[0]['top'], zlug=zlug)
diff --git a/famodel/anchors/anchors_famodel/installatioin_torque.py b/famodel/anchors/anchors_famodel/installatioin_torque.py
new file mode 100644
index 00000000..1829ab0e
--- /dev/null
+++ b/famodel/anchors/anchors_famodel/installatioin_torque.py
@@ -0,0 +1,176 @@
+
+import numpy as np
+import matplotlib.pyplot as plt
+from support_soils import sand_profile
+
+def getInstallationHelical(profile_map, location_name, D, L, d, plot=True):
+    # Constants and geometry
+    dH = 0.05                  # m
+    psi_p = 16.5               # degrees
+    delta_crit = 24            # degrees
+    Fr = 0.01
+
+    Dh = D                     # Helix diameter
+    Dc = d                     # Core diameter
+    ph = Dh/3                  # Pitch
+    E = 210e9                  # Pa
+    th = 0.10                  # m
+    tc = 0.03                  # m
+    f_y = 350e6                # Pa
+    f_y_weld = 250e6           # Pa (typical weld yield strength)
+    k = 1.04                   # Bending coefficient
+
+    profile_entry = next((p for p in profile_map if p['name'] == location_name), None)
+    if not profile_entry:
+        raise ValueError(f"Location '{location_name}' not found in profile_map")
+
+    layers = profile_entry['layers']
+
+    # Assemble sand profile
+    profile = []
+    for layer in layers:
+        if layer['soil_type'] == 'sand':
+            profile.append([layer['top'],    layer['gamma_top'], layer['phi_top'], layer['Dr_top']])
+            profile.append([layer['bottom'], layer['gamma_bot'], layer['phi_bot'], layer['Dr_bot']])
+
+    z0, f_gamma, f_phi, f_Dr, f_sigma_v_eff, f_delta = sand_profile(profile)
+
+    def qc_depth(H):
+        qc0, depth0 = 0, 0
+        qc1, depth1 = 8e6, 6
+        qc2, depth2 = 40e6, 16
+        m1 = (qc1 - qc0)/(depth1 - depth0)
+        m2 = (qc2 - qc1)/(depth2 - depth1)
+        if H <= depth1:
+            return m1 * H
+        elif H <= depth2:
+            return m2 * (H - depth1) + qc1
+        else:
+            return qc2
+
+    def qc_average(H, Dh):
+        depths = np.linspace(max(0, H - 1.5*Dh), min(H + 1.5*Dh, 20), int(1.5*Dh/dH))
+        return np.mean([qc_depth(z) for z in depths])
+
+    def calculate_torque(Dc, Dh, Fr, ph, th, dH, H):
+        gamma = f_gamma(H)
+        delta_crit_rad = np.radians(delta_crit)
+        a = Fr/np.tan(delta_crit_rad)
+        theta = np.arctan(ph/(np.pi*Dh))
+        K0 = 1 - np.sin(np.radians(32))
+        Tc = np.sum([a*qc_average(z, Dh)*np.tan(delta_crit_rad)*dH*(Dc**2/2) for z in np.arange(0, H, dH)])
+        Tb = qc_average(H, Dh)*np.pi*(Dc**3)*np.tan(delta_crit_rad)/12
+        Th = (a*qc_average(H, Dh)*np.tan(delta_crit_rad + theta)*np.pi*(Dh**3 - Dc**3)/(12*K0) +
+              a*qc_average(H, Dh)*th*np.tan(delta_crit_rad)*np.pi*(Dh**2)/2 +
+              a*qc_average(H, Dh)*th*(Dh**2 - Dc**2)/8)
+        return Tc + Tb + Th
+
+    def calculate_force(Dc, Dh, Fr, ph, th, dH, H):
+        gamma = f_gamma(H)
+        delta_crit_rad = np.radians(delta_crit)
+        a = Fr/np.tan(delta_crit_rad)
+        K0 = 1 - np.sin(np.radians(32))
+        Fc = np.sum([0.6*a*qc_average(z, Dh)*np.tan(delta_crit_rad)*dH*np.pi*Dc for z in np.arange(0, H, dH)])
+        Fb = 0.6*qc_average(H, Dh)*np.pi*(Dc**2)/4
+        Fh = (a*qc_average(H, Dh)*np.pi*(Dh**2 - Dc**2)/(4*K0) +
+              a*qc_average(H, Dh)*th*np.pi*Dh/K0 +
+              qc_average(H, Dh)*th*(Dh - Dc)/2)
+        return Fc + Fb + Fh
+
+    def calculate_core(T, Fy_c, Dc, tc, E, H, K=2):
+        tau = 16*(T/np.pi)*(Dc/(Dc**4 - (Dc - 2*tc)**4))
+        sigma_y = 4*(Fy_c/np.pi)/((Dc**2 - (Dc - 2*tc)**2))
+        sigma_eq_c = np.sqrt(sigma_y**2 + 3 * tau**2)
+        I = (np.pi/64)*(Dc**4 - (Dc - 2*tc)**4)
+        Fy_cr = np.pi**2*E*I/(K*H)**2
+        return sigma_eq_c, Fy_cr
+
+    def calculate_helix(Fy_max, Dh, Dc, th, k):
+        q = 4*Fy_max/(np.pi*(Dh**2 - Dc**2))
+        return k*q*Dh**2/(4*th**2)
+    
+    def calculate_weld_stress(Fy_max, th, Dh, weld_length):
+        M = Fy_max * th
+        Q = Fy_max
+        Aw = weld_length * th
+        sigma_w = M / (weld_length * th**2 / 6)
+        tau_w = Q / Aw
+        sigma_eq_w = np.sqrt(sigma_w**2 + 3 * tau_w**2)
+        return sigma_eq_w
+
+    def calculate_axial_capacity(Dh, H):
+        gamma = f_gamma(H)
+        # phi_p = 6.6 + 11*np.log10(qc_average(H, Dh)/np.sqrt(gamma*H))
+        phi_p = f_phi(H)
+        Fps = np.tan(np.radians(psi_p)) + np.cos(np.radians(phi_p - psi_p))*\
+            (np.tan(np.radians(phi_p) - np.tan(np.radians(psi_p))))
+        Fs1 = 2*Fps
+        Fs2 = (4/3)*Fps*np.tan(np.radians(psi_p))
+        Fu = (1 + Fs1*(H/Dh) + Fs2*(H/Dh)**2)*gamma*(np.pi/4)*(Dh**2)*H
+        return Fu
+
+    Tmax = 8e6
+    H_max = L
+    H_values = np.linspace(0.1, H_max, 100)
+    results = {
+        'H': [], 'Fu': [], 'Torque': [], 'Force': [],
+        'SigmaHelix': [], 'SigmaCore': [], 'BucklingLimit': [], 'SigmaWeld': [], 'FailureMode': []
+    }
+
+    for H in H_values:
+        T = calculate_torque(Dc, Dh, Fr, ph, th, dH, H)
+        F_inst = calculate_force(Dc, Dh, Fr, ph, th, dH, H)
+        sigma_helix = calculate_helix(F_inst, Dh, Dc, th, k)
+        sigma_core, Fy_cr = calculate_core(T, F_inst, Dc, tc, E, H)
+        sigma_weld = calculate_weld_stress(F_inst, th, Dh, weld_length=np.pi*Dc)
+        Fu = calculate_axial_capacity(Dh, H)
+
+        if T > Tmax:
+            failure_mode = 'Torque limit'
+        elif F_inst > Fy_cr:
+            failure_mode = 'Core buckling'
+        elif sigma_helix > f_y:
+            failure_mode = 'Helix stress'
+        elif sigma_weld > f_y_weld:
+            failure_mode = 'Weld stress'
+        else:
+            failure_mode = 'OK'
+
+        if failure_mode == 'OK':
+            results['H'].append(H)
+            results['Fu'].append(Fu)
+            results['Torque'].append(T)
+            results['Force'].append(F_inst)
+            results['SigmaHelix'].append(sigma_helix)
+            results['SigmaCore'].append(sigma_core)
+            results['BucklingLimit'].append(Fy_cr)
+            results['SigmaWeld'].append(sigma_weld)
+            results['FailureMode'].append(failure_mode)
+
+    if plot:
+        plt.figure(figsize=(7, 5))
+        plt.plot(results['H'], results['Fu'], label=f'Dh/Dc = {Dh/Dc:.2f}')
+        plt.title("Fu vs H")
+        plt.xlabel("Depth H (m)")
+        plt.ylabel("Axial Capacity Fu (N)")
+        plt.grid(True)
+        plt.legend()
+        plt.tight_layout()
+        plt.show()
+
+    return results
+
+if __name__ == '__main__':
+    profile_map = [
+        {
+            'name': 'CPT_1',
+            'x': 0, 'y': 0,
+            'layers': [
+                {'top': 0.0, 'bottom':  5.0, 'soil_type': 'sand', 'gamma_top': 10, 'gamma_bot': 11, 'phi_top': 32, 'phi_bot': 36, 'Dr_top': 55, 'Dr_bot': 65},
+                {'top': 5.0, 'bottom': 20.0, 'soil_type': 'sand', 'gamma_top': 11, 'gamma_bot': 12, 'phi_top': 36, 'phi_bot': 38, 'Dr_top': 65, 'Dr_bot': 80}
+            ]
+        }
+    ]
+
+    results = getInstallationHelical(profile_map, 'CPT_1', D=1.5, L=10.0, d=0.5, plot=True)
+      
\ No newline at end of file
diff --git a/famodel/anchors/anchors_famodel/installation_buckling.py b/famodel/anchors/anchors_famodel/installation_buckling.py
new file mode 100644
index 00000000..ee00f615
--- /dev/null
+++ b/famodel/anchors/anchors_famodel/installation_buckling.py
@@ -0,0 +1,164 @@
+import numpy as np
+import matplotlib.pyplot as plt
+from support_soils import clay_profile, sand_profile
+from installation_suction import getInstallationSuction
+
+def compute_Zs(s, r, t, nu):
+    return (s**2/(r*t))*np.sqrt(1 - nu**2)
+
+def compute_C(psi, rho, xi):
+    return psi*np.sqrt(1 + (rho*xi/psi)**2)
+
+def gamma_M(lam_bar):
+    if lam_bar < 0.5:
+        return 1.15
+    elif lam_bar <= 1.0:
+        return 0.85 + 0.6 * lam_bar
+    else:
+        return 1.45
+
+def getBucklingSuction(profile_map, location_name, D, L, t=None, fy=345e6):
+    '''
+    Shell buckling capacity during suction pile installation using DNV-RP-C202 and Colliard & Wallerand effective length.
+    '''
+    E = 2.1e11
+    nu = 0.3
+
+    if t is None:
+        t = D / 200
+
+    r = D/2 - t/2
+
+    profile_entry = next(p for p in profile_map if p['name'] == location_name)
+    layers = profile_entry['layers']
+    main_type = layers[0]['soil_type'].lower()
+    if main_type == 'clay':
+        clay_input = [[layers[0]['top'],    layers[0]['gamma_top'], layers[0]['Su_top']],
+                      [layers[0]['bottom'], layers[0]['gamma_bot'], layers[0]['Su_bot']]]
+        _, f_gamma, _, _, _ = clay_profile(clay_input)
+    elif main_type == 'sand':
+        sand_input = [[layers[0]['top'],    layers[0]['gamma_top'], layers[0]['phi_top']],
+                      [layers[0]['bottom'], layers[0]['gamma_bot'], layers[0]['phi_bot']]]
+        _, f_gamma, _, _, _ = sand_profile(sand_input)
+    else:
+        raise ValueError("Unsupported soil type")
+
+    depths = np.arange(0.1, L + 0.1, 0.1)  # start from 0.1 to avoid division by zero
+    suction_results = getInstallationSuction(profile_map, location_name, D, L, gamma_m_install=1.5, gamma_m_retrieval=1.25)
+    pe_values = suction_results['delta_u_suction']
+    pe_values = np.full_like(pe_values, 300e3)
+
+    UC_list = []
+    LB_list = []
+    PE_list = []
+    for z, pe in zip(depths, pe_values):
+        # Colliard & Wallerand effective length
+        x = L - z  # exposed length
+        L_B = L*(1 + 2*(x/L) - 0.0435*(x/L)**2)
+        s = L_B
+        LB_list.append(s)
+        PE_list.append(pe/1e3)
+
+        Zs = compute_Zs(s, r, t, nu)
+
+        # fEa (Axial)
+        psi_a = 4.0
+        xi_a = 0.702*Zs
+        rho_a = 0.5*(1 + r/(150 * t))**-0.5
+        C_a = compute_C(psi_a, rho_a, xi_a)
+        fEa = C_a*(np.pi**2*E/(12*(1 - nu**2)))*(t/s)**2
+
+        # fEm (Bending)
+        C_m = C_a
+        fEm = fEa
+
+        # fEtau (Shear)
+        psi_t = 5.34 + (s/L)**2
+        xi_t = 0.856*(s/L)*Zs**(3/4)
+        rho_t = 0.6
+        C_t = compute_C(psi_t, rho_t, xi_t)
+        fEtau = C_t*(np.pi**2*E/(12*(1 - nu**2)))*(t/s)**2
+        
+        # fEh (Hoop)
+        psi_h = (1 + (s/L)**2)**2
+        xi_h = 1.04*(s/L)*np.sqrt(Zs)
+        rho_h = 0.6
+        C_h = compute_C(psi_h, rho_h, xi_h)
+        fEh = C_h*(np.pi**2*E/(12*(1 - nu**2)))*(t/s)**2
+
+        sigma_a = 0.5*pe*r/t
+        sigma_m = 0
+        sigma_h = pe*r/t
+        tau = 0
+
+        sigma_j = np.sqrt((sigma_a)**2 - (sigma_a)*sigma_h + sigma_h**2 + 3*tau**2)
+
+        sigma_a0 = max(0, -sigma_a)
+        sigma_m0 = max(0, -sigma_m)
+        sigma_h0 = max(0, -sigma_h)
+
+        lam_bar_sq = (fy/sigma_j)*(
+            (sigma_a0/fEa) +
+            (sigma_m0/fEm) +
+            (sigma_h0/fEh) +
+            (tau/fEtau)
+        )
+        lam_bar = np.sqrt(lam_bar_sq)
+
+        gammaM = gamma_M(lam_bar)
+        fksd = fy/np.sqrt(1 + lam_bar**4)/gammaM
+
+        UC = sigma_j/fksd
+        UC_list.append(UC)
+
+    fig, axs = plt.subplots(1, 3, figsize=(18, 6))
+
+    axs[0].plot(UC_list, depths, label='UC', color='blue')
+    axs[0].invert_yaxis()
+    axs[0].set_xlabel('Unity check')
+    axs[0].set_ylabel('Depth (m)')
+    axs[0].set_title('Shell buckling UC vs. Depth')
+    axs[0].grid(True)
+    axs[0].legend()
+
+    axs[1].plot(LB_list, depths, label='Buckling Length (L_B)', color='blue')
+    axs[1].invert_yaxis()
+    axs[1].set_xlabel('Effective buckling length (m)')
+    axs[1].set_ylabel('Depth (m)')
+    axs[1].set_title('Buckling Length vs. Depth')
+    axs[1].grid(True)
+    axs[1].legend()
+    
+    axs[2].plot(PE_list, depths, label='Underpressure', color='green')
+    axs[2].invert_yaxis()
+    axs[2].set_xlabel('Underpressure (kPa)')
+    axs[2].set_ylabel('Depth (m)')
+    axs[2].set_title('Suction Pressure vs. Depth')
+    axs[2].grid(True)
+    axs[2].legend()
+
+    plt.tight_layout()
+    plt.show()
+
+    return {
+        'depths': depths.tolist(),
+        'UC_list': UC_list,
+        'LB_list': LB_list
+    }
+
+if __name__ == '__main__':
+    profile_map = [
+        {
+            'name': 'CPT_1',
+            'x': 0, 'y': 0,
+            'layers': [
+                {
+                    'top': 0.0, 'bottom': 20.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 9.0, 'gamma_bot': 9.0,
+                    'Su_top': 5.0, 'Su_bot': 45.0
+                }
+            ]
+        }
+    ]
+    getBucklingSuction(profile_map, 'CPT_1', D=2.0, L=10.4)
diff --git a/famodel/anchors/anchors_famodel/installation_buckling2.py b/famodel/anchors/anchors_famodel/installation_buckling2.py
new file mode 100644
index 00000000..39e13aa1
--- /dev/null
+++ b/famodel/anchors/anchors_famodel/installation_buckling2.py
@@ -0,0 +1,157 @@
+import numpy as np
+import matplotlib.pyplot as plt
+from support_soils import clay_profile, sand_profile
+from support_pycurves import py_Matlock, py_API
+from installation_suction import getInstallationSuction
+
+def compute_Zs(s, r, t, nu):
+    return (s**2/(r*t))*np.sqrt(1 - nu**2)
+
+def compute_C(psi, rho, xi):
+    return psi*np.sqrt(1 + (rho*xi/psi)**2)
+
+def gamma_M(lam_bar):
+    if lam_bar < 0.5:
+        return 1.15
+    elif lam_bar <= 1.0:
+        return 0.85 + 0.6*lam_bar
+    else:
+        return 1.45
+
+def getBucklingSuction(profile_map, location_name, D, L):
+    E = 2.1e11
+    fy = 325e6
+    nu = 0.3
+    t = (2.35 + D*20)/1e3; print(t)            # Suction pile wall thickness (m), API RP2A-WSD
+
+    R = D/2 - t/2
+
+    profile_entry = next(p for p in profile_map if p['name'] == location_name)
+    layers = profile_entry['layers']
+    main_type = layers[0]['soil_type'].lower()
+    if main_type == 'clay':
+        clay_input = [[layers[0]['top'],    layers[0]['gamma_top'], layers[0]['Su_top']],
+                      [layers[0]['bottom'], layers[0]['gamma_bot'], layers[0]['Su_bot']]]
+        _, f_gamma, f_Su, f_sigma_v_eff, _ = clay_profile(clay_input)
+    elif main_type == 'sand':
+        sand_input = [[layers[0]['top'],    layers[0]['gamma_top'], layers[0]['phi_top']],
+                      [layers[0]['bottom'], layers[0]['gamma_bot'], layers[0]['phi_bot']]]
+        _, f_gamma, f_phi, f_Dr, f_sigma_v_eff, _ = sand_profile(sand_input)
+    else:
+        raise ValueError("Unsupported soil type")
+
+    depths = np.arange(0.1, L + 0.1, 0.1)
+    suction_results = getInstallationSuction(profile_map, location_name, D, L, gamma_m_install=1.5, gamma_m_retrieval=1.25)
+    pe_values = np.interp(depths, suction_results['depths'], suction_results['delta_u_suction'])
+
+    def soil_type_map(z):
+        for layer in layers:
+            if layer['top'] <= z <= layer['bottom']:
+                return layer['soil_type'].lower()
+        raise ValueError(f"No soil type defined at depth {z}")
+
+    alpha_list = []
+    y_disp = 0.001
+    for z in depths:
+        stype = soil_type_map(z)
+        if stype == 'clay':
+            py_func, _ = py_Matlock(z, D, f_gamma(z), f_Su(z), f_sigma_v_eff(z), return_curve=True)
+        elif stype == 'sand':
+            py_func, _ = py_API(z, D, f_phi(z), f_sigma_v_eff(z), f_Dr(z), return_curve=True)
+        else:
+            raise ValueError(f"Unsupported soil type at depth {z}")
+        stiffness = py_func(y_disp)/y_disp if y_disp != 0 else 0
+        alpha_list.append(stiffness)
+    alpha_array = np.array(alpha_list)
+    integral_total = np.trapz(alpha_array, depths)
+    alpha_z = np.cumsum(alpha_array)*(depths[1] - depths[0])/integral_total
+
+    UC_list = []
+    PE_list = []
+
+    for z, pe, alpha in zip(depths[:-1], pe_values[:-1], alpha_z[:-1]):
+        s = L  # constant buckling length
+        PE_list.append(pe)
+
+        Zs = compute_Zs(s, R, t, nu)
+
+        psi_a = 4.0
+        xi_a = 0.702*Zs
+        rho_a = 0.5*(1 + R/(150*t))**-0.5
+        C_a = compute_C(psi_a, rho_a, xi_a)
+        fEa = C_a*(np.pi**2*E/(12*(1 - nu**2)))*(t/s)**2
+
+        C_m = C_a
+        fEm = fEa
+
+        psi_h = (1 + (s/L)**2)**2
+        xi_h = 1.04*(s/L)*np.sqrt(Zs)
+        rho_h = 0.6
+        C_h = compute_C(psi_h, rho_h, xi_h)
+        fEh = C_h*(np.pi**2 *E/(12*(1 - nu**2)))*(t/s)**2
+
+        psi_t = 5.34 + (s/L)**2
+        xi_t = 0.856*(s/L)*Zs**(3/4)
+        rho_t = 0.6
+        C_t = compute_C(psi_t, rho_t, xi_t)
+        fEtau = C_t*(np.pi**2*E/(12*(1 - nu**2)))*(t/s)**2
+
+        sigma_a = 0.5*pe*R*(1 - alpha)/t
+        sigma_m = 0
+        sigma_h = pe*R*(1 - alpha)/t
+        tau = 0
+
+        sigma_j = np.sqrt((sigma_a)**2 - (sigma_a)*sigma_h + sigma_h**2 + 3*tau**2)
+
+        sigma_a0 = max(0, -sigma_a)
+        sigma_m0 = max(0, -sigma_m)
+        sigma_h0 = max(0, -sigma_h)
+
+        lam_bar_sq = (fy/sigma_j)*(
+            (sigma_a0/fEa) +
+            (sigma_m0/fEm) +
+            (sigma_h0/fEh) +
+            (tau/fEtau)
+        )
+        lam_bar = np.sqrt(lam_bar_sq)
+
+        gammaM = gamma_M(lam_bar)
+        fksd = fy/np.sqrt(1 + lam_bar**4)/gammaM
+
+        UC = sigma_j/fksd
+        UC_list.append(UC)
+
+    plt.figure(figsize=(6, 6))
+    plt.plot(UC_list, depths[:-1], label='UC (with confinement)', color='darkred')
+    plt.gca().invert_yaxis()
+    plt.xlabel('Unity Check')
+    plt.ylabel('Depth (m)')
+    plt.title('Shell Buckling')
+    plt.grid(True)
+    plt.legend()
+    plt.tight_layout()
+    plt.show()
+
+    return {
+        'depths': depths.tolist(),
+        'UC_list': UC_list,
+        'PE_list': PE_list,
+        'alpha_z': alpha_z.tolist()
+    }
+
+if __name__ == '__main__':
+    profile_map = [
+        {
+            'name': 'CLAY_INSTALL',
+            'x': 0, 'y': 0,
+            'layers': [
+                {
+                    'top': 0.0, 'bottom': 20.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 9.0, 'gamma_bot': 9.0,
+                    'Su_top': 5.0, 'Su_bot': 85.0
+                }
+            ]
+        }
+    ]
+    getBucklingSuction(profile_map, 'CLAY_INSTALL', D=4.0, L=17.0)
diff --git a/famodel/anchors/anchors_famodel/capacity_drag.py b/famodel/anchors/anchors_famodel/installation_drag.py
similarity index 95%
rename from famodel/anchors/anchors_famodel/capacity_drag.py
rename to famodel/anchors/anchors_famodel/installation_drag.py
index d17969e2..c476c3ce 100644
--- a/famodel/anchors/anchors_famodel/capacity_drag.py
+++ b/famodel/anchors/anchors_famodel/installation_drag.py
@@ -1,14 +1,9 @@
-"""
-Drag embedment anchor capacity calculation functions in intermidiate model,
-currently set up for clay soils.
-Lead author: Felipe Moreno. 
-"""
 
 import yaml       # Allow access to config file for user inputs
 import numpy as np
 import matplotlib.pyplot as plt
 
-def getCapacityDrag(Af, Lf, Ls, Lca, Lj, thetafs, bm, En, 
+def getInstallationDrag(Af, Lf, Ls, Lca, Lj, thetafs, bm, En, 
                     nhu, Su0, k, Ne, thetae0, z0,
                     Nn_max, Nt_max, Nm_max, m, n, p, q, plot=True): 
         
@@ -78,7 +73,7 @@ def getCapacityDrag(Af, Lf, Ls, Lca, Lj, thetafs, bm, En,
     Vf = Af*tf
     Vs = Ls*ts*Ws*2
     Va = round(Vf + Vs,1) 
-    W = Va*rhos
+    Wp = Va*rhos
     
     # The Anchor Initial Condition
     Su = Su0 + k*z0         # Undrained shear strength at the initial embedded depth, kPa
@@ -104,7 +99,7 @@ def getCapacityDrag(Af, Lf, Ls, Lca, Lj, thetafs, bm, En,
     thetaf_values = [] 
      
     z = z0; x = x0; Ta = Ta0
-    xmax = 60; Tmax = 30000;
+    xmax = 60; Tmax = 3000;
     
     for _ in range(3000):
         thetaaf = thetaf + thetaa
@@ -164,10 +159,10 @@ def getCapacityDrag(Af, Lf, Ls, Lca, Lj, thetafs, bm, En,
         plt.show()
        
     resultsDrag = {}
-    resultsDrag['capacity'] = max(Ta_values)
-    resultsDrag['W'] = W
+    resultsDrag['Capacity'] = max(Ta_values)
     resultsDrag['embedment_depth'] = z
     resultsDrag['drag_distance'] = x
+    resultsDrag['Weight plate'] = Wp
     
     return resultsDrag
     
@@ -189,7 +184,7 @@ def getCapacityDrag(Af, Lf, Ls, Lca, Lj, thetafs, bm, En,
     m = configDrag['m']; n = configDrag['n']; p = configDrag['p']; q = configDrag['q'];
     z0 = configDrag['z0']; 
         
-    resultsDrag = getCapacityDrag(Af, Lf, Ls, Lca, Lj, thetafs, bm,En, 
+    resultsDrag = getInstallationDrag(Af, Lf, Ls, Lca, Lj, thetafs, bm,En, 
                                   nhu, Su0, k, Ne, thetae0, z0,
                                   Nn_max, Nt_max, Nm_max, m, n, p, q)  
 
diff --git a/famodel/anchors/anchors_famodel/installation_driven.py b/famodel/anchors/anchors_famodel/installation_driven.py
new file mode 100644
index 00000000..9bb85e9d
--- /dev/null
+++ b/famodel/anchors/anchors_famodel/installation_driven.py
@@ -0,0 +1,186 @@
+import numpy as np
+import matplotlib.pyplot as plt
+from capacity_soils_map import clay_profile, sand_profile, rock_profile
+
+def getInstallationDriven(profile_map, location_name, D, L, hammer, J_shaft, J_toe, plot=True, refusal_threshold=0.002, refusal_count=10):
+    dz = 0.24
+    z0 = 1.0
+    max_depth = L
+    N = int((max_depth - z0) / dz)
+
+    t_wall = (6.35 + D * 20) / 1e3
+    D_inner = D - 2 * t_wall
+    A = np.pi / 4 * (D**2 - D_inner**2)
+    E = 2.1e11
+    rhos = 7850
+    g = 9.81
+
+    m = rhos*A*dz
+    k = E*A/dz
+    dt = N/np.sqrt(E/rhos)
+
+    m_r = hammer['m_r']
+    h = hammer['h']
+    eta = hammer['efficiency']
+    E_hammer = eta*m_r*g*h
+    v0 = np.sqrt(2 * E_hammer / m_r)
+
+    soil = profile_map[location_name]
+    layers = soil['layers']
+
+    def compute_Rdynamic(v_local, z, J):
+        for layer in layers:
+            if layer['top'] <= z <= layer['bottom']:
+                if layer['soil_type'] == 'clay':
+                    profile = [[layer['top'],    layer['gamma_top'], layer['Su_top']],
+                               [layer['bottom'], layer['gamma_bot'], layer['Su_bot']]]
+                    _, _, _, _, f_alpha = clay_profile(profile)
+                    return J*f_alpha(z)*v_local*np.pi*D
+                elif layer['soil_type'] == 'sand':
+                    profile = [[layer['top'],    layer['gamma_top'], layer['phi_top'], layer['Dr_top']],
+                               [layer['bottom'], layer['gamma_bot'], layer['phi_bot'], layer['Dr_bot']]]
+                    _, _, _, _, _, f_delta = sand_profile(profile)
+                    return J*f_delta(z)*v_local*np.pi*D
+                elif layer['soil_type'] == 'rock':
+                    profile = [[layer['top'],    layer['UCS_top'], layer['Em_top']],
+                               [layer['bottom'], layer['UCS_bot'], layer['Em_bot']]]
+                    _, f_UCS, _ = rock_profile(profile)
+                    return J*f_UCS(z)*v_local*np.pi*D
+        return 0.0
+
+    def compute_Rstatic(z):
+        for layer in layers:
+            if layer['top'] <= z <= layer['bottom']:
+                if layer['soil_type'] == 'clay':
+                    profile = [[layer['top'],    layer['gamma_top'], layer['Su_top']],
+                               [layer['bottom'], layer['gamma_bot'], layer['Su_bot']]]
+                    _, _, _, _, f_alpha = clay_profile(profile)
+                    return f_alpha(z)*np.pi*D*dz
+                elif layer['soil_type'] == 'sand':
+                    profile = [[layer['top'],    layer['gamma_top'], layer['phi_top'], layer['Dr_top']],
+                               [layer['bottom'], layer['gamma_bot'], layer['phi_bot'], layer['Dr_bot']]]
+                    _, _, _, _, _, f_delta = sand_profile(profile)
+                    return f_delta(z)*np.pi*D*dz
+                elif layer['soil_type'] == 'rock':
+                    profile = [[layer['top'],    layer['UCS_top'], layer['Em_top']],
+                               [layer['bottom'], layer['UCS_bot'], layer['Em_bot']]]
+                    _, f_UCS, _ = rock_profile(profile)
+                    return f_UCS(z)*np.pi*D*dz
+        return 0.0
+
+    penetration = 0.0
+    total_energy = 0.0
+    toe_displacement = []
+    blow_counts = []
+    consecutive_small_blows = 0
+
+    blow = 0
+    while penetration < (max_depth - z0):
+        u = np.zeros(N + 1)
+        v = np.zeros(N + 1)
+        a = np.zeros(N + 1)
+
+        # Apply initial velocity to first node to help energy propagate
+        v[0] = v0
+        T = 0.5
+        nsteps = int(T/dt)
+
+        for step in range(nsteps):
+            F_internal = np.zeros(N + 1)
+            for i in range(1, N):
+                F_internal[i] = k*(u[i - 1] - 2*u[i] + u[i + 1])
+
+            F_internal[N] = k*(u[N - 1] - u[N])
+
+            for i in range(N + 1):
+                z = dz*i + z0
+                
+                if i == N:
+                    F_internal[i] -= compute_Rdynamic(v[i], z, J_toe)
+                    F_internal[i] += compute_Rstatic(z)
+                else:
+                    F_internal[i] -= compute_Rdynamic(v[i], z, J_shaft)
+
+                if step < 10:
+                    print(f"  Step {step}: z = {z:.2f}, Rd = {compute_Rdynamic(v[i], z, J_shaft):.2f}, v = {v[i]:.4f}, u = {u[i]:.4f}")
+
+            a = np.nan_to_num(F_internal / m, nan=0.0, posinf=0.0, neginf=0.0)
+            v += a * dt
+            u += v * dt
+
+            if np.any(np.abs(u) > 5):
+                print("Displacement blew up. Stopping.")
+                break
+
+        delta_z = u[-1]
+        penetration += delta_z
+
+        toe_displacement.append(penetration)
+        blow_counts.append(blow + 1)
+        total_energy += E_hammer
+
+        print(f"Blow {blow + 1}: Δz = {delta_z:.5f} m, Total Penetration = {penetration:.3f} m")
+
+        if abs(delta_z) < refusal_threshold:
+            consecutive_small_blows += 1
+        else:
+            consecutive_small_blows = 0
+
+        if consecutive_small_blows >= refusal_count:
+            print("Refusal criteria met: 10 consecutive blows with <2 mm displacement")
+            break
+
+        blow += 1
+
+    if plot:
+        plt.figure(figsize=(8, 4))
+        plt.plot(blow_counts, toe_displacement, marker='o')
+        plt.xlabel('Blow Count')
+        plt.ylabel('Cumulative Toe Displacement (m)')
+        plt.title('Toe Displacement vs Blow Count')
+        plt.grid(True)
+        plt.tight_layout()
+        plt.show()
+
+    return {
+        'blow_counts': blow_counts,
+        'toe_displacement': toe_displacement,
+        'total_energy': total_energy,
+        'final_depth': penetration,
+        'total_counts': len(blow_counts)
+    }
+
+if __name__ == '__main__':
+    profile_map = {
+        'CPT_1': {
+            'type': 'clay',
+            'x': 498234, 'y': 5725141,
+            'layers': [
+                {
+                    'top': 1.0, 'bottom': 6.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.0, 'gamma_bot': 8.0,
+                    'Su_top': 10, 'Su_bot': 20},
+                {
+                    'top': 6.0, 'bottom': 15.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.0, 'gamma_bot': 8.0,
+                    'Su_top': 80, 'Su_bot': 100},
+                {
+                    'top': 15.0, 'bottom': 30.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.0, 'gamma_bot': 9.0,
+                    'Su_top': 100, 'Su_bot': 200}
+            ]
+        }
+    }
+
+    D = 1.0
+    L = 12.0
+    hammer = {'m_r': 85000, 'h': 5.5, 'efficiency': 0.85}
+    J_shaft = 0.05
+    J_toe = 0.05
+
+    results = getInstallationDriven(profile_map, 'CPT_1', D, L, hammer, J_shaft, J_toe, plot=True)
+    for key, val in results.items():
+        print(f"{key}: {val}")
diff --git a/famodel/anchors/anchors_famodel/installation_driven2.py b/famodel/anchors/anchors_famodel/installation_driven2.py
new file mode 100644
index 00000000..db007b64
--- /dev/null
+++ b/famodel/anchors/anchors_famodel/installation_driven2.py
@@ -0,0 +1,167 @@
+import numpy as np
+import matplotlib.pyplot as plt
+from capacity_soils_map import clay_profile, sand_profile, rock_profile
+
+def compute_Rstatic(z):
+    for layer in layers:
+        if layer['top'] <= z <= layer['bottom']:
+            if layer['soil_type'] == 'clay':
+                profile = [[layer['top'],    layer['gamma_top'], layer['Su_top']],
+                           [layer['bottom'], layer['gamma_bot'], layer['Su_bot']]]
+                _, _, _, _, f_alpha = clay_profile(profile)
+                return f_alpha(z)*np.pi*D*dz
+            elif layer['soil_type'] == 'sand':
+                profile = [[layer['top'],    layer['gamma_top'], layer['phi_top'], layer['Dr_top']],
+                           [layer['bottom'], layer['gamma_bot'], layer['phi_bot'], layer['Dr_bot']]]
+                _, _, _, _, _, f_delta = sand_profile(profile)
+                return f_delta(z)*np.pi*D*dz
+            elif layer['soil_type'] == 'rock':
+                profile = [[layer['top'],    layer['UCS_top'], layer['Em_top']],
+                           [layer['bottom'], layer['UCS_bot'], layer['Em_bot']]]
+                _, f_UCS, _ = rock_profile(profile)
+                return f_UCS(z)*np.pi*D*dz
+    return 0.0
+
+def compute_Rdynamic(v_local, z, J):
+    for layer in layers:
+        if layer['top'] <= z <= layer['bottom']:
+            if layer['soil_type'] == 'clay':
+                profile = [[layer['top'],    layer['gamma_top'], layer['Su_top']],
+                           [layer['bottom'], layer['gamma_bot'], layer['Su_bot']]]
+                _, _, _, _, f_alpha = clay_profile(profile)
+                return J*f_alpha(z)*v_local*np.pi*D
+            elif layer['soil_type'] == 'sand':
+                profile = [[layer['top'],    layer['gamma_top'], layer['phi_top'], layer['Dr_top']],
+                           [layer['bottom'], layer['gamma_bot'], layer['phi_bot'], layer['Dr_bot']]]
+                _, _, _, _, _, f_delta = sand_profile(profile)
+                return J*f_delta(z)*v_local*np.pi*D
+            elif layer['soil_type'] == 'rock':
+                profile = [[layer['top'],    layer['UCS_top'], layer['Em_top']],
+                           [layer['bottom'], layer['UCS_bot'], layer['Em_bot']]]
+                _, f_UCS, _ = rock_profile(profile)
+                return J*f_UCS(z)*v_local*np.pi*D
+    return 0.0
+
+def getInstallationDriven(profile_map, location_name, D_input, L, hammer, J_shaft, J_toe, plot):
+    global D, dz, layers
+    D = D_input
+    soil = profile_map[location_name]
+    layers = soil['layers']
+    z0 = layers[0]['top']
+
+    N = 100
+    z = np.linspace(z0, L, N)
+    dz = z[1] - z[0]
+
+    dt = 0.001
+    t_max = 2.0
+    time = np.arange(0, t_max, dt)
+
+    u = np.zeros((len(time), N))
+    v = np.zeros((len(time), N))
+    F = np.zeros((len(time), N))
+
+    rho_steel = 7850
+    t = 0.05
+    A = np.pi * ((D / 2)**2 - ((D / 2) - t)**2)
+    m_total = A * L * rho_steel
+    M_prime = m_total / N
+
+    m_r = hammer['m_r']
+    h = hammer['h']
+    eff = hammer['efficiency']
+    E = m_r * 9.81 * h * eff
+
+    blow_count = 0
+    penetration = 0.0
+    z_vals = []
+    blow_vals = []
+    refusal_counter = 0
+    refusal_limit = 10
+    min_set = 0.002
+
+    while penetration < L and refusal_counter < refusal_limit:
+        blow_count += 1
+        v0 = np.sqrt(2 * E / m_r)
+        v[0, 0] = v0
+
+        for n in range(1, len(time)):
+            for i in range(1, N - 1):
+                u_xx = (u[n - 1, i + 1] - 2 * u[n - 1, i] + u[n - 1, i - 1]) / dz**2
+                F[n, i] = M_prime * u_xx
+
+            v[n] = v[n - 1] + (F[n] / M_prime) * dt
+            u[n] = u[n - 1] + v[n] * dt
+
+        delta_z = max(u[-1, :])
+        tip_depth = penetration + delta_z
+
+        Rs = compute_Rstatic(tip_depth)
+        Rt = 9.0 * compute_Rstatic(tip_depth)
+        R_total = Rs + Rt + compute_Rdynamic(v[-1, -1], tip_depth, J_shaft)
+
+        penetration += delta_z
+        z_vals.append(penetration)
+        blow_vals.append(blow_count)
+
+        if delta_z < min_set:
+            refusal_counter += 1
+        else:
+            refusal_counter = 0
+
+    if plot:
+        plt.figure()
+        plt.plot(z_vals, blow_vals, label='Blows vs Penetration')
+        plt.xlabel('Penetration Depth [m]')
+        plt.ylabel('Blow Count')
+        plt.title('Driveability Simulation')
+        plt.grid(True)
+        plt.legend()
+        plt.show()
+
+    return {
+        'z': z,
+        'z_vals': z_vals,
+        'blow_vals': blow_vals,
+        'u': u,
+        'v': v,
+        'F': F,
+        'dt': dt,
+        'dz': dz
+    }
+
+
+if __name__ == '__main__':
+    profile_map = {
+        'CPT_1': {
+            'type': 'clay',
+            'x': 498234, 'y': 5725141,
+            'layers': [
+                {
+                    'top': 1.0, 'bottom': 6.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.0, 'gamma_bot': 8.0,
+                    'Su_top': 10, 'Su_bot': 20},
+                {
+                    'top': 6.0, 'bottom': 15.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.0, 'gamma_bot': 8.0,
+                    'Su_top': 80, 'Su_bot': 100},
+                {
+                    'top': 15.0, 'bottom': 30.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 8.0, 'gamma_bot': 9.0,
+                    'Su_top': 100, 'Su_bot': 200}
+            ]
+        }
+    }
+
+    D = 1.0
+    L = 12.0
+    hammer = {'m_r': 155000, 'h': 5.5, 'efficiency': 0.85}
+    J_shaft = 0.05
+    J_toe = 0.05
+
+    results = getInstallationDriven(profile_map, 'CPT_1', D, L, hammer, J_shaft, J_toe, plot=True)
+    for key, val in results.items():
+        print(f"{key}: {val}")
\ No newline at end of file
diff --git a/famodel/anchors/anchors_famodel/installation_dynamic.py b/famodel/anchors/anchors_famodel/installation_dynamic.py
new file mode 100644
index 00000000..95c97834
--- /dev/null
+++ b/famodel/anchors/anchors_famodel/installation_dynamic.py
@@ -0,0 +1,164 @@
+
+import numpy as np
+import matplotlib.pyplot as plt
+from support_soils import clay_profile
+
+def PileWeight(L1, L2, D1, D2, tw, rho):
+    return ((np.pi/4)*(D1**2 - (D1 - 2*tw)**2)*(L1 + L2) + 4*L2*D2*tw)*rho
+
+def PileVolume(L1, L2, D1, D2, tw):
+    return (np.pi/4)*D1**2*(L1 + L2) + 4*L2*D2*tw
+
+def PileWingedSurface(length, diameter1, diameter2):
+    return 8*length*(diameter1 - diameter2)
+
+def PileShaftSurface(length, diameter):
+    return np.pi*diameter*length
+
+def getInstallationDynamic(profile_map, location_name, D1, D2, L1, L2, ballast, drop_height, plot=True):
+    """
+    Deterministic installation model of a torpedo pile in clay based on time-domain integration.
+    Implements the model by True (1976) as adapted in Kazue et al. (2020), accounting for layered soil.
+    """
+    # Constants
+    rhows = 66.90e3                  # Submerged steel specific weight (N/m3)
+    rhow = 10e3                      # Water specific weight (N/m3) 
+    Sti = 3.0
+    Se = 5.0
+    Ce = 0.02
+    delta = 0.9
+    Nc = 9.0
+    CD = 2.7
+    dt = 0.002
+    tmax = 15.0
+    beta = 28/27
+    g = 9.81
+
+    # Geometry
+    D = D1                  # use the wing diameter for frontal area
+    L = L1 + L2
+    t = (6.35 + D2*20)/1e3  # assumed same as in getCapacityTorpedo
+
+    # Retrieve soil profile and construct full profile list
+    profile_entry = next(p for p in profile_map if p['name'] == location_name)
+    layers = profile_entry['layers']
+    profile = []
+    for layer in layers:
+        if layer['soil_type'] != 'clay':
+            continue
+        profile.append([layer['top'],    layer['Su_top'], layer['gamma_top']])
+        profile.append([layer['bottom'], layer['Su_bot'], layer['gamma_bot']])
+
+    # Sort and remove duplicates if needed
+    # profile = sorted(list({(z, su, g) for z, su, g in profile}), key=lambda x: x[0])
+    z_ref, f_gamma, f_Su, _, f_delta = clay_profile(profile)
+
+    # Precompute parameters
+    Af = np.pi*(D2**2)/4 + 4*(D2 - D1)*t
+    As = PileWingedSurface(L1, D1, D2) + PileShaftSurface(L1 + L2, D2)
+    Vol = PileVolume(L1, L2, D1, D2, t)
+    Wp = PileWeight(L1, L2, D1, D2, t, rhows) + ballast; #print(f'Wp = {Wp:.2f} N')
+    M = Wp/g
+    Mprime = M + 2*rhow*Vol
+
+    # Closed-form solution for v_impact from free fall in water
+    CD_water = 1.2
+    A_water = Af
+    vt = np.sqrt((2*Mprime*g)/(rhow*CD_water*A_water))
+    t_impact = (vt/g)*np.arccosh(np.exp(g*drop_height/vt**2))
+    v_impact = vt*np.tanh(g*t_impact/vt)
+
+    # Initial conditions
+    t = [0.0]
+    z = [0.0]
+    v = [v_impact]
+    a = [Wp/Mprime]
+
+    # Integration constants
+    beta1 = dt**2*(0.5 - beta)
+    beta2 = dt**2*beta
+    gamma1 = -0.5*dt
+    gamma2 = 1.5*dt
+    nsteps = int(tmax/dt)
+
+    for i in range(nsteps):
+        zn = z[-1]
+        vn = v[-1]
+        an = a[-1]
+
+        Su = f_Su(zn)
+        gamma = f_gamma(zn)
+        delta = f_delta(zn)
+        rho = gamma/g
+        Se_dot = Se/(1 + (1/np.sqrt(Ce*vn/(Su*D2)) + 0.06)) if vn > 0 else 1.0
+
+        Mprime_local = M + 2*rho*Vol
+        FD = 0.5*rhow*CD*Af*vn*abs(vn)
+        FT = Su*Nc*Af*Se_dot
+        FS = Su*As*delta*Se_dot/Sti
+
+        f_total = (Wp - Vol*gamma) - FD - FT - FS 
+        an1 = f_total/Mprime_local
+
+        zn1 = zn + dt*vn + beta1*an + beta2*an1
+        vn1 = vn + gamma1*an + gamma2*an1
+
+        if vn1 < 0:
+            break  # penetration stops
+
+        t.append(t[-1] + dt)
+        z.append(zn1)
+        v.append(vn1)
+        a.append(an1)
+
+    if plot:
+        fig, ax1 = plt.subplots()
+        ax1.plot(t, z, 'b', label='Penetration depth (m)')
+        ax1.set_xlabel('Time (s)')
+        ax1.set_ylabel('Depth (m)')
+        ax1.grid(True)
+
+        ax2 = ax1.twinx()
+        ax2.plot(t, v, 'r', label='Velocity (m/s)')
+        ax2.set_ylabel('Velocity (m/s)')
+
+        fig.suptitle('Torpedo Pile Installation Response')
+        fig.legend(loc='upper right')
+        plt.tight_layout()
+        plt.show()
+
+    return {
+        'final_depth': z[-1],
+        'max_velocity': max(v),
+        'penetration_time': t[-1]
+    }
+
+if __name__ == '__main__':
+    profile_map = [
+        {
+            'name': 'CPT_1',
+            'x': 0, 'y': 0,
+            'layers': [
+                {'top': 0.0, 'bottom': 30.0, 'soil_type': 'clay',
+                 'gamma_top': 8.0, 'gamma_bot': 8.5,
+                 'Su_top': 5, 'Su_bot': 20},
+                {'top': 30.0, 'bottom': 100.0, 'soil_type': 'clay',
+                 'gamma_top': 8.5, 'gamma_bot': 9.0,
+                 'Su_top': 20, 'Su_bot': 60}
+            ]
+        }
+    ]
+
+    location = 'CPT_1'
+    D1 = 3.0
+    D2 = 1.5
+    L1 = 5.0
+    L2 = 5.0
+    ballast = 350000
+    drop_height = 200
+
+    results = getInstallationDynamic(profile_map, location, D1, D2, L1, L2, ballast, drop_height)
+
+    print("\n--- Torpedo Installation Results ---")
+    for k, v in results.items():
+        print(f"{k}: {v:.2f}")
diff --git a/famodel/anchors/anchors_famodel/installation_dynamic2.py b/famodel/anchors/anchors_famodel/installation_dynamic2.py
new file mode 100644
index 00000000..f55c7f21
--- /dev/null
+++ b/famodel/anchors/anchors_famodel/installation_dynamic2.py
@@ -0,0 +1,152 @@
+import numpy as np
+import matplotlib.pyplot as plt
+from support_soils import clay_profile
+
+def PileWeight(L1, L2, D1, D2, tw, gamma):
+    return ((np.pi/4)*(D1**2 - (D1 - 2*tw)**2)*(L1 + L2) + 4*L2*D2*tw)*gamma
+
+def PileVolume(L1, L2, D1, D2, tw):
+    return (np.pi/4)*D1**2*(L1 + L2) + 4*L2*D2*tw
+
+def PileWingedSurface(length, diameter1, diameter2):
+    return 8*length*(diameter1 - diameter2)
+
+def PileShaftSurface(length, diameter):
+    return np.pi*diameter*length
+
+def getInstallationDynamic(profile_map, location_name, D1, D2, L1, L2, ballast, drop_height, plot=True):
+    """
+    Penetration of torpedo pile using depth-based formulation (Eq. 2.10).
+    """
+    # Constants
+    rhows = 66.90e3     # Submerged unit weight of steel (N/m³)
+    rhow = 10e3         # Unit weight of water (N/m³)
+    Sti = 2.0           # Installation strain-rate index (-), affects side friction strain-rate correction
+    Se = 5.0            # Strain-rate multiplier (-), empirical factor for rate effects
+    Ce = 0.02           # Strain-rate coefficient (-), controls shape of strain-rate correction
+    Nc = 9.0            # Bearing capacity factor for undrained clay [-], used in tip resistance (q = Nc * Su)
+    CD = 2.7            # Drag coefficient (-), for a cylindrical body falling in water
+    dz = 1              # Depth increment (m), used in depth-stepping integration
+    g = 9.81            # Gravitational acceleration (m/s²)
+
+
+    # Geometry
+    D = D1
+    L = L1 + L2
+    t = (6.35 + D2*20)/1e3
+
+    # Soil profile
+    profile_entry = next(p for p in profile_map if p['name'] == location_name)
+    layers = profile_entry['layers']
+    profile = []
+    for layer in layers:
+        if layer['soil_type'] != 'clay': continue
+        profile.append([layer['top'],    layer['gamma_top'], layer['Su_top']])
+        profile.append([layer['bottom'], layer['gamma_bot'], layer['Su_bot']])
+    # profile = sorted(list({(z, su, g) for z, su, g in profile}), key=lambda x: x[0])
+    z0, f_gamma, f_Su, _, f_delta = clay_profile(profile)
+    # print('\n--- f_gamma and f_Su vs Depth ---')
+    # z_start = z0
+    # z_end = profile[-1][0]
+    # z_vals = np.linspace(z_start, z_end, 10)
+    # for z_val in z_vals:
+    #     gamma_val = f_gamma(z_val)
+    #     Su_val = f_Su(z_val)
+    #     print(f'z = {z_val:.1f} m → gamma = {gamma_val:.2f} N/m³, Su = {Su_val:.2f} Pa')
+
+    # Parameters
+    Af = np.pi*(D2**2)/4 + 4*(D2 - D1)*t
+    As = PileWingedSurface(L1, D1, D2) + PileShaftSurface(L1 + L2, D2)
+    Vol = PileVolume(L1, L2, D1, D2, t)
+    Wp = PileWeight(L1, L2, D1, D2, t, rhows + rhow) + ballast; print(f'Wp = {Wp:.2f} N')
+    M = Wp/g
+    Mprime = M + 2*f_gamma(2*L/3)*Vol
+
+    CD_water = 1.2
+    vt = np.sqrt((2*Mprime*g)/(rhow*CD_water*Af))
+    t_impact = (vt/g)*np.arccosh(np.exp(g*drop_height/vt**2))
+    v_impact = vt*np.tanh(g*t_impact/vt)
+
+    # Loop
+    v = [v_impact]; #print(v)
+    z = [0.0]
+    term1_values, term2_values = [0.0], [0.0]
+    i = 0
+    while v[-1] > 0:
+        zi = z[-1]
+        vi = v[-1]
+        Sui = f_Su(zi); #print(f'Sui = {Sui:.2f} Pa')
+        gammai = f_gamma(zi); #print(f'gammai  = {gammai:.2f} N/m3')
+        rhoi = gammai/g; #print(f'rhoi  = {rhoi:.2f} kg/m3')
+        deltai = f_delta(zi)
+        Mprime_local = M + 2*rhoi*Vol
+        term1 = (Wp - Vol*gammai) - (0.5*CD*rhoi*Af*vi**2); #print(f'term1  = {term1:.2f} N')
+        term2 = Sui*(Af*Nc + As*deltai/Sti)
+        Se_dot = Se/(1 + (1/np.sqrt(Ce*vi/(Sui*D)) + 0.06)); #print(f'Se_dot  = {Se_dot:.2f}')
+        top = 2*dz*(term1 - term2)*Se_dot; #print(f'top  = {top:.2f}')
+        bottom = vi*Mprime_local; #print(f'bottom  = {bottom:.2f}')
+        vi1 = vi + top/bottom
+        if vi1 < 0.01:
+            print(f'Stopping due to low velocity at z = {zi:.2f} m')
+            break
+
+        v.append(vi1)
+        z.append(zi + dz)
+        term1_values.append(term1)
+        term2_values.append(term2)
+        i += 1
+        #print(f'z = {zi:.2f} m | term1 (drive) = {term1:.2f} N | term2 (resist) = {term2:.2f} N | net = {term1 - term2:.2f} N')
+
+    if plot:
+        fig, ax1 = plt.subplots()
+        ax1.plot(z, v, 'b', label='Velocity vs Depth')
+        ax1.set_xlabel('Depth (m)')
+        ax1.set_ylabel('Velocity (m/s)')
+        
+        ax2 = ax1.twinx()
+        ax2.plot(z, term1_values, 'r', label='Drive (N)')
+        ax2.plot(z, term2_values, 'g', label='Resist (N)')
+        ax2.set_ylabel('Forces (N)')
+        
+        ax1.grid(True)
+        plt.title('Depth-based Penetration of Torpedo Pile')
+        plt.legend(loc='upper right')
+        plt.tight_layout()
+        plt.show()
+
+    return {
+        'final_depth': z[-1],
+        'v_max': max(v),
+        'v_impact': v_impact,
+        'steps': i
+    }
+
+if __name__ == '__main__':
+    profile_map = [
+        {
+            'name': 'CPT_1',
+            'x': 0, 'y': 0,
+            'layers': [
+                {'top': 0.0, 'bottom': 60.0, 'soil_type': 'clay',
+                 'gamma_top': 8.5, 'gamma_bot': 8.5,
+                 'Su_top': 5, 'Su_bot': 85},
+                {'top': 40.0, 'bottom': 400.0, 'soil_type': 'clay',
+                 'gamma_top': 8.5, 'gamma_bot': 8.5,
+                 'Su_top': 85, 'Su_bot': 805}
+            ]
+        }
+    ]
+
+    location = 'CPT_1'
+    D1 = 3.0
+    D2 = 1.5
+    L1 = 10.0
+    L2 = 5.0
+    ballast = 10000
+    drop_height = 20
+
+    results = getInstallationDynamic(profile_map, location, D1, D2, L1, L2, ballast, drop_height)
+
+    print("\n--- Torpedo Installation Results ---")
+    for k, v in results.items():
+        print(f"{k}: {v:.2f}")
diff --git a/famodel/anchors/anchors_famodel/installation_dynamic3.py b/famodel/anchors/anchors_famodel/installation_dynamic3.py
new file mode 100644
index 00000000..625b4161
--- /dev/null
+++ b/famodel/anchors/anchors_famodel/installation_dynamic3.py
@@ -0,0 +1,126 @@
+
+import numpy as np
+import matplotlib.pyplot as plt
+from installation_dynamic import getInstallationDynamic
+from scipy.stats import lognorm
+
+def getInstallationDynamicMC(profile_map, location, D1, D2, L1, L2, ballast, drop_height, N_sim=2000):
+    np.random.seed(16)
+    
+    # Lognormal distribution parameters
+    Suk_mean, Suk_std = 1.9, 0.9
+    Sti_mean, Sti_std = 3.2, 1.0
+
+    Suk_samples = np.random.lognormal(mean=np.log(Suk_mean), sigma=Suk_std/Suk_mean, size=N_sim)
+    Sti_samples = np.random.lognormal(mean=np.log(Sti_mean), sigma=Sti_std/Sti_mean, size=N_sim)
+
+    final_depths = []
+
+    for Suk, Sti in zip(Suk_samples, Sti_samples):
+        # Update profile with consistent linear Su(z)
+        profile = [dict(profile_map[0])]  
+        Su0 = profile[0]['layers'][0]['Su_top']
+        for layer in profile[0]['layers']:
+            z_top = layer['top']
+            z_bot = layer['bottom']
+            layer['Su_top'] = Su0 + Suk*z_top
+            layer['Su_bot'] = Su0 + Suk*z_bot
+        
+        # Override getInstallationDynamic with fixed Sti
+        result = getInstallationDynamic(profile, location, D1, D2, L1, L2, ballast, drop_height, plot=False)
+        
+        final_depths.append(result['final_depth'])
+        
+    # Fit lognormal distribution to the data
+    shape, loc, scale = lognorm.fit(final_depths, floc=0)  
+    x = np.linspace(min(final_depths), max(final_depths), 500)
+    pdf = lognorm.pdf(x, shape, loc=loc, scale=scale)
+
+    # Create subplot
+    fig, axs = plt.subplots(1, 2, figsize=(12, 5))
+    
+    # Fit lognormals
+    s_Suk, loc_Suk, scale_Suk = lognorm.fit(Suk_samples, floc=0)
+    s_Sti, loc_Sti, scale_Sti = lognorm.fit(Sti_samples, floc=0)
+        
+    # Generate x values for plotting
+    x_Suk = np.linspace(min(Suk_samples), max(Suk_samples), 500)
+    x_Sti = np.linspace(min(Sti_samples), max(Sti_samples), 500)
+    
+    # Compute PDFs
+    pdf_Suk = lognorm.pdf(x_Suk, s_Suk, loc=loc_Suk, scale=scale_Suk)
+    pdf_Sti = lognorm.pdf(x_Sti, s_Sti, loc=loc_Sti, scale=scale_Sti)
+    
+    # Compute max density from histograms and PDFs for setting common ylim
+    hist_Suk_vals, _ = np.histogram(Suk_samples, bins=40, density=True)
+    hist_Sti_vals, _ = np.histogram(Sti_samples, bins=40, density=True)
+    y_max = max(max(hist_Suk_vals), max(hist_Sti_vals), max(pdf_Suk), max(pdf_Sti)) * 1.1
+    
+    # Plot Suk PDF
+    axs[0].hist(Suk_samples, bins=40, density=True, alpha=0.6, color='lightgreen', edgecolor='g', label='Samples')
+    axs[0].plot(x_Suk, pdf_Suk, 'r', label='Fitted Lognormal')
+    axs[0].set_title('Lognormal Fit for $S_{uk}$')
+    axs[0].set_xlabel('Suk (kPa/m)')
+    axs[0].set_ylabel('Density')
+    axs[0].set_ylim(0, y_max)
+    axs[0].legend()
+    axs[0].grid(True)
+    
+    # Plot Sti PDF
+    axs[1].hist(Sti_samples, bins=40, density=True, alpha=0.6, color='lightblue', edgecolor='b', label='Samples')
+    axs[1].plot(x_Sti, pdf_Sti, 'r', label='Fitted Lognormal')
+    axs[1].set_title('Lognormal Fit for $S_{ti}$')
+    axs[1].set_xlabel('Sti (dimensionless)')
+    axs[1].set_ylabel('Density')
+    axs[1].set_ylim(0, y_max)
+    axs[1].legend()
+    axs[1].grid(True)
+       
+    # Plot histogram with fitted lognormal
+    plt.figure(figsize=(8, 5))
+    plt.hist(final_depths, bins=40, alpha=0.6, density=True, color='lightsalmon', edgecolor='r', label='Simulated PDF')
+    plt.plot(x, pdf, 'r', lw=2, label='Fitted Lognormal')
+    plt.axvline(np.median(final_depths), color='k', linestyle='--', label=f'Median = {np.median(final_depths):.2f} m')
+    plt.title('Monte Carlo Simulation with Fitted Lognormal Distribution')
+    plt.xlabel('Penetration (m)')
+    plt.ylabel('Density')
+    plt.legend()
+    plt.grid(True)
+    plt.tight_layout()
+    plt.show()
+    
+    # Print parameters
+    print(f'Lognormal fit parameters:')
+    print(f'  mean                   = {np.mean(final_depths):.2f}')
+    print(f'  mean - 1 std deviation = {np.mean(final_depths) - np.std(final_depths):.2f}')
+    print(f'  mean + 1 std deviation = {np.mean(final_depths) + np.std(final_depths):.2f}')
+
+    return final_depths
+
+# Example usage in main
+if __name__ == '__main__':
+    profile_map = [
+        {
+            'name': 'CPT_1',
+            'x': 0, 'y': 0,
+            'layers': [
+                {'top': 0.0, 'bottom': 30.0, 'soil_type': 'clay',
+                 'gamma_top': 8.0, 'gamma_bot': 8.5,
+                 'Su_top': 5, 'Su_bot': 20},
+                {'top': 30.0, 'bottom': 180.0, 'soil_type': 'clay',
+                 'gamma_top': 8.5, 'gamma_bot': 9.0,
+                 'Su_top': 20, 'Su_bot': 150}
+            ]
+        }
+    ]
+
+    location = 'CPT_1'
+    D1 = 3.0
+    D2 = 1.2
+    L1 = 5.0
+    L2 = 5.0
+    ballast = 300000
+    drop_height = 200
+
+    # Run Monte Carlo Simulation
+    depths = getInstallationDynamicMC(profile_map, location, D1, D2, L1, L2, ballast, drop_height)
diff --git a/famodel/anchors/anchors_famodel/installation_suction.py b/famodel/anchors/anchors_famodel/installation_suction.py
new file mode 100644
index 00000000..7c474082
--- /dev/null
+++ b/famodel/anchors/anchors_famodel/installation_suction.py
@@ -0,0 +1,215 @@
+import numpy as np
+import matplotlib.pyplot as plt
+from support_soils import clay_profile
+
+def PileWeight(Len, Dia, tw, rho):
+    return ((np.pi/4)*((Dia**2 - (Dia - 2*tw)**2)*Len + (np.pi/4)*Dia**2*tw))*rho
+
+def getInstallationSuction(profile_map, location_name, D, L, gamma_m_install=1.5, gamma_m_retrieval=1.25):
+    '''
+    Installation and retrieval pressure assessment for suction piles in clay using a layered profile.
+    Returns a dictionary with pressure values and resistances.
+    '''
+    # Constants and geometry
+    profile_entry = next(p for p in profile_map if p['name'] == location_name)
+    layers = profile_entry['layers']
+
+    rhows = 66.90e3                  # Submerged steel specific weight (N/m3)
+    rhow = 10e3                      # Water specific weight (N/m3) 
+
+    WT = D/200; print(WT)
+    t = (6.35 + D*20)/1e3; print(t)  # Suction pile wall thickness (m), API RP2A-WSD
+    Di = D - 2*WT
+    Asi = np.pi * Di
+    Aso = np.pi * D
+    Awall = 0.25  # m²
+    Aplug = np.pi * Di**2 / 4
+    Nc_strip_deep = 7.5
+    Nc_circle = 9.0
+    alphaD_su = 0.25
+    Wp = PileWeight(L, D, WT, rhows); print(Wp)
+    Wsub_steel = 750e3  # in N
+
+    # Convert layer data into clay profile format
+    z0 = layers[0]['top']
+    z_bot = layers[0]['bottom']
+    gamma_top = layers[0]['gamma_top']
+    gamma_bot = layers[0]['gamma_bot']
+    Su_top = layers[0]['Su_top']
+    Su_bot = layers[0]['Su_bot']
+
+    clay_input = [
+        [z0,    gamma_top, Su_top],
+        [z_bot, gamma_bot, Su_bot]
+    ]
+
+    _, f_gamma, f_Su, f_sigma_v_eff, f_alpha = clay_profile(clay_input)
+
+    # Diagnostic: evaluate and plot alpha(z)
+    z_plot = np.linspace(z0, z_bot, 100)
+    alpha_plot = f_alpha(z_plot)
+
+    # print('\n--- Adhesion Factor α(z) ---')
+    # for z_check in [0, 2, 4, 6, 8, 10, 12, 14, 17]:
+        # print(f"z = {z_check:>5.2f} m → α = {f_alpha(z_check):.3f}")
+
+    # plt.figure(figsize=(5, 4))
+    # plt.plot(alpha_plot, z_plot, label='α(z)', color='purple')
+    # plt.gca().invert_yaxis()
+    # plt.grid(True)
+    # plt.xlabel('Adhesion Factor α')
+    # plt.ylabel('Depth (m)')
+    # plt.title('API Clay Adhesion Factor vs Depth')
+    # plt.tight_layout()
+    # plt.show()
+
+    # Prepare output arrays
+    depths = np.arange(0, L + 0.1, 0.1)
+    Rsuction_list = []
+    delta_u_suction_list = []
+    delta_u_retrieval_list = []
+    delta_u_all_install_list = []
+    delta_u_all_retrieval_list = []
+    SWP_depth = None
+
+    for L in depths:
+        z_tip = L
+        z_mid = L/2
+        z_tip_ext = L + alphaD_su*Di
+
+        su_av_L = f_Su(z_mid)
+        int_su = (su_av_L)*L
+        su_tip = f_Su(z_tip)
+        su_av_tip = f_Su(z_tip_ext)
+        # alpha_i = alpha_o = float(f_alpha(z_mid))
+        alpha_i = alpha_o = 0.3
+
+        Fi = Asi*alpha_i*int_su
+        Fo = Aso*alpha_o*int_su
+        Qw = Awall*Nc_strip_deep*su_tip
+
+        Rsuction = Fi + Fo + Qw
+        Rretrieval = Rsuction
+        delta_u_suction = max((Rsuction - Wp)/Aplug, 0.0) 
+        delta_u_retrieval = (Rretrieval + Wp)/Aplug
+        delta_u_all_install   = Fi/Aplug + Nc_circle*su_av_tip/gamma_m_install
+        delta_u_all_retrieval = Fi/Aplug + Nc_circle*su_av_tip/gamma_m_retrieval
+
+        Rsuction_list.append(Rsuction)
+        delta_u_suction_list.append(delta_u_suction)
+        delta_u_retrieval_list.append(delta_u_retrieval)
+        delta_u_all_install_list.append(delta_u_all_install)
+        delta_u_all_retrieval_list.append(delta_u_all_retrieval)
+
+        if SWP_depth is None and Rsuction >= Wp:
+            SWP_depth = L
+
+    # Plotting
+    fig, axs = plt.subplots(1, 3, figsize=(10, 7))
+
+    axs[0].plot(Rsuction_list, depths, label='Installation Resistance', color='blue')
+    if SWP_depth is not None:
+        axs[0].axvline(Wp, color='red', linestyle='--', label=f'SWP = {SWP_depth:.2f} m')
+    axs[0].set_xlabel('Installation Resistance (N)')
+    axs[0].set_ylabel('Penetration (m)')
+    axs[0].set_title('Installation Resistance vs Penetration')
+    axs[0].grid(True)
+    axs[0].invert_yaxis()
+    axs[0].legend()
+
+    axs[1].plot(delta_u_suction_list, depths, label='Underpressure', color='green')
+    axs[1].plot(delta_u_all_install_list, depths, label='Δu allowable install', color='orange')
+    if SWP_depth is not None:
+        axs[1].axhline(SWP_depth, color='red', linestyle='--', label=f'SWP = {SWP_depth:.2f} m')
+    axs[1].set_xlabel('Underpressure (Pa)')
+    axs[1].set_ylabel('Penetration (m)')
+    axs[1].set_title('Underpressure vs Penetration')
+    axs[1].grid(True)
+    axs[1].invert_yaxis()
+    axs[1].legend()
+    
+    axs[2].plot(delta_u_retrieval_list, depths, label='Overpressure', color='green')
+    axs[2].plot(delta_u_all_retrieval_list, depths, label='Δu allowable retrieve', color='orange')
+    axs[2].set_xlabel('Overpressure (Pa)')
+    axs[2].set_ylabel('Penetration (m)')
+    axs[2].set_title('Overpressure vs Penetration')
+    axs[2].grid(True)
+    axs[2].invert_yaxis()
+    axs[2].legend()
+
+    plt.tight_layout()
+    plt.show()
+
+    # Final state outputs
+    L = L
+    z_tip = L
+    z_mid = L/2
+    z_tip_ext = L + alphaD_su*Di
+
+    su_av_L = f_Su(z_mid)
+    int_su = su_av_L*L
+    su_tip = f_Su(z_tip)
+    su_av_tip = f_Su(z_tip_ext)
+    alpha_i = alpha_o = float(f_alpha(z_mid))
+    alpha_i = alpha_o = 0.3
+
+    Fi = Asi*alpha_i*int_su
+    Fo = Aso*alpha_o*int_su
+    Qw = Awall*Nc_strip_deep*su_tip
+
+    Rsuction = Fi + Fo + Qw
+    Rretrieval = Rsuction
+
+    delta_u_suction = max((Rsuction - Wp)/Aplug, 0.0)  
+    delta_u_retrieval = (Rretrieval + Wp)/Aplug  
+
+    delta_u_all_install   = Fi/Aplug + Nc_circle*su_av_tip/gamma_m_install
+    delta_u_all_retrieval = Fi/Aplug + Nc_circle*su_av_tip/gamma_m_retrieval
+
+    return {
+        'layers': layers,
+        'depths': depths,
+        'z0': z0,
+        'D': D,
+        'L': L,
+        'Di': Di,
+        'Asi': Asi,                       # m
+        'Aso': Aso,                       # m
+        'Aplug': Aplug,                   # m²
+        'su_av_L': su_av_L/1e3,           # kPa
+        'int_su': int_su/1e3,             # kN/m
+        'su_tip': su_tip/1e3,             # kPa
+        'su_av_tip': su_av_tip/1e3,       # kPa
+        'Fi': Fi/1e3,                     # kN
+        'Fo': Fo/1e3,                     # kN
+        'Qw': Qw/1e3,                     # kN
+        'Rsuction': Rsuction/1e6,         # MN
+        'Rretrieval': Rretrieval/1e6,     # MN
+        'delta_u_suction': delta_u_suction_list,              # kPa
+        'delta_u_retrieval': delta_u_retrieval/1e3,           # kPa
+        'delta_u_all_install': delta_u_all_install/1e3,       # kPa
+        'delta_u_all_retrieval': delta_u_all_retrieval/1e3,   # kPa
+        'SWP_depth': SWP_depth}
+
+if __name__ == '__main__':
+    profile_map = [
+        {
+            'name': 'CLAY_INSTALL',
+            'x': 0, 'y': 0,
+            'layers': [
+                {
+                    'top': 0.0, 'bottom': 20.0,
+                    'soil_type': 'clay',
+                    'gamma_top': 9.0, 'gamma_bot': 9.0,
+                    'Su_top': 5.0, 'Su_bot': 45.0
+                }
+            ]
+        }
+    ]
+
+    results = getInstallationSuction(profile_map, 'CLAY_INSTALL', D=4.0, L=17.0)
+    for k, v in results.items():
+        if isinstance(v, float):
+            print(f"{k:<25} = {v:.2f}")
+        else:
+            print(f"{k:<25} = {v}")
\ No newline at end of file
diff --git a/famodel/anchors/anchors_famodel_map/capacity_plots_map.py b/famodel/anchors/anchors_famodel/support_plots.py
similarity index 89%
rename from famodel/anchors/anchors_famodel_map/capacity_plots_map.py
rename to famodel/anchors/anchors_famodel/support_plots.py
index d733fade..c01a68fc 100644
--- a/famodel/anchors/anchors_famodel_map/capacity_plots_map.py
+++ b/famodel/anchors/anchors_famodel/support_plots.py
@@ -3,6 +3,28 @@
 import matplotlib.pyplot as plt
 
 def plot_pile(layers, y, z, D, L, z0=None, zlug=None, hinge_location=None):
+    '''Plot the soil profile and a driven pile with deflected shape in layered soil.
+
+    Parameters
+    ----------
+        layers : list of dicts
+            Each layer has 'top', 'bottom', 'soil_type', and strength parameters
+            such as 'Su_top' (clay), 'phi_top' (sand) or 'UCS_top' (rock)
+        y : array-like
+            Lateral displacement profile from FD solution (typically y[2:-2])
+        z : array-like
+            Depth values associated with displacement points (typically z[2:-2])
+        D : float
+            Pile diameter (m)
+        L : float
+            Embedded pile length (m)
+        z0 : float, optional
+            Mudline elevation m) from pile head reference (z = 0)
+        zlug : float, optional
+            Depth of the padeye below pile head (m)
+        hinge_location : int, optional
+            Index of plastic hinge location in y/z arrays.
+    '''
     fig, ax = plt.subplots(figsize=(5, 5))
 
     lambdap = L / D
@@ -74,7 +96,7 @@ def plot_pile(layers, y, z, D, L, z0=None, zlug=None, hinge_location=None):
     plt.tight_layout()
     plt.show()
     
-def plot_suction(layers, L, D, z0=None, zlug=None, title='Suction Pile and Soil Layers'):
+def plot_suction(layers, L, D, z0=None, zlug=None):
     '''Plot the soil profile and a suction pile geometry using updated profile_map structure.
 
     Parameters:
@@ -87,8 +109,6 @@ def plot_suction(layers, L, D, z0=None, zlug=None, title='Suction Pile and Soil
             Pile diameter (m)
         zlug : float
             Padeye depth (m, referenced to pile head = 0)
-        title : string 
-            Plot title
     '''
     fig, ax = plt.subplots(figsize=(8, 5))
     xmax = 2*D
@@ -142,13 +162,13 @@ def plot_suction(layers, L, D, z0=None, zlug=None, title='Suction Pile and Soil
     ax.set_ylabel('Depth (m)')
     ax.set_xlim(-xmax, xmax)
     ax.set_ylim(L + 2*D, -D)
-    ax.set_title(title)
+    ax.set_title('Suction Pile and Soil Layers')
     ax.grid()
     ax.legend()
     plt.tight_layout()
     plt.show()
 
-def plot_torpedo(layers, D1, D2, L1, L2, z0, zlug, title='Torpedo Pile and Soil Layers'):
+def plot_torpedo(layers, D1, D2, L1, L2, z0, zlug):
     '''Plot the soil layers and geometry of a torpedo pile using absolute depth for soil and pile head at z=0.
 
     Parameters:
@@ -165,8 +185,6 @@ def plot_torpedo(layers, D1, D2, L1, L2, z0, zlug, title='Torpedo Pile and Soil
             Winged length (m)
         L2 : float
             Shaft length (m)
-        title : str
-            Plot title
     '''
     fig, ax = plt.subplots(figsize=(7, 7))
 
@@ -226,13 +244,13 @@ def plot_torpedo(layers, D1, D2, L1, L2, z0, zlug, title='Torpedo Pile and Soil
     ax.set_ylim(zmax, zmin)
     ax.set_xlabel('Horizontal extent (m)')
     ax.set_ylabel('Depth (m)')
-    ax.set_title(title)
+    ax.set_title('Torpedo Pile and Soil Layers')
     ax.grid()
     ax.legend()
     plt.tight_layout()
     plt.show()
  
-def plot_helical(layers, D, L, d, z0, zlug, n_helix=1, spacing=1.0, title='Helical Pile and Soil Layers'):
+def plot_helical(layers, D, L, d, z0, zlug, n_helix=1, spacing=1.0):
     '''Plot a helical pile in layered soil with shaft and angled helices, starting at zlug.
 
     Parameters:
@@ -251,8 +269,6 @@ def plot_helical(layers, D, L, d, z0, zlug, n_helix=1, spacing=1.0, title='Helic
         Number of helices (typically 1)
     spacing : float
         Vertical spacing between helices (m)
-    title : str
-        Plot title
     '''
     fig, ax = plt.subplots(figsize=(5, 6))
 
@@ -322,13 +338,13 @@ def plot_helical(layers, D, L, d, z0, zlug, n_helix=1, spacing=1.0, title='Helic
     ax.set_ylim(L + D, min(zlug - D, min(layer['top'] for layer in layers) - 2))
     ax.set_xlabel('Horizontal extent (m)')
     ax.set_ylabel('Depth (m)')
-    ax.set_title(title)
+    ax.set_title('Helical Pile and Soil Layers')
     ax.grid()
     ax.legend()
     plt.tight_layout()
     plt.show()
 
-def plot_plate(layers, B, L, z0, zlug, beta, title='Plate Anchor in Layered Soil'):
+def plot_plate(layers, B, L, z0, zlug, beta):
     '''Plot soil layers and an inclined plate anchor centered at zlug.
 
     Parameters:
@@ -345,8 +361,6 @@ def plot_plate(layers, B, L, z0, zlug, beta, title='Plate Anchor in Layered Soil
             Center embedment of the plate (m)
         beta : float
             Inclination angle of plate (deg)
-        title : str
-            Plot title
     '''
     fig, ax = plt.subplots(figsize=(5, 5))
     xmax = 3*B
@@ -397,7 +411,7 @@ def plot_plate(layers, B, L, z0, zlug, beta, title='Plate Anchor in Layered Soil
     ax.set_ylim(zmax, zmin)
     ax.set_xlabel("Horizontal extent (m)")
     ax.set_ylabel("Depth (m)")
-    ax.set_title(title)
+    ax.set_title('Plate Anchor in Layered Soil')
     ax.legend(loc='lower right')
     ax.grid(True)
     plt.tight_layout()
@@ -454,7 +468,7 @@ def plot_load(layers, drag_values, depth_values, Tm, thetam, Ta, thetaa, zlug):
         elif soil == 'sand':
             phi = layer.get('phi_top', 30)
             gamma = layer.get('gamma_top', 10)
-            color_fill = plt.cm.YlOrBr(phi / max_phi)
+            color_fill = plt.cm.YlOrBr(phi/max_phi)
             label_soil = f'ϕ = {phi:.0f}°, γ = {gamma:.1f} kN/m³'
         else:
             color = 'gray'
@@ -469,7 +483,7 @@ def plot_load(layers, drag_values, depth_values, Tm, thetam, Ta, thetaa, zlug):
     scale = 2e6  # Arrow scaling factor for better visual readability
     
     # Plot the inverse catenary profile
-    ax.plot(drag_values, depth_values, color='b', label='Mooring line')
+    ax.plot(drag_values, depth_values, color='k', label='Mooring line')
 
     # Load arrows
     ax.arrow(0, -layers[0]['top'],
@@ -478,19 +492,29 @@ def plot_load(layers, drag_values, depth_values, Tm, thetam, Ta, thetaa, zlug):
 
     ax.arrow(drag_values[-1], depth_values[-1],
              Ta*np.cos(np.deg2rad(thetaa))/scale, Ta*np.sin(np.deg2rad(thetaa))/scale,
-             head_width=0.25, head_length=0.5, color='g', label='Padeye Load')
+             head_width=0.25, head_length=0.5, color='g', label='Lug load')
+    
+    ax.plot(0, -layers[0]['top'], 'ro', zorder=5)
 
     if zlug is not None:
         ax.plot(drag_values[-1], -zlug, 'go', label=f'Padeye (zlug = {zlug:.2f} m)')
     
+    # Coordinates of lug arrow tail
+    xlug = drag_values[-1]
+    ylug = depth_values[-1]
+    
+    # Mark the base of the lug vector with a green dot and depth label
+    ax.plot(xlug, ylug, 'go', zorder=5)
+    ax.annotate(f'z = {-ylug:.2f} m', (xlug - 0.5, ylug - 0.75), color='g')
+
     # Add mudline and padeye markers
-    ax.axhline(-layers[0]['top'], color='k', linestyle='--', lw=1.5, label=f'Mudline')
+    ax.axhline(-layers[0]['top'], color='b', linestyle='--', lw=1.5, label=f'Mudline')
 
     # Annotate loads
     ax.annotate(f"{Tm/1e6:.2f} MN", (Tm*np.cos(np.deg2rad(thetam))/scale, 
-                                     -layers[0]['top'] + Tm*np.sin(np.deg2rad(thetam))/scale), color='r')
+                                     -layers[0]['top']), color='r')
     ax.annotate(f"{Ta/1e6:.2f} MN", (drag_values[-1] + Ta*np.cos(np.deg2rad(thetaa))/scale,
-                                     depth_values[-1] + Ta*np.sin(np.deg2rad(thetaa))/scale), color='g')
+                                     depth_values[-1]), color='g')
 
     # Deduplicate legend entries
     handles, labels = ax.get_legend_handles_labels()
@@ -501,8 +525,8 @@ def plot_load(layers, drag_values, depth_values, Tm, thetam, Ta, thetaa, zlug):
     ax.set_ylabel('Embedded depth (m)')
     ax.set_title('Inverse Catenary in Layered Soil')
     ax.grid(True)
-    #ax.set_ylim(min(zlug - 10, min(depth_values) - 5), max(15, max(depth_values) + 5))
-    ax.legend(loc='lower left')
+    ax.set_ylim(min(zlug - 10, min(depth_values) - 5), max(5, max(depth_values) + 5))
+    ax.legend(loc='lower right')
     plt.tight_layout()
     plt.show()
 
@@ -515,7 +539,7 @@ def plot_pycurve(pycurve_data):
     pycurve_data : list of tuples
         Each tuple must be (y_vals, p_vals, z_depth, soil_type)
     '''
-    fig, ax = plt.subplots(figsize=(6, 5))
+    fig, ax = plt.subplots(figsize=(6, 5), constrained_layout=True)
 
     for y, p, z, soil in pycurve_data:
         label = f'{soil.capitalize()} @ z = {z:.1f} m'
@@ -525,6 +549,5 @@ def plot_pycurve(pycurve_data):
     ax.set_ylabel('Soil resistance p (N/m)')
     ax.set_title('p–y Curves at Various Depths')
     ax.grid(True)
-    ax.legend()
-    plt.tight_layout()
+    # ax.legend(fontsize='small')
     plt.show()
diff --git a/famodel/anchors/anchors_famodel_map/capacity_pycurves_map.py b/famodel/anchors/anchors_famodel/support_pycurves.py
similarity index 86%
rename from famodel/anchors/anchors_famodel_map/capacity_pycurves_map.py
rename to famodel/anchors/anchors_famodel/support_pycurves.py
index 377a9a8f..c8cf40e0 100644
--- a/famodel/anchors/anchors_famodel_map/capacity_pycurves_map.py
+++ b/famodel/anchors/anchors_famodel/support_pycurves.py
@@ -3,7 +3,7 @@
 import matplotlib.pyplot as plt
 from scipy.interpolate import interp1d
 
-def py_Matlock(z, D, zlug, f_Su, f_sigma_v_eff, f_gamma, z0=None, return_curve=False):
+def py_Matlock(z, D, gamma, Su, sigma_v_eff, z0=None, return_curve=False):
    ''' Generate Matlock (1970) p–y curve at a given depth in clay.
 
     Parameters
@@ -12,8 +12,6 @@ def py_Matlock(z, D, zlug, f_Su, f_sigma_v_eff, f_gamma, z0=None, return_curve=F
         Depth relative to pile head (m)
     D : float
         Pile diameter (m)
-    zlug : float
-        Load eccentricity above or below mudline (m)
     f_Su : function
         Undrained shear strength (Pa)
     f_sigma_v_eff : function
@@ -31,9 +29,9 @@ def py_Matlock(z, D, zlug, f_Su, f_sigma_v_eff, f_gamma, z0=None, return_curve=F
         Interpolation function for p–y relationship (N/m vs m)
     '''
     
-   Su = f_Su(z)
-   sigma_v_eff = f_sigma_v_eff(z)
-   gamma = f_gamma(z)
+    # Su = f_Su(z)
+    # sigma_v_eff = f_sigma_v_eff(z)
+    # gamma = f_gamma(z)
    
    # Strain at half the strength as defined by Matlock (1970). 
    # Typically ranges from 0.005 (stiff clay) to 0.02 (soft clay).
@@ -63,11 +61,11 @@ def py_Matlock(z, D, zlug, f_Su, f_sigma_v_eff, f_gamma, z0=None, return_curve=F
    y = Y*y_50
    p = P*p_ult
 
-   f = interp1d(y, p, kind='linear', bounds_error=False, fill_value=0.0)   # Interpolation function for p-y curve
+   f = interp1d(y, p, kind='linear', bounds_error=False, fill_value=0.0)   
 
    return (f, (y, p)) if return_curve else f 
        
-def py_API(z, D, zlug, f_phi, f_sigma_v_eff, f_Dr, z0=None, return_curve=False):   
+def py_API(z, D, phi, sigma_v_eff, Dr, z0=None, return_curve=False):   
     ''' Generate API RP2A (1993) p–y curve at a given depth in sand.
 
     Parameters
@@ -76,8 +74,6 @@ def py_API(z, D, zlug, f_phi, f_sigma_v_eff, f_Dr, z0=None, return_curve=False):
         Depth relative to pile head (m)
     D : float
         Pile diameter (m)
-    zlug : float
-        Load eccentricity above or below mudline (m)
     f_phi : function
         Friction angle (deg)
     f_sigma_v_eff : function
@@ -95,9 +91,9 @@ def py_API(z, D, zlug, f_phi, f_sigma_v_eff, f_Dr, z0=None, return_curve=False):
         Interpolation function for p–y relationship (N/m vs m)
     '''
     
-    phi = f_phi(z)
-    sigma_v_eff = f_sigma_v_eff(z)
-    Dr = f_Dr(z)
+    # phi = f_phi(z)
+    # sigma_v_eff = f_sigma_v_eff(z)
+    # Dr = f_Dr(z)
          
     # Interpolate coefficients depending on the effective friction angle
     phi_ref = [  20,   25,   30,   35,   40]
@@ -128,14 +124,14 @@ def py_API(z, D, zlug, f_phi, f_sigma_v_eff, f_Dr, z0=None, return_curve=False):
     A = max(3 - 0.8*z/D, 0.9)
     
     # Apply API p–y formulation
-    ε = 1e-6  # prevent division by zero
-    p = A*p_ult*np.tanh(k*z*y/(A*p_ult + ε))
+    epsilon = 1e-6  # prevent division by zero
+    p = A*p_ult*np.tanh(k*z*y/(A*p_ult + epsilon))
     
     f = interp1d(y, p, kind='linear', bounds_error=False, fill_value=0.0)
     
     return (f, (y, p)) if return_curve else f  
 
-def py_Reese(z, D, zlug, f_UCS, f_Em, z0=None, return_curve=False):
+def py_Reese(z, D, UCS, Em, z0=None, return_curve=False):
     ''' Generate Reese (1997) p–y curve at a given depth in weak rock.
 
     Parameters
@@ -144,8 +140,6 @@ def py_Reese(z, D, zlug, f_UCS, f_Em, z0=None, return_curve=False):
         Depth relative to pile head (m)
     D : float
         Pile diameter (m)
-    zlug : float
-        Load eccentricity above or below mudline (m)
     f_UCS : function
         Unconfined compressive strength UCS(z) (Pa)
     f_Em : function
@@ -161,8 +155,8 @@ def py_Reese(z, D, zlug, f_UCS, f_Em, z0=None, return_curve=False):
         Interpolation function for p–y relationship (N/m vs m)
     '''
     
-    UCS = f_UCS(z)
-    Em = f_Em(z)
+    # UCS = f_UCS(z)
+    # Em = f_Em(z)
   
     RQD = 52                     # Assumed fair rock quality (moderately weathered rocks) 
     Dref = 0.305;                # Reference diamter (m)
@@ -191,13 +185,13 @@ def py_Reese(z, D, zlug, f_UCS, f_Em, z0=None, return_curve=False):
    
     # Normalized lateral displacement
     N = 20
-    y = np.concatenate((-np.logspace(4,-3,N),[0],np.logspace(-3,4,N)))
-    y = np.linspace(-0.02*D, 0.02*D, 200)  # ±2 cm
+    y = np.concatenate((-np.logspace(.1,-2,N),[0],np.logspace(-2,.1,N)))
+    # y = np.linspace(-0.2*D, 0.2*D, 200)  # ±2 cm
     
     p = []
     for val in y:
         if abs(val) < y_a:
-            p_val = np.sign(val)*Kir*val
+            p_val = Kir*val
         else:
             p_val = np.sign(val)*min((p_ur/2)*(abs(val)/y_rm)**0.25, p_ur)
         p.append(p_val)                                  
@@ -206,7 +200,7 @@ def py_Reese(z, D, zlug, f_UCS, f_Em, z0=None, return_curve=False):
     
     return (f, (y, p)) if return_curve else f      
 
-def py_Lovera(z, D, f_UCS, f_Em, zlug, z0, delta_grout=0.075, E_grout=20e9, delta_crushed=0.025, return_curve=False):
+def py_Lovera(z, D, UCS, Em, zlug, z0, delta_grout=0.075, E_grout=20e9, delta_crushed=0.025, return_curve=False):
     ''' Generate Lovera (2019) p–y curve at a given depth for layered rock interfaces.
 
     Parameters
@@ -242,7 +236,7 @@ def py_Lovera(z, D, f_UCS, f_Em, zlug, z0, delta_grout=0.075, E_grout=20e9, delt
         return lambda y: np.zeros_like(y)
 
     # Retrieve elastic modulus at depth
-    Em = f_Em(z)
+    # Em = f_Em(z)
     nu = 0.3  # Typical Poisson's ratio for rock
     G_rock = Em/(2*(1 + nu))
     k_rock = 4*G_rock
diff --git a/famodel/anchors/anchors_famodel_map/capacity_soils_map.py b/famodel/anchors/anchors_famodel/support_soils.py
similarity index 100%
rename from famodel/anchors/anchors_famodel_map/capacity_soils_map.py
rename to famodel/anchors/anchors_famodel/support_soils.py
diff --git a/famodel/anchors/anchors_famodel_map/capacity_solvers.py b/famodel/anchors/anchors_famodel/support_solvers.py
similarity index 97%
rename from famodel/anchors/anchors_famodel_map/capacity_solvers.py
rename to famodel/anchors/anchors_famodel/support_solvers.py
index b63b0826..e73b9251 100644
--- a/famodel/anchors/anchors_famodel_map/capacity_solvers.py
+++ b/famodel/anchors/anchors_famodel/support_solvers.py
@@ -50,8 +50,11 @@ def fd_solver(n, N, h, D, t, fy, EI, Ha, Va, zlug, z0, k_secant):
         Index of the node with hinge formation
     '''  
     
-    # Initialize and assemble matrix
+    # Initialize 
+    N = n + 5 
     X = np.zeros((N, N))
+    q = np.zeros(N)
+    # k_secant = np.zeros(N)
 
     # (n+1) finite difference equations for (n+1) real nodes
     for i in range(0, n+1):
@@ -84,13 +87,11 @@ def fd_solver(n, N, h, D, t, fy, EI, Ha, Va, zlug, z0, k_secant):
     X[n+4, -3] =  0.0
     X[n+4, -4] =  2.0 - Va*h**2/EI
     X[n+4, -5] = -1.0
-
-    # Initialize vector q
-    q = np.zeros(N)
     
     # Always apply shear
     # Index of the node where the horizontal load is applied (padeye)
     zlug_index = int(zlug/h)
+    #zlug_index = max(1, int(zlug/h))  # avoid node 0
     q[zlug_index] = 2*Ha*h**3
                  
     y = linalg.solve(EI*X, q)
diff --git a/famodel/anchors/anchors_famodel_map/capacity_helical_map.py b/famodel/anchors/anchors_famodel_map/capacity_helical_map.py
deleted file mode 100644
index 4a495a4e..00000000
--- a/famodel/anchors/anchors_famodel_map/capacity_helical_map.py
+++ /dev/null
@@ -1,172 +0,0 @@
-
-import numpy as np
-from .capacity_driven_map import getCapacityDriven, plot_pile
-from .capacity_soils_map import clay_profile, sand_profile
-from .capacity_plots_map import plot_helical
-
-def getCapacityHelical(profile_map, location_name, D, L, d, zlug, Ha, Va, plot=True):
-    '''Calculate the vertical and horizontal capacity of a helical pile using a soil profile.
-    The calculation is based on the soil profile, anchor geometry and inclined load.
-
-    Parameters
-    ----------
-    profile : array
-        Soil profiles (z, parameters)
-            Clay soil profile (z, Su, gamma)
-            Sand soil profile (z, phi, gamma, Dr)
-    soil_type : string
-        Select soil condition, 'clay' or 'sand'
-    D : float 
-        Helix diameter (m)
-    L : float 
-        Shaft length (m)
-    d : float 
-        Shaft diameter (m)
-    zlug : float
-        Depth to padeye (m)
-    Ha : float
-        Horizontal load applied at padeye (N)
-    Va : float
-        Vertical load applied at padeye (N)
-    plot : bool
-        Plot the p-y curve and the deflection pile condition if True
-
-    Returns
-    -------
-    y : array
-        Lateral displacement at each node (real nodes only)
-    z : array
-        Node depth positions corresponding to y (m)
-    resultsHelical : dict
-        Dictionary containing displacements, moment capacity, hinge state and vertical capacity
-    '''
-
-    profile_entry = next(p for p in profile_map if p['name'] == location_name)
-    layers = profile_entry['layers']
-
-    t = (6.35 + D*20)/1e3            # Helical pile wall thickness (m), API RP2A-WSD
-    rhows = 66.90e3                  # Submerged steel specific weight (kN/m3)
-    rhow = 10e3                      # Water specific weight (kN/m3) 
-
-    def PileWeight(Len, Dia1, Dia2, tw, rho):
-        return ((np.pi/4)*((Dia1**2 - (Dia1 - 2*tw)**2)*Len + (np.pi/4)*Dia2**2*tw))*rho
-
-    z_helix = zlug + (L - D)
-    matched_layer = next((layer for layer in layers if layer['top'] <= z_helix <= layer['bottom']), None)
-    if matched_layer is None:
-        raise ValueError(f"No soil layer found at z = {z_helix:.2f} m")
-
-    if matched_layer['soil_type'] == 'clay':
-        profile = [[matched_layer['top'], matched_layer['Su_top'], matched_layer['gamma_top']],
-                   [matched_layer['bottom'], matched_layer['Su_bot'], matched_layer['gamma_bot']]]
-        z0, f_Su, f_sigma_v_eff, f_gamma, f_alpha = clay_profile(profile)
-
-        z_helix = np.clip(z_helix, matched_layer['top'], matched_layer['bottom'])
-        Su = f_Su(z_helix)
-        sigma_v_eff = max(f_sigma_v_eff(z_helix), 1.0)
-        psi_val = Su/sigma_v_eff
-        alpha = min(0.5*psi_val**-0.50, 1) if psi_val <= 1.0 else min(0.5 * psi_val**-0.25, 1)
-
-        Nc = min(6.0*(1 + 0.2*d/D), 9)
-        Qh = ((np.pi/4)*(D**2 - d**2)*Nc*Su + f_gamma(z_helix)*D)*0.75
-        Qs = np.pi*d*L*alpha*Su
-        Qu = PileWeight(L, D, d, t, rhows) + Qh + Qs
-
-    elif matched_layer['soil_type'] == 'sand':
-        profile = [[matched_layer['top'], matched_layer['phi_top'], matched_layer['gamma_top'], matched_layer['Dr_top']],
-                   [matched_layer['bottom'], matched_layer['phi_bot'], matched_layer['gamma_bot'], matched_layer['Dr_bot']]]
-        z0, f_phi, f_sigma_v_eff, f_gamma, f_Dr, f_delta = sand_profile(profile)
-
-        z_helix = np.clip(z_helix, matched_layer['top'], matched_layer['bottom'])
-        gamma = f_gamma(z_helix)
-        Dr = f_Dr(z_helix)
-        delta = f_delta(z_helix)
-        phi = f_phi(z_helix)
-
-        Nq = 0.5*(12*phi)**(phi/54)
-        Qh = (np.pi/4)*(D**2 - d**2)*Nq*gamma*z_helix
-        Qs = np.pi*d*L*delta*gamma*z_helix
-        Qu = PileWeight(L, D, d, t, rhows) + Qh + Qs
-        
-    
-    Wp = PileWeight(L, D, d, t, (rhows + rhow))    
-
-    # Unity Check based only on vertical capacity
-    UC_vertical = Va/Qu
-
-    # Compute horizontal capacity using p-y method
-    layers, y, z, results_lateral = getCapacityDriven(profile_map, location_name, D, L, zlug, Ha, Va, plot=True)
-
-    plot_pile(layers, y, z, D, L, z0=layers[0]['top'], zlug=zlug, hinge_location=None)
-
-    Hcap = results_lateral['Horizontal max.']
-    UC_horizontal = Ha/Hcap if Hcap != 0 else np.inf
-
-    resultsHelical = {
-        'Vertical max.': Qu,
-        'Weight': Wp,
-        'Unity Check (Vertical)': UC_vertical,
-        'Horizontal max.': Hcap,
-        'Unity Check (Horizontal)': UC_horizontal
-    }
-
-    if matched_layer['soil_type'] == 'clay':
-        resultsHelical['Su @ helix'] = Su
-        resultsHelical['Alpha'] = alpha
-    elif matched_layer['soil_type'] == 'sand':
-        resultsHelical['Dr @ helix'] = Dr
-        resultsHelical['Delta'] = delta
-        resultsHelical['Phi'] = phi
-
-    return layers, resultsHelical
-
-if __name__ == '__main__':
-    
-    profile_map = [
-        {
-            'name': 'CPT_1',
-            'x': 498234, 'y': 5725141,
-            'layers': [
-                {
-                    'top': 1.0, 'bottom': 3.0,
-                    'soil_type': 'clay',
-                    'gamma_top': 8.0, 'gamma_bot': 9.0,
-                    'Su_top': 60, 'Su_bot': 50},
-                {
-                    'top': 3.0, 'bottom': 7.0,
-                    'soil_type': 'clay',
-                    'gamma_top': 15.0, 'gamma_bot': 25.0,
-                    'Su_top': 100, 'Su_bot': 150},
-                # {
-                #     'top': 6.0, 'bottom': 15.0,
-                #     'soil_type': 'sand',
-                #     'gamma_top': 8.0, 'gamma_bot': 8.0,
-                #     'phi_top': 32, 'phi_bot': 38,
-                #     'Dr_top': 70, 'Dr_bot': 75},
-                {
-                    'top': 7.0, 'bottom': 15.0,
-                    'soil_type': 'clay',
-                    'gamma_top': 25.0, 'gamma_bot': 50.0,
-                    'Su_top': 200, 'Su_bot': 400}]
-        }
-    ]  
-
-    D = 1.5        # Helix diameter (m)
-    L = 12.0       # Pile length (m)
-    d = 0.5        # Shaft diameter (m)
-    zlug = 3       # Padeye depth (m)
-    Ha = 30e3      # Horizontal load (N)
-    Va = 50e3      # Vertical load (N)
-
-    print("--- Clay Profile ---")
-    layers, resultsHelical = getCapacityHelical(profile_map, 'CPT_1', D, L, d, zlug, Ha, Va, plot=True)
-    for key, val in resultsHelical.items():
-        if isinstance(val, float):
-            print(f"{key}: {val:.3f}")
-        else:
-            print(f"{key}: {val}")
-    
-    plot_helical(layers, D=D, L=L, d=d, z0=layers[0]['top'], zlug=zlug, n_helix=1, spacing=1.0, title='Helical Pile in Sand Profile')
-  
-
-
diff --git a/famodel/anchors/anchors_famodel_map/capacity_load_map.py b/famodel/anchors/anchors_famodel_map/capacity_load_map.py
deleted file mode 100644
index 7ebca3b7..00000000
--- a/famodel/anchors/anchors_famodel_map/capacity_load_map.py
+++ /dev/null
@@ -1,212 +0,0 @@
-
-import numpy as np
-import matplotlib.pyplot as plt
-from .capacity_soils_map import clay_profile, sand_profile
-from .capacity_plots_map import plot_load
-
-def getTransferLoad(profile_map, Tm, thetam, zlug, line_type, d, w=None, plot=False):
-    '''Calculate the transfer load from mudline to main padeye using a layered soil profile.
-
-    Parameters
-    ----------
-    profile_map : list of dicts
-        Soil profile in profile_map format
-    Tm : float
-        Mooring line load at mudlevel (N)
-    thetam : float
-        Mooring line angle at mudlevel (deg)
-    zlug : float
-        Embedment depth of the lug (m)
-    line_type : str
-        'chain' or 'wire'
-    d : float
-        Chain diameter (m)
-    w : float
-        Mooring line unit weight (N/m)
-    plot : bool
-        Show plot
-
-    Returns
-    -------
-    dict
-        Dictionary with transferred load components and depth.
-    '''
-
-    deltas = 0.2  # discretization step
-
-    # Line mechanical properties
-    if line_type == 'chain':
-        Et, En = 10, 2.5
-    elif line_type == 'wire':
-        Et, En = np.pi, 1
-    W = w*deltas
-
-    # Soil layer access
-    layers = profile_map[0]['layers']
-    z0 = min(layer['top'] for layer in layers)
-    Nc = 8.5
-
-    # Initial values
-    z0 = min(layer['top'] for layer in layers)
-    T = Tm
-    theta = np.deg2rad(thetam)
-    drag = 0
-    depth = z0 + 0.01
-
-    # Tracing lists
-    drag_values, depth_values = [], []
-
-    while (zlug - depth) >= 0:
-        matched_layer = next((layer for layer in layers if layer['top'] <= depth <= layer['bottom']), None)
-        if matched_layer is None:
-            break
-        
-        if matched_layer['soil_type'] == 'clay':
-            matched_layer = next((layer for layer in layers if layer['soil_type'] == 'clay' and layer['top'] <= depth <= layer['bottom']), None)
-            if matched_layer is None:
-                break
-            profile = [[matched_layer['top'], matched_layer['gamma_top'], matched_layer['Su_top']],
-                       [matched_layer['bottom'], matched_layer['gamma_bot'], matched_layer['Su_bot']]]
-            z0_local, f_gamma, f_Su, f_sigma_v_eff, f_alpha = clay_profile(profile)
-
-            Su = f_Su(depth)
-            alpha = f_alpha(depth)
-            d_theta = (En*d*Nc*Su - W*np.cos(theta))/T*deltas
-            dT = (Et*d*alpha*Su + W*np.sin(theta))*deltas
-
-        elif matched_layer['soil_type'] == 'sand':
-            matched_layer = next((layer for layer in layers if layer['soil_type'] == 'sand' and layer['top'] <= depth <= layer['bottom']), None)
-            if matched_layer is None:
-                break
-            
-            profile = [[matched_layer['top'], matched_layer['gamma_top'], matched_layer['phi_top'], matched_layer['Dr_top']],
-                       [matched_layer['bottom'], matched_layer['gamma_bot'], matched_layer['phi_bot'], matched_layer['Dr_bot']]]
-            z0_local, f_gamma, f_phi, f_Dr, f_sigma_v_eff, f_delta = sand_profile(profile)
-
-            gamma_z = f_gamma(depth)
-            delta_z = f_delta(depth)
-            phi = f_phi(depth)
-            Nq = np.exp(np.pi*np.tan(np.deg2rad(phi)))*(np.tan(np.deg2rad(45 + phi/2)))**2
-            print(f'Nq = {Nq:.2f}, depth = {depth:.2f} m')
-            d_theta = (En*d*Nq*gamma_z*depth - W*np.cos(theta))/T*deltas
-            dT = (Et*d*gamma_z*depth*np.tan(np.deg2rad(delta_z)) + W*np.sin(theta))*deltas
-            
-        else:
-            raise ValueError(f"Unsupported soil type: {matched_layer['soil_type']}")
-
-        d_drag  = deltas*np.cos(theta)
-        d_depth = deltas*np.sin(theta)
-
-        theta += d_theta
-        T -= dT
-        drag += d_drag
-        depth += d_depth
-
-        if abs(Tm - T) > 0.75*Tm:
-            raise Exception(f"Load transfer unrealistic: Tm = {Tm/1e6:.2f} MN vs T = {T/1e6:.2f} MN")
-        if not (0 < np.rad2deg(theta) < 90):
-            raise Exception(f"Load angle unrealistic: {np.rad2deg(theta):.2f} deg")
-
-        drag_values.append(-drag); 
-        depth_values.append(-depth); 
-
-    Ta = T; thetaa = theta
-    
-    print(f'Input Tm = {Tm}, thetam = {thetam}, zlug = {zlug}')
-    print(f'Output Hm = {Tm*np.cos(np.deg2rad(thetam))}, Vm = {Tm*np.sin(np.deg2rad(thetam))}')
-    print(f'Output Ta = {Ta}, thetaa = {np.rad2deg(thetaa)}')
-    print(f'Output Ha = {Ta*np.cos(thetaa)}, Va = {Ta*np.sin(thetaa)}')
-
-    resultsLoad = {
-        'Tm': Tm,
-        'thetam': thetam,
-        'Ta': Ta,
-        'thetaa': np.rad2deg(thetaa),
-        'length': deltas*len(drag_values),
-        'drag_values': drag_values,
-        'depth_values': depth_values
-    }
-
-    return layers, resultsLoad
-
-
-if __name__ == '__main__':
-
-    profile_map = [
-        {
-            'name': 'CPT_1',
-            'x': 498234, 'y': 5725141,
-            'layers': [
-                {
-                    'top': 1.0, 'bottom': 2.0,
-                    'soil_type': 'clay',
-                    'gamma_top': 8.0, 'gamma_bot': 8.0,
-                    'Su_top': 10, 'Su_bot': 25},
-                {
-                    'top': 2.0, 'bottom': 8.0,
-                    'soil_type': 'clay',
-                    'gamma_top': 8.0, 'gamma_bot': 8.0,
-                    'Su_top': 25, 'Su_bot': 50},
-                {
-                    'top': 8.0, 'bottom': 16.0,
-                    'soil_type': 'clay',
-                    'gamma_top': 8.0, 'gamma_bot': 8.0,
-                    'Su_top': 50, 'Su_bot': 100}
-            ]
-        }
-    ]
-    # profile_map = [
-    #     {
-    #         'name': 'CPT_1',
-    #         'x': 498234, 'y': 5725141,
-    #         'layers': [
-    #             # {
-    #             #     'top': 0.0, 'bottom': 5.0,
-    #             #     'soil_type': 'sand',
-    #             #     'gamma_top': 9.5, 'gamma_bot': 9.5,
-    #             #     'phi_top': 28, 'phi_bot': 30,
-    #             #     'Dr_top': 70, 'Dr_bot': 70},
-    #             {
-    #                 'top': 0.0, 'bottom': 5.0,
-    #                 'soil_type': 'clay',
-    #                 'gamma_top': 8.0, 'gamma_bot': 8.0,
-    #                 'Su_top': 25, 'Su_bot': 25},
-    #             {
-    #                 'top': 5.0, 'bottom': 10.0,
-    #                 'soil_type': 'sand',
-    #                 'gamma_top': 9.5, 'gamma_bot': 9.5,
-    #                 'phi_top': 32, 'phi_bot': 36,
-    #                 'Dr_top': 70, 'Dr_bot': 70},
-    #             {
-    #                 'top': 10.0, 'bottom': 15.0,
-    #                 'soil_type': 'sand',
-    #                 'gamma_top': 9.5, 'gamma_bot': 9.5,
-    #                 'phi_top': 42, 'phi_bot': 45,
-    #                 'Dr_top': 70, 'Dr_bot': 70}
-    #         ]
-    #     }
-    # ]
-
-    Tm = 6e6              # Load at mudline (N)
-    thetam = 10           # Angle at mudline (deg)
-    zlug = 8              # Padeye depth (m)
-    line_type = 'chain'
-    d = 0.16              # Chain diameter (m)
-    w = 5000              # Line weight (N/m)
-
-    layers, resultsLoad = getTransferLoad(profile_map, Tm, thetam, zlug, line_type, d, w, plot=True)
-
-    # print("\n--- Transfer Load Results ---")
-    # for key, val in resultsLoad.items():
-    #     if isinstance(val, float):
-    #         print(f"{key}: {val:.3f}")
-    #     elif isinstance(val, list):
-    #         print(f"{key}:")
-    #         for v in val:
-    #             print(f"  {v:.3f}")
-    #     else:
-    #         print(f"{key}: {val}")
-
-    plot_load(layers, resultsLoad['drag_values'], resultsLoad['depth_values'], 
-              resultsLoad['Tm'], resultsLoad['thetam'], resultsLoad['Ta'], 
-              resultsLoad['thetaa'], zlug=zlug)
\ No newline at end of file
diff --git a/famodel/anchors/anchors_famodel_map/capacity_plate_map.py b/famodel/anchors/anchors_famodel_map/capacity_plate_map.py
deleted file mode 100644
index 56e50b44..00000000
--- a/famodel/anchors/anchors_famodel_map/capacity_plate_map.py
+++ /dev/null
@@ -1,177 +0,0 @@
-
-import numpy as np
-import matplotlib.pyplot as plt
-from .capacity_soils_map import clay_profile
-from .capacity_plots_map import plot_plate
-
-def getCapacityPlate(profile_map, location_name, B, L, zlug, beta, Ha, Va, plot=True):
-    '''Calculate the plate anchor capacity using clay soil layers from profile_map.
-    The calculation is based on the soil profile, anchor geometry and inclined load.
-
-    Parameters
-    ----------
-    profile_map : list of dict
-        Soil profile map with coordinates and layers per location.
-    location_name : str
-        Name of the location to select the soil profile.
-    B : float
-        Plate width (m)
-    L : float
-        Plate length (m)
-    zlug : float
-        Embedment depth of the main padeye (m)
-    beta : float
-        Inclination angle of the plate (deg)
-    Ha : float
-        Applied horizontal load (N)
-    Va : float
-        Applied vertical load (N)
-    plot : bool
-        Whether to generate plots.
-
-    Returns
-    -------
-    Dictionary with Capacity, Weight, UC, etc.
-    '''
-
-    # Extract and filter clay layers from profile_map
-    profile_entry = next(p for p in profile_map if p['name'] == location_name)
-    layers = [layer for layer in profile_entry['layers'] if layer['soil_type'] == 'clay']
-
-    if not layers:
-        raise ValueError('Plate anchor capacity model only supports clay soils.')
-
-    # Build the profile array: [[z, Su, gamma], ...]
-    profile = []
-    for layer in layers:
-        profile.append([layer['top'], layer['gamma_top'], layer['Su_top']])
-        profile.append([layer['bottom'], layer['gamma_bot'], layer['Su_bot']])
-        
-    print("layer gamma_top (raw):", layer['gamma_top'])
-    print("layer gamma_bot (raw):", layer['gamma_bot'])
-
-    profile = np.array(sorted(profile, key=lambda x: x[0]))
-
-    # Parameters and constants
-    Los = 0.05
-    B_t = 40
-    rhows = 66.90e3  # Submerged steel (N/m3)
-    rhow = 10e3      # Seawater (N/m3)
-
-    # Evaluate interpolated Su and gamma
-    z0, f_gamma, f_Su, f_sigma_v_eff, f_alpha = clay_profile(profile)
-    t = round(B/B_t, 2)
-    V_steel = round(B*L*t, 2)
-    zlug_B = zlug/B
-
-    # Profile check points
-    npts = 10
-    z_offsets = np.linspace(-0.5, 0.5, npts)*B*np.sin(np.deg2rad(beta))
-    z_points = zlug + z_offsets; print(z_points)
-
-    Su_vals = [f_Su(z) for z in z_points]
-    gamma_10 = f_gamma(z_points[2]); print(gamma_10)
-    gamma_vals = [f_gamma(z) for z in z_points]; print("gamma_vals:", [f"{val:.2f}" for val in gamma_vals], "N/m3")
-    Su = np.mean(Su_vals); print(f"Su: {Su:.2f} Pa")
-    gamma = np.mean(gamma_vals); print(f"gamma: {gamma:.2f} N/m3")
-    
-    print("Profile being sent to clay_profile():")
-    for row in profile:
-        print(f"z = {row[0]:.2f} m, gamma = {row[1]:.2f} kN/m³, Su = {row[2]:.2f} kPa")
-
-    # Shear strength gradient
-    k = np.polyfit(z_points, Su_vals, 1)[0]
-    print(f"k: {k:.2f}")
-
-    # Pile weight including auxiliary parts
-    Wp = 1.35*V_steel*(rhows + rhow)
-
-    # Capacity factors
-    Nco_0_0  = 2.483*np.log(zlug_B) + 1.974
-    Nco_90_0 = 2.174*np.log(zlug_B) + 3.391
-    kBSh = k*B/Su
-    print(f"kBSh: {kBSh:.2f}")
-
-    f0  = np.where(zlug_B < 4, 1.77*(zlug_B**0.3) - 1.289, 0.192*zlug_B + 0.644)
-    f90 = np.where(zlug_B < 4, 0.68*(zlug_B**0.5) - 0.410, 0.153*zlug_B + 0.341)
-
-    S_kB_0  = 1 - f0*kBSh
-    S_kB_90 = 1 - f90*kBSh
-    Nco_0  = S_kB_0*Nco_0_0
-    Nco_90 = S_kB_90*Nco_90_0
-    Nco = Nco_0 + (Nco_90 - Nco_0)*(beta/90)**2
-
-    Nco_s_0_0  = np.where(2.90*zlug_B + 6.02 <= 11.59, 2.90*zlug_B + 6.02, 11.596)
-    Nco_s_90_0 = np.where(2.72*zlug_B + 4.02 <= 11.59, 2.72*zlug_B + 4.02, 11.596)
-
-    S_s_kB_0 = np.where(zlug_B <= 2, 1 + (0.8 - 0.3*zlug_B)*kBSh - (0.383*kBSh**1.36), 1)
-    f90s = np.where(zlug_B <= 3, 0.267*zlug_B, 0.6)
-    S_s_kB_90 = 1 - f90s*kBSh
-    Nco_s_0 = S_s_kB_0*Nco_s_0_0
-    Nco_s_90 = S_s_kB_90*Nco_s_90_0
-    Nco_s = Nco_s_90 + (Nco_s_0 - Nco_s_90)*((90 - beta)/90)**2
-
-    Nc_final = max(Nco + (gamma*zlug)/Su, Nco_s)
-    print(f"Nc_star: {Nco + (gamma*zlug)/Su:.2f}")
-    print(f"Nc_star: {Nco_s:.2f}")
-    qu = Nc_final*Su
-    Tmax = round(qu*(1 - Los)*B*L, 2)
-    Hmax = Tmax*np.cos(np.deg2rad(90 - beta))
-    Vmax = Tmax*np.sin(np.deg2rad(90 - beta))
-
-    Ta = np.sqrt(Ha**2 + Va**2)
-    UC = Ta/Tmax
-
-    resultsPlate = {
-        'Capacity': Tmax,
-        'Horizontal max.': Hmax,
-        'Vertical max.': Vmax,
-        'Unity check': UC,
-        'Weight plate': Wp
-    }
-    
-    return layers, resultsPlate
-
-if __name__ == '__main__':
-    profile_map = [
-        {
-            'name': 'CPT_1',
-            'x': 498234, 'y': 5725141,
-            'layers': [
-                {
-                    'top': 0.0, 'bottom': 9.5,
-                    'soil_type': 'clay',
-                    'gamma_top': 8.0, 'gamma_bot': 8.5,
-                    'Su_top': 10, 'Su_bot': 25
-                },
-                {
-                    'top': 9.5, 'bottom': 11.5,
-                    'soil_type': 'clay',
-                    'gamma_top': 8.5, 'gamma_bot': 8.5,
-                    'Su_top': 25, 'Su_bot': 45
-                },
-                {
-                    'top': 11.5, 'bottom': 25.0,
-                    'soil_type': 'clay',
-                    'gamma_top': 8.5, 'gamma_bot': 9.0,
-                    'Su_top': 45, 'Su_bot': 50
-                }
-            ]
-        }
-    ]
-
-    B = 2.0
-    L = 2.0
-    zlug = 10.0
-    Ha = 350e3
-    Va = 400e3
-    alpha = np.rad2deg(np.arctan2(Va, Ha))
-    beta = 90 - alpha
-
-    layers, results = getCapacityPlate(profile_map, 'CPT_1', B, L, zlug, beta, Ha, Va)
-
-    print("\n--- Plate Anchor Capacity Results ---")
-    for key, val in results.items():
-        print(f"{key}: {val:.2f}")
-        
-    plot_plate(layers, B, L, z0 = layers[0]['top'], zlug=zlug, beta=beta, title='Plate Anchor in Layered Soil')
diff --git a/famodel/anchors/anchors_famodel_map/capacity_suction_map.py b/famodel/anchors/anchors_famodel_map/capacity_suction_map.py
deleted file mode 100644
index db296616..00000000
--- a/famodel/anchors/anchors_famodel_map/capacity_suction_map.py
+++ /dev/null
@@ -1,401 +0,0 @@
-
-import numpy as np
-import matplotlib.pyplot as plt
-from scipy.optimize import fsolve
-from .capacity_soils_map import clay_profile, sand_profile
-from .capacity_plots_map import plot_suction
-
-
-def PileSurface(Len, Dia):
-    return np.pi*Dia*Len
-
-def PileWeight(Len, Dia, tw, rho):
-    return ((np.pi/4)*((Dia**2 - (Dia - 2*tw)**2)*Len + (np.pi/4)*Dia**2*tw))*rho
-
-def SoilWeight(Len, Dia, tw, gamma_soil):
-    return (np.pi/4)*(Dia - 2*tw)**2*Len*gamma_soil
-
-def rlugTilt(r, z, theta):
-    return r*np.cos(np.deg2rad(theta)) - z*np.sin(np.deg2rad(theta))
-
-def zlugTilt(r, z, theta):
-    return r*np.sin(np.deg2rad(theta)) + z*np.cos(np.deg2rad(theta))
-
-def getCapacitySuction(profile_map, location_name, D, L, zlug, Ha, Va, thetalug=5, psilug=7.5, plot=True):
-    '''Calculate the inclined load capacity of a suction pile in sand or clay following S. Kay methodology.
-    The calculation is based on the soil profile, anchor geometry and inclined load.  
-    
-    Parameters
-    ----------
-    profile : array
-        Soil profile as a 2D array: (z, parameters)
-            Clay soil profile (z (m), Su (kPa), gamma (kN/m³))
-            Sand soil profile (z (m), phi (deg), gamma (kN/m³), Dr (%))
-    soil_type : string
-        Select soil condition, 'clay' or 'sand'
-    D : float 
-        Suction pile diameter (m)
-    L : float 
-        Suction pile length from pile head (m)
-    zlug: float
-        Embedded depth of the main padeye (m)
-    thetalug: float
-        Angle of tilt misaligment (deg) (default value: 5.0)
-    psilug: float
-        Angle of twist misaligment (deg) (default value: 7.5)
-    Ha : float       
-        Horizontal load at pile lug elevation (N)
-    Va : float          
-        Vertical load at pile lug elevation (N)
-    plot : bool
-        Plot the capacity envelope if True
-                    
-    Returns
-    -------
-    Dictionary with capcity, weigths and UC.
-    ''' 
-    
-    # Retrieve soil layers from map
-    profile_entry = next(p for p in profile_map if p['name'] == location_name)
-    layers = profile_entry['layers']
-    
-    z0 = layers[0]['top']            # Mudline elevation    
-    lambdap = (L - z0)/D             # Suction pile slenderness ratio
-    t = (6.35 + D*20)/1e3            # Suction pile wall thickness (m), API RP2A-WSD
-    rlug = D/2                       # Radial position of the lug
-    thetalug = 5                     # Angle of tilt misaligment, default is 5. (deg)
-    psilug = 7.5                     # Angle of twist misaligment, default is 7.5. (deg)
-    rhows = 66.90e3                  # Submerged steel specific weight (N/m3)
-    rhow = 10e3                      # Water specific weight (N/m3) 
-    
-    Np_fixed = 10.25
-    Np_free = 4.0
-    Nc = min(6.2*(1 + 0.34*np.arctan(lambdap)), 9)
-    
-    # Initialize
-    sum_ez_weighted = 0.0
-    sum_Hmax = 0.0
-    Vmax_final = 0.0
-    layer_data = []
-
-    # Profile check points
-    npts = 10
-
-    for layer in layers:
-        soil_type = layer['soil_type']
-        z_top = layer['top']
-        z_bot = layer['bottom']
-
-        if soil_type == 'clay':
-            # Prepare soil profile for clay
-            profile = [
-                [z_top, layer['gamma_top'], layer['Su_top']],
-                [z_bot, layer['gamma_bot'], layer['Su_bot']]
-            ]
-    
-            z_ref, f_gamma, f_Su, f_sigma_v_eff, f_alpha = clay_profile(profile)
-    
-            # Clip the layer first
-            z_top_clip = max(z_top, z0)
-            z_bot_clip = min(z_bot, z0 + (L - z0))
-            dz_clip = z_bot_clip - z_top_clip; # print(f'dz_clip  = {dz_clip:.2f} m')
-    
-            if dz_clip <= 0:
-                continue  # Skip layers fully above or below
-    
-            # Calculate properties over clipped dz
-            z_vals = np.linspace(z_top_clip, z_bot_clip, npts)
-            Su_vals = f_Su(z_vals)
-            Su_total = np.trapz(Su_vals, z_vals)
-            Su_moment = np.trapz(Su_vals*z_vals, z_vals)
-    
-            Su_av_z = Su_total/dz_clip; # print(f'Su_av_z  = {Su_av_z:.2f} Pa')
-            ez_layer = Su_moment/Su_total; 
-            Su_bot = f_Su(z_bot_clip)
-            gamma_vals = f_gamma(z_vals)
-            gamma_av = np.mean(gamma_vals)
-    
-            # Calculate Hmax for clay
-            Hmax_layer = Np_fixed*D*dz_clip*Su_av_z; print(f'Su_av_z  = {Su_av_z:.2f} Pa')
-    
-            layer_data.append({
-                'z_top': z_top_clip,
-                'z_bot': z_bot_clip,
-                'dz': dz_clip,
-                'Hmax_layer': Hmax_layer,
-                'ez_layer': ez_layer
-            })
-    
-            sigma_v_eff = f_sigma_v_eff(np.mean(z_vals))
-            alpha_av = float(f_alpha(np.mean(z_vals)))
-            
-            # Side shear To and Ti
-            To = PileSurface(dz_clip, D)*alpha_av*Su_av_z
-            Ti = PileSurface(dz_clip, D - 2*t)*alpha_av*Su_av_z
-            
-            # Tip resistance
-            if abs(z_bot_clip - (z0 + (L - z0))) < 1e-3:  # tip check
-                Tbase = (np.pi/12)*D**3*Su_bot
-            else:
-                Tbase = 0.0
-            
-            Tmax = min(To + Ti, To + Tbase)
-            
-            # Torque induced by horizontal load
-            T = Ha*rlug*np.sin(np.deg2rad(psilug))
-            
-            nhuT = T/Tmax 
-            nhuV = Ha/To 
-            nhuVstar = np.sqrt(nhuV**2 - nhuT**2) 
-            alphastar = alpha_av*(nhuVstar/nhuV); print(f"alphastar   = {alphastar:.3f}")
-            
-            # Constant weight
-            Pile_Head = PileWeight(z0, D, t, rhows)
-            
-            # Vertical failure modes
-            if np.isclose(z_bot_clip, z0 + (L - z0), atol=0.1):
-                Vmax1 = PileWeight(dz_clip, D, t, rhows) + PileSurface(dz_clip, D)*alphastar*Su_av_z + Nc*Su_bot*(np.pi/4)*D**2
-            else:
-                Vmax1 = np.inf  # No tip resistance unless at tip
-            
-            Vmax2 = PileWeight(dz_clip, D, t, rhows) + PileSurface(dz_clip, D)*alphastar*Su_av_z + PileSurface(dz_clip, D - 2*t)*alphastar*Su_av_z
-            Vmax3 = PileWeight(dz_clip, D, t, rhows) + PileSurface(dz_clip, D)*alphastar*Su_av_z + SoilWeight(dz_clip, D, t, gamma_av)
-            
-            Vmax_layer = min(Vmax1, Vmax2, Vmax3)
-            
-            # Sum vertical capacities
-            Vmax_final += Vmax_layer
-            
-            # Print layer debug info
-            print(f"Vmax_layer    = {Vmax_layer:.2f} N")
-            print(f"Vmax1   = {Vmax1:.2f} N")
-            print(f"Vmax2   = {Vmax2:.2f} N")
-            print(f"Vmax3   = {Vmax3:.2f} N")
-            
-        elif soil_type == 'sand':
-            # Prepare soil profile for sand
-            profile = [
-                [z_top, layer['gamma_top'], layer['phi_top'], layer['Dr_top']],
-                [z_bot, layer['gamma_bot'], layer['phi_bot'], layer['Dr_bot']]
-            ]
-        
-            z_ref, f_gamma, f_phi, _, f_sigma_v_eff, f_delta = sand_profile(profile)
-        
-            # Clip the layer within pile embedded length
-            z_top_clip = max(z_top, z0)
-            z_bot_clip = min(z_bot, z0 + (L - z0))
-            dz_clip = z_bot_clip - z_top_clip
-        
-            if dz_clip <= 0:
-                continue  # Skip non-overlapping layers
-        
-            # Calculate properties over clipped dz
-            z_vals = np.linspace(z_top_clip, z_bot_clip, npts)
-            phi_vals = f_phi(z_vals)
-            sigma_vals = f_sigma_v_eff(z_vals)
-            delta_vals = f_delta(z_vals)
-        
-            phi_av = np.mean(phi_vals)
-            sigma_av = np.mean(sigma_vals)
-            delta_av = np.mean(delta_vals)
-        
-            sigma_tip = f_sigma_v_eff(z_bot_clip)
-            
-            Nq = np.e**(np.pi*np.tan(np.radians(phi_av)))*(np.tan(np.radians(45) + np.radians(phi_av)/2))**2
-        
-            # Calculate Hmax for sand
-            Hmax_layer = 0.5*Nq*D*gamma_av*dz_clip**2
-        
-            layer_data.append({
-                'z_top': z_top_clip,
-                'z_bot': z_bot_clip,
-                'dz': dz_clip,
-                'Hmax_layer': Hmax_layer,
-                'ez_layer': np.mean(z_vals)
-            })
-        
-            # Side friction
-            To = PileSurface(dz_clip, D)*delta_av*sigma_av
-            Ti = PileSurface(dz_clip, D - 2*t)*delta_av*sigma_av
-        
-            if abs(z_bot_clip - (z0 + (L - z0))) < 1e-3:
-                Tbase = np.pi/4*D**2*sigma_tip
-            else:
-                Tbase = 0.0
-        
-            Tmax = min(To + Ti, To + Tbase)
-        
-            # Torque induced by horizontal load
-            T = Ha*rlug*np.sin(np.deg2rad(psilug))
-            nhuT = T/Tmax 
-            nhuV = Ha/To 
-            nhuVstar = np.sqrt(nhuV**2 - nhuT**2) 
-            deltastar = delta_av*(nhuVstar/nhuV) 
-               
-            # Vertical failure modes
-            Vmax2 = Pile_Head + PileWeight(dz_clip, D, t, rhows) + PileSurface(dz_clip, D)*deltastar*sigma_av + PileSurface(dz_clip, D - 2*t)*deltastar*sigma_av
-            Vmax3 = Pile_Head + PileWeight(dz_clip, D, t, rhows) + PileSurface(dz_clip, D)*deltastar*sigma_av + SoilWeight(dz_clip, D, t, gamma_av)
-        
-            Vmax_layer = min(Vmax2, Vmax3)
-            
-            # Sum vertical capacities
-            Vmax_final += Vmax_layer
-        
-            print(f"Vmax_layer (sand) = {Vmax_layer:.2f} N")
-            print(f"Vmax2 (sand) = {Vmax2:.2f} N")
-            print(f"Vmax3 (sand) = {Vmax3:.2f} N")
-
-    # sum Hmax and weighted ez
-    for data in layer_data:
-        z_top = data['z_top']
-        z_bot = data['z_bot']
-        Hmax_layer = data['Hmax_layer']
-        ez_layer = data['ez_layer']
-        dz_layer = data['dz']
-
-        z_embedded_start = z0
-        z_embedded_end = z0 + (L - z0)
-
-        if z_top >= z_embedded_start and z_bot <= z_embedded_end:
-            sum_ez_weighted += Hmax_layer*ez_layer
-            sum_Hmax += Hmax_layer
-            # print(f'ez_layer (full) = {ez_layer:.2f} m')
-
-        elif z_top < z_embedded_end and z_bot > z_embedded_start:
-            dz_inside = min(z_bot, z_embedded_end) - max(z_top, z_embedded_start)
-            if dz_inside > 0:
-                ratio = dz_inside/dz_layer
-                sum_ez_weighted += Hmax_layer*ratio*ez_layer
-                sum_Hmax += Hmax_layer * ratio
-                # print(f'ez_layer (partial) = {ez_layer:.2f} m')
-
-    ez_global = sum_ez_weighted/sum_Hmax 
-    # print(f'sum_ez_weighted = {sum_ez_weighted:.2f}')
-    print(f'ez_global = {ez_global:.2f} m')
-    print(f'Hmax  = {sum_Hmax:.2f} m')
-
-    # Calculate moment and Hmax_final
-    M_total = -Va*rlugTilt(rlug, zlug, thetalug) - Ha*(zlugTilt(rlug, zlug, thetalug) - ez_global)
-    # print(f"rlug_eff = {rlugTilt(rlug, zlug, thetalug):.2f} m")
-    # print(f"zlug_eff = {zlugTilt(rlug, zlug, thetalug):.2f} m")
-    print(f"M_total = {M_total:.2f} Nm")
-    
-    # ΔφMH from Kay 2014
-    if 0.5 <= lambdap < 1.125:
-        delta_phi = 0.32 + 4.32*lambdap; #print(delta_phi)
-    elif 1.125 <= lambdap < 2.0:
-        delta_phi = 7.13 - 1.71*lambdap; #print(delta_phi)
-    elif 2.0 <= lambdap <= 6.0:
-        delta_phi = 4.55 - 0.425*lambdap; #print(delta_phi)
-    else:
-        raise ValueError('L/D out of bounds for MH ellipse.')
-
-    phi_MH = -np.arctan(ez_global/(L - z0)) - np.deg2rad(delta_phi)
-    a_MH = Np_fixed/np.cos(phi_MH)
-    delta_bMH = 0.45*(lambdap)**(-0.9) if lambdap <= 1.5 else 0
-    b_MH = -Np_free*np.sin(phi_MH) + delta_bMH
-    print('M cos(phi)/a_MH =', (M_total*np.cos(phi_MH))/a_MH)
-    print('M sin(phi)/b_MH =', (M_total*np.sin(phi_MH))/b_MH)
-
-    def f(H_var):
-        term1 = ((M_total*np.cos(phi_MH) + H_var*np.sin(phi_MH))/a_MH)**2
-        term2 = ((M_total*np.sin(phi_MH) - H_var*np.cos(phi_MH))/b_MH)**2
-        return term1 + term2 - 1
-
-    try:
-        Hmax_final = max(fsolve(f, sum_Hmax*0.8)[0], 0.0)
-    except:
-        Hmax_final = 0.0
-
-    print(f"Hmax_final (MH ellipse) = {Hmax_final:.2f} N")
-    
-    # Constant weight
-    pile_head = PileWeight(z0, D, t, rhows); print(f"pile_head    = {pile_head:.2f} N")
-    Vmax_final += pile_head; print(f"Vmax_final    = {Vmax_final:.2f} N")
-    
-    # Unity check
-    UC = (Ha/Hmax_final)**(0.5 + lambdap) + (Va/Vmax_final)**(4.5 + lambdap/3) if Hmax_final and sum_Hmax else np.inf
-
-    # Plotting
-    if plot:
-        x = np.linspace(0, 1, 100)
-        y = (1 - x**(4.5 + lambdap/3))**(1/(0.5 + lambdap))
-        
-        plt.figure(figsize=(6, 5))
-        plt.plot(Hmax_final*x, Vmax_final*y, 'b', label='VH Envelope')
-        plt.plot(Ha, Va, 'ro', label='Applied Load')
-        plt.xlabel('Horizontal Capacity (N)')
-        plt.ylabel('Vertical Capacity (N)')
-        plt.title('VH suction pile capacity envelope')
-        plt.grid(True)
-        plt.legend()
-        plt.tight_layout()
-        plt.show()
-
-    resultsSuction = {
-        'Horizontal max.': Hmax_final,
-        'Vertical max.': Vmax_final,
-        'Unity check': UC,
-        # 'Weight pile': Wp,
-        # 'Weight soil': Wsoil,
-        't': t
-    }
-
-    return layers, resultsSuction
-
-if __name__ == '__main__':
-
-    profile_map = [
-    {
-        'name': 'CPT_1',
-        'x': 498234, 'y': 5725141,
-        'layers': [
-            {
-                'top': 2.0, 'bottom': 4.0,
-                'soil_type': 'clay',
-                'gamma_top': 8.0, 'gamma_bot': 8.5,
-                'Su_top': 25, 'Su_bot': 50},
-            {
-                'top': 4.0, 'bottom': 8.0,
-                'soil_type': 'clay',
-                'gamma_top': 8.5, 'gamma_bot': 9.0,
-                'Su_top': 50, 'Su_bot': 75},
-            {
-                'top': 8.0, 'bottom': 16.0,
-                'soil_type': 'clay',
-                'gamma_top': 9.0, 'gamma_bot': 9.5,
-                'Su_top': 75, 'Su_bot': 100},
-            {
-                'top': 16.0, 'bottom': 25.0,
-                'soil_type': 'clay',
-                'gamma_top': 9.5, 'gamma_bot': 9.5,
-                'Su_top': 100, 'Su_bot': 100}]
-        }
-    ]
-
-
-    # Pile and load properties
-    D = 2.5                           # Pile diameter (m)
-    L = 10.0                          # Pile length (m)
-    zlug = 8.0                        # Lug depth (m)
-    theta = 5                         # Tilt misalignment angle (deg)
-    psi = 7.5                         # Twist misalignment angle (deg)
-    Ha = 6e6                          # Applied horizontal load (N)
-    Va = 2e6                          # Applied vertical load (N)
-
-    # Calculate
-    layers, resultsSuction = getCapacitySuction(
-        profile_map, 'CPT_1',         # Soil properties and location of the pile
-        D, L, zlug,                   # Pile geometrical properties
-        Ha, Va,                       # Pile loading conditions   
-        thetalug=theta, psilug=psi,   # Pile misaligment tolerances 
-        plot=True
-    )
-
-    # print('\n--- Suction Pile Capacity Results ---')
-    # print(f"Hmax_final = {resultsSuction['Hmax_final']:.2f} N")
-    # print(f"Vmax_final = {resultsSuction['Vmax_final']:.2f} N")
-    # print(f"Unity check (UC) = {resultsSuction['UnityCheck']:.4f}")
-    # print(f"Total Moment (M_total) = {resultsSuction['M_total']:.2f} Nm")
-
-    plot_suction(layers, L, D, z0 = layers[0]['top'], zlug=zlug, title='Suction Pile and Soil Layers')
diff --git a/famodel/anchors/anchors_famodel_map/capacity_torpedo_map.py b/famodel/anchors/anchors_famodel_map/capacity_torpedo_map.py
deleted file mode 100644
index adf5580f..00000000
--- a/famodel/anchors/anchors_famodel_map/capacity_torpedo_map.py
+++ /dev/null
@@ -1,272 +0,0 @@
-
-import numpy as np
-import matplotlib.pyplot as plt
-from .capacity_soils_map import clay_profile
-from .capacity_plots_map import plot_torpedo
-
-def getCapacityTorpedo(profile_map, location_name, D1, D2, L1, L2, zlug, ballast, Ha, Va, plot=True):
-    '''Calculate the inclined load capacity of a torpedo pile in clay following S. Kay methodology.
-    The calculation is based on the soil profile, anchor geometry and inclined load.  
-
-    Parameters
-    ----------
-    profile : array
-        Clay soil profile (z, Su, gamma)
-            Clay soil profile (z (m), Su (kPa), gamma (kN/m³))
-    soil_type : string
-        Select soil condition, 'clay' 
-    D1 : float 
-        Wing diameter (m)
-    D2 : float    
-        Shaft diameter (m)
-    L1 : float 
-        Winged section length (m)
-    L2 : float 
-        Shaft section length (m)
-    zlug : float 
-        Padeye embedment depth (m)       
-    Ha : float       
-        Horizontal load at pile lug elevation (N)
-    Va : float          
-        Vertical load at pile lug elevation (N)
-    plot : bool
-        Plot the capacity envelope if True
-
-    Returns
-    -------
-    Dictionary with capcity, weigth and UC.
-    '''
-
-    # Retrieve soil layers from map
-    profile_entry = next(p for p in profile_map if p['name'] == location_name)
-    layers = profile_entry['layers']
-
-    L = L1 + L2
-    t = (6.35 + D2*20)/1e3
-    rhows = 66.90e3
-    rhow = 10e3
-
-    def PileWeight(Len1, Len2, Dia1, Dia2, tw, rho):
-        return ((np.pi/4)*(Dia1**2 - (Dia1 - 2*tw)**2)*(Len1 + Len2) + 4*Len2*Dia2*tw)*rho
-
-    def PileWingedSurface(length, diameter):
-        return np.pi*diameter*length
-
-    def PileShaftSurface(length, diameter1, diameter2):
-        return 8*length*(diameter1 - diameter2)
-
-    z_start = zlug
-    z_wing = zlug + L1
-    z_end = zlug + L
-
-    layer_data = []
-    Vmax_total = 0.0
-    
-    # Profile check points
-    npts = 10
-
-    for layer in layers:
-        if layer['soil_type'] != 'clay':
-            raise ValueError('Torpedo pile capacity model only supports clay soils.')
-
-        z_layer_top = layer['top']
-        z_layer_bot = layer['bottom']
-
-        z_clip_top = max(z_layer_top, z_start)
-        z_clip_bot = min(z_layer_bot, z_end)
-
-        if z_clip_bot <= z_clip_top:
-            continue
-
-        segments = []
-        if z_clip_bot <= z_wing:
-            segments.append((z_clip_top, z_clip_bot, D1))
-        elif z_clip_top >= z_wing:
-            segments.append((z_clip_top, z_clip_bot, D2))
-        else:
-            segments.append((z_clip_top, z_wing, D1))
-            segments.append((z_wing, z_clip_bot, D2))
-
-        for z_seg_top, z_seg_bot, D in segments:
-            dz_seg = z_seg_bot - z_seg_top
-            if dz_seg <= 0:
-                continue
-
-            profile = [
-                [z_seg_top, layer['Su_top'], layer['gamma_top']],
-                [z_seg_bot, layer['Su_bot'], layer['gamma_bot']]
-            ]
-            z_ref, f_Su, _, f_gamma, f_alpha = clay_profile(profile)
-
-            z_vals = np.linspace(z_seg_top, z_seg_bot, npts)
-            Su_vals = f_Su(z_vals)
-            alpha_vals = np.array([f_alpha(z) for z in z_vals])
-
-            Su_total = np.trapz(Su_vals, z_vals)
-            Su_moment = np.trapz(z_vals*Su_vals, z_vals)
-            print("xxxxxxxxxxxxxxxxxxxxxxxxx")
-            Su_av_z = Su_total/dz_seg
-            print(f"Su_av_z = {Su_av_z:.2f} Pa")
-            ez_layer = Su_moment /Su_total
-            print(f"dz_seg = {dz_seg:.2f} m")
-            print(f"ez_layer = {ez_layer:.2f} m")
-            alpha_av = np.mean(alpha_vals)
-            print(f"alpha_av = {alpha_av:.2f}")
-
-            Np_free = 3.45
-            Hmax_layer = Np_free*dz_seg*D*Su_av_z
-            print(f"Hmax_layer = {Hmax_layer:.2f} N")
-            print(f"D = {D:.2f} m")
-
-            surface_area = PileWingedSurface(dz_seg, D) if D == D1 else PileShaftSurface(dz_seg, D1, D2)
-            Vmax_layer = surface_area*alpha_av*Su_av_z
-            Vmax_total += Vmax_layer
-            print(f"Vmax_layer = {Vmax_layer:.2f} N")
-            
-            layer_data.append({
-                'z_top': z_seg_top,
-                'z_bot': z_seg_bot,
-                'dz': dz_seg,
-                'Hmax_layer': Hmax_layer,
-                'ez_layer': ez_layer,
-                'Su_av_z': Su_av_z,
-                'D_used': D
-            })
-
-    if not layer_data:
-        raise ValueError('No overlapping clay layers within pile depth.')
-
-    sum_Hmax = 0.0
-    sum_ez_weighted = 0.0
-
-    for data in layer_data:
-        z_top = data['z_top']
-        z_bot = data['z_bot']
-        Hmax_layer = data['Hmax_layer']
-        ez_layer = data['ez_layer']
-        dz_layer = data['dz']
-
-        z_embedded_start = zlug
-        z_embedded_end = zlug + L
-
-        if z_top >= z_embedded_start and z_bot <= z_embedded_end:
-            sum_ez_weighted += Hmax_layer*ez_layer
-            sum_Hmax += Hmax_layer
-        elif z_top < z_embedded_end and z_bot > z_embedded_start:
-            dz_inside = min(z_bot, z_embedded_end) - max(z_top, z_embedded_start)
-            if dz_inside > 0:
-                ratio = dz_inside/dz_layer
-                sum_ez_weighted += Hmax_layer*ratio*ez_layer
-                sum_Hmax += Hmax_layer * ratio
-
-    ez_global = sum_ez_weighted/sum_Hmax
-    print(f'ez_global = {ez_global:.2f} m')    
-    print(f'sum_Hmax = {sum_Hmax:.2f} N')
-
-    Vmax_total += PileWeight(L1, L2, D1, D2, t, rhows) + ballast
-    Wp = 1.10 * PileWeight(L1, L2, D1, D2, t, rhows + rhow) + ballast
-
-    ez_ratio = (ez_global - zlug)/L; print(f"ez_ratio = {ez_ratio:.2f} m")
-    
-    # Average effective width
-    L = L1 + L2
-    A_wing_plane_1 = (D1 - D2)*L1
-    A_wing_plane_2 = (D1 - D2)*np.cos(np.deg2rad(45))/2*L1
-    A_shaft = D2*L
-    
-    # Choose based on direction:
-    plane = '1'  # or '2'
-    
-    if plane == '1':
-        Dstar = (A_wing_plane_1 + A_shaft)/L
-    elif plane == '2':
-        Dstar = (A_wing_plane_2 + A_shaft)/L
-
-    # Assign aVH and bVH based on ez_su/L
-    if np.isclose(ez_ratio, 2/3, atol=0.05):
-        aVH = 0.5 + L/Dstar
-        bVH = 4.5 - L/(3*Dstar)
-        mode = 'deep mobilization (2/3)'
-    elif 0.40 <= ez_ratio <= 0.75:
-        aVH = 4.5 + L/(2*Dstar)
-        bVH = 3.5 - L/(4*Dstar)
-        mode = 'moderate mobilization (1/2 – 3/4)'
-    # else:
-    #     aVH = 4.0
-    #     bVH = 4.0
-    #     mode = 'default exponents (fallback)'
-    print(f'Interaction exponents set to aVH = {aVH:.2f}, bVH = {bVH:.2f} [{mode}]')
-    
-    UC = (Ha/sum_Hmax)**aVH + (Va/Vmax_total)**bVH
-
-    if plot:
-        deg = np.linspace(0, 90, 20)
-        x = np.cos(np.deg2rad(deg))
-        y = (1 - x**bVH)**(1/aVH)
-        X = sum_Hmax*x
-        Y = Vmax_total*y
-
-        plt.figure(figsize=(6, 5))
-        plt.plot(X, Y, color='blue', label='VH Envelope')
-        plt.plot(Ha, Va, 'o', color='red', label='Load Point')
-        plt.xlabel('Horizontal Capacity (N)')
-        plt.ylabel('Vertical Capacity (N)')
-        plt.title('VH torpedo pile capacity envelope')
-        plt.grid(True)
-        plt.legend()
-        plt.tight_layout()
-        plt.show()
-
-    resultsTorpedo = {
-        'Horizontal max.': sum_Hmax,
-        'Vertical max.': Vmax_total,
-        'Unity check': UC,
-        'Weight pile': Wp,
-        'ez_global': ez_global,
-        'layer_data': layer_data
-    }
-
-    return layers, resultsTorpedo
-
-if __name__ == '__main__':
-
-    profile_map = [
-        {
-            'name': 'CPT_1',
-            'x': 498234, 'y': 5725141,
-            'layers': [
-                {
-                    'top': 0.0, 'bottom': 20.0,
-                    'soil_type': 'clay',
-                    'gamma_top': 8.0, 'gamma_bot': 8.5,
-                    'Su_top': 50, 'Su_bot': 70},
-                {
-                    'top': 20.0, 'bottom': 25.0,
-                    'soil_type': 'clay',
-                    'gamma_top': 8.5, 'gamma_bot': 8.5,
-                    'Su_top': 80, 'Su_bot': 100},
-                {
-                    'top': 25.0, 'bottom': 50.0,
-                    'soil_type': 'clay',
-                    'gamma_top': 8.5, 'gamma_bot': 9.0,
-                    'Su_top': 125, 'Su_bot': 150}]
-        }
-    ]
-
-    D1 = 3.0
-    D2 = 1.5
-    L1 = 11.0
-    L2 = 5.0
-    zlug = 15.0
-    ballast = 10000
-    Ha = 6.0e6
-    Va = 8.0e6
-
-    layers, results = getCapacityTorpedo(profile_map, 'CPT_1', D1, D2, L1, L2, zlug, ballast, Ha, Va)
-
-    # print("\n--- Torpedo Pile Capacity Results ---")
-    # for key, val in results.items():
-    #     if key != 'layer_data':
-    #         print(f"{key}: {val:.2f}")
-            
-    plot_torpedo(layers, D1, D2, L1, L2, z0 = layers[0]['top'], zlug=zlug, title='Torpedo Pile in Clay Profile')
diff --git a/famodel/anchors/anchors_famodel_profile/capacity_dandg.py b/famodel/anchors/anchors_famodel_profile/capacity_dandg.py
deleted file mode 100644
index 1970a91c..00000000
--- a/famodel/anchors/anchors_famodel_profile/capacity_dandg.py
+++ /dev/null
@@ -1,272 +0,0 @@
-
-import numpy as np
-import matplotlib.pyplot as plt
-from scipy.interpolate import interp1d
-from scipy import linalg
-from .capacity_soils import rock_profile
-from .capacity_pycurves import py_Lovera
-from .capacity_plots import plot_pile
-
-def getCapacityDandG(profile, soil_type, L, D, zlug, Ha, Va, plot=True):
-    '''Models a laterally loaded pile using the p-y method. The solution for
-    lateral displacements is obtained by solving the 4th order ODE, 
-    EI*d4y/dz4 - V*d2y/dz2 + ky = 0 using the finite difference method.
-    EI*d4y/dz4 - V*d2y/dz2 + K*z*dy/dz + ky = 0 using the finite difference method.
-
-    Assumes that EI remains constant with respect to curvature i.e. pile
-    material remains in the elastic region.
-
-    Parameters
-    ----------
-    profile : array
-        Rock profile as a 2D array: (z (m), UCS (MPa), Em (MPa))
-    soil_type : string
-        Select soil condition, 'rock'
-    L : float 
-        Pile length (m)
-    D : float 
-        Pile diameter (m)
-    zlug : float
-        Load eccentricity above the mudline or depth to mudline relative to the pile head (m)
-    Ha : float       
-        Horizontal load at pile lug elevation (N)
-    Va : float          
-        Vertical load at pile lug elevation (N)
-    plot : bool
-        Plot the p-y curve and the deflection pile condition if True
-
-    Returns
-    -------
-    y : array
-        Lateral displacement at each node (n+1 real + 4 imaginary)
-    z : array
-        Node location along pile (m)
-    resultsDandG : dict
-        Dictionary with lateral, rotational, vertical and pile weight results
-    '''
-
-    n = 50; loc = 2              # Number of nodes (-)
-    tol = 1e-16; max_iter = 50   # Iteration parameters (-)
-    nhuc = 1; nhu = 0.3          # Resistance factor (-)
-    delta_r = 0.08               # Mean roughness height (m)
-    
-    t = (6.35 + D*20)/1e3        # Pile wall thickness (m), API RP2A-WSD
-    E = 200e9                    # Elastic modulus of pile material (Pa)
-    rhows = 66.90e3              # Submerged steel specific weight (N/m3)
-    rhow = 10e3                  # Water specific weight (N/m3) 
-    
-    # Pile geometry
-    I = (np.pi/64.0)*(D**4 - (D - 2*t)**4)
-    EI = E*I
-    h = L/n                      # Element size
-    N = (n + 1) + 4              # (n+1) Real + 4 Imaginary nodes
-    
-    # Dry and wet mass of the pile    
-    def PileWeight(Len, Dia, tw, rho):
-        Wp = ((np.pi/4)*(Dia**2 - (Dia - 2*tw)**2)*Len)*rho
-        return Wp 
-
-    # Array for displacements at nodes, including imaginary nodes.
-    y = np.ones(N)*(0.01*D)      # An initial value of 0.01D was arbitrarily chosen
-
-    # Initialize and assemble array/list of p-y curves at each real node
-    z = np.zeros(N)
-    k_secant = np.zeros(N)
-    py_funs = []
-    DQ = []
-    z0, f_UCS, f_Em = rock_profile(profile)
-    
-
-    for i in [0, 1]:              # Top two imaginary nodes
-        z[i] = (i - 2)*h
-        py_funs.append(0)
-        k_secant[i] = 0.0
-   
-    for i in range(2, n+3):       # Real nodes
-        z[i] = (i - 2)*h       
-        if z[i] < z0:
-             # No p-y curve above mudline
-             py_funs.append(lambda y_val: np.zeros_like(y_val))
-             k_secant[i] = 0.0
-             DQ.append(0.0)
-        else:
-             py_funs.append(py_Lovera(z[i], D, f_UCS, f_Em, zlug, z0, plot=True)) 
-             # print(f"z = {z[i]:.2f} m, UCS = {f_UCS(z[i]):.2e} Pa, Em = {f_Em(z[i]):.2e} Pa")
-             UCS = f_UCS(z[i])
-             Em = f_Em(z[i])
-             SCR = nhuc*Em/(UCS*(1 + nhu))*delta_r/D
-             alpha = 0.36*SCR - 0.0005
-             fs = alpha*UCS
-             Dq = np.pi*D*fs*z[i]
-             DQ.append(Dq)
-             Vmax = PileWeight(L, D, t, rhows) + DQ[-1]
-             
-             k_secant[i] = py_funs[i](y[i])/y[i]
-
-    for i in [n+3, n+4]:         # Bottom two imaginary nodes
-        z[i] = (i - 2)*h
-        py_funs.append(0)
-        k_secant[i] = 0.0
-   
-    for j in range(max_iter):
-        y_old = y.copy()
-        y = fd_solver(n, N, h, EI, Ha, Va, zlug, z0, k_secant)
-        
-        # Update stiffness
-        for i in range(2, n+3):
-            if callable(py_funs[i]):
-                k_secant[i] = py_funs[i](y[i])/y[i] if y[i] != 0 else 0.0
-    
-        # Check convergence
-        if np.linalg.norm(y - y_old, ord=2) < tol:
-            print(f'[Converged in {j+1} iterations]')
-            break
-    else:
-        print('[Warning: Solver did not converge]')
-
-    if plot:
-        y1 = np.linspace(-2.*D, 2.*D, 500)
-        plt.plot(y1, py_funs[loc](y1))
-        plt.xlabel('y (m)'), plt.ylabel('p (N/m)')
-        plt.grid(True)
-        
-        fig, ax = plt.subplots(figsize=(3, 5))
-        y0 = np.zeros_like(z[2:-2])
-        # Plot original vertical pile
-        ax.plot(y0, z[2:-2], 'k', label='Original pile axis')
-        # Plot deflected shape
-        ax.plot(y[2:-2], z[2:-2], 'r', label='Deflected shape')
-        # Padeye marker
-        ax.plot(0, zlug, 'ko', label=f'Padeye (zlug = {zlug:.2f} m)')
-        # Mudline marker 
-        ax.axhline(z0, color='blue', linestyle='--', label=f'Mudline (z0 = {z0:.2f} m)')
-        
-        ax.set_xlabel('Lateral displacement (m)')
-        ax.set_ylabel('Depth (m)')
-        ax.set_xlim([-0.1*D, 0.1*D])
-        ax.set_ylim([L + 5, -2])  # Downward is positive z 
-        ax.grid(ls='--')
-        ax.legend()  
-            
-    # Relevant index of nodes
-    zlug_index = int(zlug/h); print(zlug_index)
-    ymax_index = int(np.max(y)); print(ymax_index)    
-    
-    resultsDandG = {
-        'Weight pile': PileWeight(L, D, t, rhows + rhow),
-        'Vertical max.': Vmax,
-        'Lateral displacement': y[ymax_index],
-        'Rotational displacement': np.rad2deg(abs(y[ymax_index - 1] - y[ymax_index])/h),
-        'Unity check (vertical)': Va/Vmax if Vmax != 0 else np.inf,
-        'Unity check (horizontal)': 0.0,  # Placeholder; no Mp or Mi in current model
-        'Bending moment': None,
-        'Plastic moment': None,
-        'Plastic hinge': None,
-        'Hinge location': None,
-        'p-y model': 'Lovera (2023)',
-        }
-    
-    return y[2:-2], z[2:-2], resultsDandG
-
-def fd_solver(n, N, h, EI, Ha, Va, zlug, z0, k_secant):
-    '''Solves the finite difference equations from 'py_analysis_1'. This function should be run iteratively for
-    non-linear p-y curves by updating 'k_secant' using 'y'. A single iteration is sufficient if the p-y curves
-    are linear.
-
-    Parameters
-    ----------
-    n : int
-        Number of elements (-)
-    N : int
-        Total number of nodes (-)
-    h : float
-        Element size (m)
-    EI : float
-        Flexural rigidity of the pile (Nm²)
-    Ha : float
-        Horizontal load at padeye (N)
-    Va : float
-        Vertical load at padeye (N)
-    zlug : float
-        Padeye depth from pile head (m)
-    z0 : float
-        Mudline elevation from pile head (m)
-    k_secant : array
-        Secant stiffness at each node
-
-    Returns
-    -------
-    y : array
-        Lateral displacement at each node (n+1 real + 4 imaginary)
-    '''
-    
-    # Initialize and assemble matrix
-    X = np.zeros((N, N))
-
-    # (n+1) finite difference equations for (n+1) real nodes
-    for i in range(0,n+1):
-        X[i, i]   =  1.0
-        X[i, i+1] = -4.0 + Va*h**2/EI
-        X[i, i+2] =  6.0 - 2*Va*h**2/EI + k_secant[i+2]*h**4/EI
-        X[i, i+3] = -4.0 + Va*h**2/EI
-        X[i, i+4] =  1.0
-
-    # Curvature at pile head
-    X[n+1, 1] =  1.0
-    X[n+1, 2] = -2.0
-    X[n+1, 3] =  1.0
-
-    # Shear at pile head
-    X[n+2, 0] = -1.0
-    X[n+2, 1] =  2.0 - Va*h**2/EI
-    X[n+2, 2] =  0.0
-    X[n+2, 3] = -2.0 + Va*h**2/EI
-    X[n+2, 4] =  1.0
-
-    # Curvature at pile tip
-    X[n+3, -2] =  1.0
-    X[n+3, -3] = -2.0
-    X[n+3, -4] =  1.0
-
-    # Shear at pile tip
-    X[n+4, -1] =  1.0
-    X[n+4, -2] = -2.0 + Va*h**2/EI
-    X[n+4, -3] =  0.0
-    X[n+4, -4] =  2.0 - Va*h**2/EI
-    X[n+4, -5] = -1.0
-
-    # Initialize vector q
-    q = np.zeros(N)
-    
-    # Index of the node where the horizontal load is applied (padeye)
-    zlug_index = int(zlug/h)
-    q[zlug_index] = 2*Ha*h**3
-
-    # Solve for displacement
-    y = linalg.solve(EI*X, q)
-
-    return y
-   
-if __name__ == '__main__':
-    
-    profile_rock = np.array([
-        [ 2.0, 2, 200],
-        [ 5.0, 2, 200],
-        [ 9.0, 2, 200],
-        [30.0, 2, 200]
-    ])
-    
-    D = 3.0           # Diameter (m)
-    L = 10.0          # Length (m)
-    zlug = 1          # Padeye elevation (m)
-    Ha = 8.0e6        # Horizontal load (N)
-    Va = 3.0e6        # Vertical load (N)
-    
-    y, z, resultsDandG = getCapacityDandG(profile_rock, 'rock', L, D, zlug, Ha, Va, plot=True)
-    for key, val in resultsDandG.items():
-        if isinstance(val, float):
-            print(f"{key}: {val:.3f}")
-        else:
-            print(f"{key}: {val}")
-    
-    plot_pile(profile_rock, 'rock', y, z, D, L, profile_rock[0, 0], zlug)
diff --git a/famodel/anchors/anchors_famodel_profile/capacity_driven.py b/famodel/anchors/anchors_famodel_profile/capacity_driven.py
deleted file mode 100644
index 485f7e8c..00000000
--- a/famodel/anchors/anchors_famodel_profile/capacity_driven.py
+++ /dev/null
@@ -1,418 +0,0 @@
-
-import numpy as np
-import matplotlib.pyplot as plt
-from scipy.interpolate import interp1d
-from scipy import linalg
-from .capacity_soils import clay_profile, sand_profile, rock_profile
-from .capacity_pycurves import py_Matlock, py_API, py_Reese
-from .capacity_plots import plot_pile
-
-def getCapacityDriven(profile, soil_type, L, D, zlug, Ha, Va, plot=True):   
-    '''Models a laterally loaded pile using the p-y method. The solution for
-    lateral displacements is obtained by solving the 4th order ODE, EI*d4y/dz4
-    EI*d4y/dz4 - V*d2y/dz2 + ky = 0 using the finite difference method.
-    EI*d4y/dz4 - V*d2y/dz2 + K*z*dy/dz + ky = 0 using the finite difference method.
-    
-    Assumes that EI remains constant with respect to curvature i.e. pile
-    material remains in the elastic region.
-
-    Parameters
-    ----------
-    profile : array
-        Soil profile as a 2D array: (z, parameters)
-            Clay: (z (m), Su (kPa), gamma (kN/m³))
-            Sand: (z (m), phi (deg), gamma (kN/m³), Dr (%))
-            Rock: (z (m), UCS (MPa), Em (MPa))
-    soil_type : string
-        Select soil condition: 'clay', 'sand', or '(weak) rock'
-    L : float
-        Pile length (m)
-    D : float
-        Pile diameter (m)
-    zlug : float
-        Depth of padeye from pile head (m)
-    Ha : float
-        Horizontal load applied at padeye (N)
-    Va : float
-        Vertical load applied at padeye (N)
-    plot : bool
-        Plot the p-y curve and the deflection pile condition if True
-
-    Returns
-    -------
-    y : array
-        Lateral displacement at each node (real nodes only)
-    z : array
-        Node depth positions corresponding to y (m)
-    resultsDriven : dict
-        Dictionary containing displacements, moment capacity, hinge state and vertical capacity
-    '''
-
-    n = 50; iterations = 10; loc = 2
-    nhuc = 1; nhu = 0.3         # Resistance factor (-)
-    delta_r = 0.08              # Mean roughness height (m)
-    
-    t = (6.35 + D*20)/1e3       # Pile wall thickness (m), API RP2A-WSD
-    E = 200e9                   # Elastic modulus of pile material (Pa)
-    fy = 350e6                  # Yield strength of pile material (Pa)
-    rhows = 66.90e3             # Submerged steel specific weight (N/m3)
-    rhow = 10e3                 # Water specific weight (N/m3) 
-    
-    # Pile geometry
-    I = (np.pi/64.0)*(D**4 - (D - 2*t)**4)
-    EI = E*I
-    h  = L/n                    # Element size
-    N  = (n + 1) + 4            # (n+1) Real + 4 Imaginary nodes
-    
-    # Outer and inner surface of the pile skirt
-    def PileSurface(Len, Dia):
-        Sp = np.pi*Dia*Len
-        return Sp    
-    # Dry and wet mass of the pile    
-    def PileWeight(Len, Dia, tw, rho):
-        Wp = ((np.pi/4)*(Dia**2 - (Dia - 2*tw)**2)*Len)*rho 
-        return Wp 
-    # Mass of the soil plug      
-    def SoilWeight(Len, Dia, tw, gamma_soil): 
-        Wsoil =(np.pi/4)*(Dia - 2*tw)**2*Len*gamma_soil
-        return Wsoil
-
-    # Array for displacements at nodes, including imaginary nodes.
-    y = np.ones(N)*(0.01*D)     # An initial value of 0.01D was arbitrarily chosen
-
-    # Initialize and assemble array/list of p-y curves at each real node
-    z = np.zeros(N)
-    py_funs  = []; PileShaft =[]
-    k_secant = np.zeros(N)
-    DQ = []
-
-    for i in [0, 1]:            # Top two imaginary nodes
-        z[i] = (i - 2)*h
-        py_funs.append(0)
-        k_secant[i] = 0.0
-
-    for i in range(2, n+3):    # Real nodes
-        z[i] = (i - 2)*h      
-        if soil_type == 'clay':
-            z0, f_Su, f_sigma_v_eff, f_gamma, f_alpha = clay_profile(profile)
-            if z[i] < z0:
-                # No p-y curve above mudline
-                py_funs.append(lambda y_val: np.zeros_like(y_val))
-                k_secant[i] = 0.0
-                PileShaft.append(0.0)
-            else:
-                Su = f_Su(z[i])
-                sigma_v_eff = f_sigma_v_eff(z[i])
-                gamma = f_gamma(z[i])
-                alpha = f_alpha(z[i])
-                py_funs.append(py_Matlock(z[i], D, zlug, f_Su, f_sigma_v_eff, f_gamma, z0=z0, plot=plot))
-                Vo = np.pi*D*alpha*Su*z[i]**2
-                PileShaft.append(Vo)
-                k_val = py_funs[i](y[i])
-                k_secant[i] = k_val/y[i] if y[i] != 0 else 0.0
-            
-        elif soil_type == 'sand':
-            z0, f_phi, f_sigma_v_eff, f_gamma, f_Dr, f_delta = sand_profile(profile)
-            if z[i] < z0:
-                # No p-y curve above mudline
-                py_funs.append(lambda y_val: np.zeros_like(y_val))
-                k_secant[i] = 0.0
-                PileShaft.append(0.0)
-            else:
-                phi = f_phi(z[i])
-                sigma_v_eff = f_sigma_v_eff(z[i])
-                gamma = f_gamma(z[i])
-                delta = f_delta(z[i])
-                py_funs.append(py_API(z[i], D, zlug, f_phi, f_sigma_v_eff, f_Dr, z0=z0, plot=plot))
-                fs = delta * sigma_v_eff
-                Vo = np.pi*D*fs*z[i]
-                PileShaft.append(Vo)
-                k_val = py_funs[i](y[i])
-                k_secant[i] = k_val/y[i] if y[i] != 0 else 0.0
-            
-        elif soil_type in ['rock', 'weak_rock']:
-            z0, f_UCS, f_Em = rock_profile(profile)            
-            if z[i] < z0:
-                # No p-y curve above mudline
-                py_funs.append(lambda y_val: np.zeros_like(y_val))
-                k_secant[i] = 0.0
-                DQ.append(0.0)
-            else:
-                UCS = f_UCS(z[i])
-                Em = f_Em(z[i])
-                py_funs.append(py_Reese(z[i], D, zlug, f_UCS, f_Em, z0=z0, plot=plot))
-                SCR = nhuc*Em/(UCS*(1 + nhu))*delta_r/D
-                alpha = 0.36*SCR - 0.0005
-                fs = alpha*UCS
-                Dq = np.pi*D*fs*z[i]
-                DQ.append(Dq)
-                k_val = py_funs[i](y[i])
-                k_secant[i] = k_val/y[i] if y[i] != 0 else 0.0
-       
-    for i in [n+3, n+4]:       # Bottom two imaginary nodes
-        z[i] = (i - 2)*h
-        py_funs.append(0)
-        k_secant[i] = 0.0
-
-    # Compute individual contributions to total vertical load
-    Wp    = PileWeight(L, D, t, rhows)                                           # Pile self-weight (wet)
-    Wsoil = SoilWeight(L, D, t, gamma) if soil_type in ['clay', 'sand'] else 0.0 # Soil plug only in soil profiles
-    Wshaft = PileShaft[-1] if soil_type in ['clay', 'sand'] else 0.0             # Shaft resistance for soils
-    Wtip   = DQ[-1] if soil_type in ['rock', 'weak_rock'] else 0.0               # Tip resistance for rock
-    
-    # Compute total vertical capacity
-    Vmax = Wp + Wsoil + Wshaft + Wtip
-    
-    for j in range(iterations):
-        y, Mi, Mp, hinge_formed, hinge_location = fd_solver(n, N, h, D, t, fy, EI, Ha, Va, zlug, z0, k_secant)
-        for i in range(2, n+3):
-            if callable(py_funs[i]):
-                k_secant[i] = py_funs[i](y[i])/y[i]
-                
-    if plot:
-        y1 = np.linspace(-2.*D, 2.*D, 500)
-        plt.plot(y1, py_funs[loc](y1))
-        plt.xlabel('y (m)'), plt.ylabel('p (N/m)')
-        plt.grid(True)
-        
-        fig, ax = plt.subplots(figsize=(3, 5))
-        y0 = np.zeros_like(z[2:-2])
-        # Plot original vertical pile
-        ax.plot(y0, z[2:-2], 'k', label='Original pile axis')
-        # Plot deflected shape
-        ax.plot(y[2:-2], z[2:-2], 'r', label='Deflected shape')
-        # Padeye marker
-        ax.plot(0, zlug, 'ko', label=f'Padeye (zlug = {zlug:.2f} m)')
-        # Mudline marker 
-        ax.axhline(z0, color='blue', linestyle='--', label=f'Mudline (z0 = {z0:.2f} m)')
-        
-        ax.set_xlabel('Lateral displacement (m)')
-        ax.set_ylabel('Depth (m)')
-        ax.set_xlim([-0.1*D, 0.1*D])
-        ax.set_ylim([L + 5, -2])  # Downward is positive z 
-        ax.grid(ls='--')
-        ax.legend() 
-
-    # Relevant index of nodes
-    zlug_index = int(zlug/h); print(zlug_index)
-    ymax_index = int(np.max(y)); print(ymax_index)      
-
-    resultsDriven = {
-        'Weight pile': PileWeight(L, D, t, rhows + rhow),
-        'Vertical max.': Vmax,
-        'Horizontal max.': abs(Mi)/abs(zlug) if zlug != 0 else 1e-6,
-        'Unity check (vertical)': Va/Vmax if Vmax != 0 else np.inf,
-        'Unity check (horizontal)': Ha/(abs(Mi)/abs(zlug)) if zlug != 0 else np.inf,
-        'Lateral displacement': y[ymax_index],
-        'Rotational displacement': np.rad2deg(abs(y[ymax_index - 1] - y[ymax_index])/h),
-        'Bending moment': abs(Mi),
-        'Plastic moment': Mp,
-        'Plastic hinge': hinge_formed,
-        'Hinge location': hinge_location,
-        'p-y model': 'Matlock (1970)' if soil_type == 'clay' else 'API RP2A (1993)' if soil_type == 'sand' else 'Reese (1997)',
-        }
-
-    
-    return y[2:-2], z[2:-2], resultsDriven
-
-def fd_solver(n, N, h, D, t, fy, EI, Ha, Va, zlug, z0, k_secant):
-    '''Solves the finite difference equations from 'py_analysis_1'. This function should be run iteratively for
-    non-linear p-y curves by updating 'k_secant' using 'y'. A single iteration is sufficient if the p-y curves
-    are linear.
-
-    Parameters
-    ----------
-    n : int
-        Number of elements
-    N : int
-        Total number of nodes (real + imaginary)
-    h : float
-        Element size (m)
-    D : float
-        Pile diameter (m)
-    t : float
-        Pile wall thickness (m)
-    fy : float
-        Yield strength of pile material (Pa)
-    EI : float
-        Flexural rigidity of the pile (Nm²)
-    Ha : float       
-        Horizontal load at pile lug elevation (N)
-    Va : float          
-        Vertical load at pile lug elevation (N)
-    zlug : float
-        Depth of padeye from pile head (m)
-    z0 : float
-        Mudline depth from pile head (m)
-    k_secant : array
-        Secant stiffness from p-y curves at each node
-
-    Returns
-    -------
-    y : array
-        Lateral displacement at each node
-    Mi : float
-        Maximum internal bending moment (Nm)
-    Mp : float
-        Plastic moment capacity of the pile (Nm)
-    hinge_formed : bool
-        Whether plastic hinge is formed
-    hinge_location : int
-        Index of the node with hinge formation
-    '''
-     
-    # Initialize and assemble matrix
-    X = np.zeros((N, N))
-
-    # (n+1) finite difference equations for (n+1) real nodes
-    for i in range(0, n+1):
-        X[i, i]   =  1.0
-        X[i, i+1] = -4.0 + Va*h**2/EI
-        X[i, i+2] =  6.0 - 2*Va*h**2/EI + k_secant[i+2]*h**4/EI
-        X[i, i+3] = -4.0 + Va*h**2/EI
-        X[i, i+4] =  1.0
-
-    # Curvature at pile head
-    X[n+1, 1] =  1.0
-    X[n+1, 2] = -2.0
-    X[n+1, 3] =  1.0
-
-    # Shear at pile head
-    X[n+2, 0] = -1.0
-    X[n+2, 1] =  2.0 - Va*h**2/EI
-    X[n+2, 2] =  0.0
-    X[n+2, 3] = -2.0 + Va*h**2/EI
-    X[n+2, 4] =  1.0
-
-    # Curvature at pile tip
-    X[n+3, -2] =  1.0
-    X[n+3, -3] = -2.0
-    X[n+3, -4] =  1.0
-
-    # Shear at pile tip
-    X[n+4, -1] =  1.0
-    X[n+4, -2] = -2.0 + Va*h**2/EI
-    X[n+4, -3] =  0.0
-    X[n+4, -4] =  2.0 - Va*h**2/EI
-    X[n+4, -5] = -1.0
-
-    # Initialize vector q
-    q = np.zeros(N)
-    
-    # Always apply shear
-    # Index of the node where the horizontal load is applied (padeye)
-    zlug_index = int(zlug/h)
-    q[zlug_index] = 2*Ha*h**3
-                 
-    y = linalg.solve(EI*X, q)
-
-    # Compute the plastic moment capacity Mp
-    Zp = (1/6)*(D**3 - (D - 2*t)**3)  # Plastic section modulus for hollow pile (m3)
-    Mp = Zp*fy                        # Plastic moment capacity (N/m)
-
-    # Check for plastic hinge formation
-    Mi, Mp, hinge_formed, hinge_location = plastic_hinge(y, h, EI, Mp)
-    
-    return y, Mi, Mp, hinge_formed, hinge_location
-   
-def plastic_hinge(y, h, EI, Mp):
-    '''Check for plastic hinge formation along the pile.
-    
-    Parameters
-    ----------
-    y : array
-        Lateral displacements at each node
-    h : float
-        Element size (m)
-    EI : float
-        Flexural rigidity of the pile (Nm²)
-    Mp : float
-        Plastic moment capacity (Nm)
-
-    Returns
-    -------
-    Mi_max : float
-        Maximum internal moment along the pile (Nm)
-    Mp : float
-        Plastic moment capacity (Nm)
-    hinge_formed : bool
-        True if plastic hinge is formed
-    hinge_location : int
-        Node index where hinge forms (if any)
-    '''
-    
-    hinge_formed = False
-    hinge_location = -1
-    Mi_all = []
-        
-    # Loop through each internal node and compute the bending moment
-    for i in range(1, len(y) - 1):
-        Mi = EI * (y[i+1] - 2*y[i] + y[i-1])/h**2
-        Mi_all.append(Mi)
-
-        if abs(Mi) >= Mp and not hinge_formed:
-            hinge_formed = True
-            hinge_location = i
-
-    Mi_max = max(Mi_all, key=abs) if Mi_all else 0.0
-
-    return Mi_max, Mp, hinge_formed, hinge_location
-
-if __name__ == '__main__':
-    
-    profile_clay = np.array([
-        [ 1.0, 600, 8],     
-        [ 6.0, 200, 8],
-        [15.0, 400, 8],
-        [30.0, 600, 9]
-    ])
-    
-    profile_sand = np.array([
-        [ 2.0, 28,  8, 75],
-        [10.0, 34,  9, 75],
-        [15.0, 36, 10, 75],
-        [40.0, 45,  9, 85]
-    ])
-    
-    profile_rock = np.array([
-        [ 2.0, 0.5, 1e3],
-        [ 5.0, 2.0, 2e4],
-        [30.0, 1.0, 5e4]
-    ])
-
-    D = 2.5           # Diameter (m)
-    L = 25.0          # Length (m)
-    zlug = 1          # Padeye depth (m)
-    
-    # === CLAY ===
-    y_clay, z_clay, resultsDriven_clay = getCapacityDriven(profile_clay, 'clay', L, D, zlug, Ha=5.0e6,  Va=1.5e5, plot=True)
-    for key, val in resultsDriven_clay.items():
-        if isinstance(val, float):
-            print(f"{key}: {val:.3f}")
-        else:
-            print(f"{key}: {val}")
-
-    plot_pile(profile_clay, 'clay', y_clay, z_clay, D, L, profile_clay[0, 0], zlug, resultsDriven_clay.get('Hinge location'))
-
-    # # === SAND ===
-    # y_sand, z_sand, resultsDriven_sand = getCapacityDriven(profile_sand, 'sand', L, D, zlug, Ha=2.5e6, Va=2.0e6, plot=True)
-    # for key, val in resultsDriven_sand.items():
-    #     if isinstance(val, float):
-    #         print(f"{key}: {val:.3f}")
-    #     else:
-    #         print(f"{key}: {val}")
-
-    # plot_pile(profile_sand, 'sand',  y_sand, z_sand, D, L, profile_sand[0, 0], zlug, resultsDriven_sand.get('Hinge location'))
-
-    # # === ROCK ===
-    # y_rock, z_rock, resultsDriven_rock = getCapacityDriven(profile_rock, 'rock', L, D, zlug, Ha=3.5e6, Va=3.0e6, plot=True)
-    # for key, val in resultsDriven_rock.items():
-    #     if isinstance(val, float):
-    #         print(f"{key}: {val:.3f}")
-    #     else:
-    #         print(f"{key}: {val}")
-
-    # plot_pile(profile_rock, 'rock', y_rock, z_rock, D, L, profile_rock[0, 0], zlug, resultsDriven_rock.get('Hinge location'))
-
-
-
diff --git a/famodel/anchors/anchors_famodel_profile/capacity_helical.py b/famodel/anchors/anchors_famodel_profile/capacity_helical.py
deleted file mode 100644
index d425aea8..00000000
--- a/famodel/anchors/anchors_famodel_profile/capacity_helical.py
+++ /dev/null
@@ -1,152 +0,0 @@
-
-import numpy as np
-import matplotlib.pyplot as plt
-from .capacity_driven import getCapacityDriven, plot_pile
-from .capacity_soils import clay_profile, sand_profile
-from .capacity_plots import plot_helical
-
-def getCapacityHelical(profile, soil_type, D, L, d, zlug, Ha, Va, plot=True):
-    '''Calculate the vertical and horizontal capacity of a helical pile using a soil profile.
-    The calculation is based on the soil profile, anchor geometry and inclined load.
-
-    Parameters
-    ----------
-    profile : array
-        Soil profiles (z, parameters)
-            Clay: (z (m), Su (kPa), gamma (kN/m³))
-            Sand: (z (m), phi (deg), gamma (kN/m³), Dr (%))
-    soil_type : string
-        Select soil condition, 'clay' or 'sand'
-    D : float 
-        Helix diameter (m)
-    L : float 
-        Shaft length (m)
-    d : float 
-        Shaft diameter (m)
-    zlug : float
-        Depth to padeye (m)
-    Ha : float
-        Horizontal load at pile lug elevation (N)   
-    Va : float
-        Vertical load at pile lug elevation (N)
-    plot : bool
-        Plot the p-y curve and the deflection pile condition if True
-
-    Returns
-    -------
-    Dictionary with capacity, displacements, weight and UC.
-    '''
-
-    t = (6.35 + D*20)/1e3            # Helical pile wall thickness (m), API RP2A-WSD
-    rhows = 66.90e3                  # Submerged steel specific weight (kN/m3)
-    rhow = 10e3                      # Water specific weight (kN/m3) 
-
-    def PileWeight(Len, Dia1, Dia2, tw, rho):
-        return ((np.pi/4)*((Dia1**2 - (Dia1 - 2*tw)**2)*Len + (np.pi/4)*Dia2**2*tw))*rho
-
-    if soil_type == 'clay':
-        z0, f_Su, f_sigma_v_eff, f_gamma, f_alpha = clay_profile(profile)
-
-        z_helix = np.clip(zlug + (L - D), profile[0, 0], profile[-1, 0])
-        Su = f_Su(z_helix)
-        sigma_v_eff = max(f_sigma_v_eff(z_helix), 1.0)
-        psi_val = Su/sigma_v_eff
-        alpha = min(0.5*psi_val**-0.50, 1) if psi_val <= 1.0 else min(0.5 * psi_val**-0.25, 1)
-
-        Nc = min(6.0*(1 + 0.2*d/D), 9)
-        Qh = ((np.pi/4)*(D**2 - d**2)*Nc*Su + f_gamma(z_helix)*D)*0.75
-        Qs = np.pi*d*L*alpha*Su
-        Qu = PileWeight(L, D, d, t, rhows) + Qh + Qs
-
-    elif soil_type == 'sand':
-        z0, f_phi, f_sigma_v_eff, f_gamma, f_Dr, f_delta = sand_profile(profile)
-
-        z_helix = np.clip(zlug + (L - D), profile[0, 0], profile[-1, 0])
-        gamma = f_gamma(z_helix)
-        Dr = f_Dr(z_helix)
-        delta = f_delta(z_helix)
-        phi = f_phi(z_helix)
-
-        Nq = 0.5*(12*phi)**(phi/54)
-        Qh = (np.pi/4)*(D**2 - d**2)*Nq*gamma*z_helix
-        Qs = np.pi*d*L*delta*gamma*z_helix
-        Qu = PileWeight(L, D, d, t, rhows) + Qh + Qs
-        
-    # Pile weight (inc. auxilary items) assessed as a factor
-    Wp = 1.10*PileWeight(L, D, d, t, (rhows + rhow))    
-
-    # Unity Check based only on vertical capacity
-    UC_vertical = Va/Qu
-
-    # Compute horizontal capacity using p-y method
-    y, z, results_lateral = getCapacityDriven(profile, soil_type, L, d, zlug, Ha, Va, plot=True)
-    if soil_type == 'clay':
-        plot_pile(profile_clay, 'clay', y, z, D, L, z0, zlug, hinge_location=None)
-    elif soil_type == 'sand':
-        plot_pile(profile_sand, 'sand', y, z, D, L, z0, zlug, hinge_location=None)
-
-    Hcap = Ha if 'Plastic moment' not in results_lateral else results_lateral['Bending moment']/abs(zlug) if zlug != 0 else 1e-6
-    UC_horizontal = Ha/Hcap if Hcap != 0 else np.inf
-
-    resultsHelical = {
-        'Weight pile': Wp,
-        'Vertical max.': Qu,
-        'Horizontal max.': Hcap,
-        'Unity check (vertical)': UC_vertical,
-        'Unity check (horizontal)': UC_horizontal,
-        'Lateral displacement': results_lateral.get('Lateral displacement', None),
-        'Rotational displacement': results_lateral.get('Rotational displacement', None),
-        'Bending moment': results_lateral.get('Bending moment', None),
-        'Plastic moment': results_lateral.get('Plastic moment', None),
-        'Plastic hinge': results_lateral.get('Plastic hinge', None),
-        'Hinge location': results_lateral.get('Hinge location', None),
-        'p-y model': results_lateral.get('p-y model', None),
-        }
-
-    return resultsHelical
-
-if __name__ == '__main__':
-    
-    profile_clay = np.array([
-        [ 1.0, 10, 8.0],
-        [ 5.0, 15, 8.5],
-        [10.0, 25, 8.5],
-        [25.0, 50, 9.0]
-    ])
-
-    profile_sand = np.array([
-        [ 1.0, 28,  9.5, 40, 60],
-        [ 5.0, 34, 10.0, 42, 70],
-        [ 8.0, 38, 10.0, 44, 75],
-        [15.0, 38, 11.5, 45, 85]
-    ])  
-
-    D = 1.8        # Helix diameter (m)
-    L = 12.0       # Pile length (m)
-    d = 0.8        # Shaft diameter (m)
-    zlug = 2       # Padeye depth (m)
-    Va = 50e3      # Vertical load (N)
-    Ha = 30e3      # Horizontal load (N)
-
-    # === CLAY ===
-    # resultsHelical_clay = getCapacityHelical(profile_clay, 'clay', D, L, d, zlug, Ha, Va, plot=True)
-    # for key, val in resultsHelical_clay.items():
-    #     if isinstance(val, float):
-    #         print(f"{key}: {val:.3f}")
-    #     else:
-    #         print(f"{key}: {val}")
-    
-    # plot_helical(profile_clay, 'clay', D, L, d, zlug, n_helix=1, spacing=1.0, title='Helical Pile in Clay Profile')
-
-     # === SAND ===
-    resultsHelical_sand = getCapacityHelical(profile_sand, 'sand', D, L, d, zlug, Ha, Va, plot=True)
-    for key, val in resultsHelical_sand.items():
-        if isinstance(val, float):
-            print(f"{key}: {val:.3f}")
-        else:
-            print(f"{key}: {val}")
-        
-    plot_helical(profile_sand, 'sand', D, L, d, zlug, n_helix=1, spacing=1.0, title='Helical Pile in Sand Profile')
-    
-
-
diff --git a/famodel/anchors/anchors_famodel_profile/capacity_load.py b/famodel/anchors/anchors_famodel_profile/capacity_load.py
deleted file mode 100644
index 7c75ed1e..00000000
--- a/famodel/anchors/anchors_famodel_profile/capacity_load.py
+++ /dev/null
@@ -1,189 +0,0 @@
-
-import numpy as np
-import matplotlib.pyplot as plt
-from .capacity_soils import clay_profile, sand_profile
-from .capacity_plots import plot_load
-
-def getTransferLoad(profile, soil_type, Tm, thetam, zlug, line_type, d, w=None, plot=True):
-    '''Calculate the transfer load from mudline to main padeye using a layered soil profile.
-
-    Parameters
-    ----------
-    profile : array
-        Soil profile as a 2D array: (z, parameters)
-            Clay soil profile (z (m), Su (kPa), gamma (kN/m³))
-            Sand soil profile (z (m), phi (deg), gamma (kN/m³), Dr (%))
-    soil_type : string
-        Select soil condition, 'clay' or 'sand'
-    Tm : float
-        Mooring line load at mudlevel (N)
-    thetam : float
-        Mooring line angle at mudlevel (deg)
-    zlug : float
-        Embedment depth of the lug (m)
-    line_type : string
-        Select mooring line type, 'chain' or 'wire'
-    d : float
-        Mooring line diameter (m)
-    w : float
-        Mooring line unit weight (N/m)
-    plot : bool
-        Plot the inverse catenary mooring line profile if True
-
-    Returns
-    -------
-    dict
-        Dictionary with transferred load components and depth.
-    '''
-    
-    deltas = 0.2  # discretization step
-    
-    profile = np.array(profile)
-
-    # Line mechanical properties
-    if line_type == 'chain':
-        Et, En = 10, 2.5
-    elif line_type == 'wire':
-        Et, En = np.pi, 1
-    W = w*deltas
-
-    # Soil profile and interpolators
-    if soil_type == 'clay':
-        Nc = 8.5
-        z0, f_Su, _, f_gamma, f_alpha = clay_profile(profile)
-    elif soil_type == 'sand':
-        nhu = 0.5
-        z0, f_phi, _, f_gamma, _, f_delta = sand_profile(profile)
-
-    # Initial values
-    T = Tm
-    theta = np.deg2rad(thetam)
-    drag = 0
-    depth = z0 + 0.1
-
-    # Tracing lists
-    drag_values, depth_values = [], []
-
-    while (zlug - depth) >= 0:
-        if soil_type == 'clay':
-            Su = f_Su(depth)
-            alpha = f_alpha(depth)
-            dtheta = (En*d*Nc*Su - W*np.cos(theta))/T*deltas
-            dT = (Et*d*alpha*Su + W*np.sin(theta))*deltas
-        elif soil_type == 'sand':
-            gamma_z = f_gamma(depth)
-            delta_z = f_delta(depth)
-            phi = f_phi(depth)
-            Nq = np.exp(np.pi*np.tan(np.deg2rad(phi)))*(np.tan(np.deg2rad(45 + phi/2)))**2
-            print(f'Nq = {Nq:.2f}, depth = {depth:.2f} m')
-            dtheta = (En*d*Nq*gamma_z*depth - W*np.cos(theta))/T*deltas
-            dT = (Et*d*gamma_z*depth*np.tan(np.deg2rad(delta_z)) + W*np.sin(theta))*deltas
-
-        ddrag  = deltas*np.cos(theta)
-        ddepth = deltas*np.sin(theta)
-
-        theta += dtheta
-        T -= dT
-        drag += ddrag
-        depth += ddepth
-
-        if abs(Tm - T) > 0.75*Tm:
-            raise Exception(f"Load transfer unrealistic: Tm = {Tm/1e6:.2f} MN vs T = {T/1e6:.2f} MN")
-
-        if not (0 < np.rad2deg(theta) < 90):
-            raise Exception(f"Load angle unrealistic: {np.rad2deg(theta):.2f} deg")
-
-        drag_values.append(-drag)
-        depth_values.append(-depth)
-
-    Ta = T; thetaa = theta
-    # H = Ta*np.cos(thetaa)
-    # V = Ta*np.sin(thetaa)
-    
-    if plot:
-        plot_load(
-            profile, soil_type,
-            drag_values, depth_values,
-            Tm, thetam,
-            Ta, thetaa,
-            zlug
-        )
-
-    resultsLoads = {
-        'Tm': Tm,
-        'thetam': thetam,
-        'Ta': Ta,
-        'thetaa': thetaa,
-        'length': deltas*len(drag_values),
-        'drag_values': drag_values,
-        'depth_values': depth_values
-    }
-
-    return resultsLoads
-
-if __name__ == '__main__':
-    
-    # Define a clay profile: [depth (m), Su (kPa), gamma (kN/m3)]
-    # profile_clay = np.array([
-    # [ 0.0,   0, 0.0],  
-    # [ 2.0,  25, 8.0],
-    # [ 8.0,  50, 8.0],
-    # [16.0, 100, 8.0]
-    # ])
-    
-    # Define a sand profile: [depth (m), phi (deg), gamma (kN/m3), Dr (%)]
-    profile_sand = np.array([
-        [ 0.0, 30, 9.5, 70],
-        [ 5.0, 30, 9.5, 70],
-        [10.0, 30, 9.5, 70],
-        [15.0, 30, 9.5, 70]
-    ])
-    
-    # # Input parameters
-    # Tm = 1.2e7            # Load at mudline (N)
-    # thetam = 10           # Angle at mudline (deg)
-    # zlug = 8.3            # Padeye depth (m)
-    # line_type = 'chain'
-    # d = 0.16              # Chain diameter (m)
-    # w = 4093              # Line weight (N/m)
-    
-    # # Run transfer load calculation
-    # results = getTransferLoad(profile_clay, soil_type, Tm, thetam, zlug, line_type, d, w, plot=True)
-    # print("\n--- Transfer Load Results (Clay) ---")
-    # for key, val in results.items():
-    #     if isinstance(val, float):
-    #         print(f"{key}: {val:.3f}")
-    #     elif isinstance(val, list):
-    #         print(f"{key}:")
-    #         for v in val:
-    #             print(f"  {v:.3f}")
-    #     else:
-    #         print(f"{key}: {val}")
-        
-    # plot_load(profile_clay, soil_type, results['drag_values'], results['depth_values'], results['Tm'], results['thetam'], results['Ta'], results['thetaa'], zlug)
-      
-
-    # Input parameters
-    Tm = 8.2e6
-    thetam = 10
-    zlug = 8
-    line_type = 'chain'
-    d = 0.25
-    soil_type = 'sand'
-    w = 4093
-    
-    results = getTransferLoad(profile_sand, soil_type, Tm, thetam, zlug, line_type, d, w, plot=True)
-    
-    # print("\n--- Transfer Load Results (Sand) ---")
-    # for key, val in results.items():
-    #     if isinstance(val, float):
-    #         print(f"{key}: {val:.3f}")
-    #     elif isinstance(val, list):
-    #         print(f"{key}:")
-    #         for v in val:
-    #             print(f"  {v:.3f}")
-    #     else:
-    #         print(f"{key}: {val}")
-    
-    plot_load(profile_sand, soil_type, results['drag_values'], results['depth_values'], results['Tm'], results['thetam'], results['Ta'], results['thetaa'], zlug)
-
diff --git a/famodel/anchors/anchors_famodel_profile/capacity_plate.py b/famodel/anchors/anchors_famodel_profile/capacity_plate.py
deleted file mode 100644
index cb718fa2..00000000
--- a/famodel/anchors/anchors_famodel_profile/capacity_plate.py
+++ /dev/null
@@ -1,143 +0,0 @@
-
-import numpy as np
-import matplotlib.pyplot as plt
-from .capacity_soils import clay_profile
-from .capacity_plots import plot_plate
-
-def getCapacityPlate(profile, soil_type, B, L, zlug, beta, Ha, Va, plot=True):
-    '''Calculate the plate anchor capacity using a full clay soil profile and return capacity + UC.
-    The calculation is based on the soil profile, anchor geometry and inclined load.
-
-    Parameters
-    ----------
-    profile : ndarray
-        Clay soil profile as a 2D array: [[depth, Su, gamma], ...]
-    soil_type : str
-        Currently only 'clay' is supported.
-    B : float
-        Plate width (m)
-    L : float
-        Plate length (m)
-    zlug : float
-        Embedment depth of the main padeye (m)
-    beta : float
-        Inclination angle of the plate (deg)
-    Ha : float
-        Applied horizontal load (kN)
-    Va : float
-        Applied vertical load (kN)
-    plot : bool
-        Placeholder for future use.
-
-    Returns
-    -------
-    Dictionary with capacity, weight and UC.
-    '''
-    
-    Los = 0.05
-    B_t = 40
-    rhows = 66.90e3        # Submerged steel specific weight (kN/m3)
-    rhow = 10e3            # Water specific weight (kN/m3) 
-    
-    # Extract soil parameters from profile
-    z0, f_Su, _, f_gamma, _ = clay_profile(profile)
-
-    # Geometry
-    t = round(B/B_t, 2)
-    V_steel = round(B*L*t, 2)
-    zlug_B = zlug/B
-    
-    # Define 5 evaluation points along inclined width
-    N = 5
-    z_offsets = np.linspace(-0.5, 0.5, N)*B*np.sin(np.deg2rad(beta))
-    z_points = zlug + z_offsets; print(z_points)
-
-    # Evaluate Su and gamma at these points
-    Su_vals = [f_Su(z) for z in z_points]
-    gamma_10 = f_gamma(z_points[2]); print(gamma_10)
-    gamma_vals = [f_gamma(z) for z in z_points]; print("gamma_vals:", [f"{val:.2f}" for val in gamma_vals], "N/m3")
-    Su = np.mean(Su_vals); print(f"Su: {Su:.2f} Pa")
-    gamma = np.mean(gamma_vals); print(f"gamma: {gamma:.2f} N/m3")
-    
-    print("Profile being sent to clay_profile():")
-    for row in profile:
-        print(f"z = {row[0]:.2f} m, Su = {row[1]:.2f} kPa, gamma = {row[2]:.2f} kN/m³")
-
-    # Compute shear strength gradient k from linear fit
-    k = np.polyfit(z_points, Su_vals, 1)[0]
-    print(f"k: {k:.2f}")
-    
-    # Pile weight (inc. auxiliary elements) assessed as a factor
-    Wp = 1.35*V_steel*(rhows + rhow)
-
-    # Capacity factors
-    Nco_0_0  = 2.483*np.log(zlug_B) + 1.974
-    Nco_90_0 = 2.174*np.log(zlug_B) + 3.391
-    kBSh = k*B/Su
-    print(f"kBSh: {kBSh:.2f}")
-
-    f0  = np.where(zlug_B < 4, 1.77*(zlug_B**0.3) - 1.289, 0.192*zlug_B + 0.644)
-    f90 = np.where(zlug_B < 4, 0.68*(zlug_B**0.5) - 0.410, 0.153*zlug_B + 0.341)
-
-    S_kB_0  = 1 - f0*kBSh
-    S_kB_90 = 1 - f90*kBSh
-    Nco_0  = S_kB_0*Nco_0_0
-    Nco_90 = S_kB_90*Nco_90_0
-    Nco = Nco_0 + (Nco_90 - Nco_0)*(beta/90)**2
-
-    Nco_s_0_0  = np.where(2.90*zlug_B + 6.02 <= 11.59, 2.90*zlug_B + 6.02, 11.596)
-    Nco_s_90_0 = np.where(2.72*zlug_B + 4.02 <= 11.59, 2.72*zlug_B + 4.02, 11.596)
-
-    S_s_kB_0 = np.where(zlug_B <= 2, 1 + (0.8 - 0.3*zlug_B)*kBSh - (0.383*kBSh**1.36), 1)
-    f90s = np.where(zlug_B <= 3, 0.267*zlug_B, 0.6)
-    S_s_kB_90 = 1 - f90s*kBSh
-    Nco_s_0 = S_s_kB_0*Nco_s_0_0
-    Nco_s_90 = S_s_kB_90*Nco_s_90_0
-    Nco_s = Nco_s_90 + (Nco_s_0 - Nco_s_90)*((90 - beta)/90)**2
-
-    # Existing capacity factor and base pressure
-    Nc_final = max(Nco + (gamma*zlug)/Su, Nco_s) # anchor pullout capacity factor [kN]
-    print(f"Nc_star: {Nco + (gamma*zlug)/Su:.2f}")
-    print(f"Nc_star: {Nco_s:.2f}")
-    qu = Nc_final*Su                   # Bearing pressure capacity of the anchor plate
-    Tmax = round(qu*(1 - Los)*B*L, 2)  # Bearing tension force capacity of the anchor plate
-    Hmax = Tmax*np.cos(np.deg2rad(90 - beta))
-    Vmax = Tmax*np.sin(np.deg2rad(90 - beta))
-    
-    Ta = np.sqrt(Ha**2 + Va**2)
-    UC = Ta/Tmax
-
-    resultsPlate = {
-        'Capacity': Tmax,
-        'Horizontal max.': Hmax,
-        'Vertical max.': Vmax,
-        'Unity check': UC,
-        'Weight plate': Wp
-    }
-    
-    return resultsPlate
-
-if __name__ == '__main__':
-    
-    profile_clay = np.array([
-        [ 0.0, 10, 8.0],
-        [ 9.5, 25, 8.5],
-        [11.5, 45, 8.5],
-        [25.0, 50, 9.0]
-    ])
-    
-    B = 2.0                                 # Plate width (m)
-    L = 2.0                                 # Plate length (m)
-    zlug = 10.0                             # Padeye depth (m)
-    Ha = 350e3                              # Horizontal load (N)
-    Va = 400e3                              # Vertical load (N)
-    alpha = np.rad2deg(np.arctan2(Va, Ha))  # Load angle from horizontal (deg)
-    beta = 90 - alpha                       # Plate angle after keying (m)
-    
-    results = getCapacityPlate(profile_clay, 'clay', B, L, zlug, beta, Ha, Va)
-    print("\n--- Plate Anchor Capacity Results ---")
-    for key, val in results.items():
-        print(f"{key}: {val:.2f}")
-        
-    # plot_plate(profile_clay, 'clay', B, L, zlug, beta, title='Inclined Plate Anchor in Clay')
-    
diff --git a/famodel/anchors/anchors_famodel_profile/capacity_plots.py b/famodel/anchors/anchors_famodel_profile/capacity_plots.py
deleted file mode 100644
index fb096f3e..00000000
--- a/famodel/anchors/anchors_famodel_profile/capacity_plots.py
+++ /dev/null
@@ -1,435 +0,0 @@
-
-import numpy as np
-import matplotlib.pyplot as plt
-
-def plot_pile(profile, soil_type, y, z, D, L, z0=None, zlug=None, hinge_location=None):
-    '''Plots the deflected shape of the pile alongside the original vertical line.
-
-    Parameters:
-    ----------
-    profile :
-        
-    soil_type : str
-        
-    y : np.array
-        Lateral displacements (m)
-    z : np.array
-        Depths from pile head (m)
-    D : float
-        Pile diameter (m)
-    L : float
-        Pile length (m)
-    z0 : float, optional
-        Depth of the mudline from the pile head (m)
-    zlug : float, optional
-        Depth of the padeye from the pile head (m)
-    hinge_location : int, optional
-        Node index where a plastic hinge formed (if any)
-    label : str
-        Label for deflected shape line
-    color : str
-        Line color for deflected shape
-    '''
-    fig, ax = plt.subplots(figsize=(3, 5))
-    
-    lambdap = L / D
-
-    # Adjust horizontal scale based on slenderness
-    if lambdap >= 4:
-        xmax = 5*D     # Slender (e.g., driven pile)
-    elif lambdap <= 2:
-        xmax = 2*D     # Stubby (e.g., drilled & grouted)
-    else:
-        xmax = 3*D     # Intermediate case
-
-    # Mudline marker 
-    if z0 is not None:
-        ax.axhline(z0, color='blue', linestyle='--', label=f'Mudline (z0 = {z0:.2f} m)')
-        #ax.fill_betweenx(z, -0.05 * D, 0.05 * D, where=(z >= z0), color='lightgray', alpha=0.3, label='Soil zone')
-
-    # Padeye marker (on right wall of pile)
-    if zlug is not None:
-        ax.plot(D/2, zlug, 'ko', label=f'Padeye (zlug = {zlug:.2f} m)')
-
-    # Draw pile as rectangle (from head to tip)
-    pile = plt.Rectangle((-D/2, 0), D, L, edgecolor='k', facecolor='none', lw=2, label='Driven Pile')
-    ax.add_patch(pile)
-       
-    seen_labels = set()
-    # Plot soil layers as background fills
-    for i in range(len(profile) - 1):
-        z_top = profile[i][0]
-        z_bot = profile[i+1][0]
-        if soil_type == 'clay':
-            Su = profile[i][1]
-            color = plt.cm.Oranges(Su/np.max(profile[:, 1]))
-            label = f'Su = {Su:.0f} kPa'
-        elif soil_type == 'sand':
-            phi = profile[i][1]
-            gamma = profile[i][2]
-            color = plt.cm.YlOrBr(phi/np.max(profile[:, 1]))
-            label = f'ϕ = {phi:.0f}°, γ = {gamma:.1f} kN/m³'
-        elif soil_type == 'rock':
-            UCS = profile[i][1]
-            Em = profile[i][2]
-            color = plt.cm.Greys(UCS/np.max(profile[:, 1]))
-            label = f'UCS = {UCS:.2f} MPa, Em = {Em:.1f} MPa'
-            
-        # Only assign label if not already used
-        if label not in seen_labels:
-            ax.axhspan(z_bot, z_top, color=color, alpha=0.4, label=label)
-            seen_labels.add(label)
-        else:
-            ax.axhspan(z_bot, z_top, color=color, alpha=0.4)
-
-    ax.set_xlabel('Lateral displacement (m)')
-    ax.set_ylabel('Depth (m)')
-    ax.set_xlim(-xmax, xmax)
-    ax.set_ylim([L + 5, -2])  # Downward is positive z
-    ax.grid(ls='--')
-    ax.legend()
-    ax.set_title('Pile Deflection Profile')
-    plt.tight_layout()
-    plt.show()
-    
-    
-def plot_suction(profile, soil_type, L, D, zlug=None, title='Suction Pile and Soil Layers', ax=None):
-    '''Plot the soil profile and a suction pile geometry using array structure for profile.
-
-    Parameters:
-    ----------
-        profile : list or ndarray of lists (z, Su or phi or UCS, gamma)
-        soil_type : str
-            'clay', 'sand', or 'rock'
-        L : float
-            Embedded length (m)
-        D : float
-            Pile diameter (m)
-        zlug : float
-            Padeye depth (m, referenced to pile head = 0)
-        title : string
-            Plot title
-    '''
-    import numpy as np
-    import matplotlib.pyplot as plt
-
-    profile = np.array(profile)
-    if ax is None:
-        fig, ax = plt.subplots(figsize=(5, 5))
-    xmax = 2*D
-
-    # Split numerical values from profile
-    z_vals = [float(row[0]) for row in profile]
-    values = [float(row[1]) for row in profile]
-    
-    seen_labels = set()
-    # Plot soil layers as background fills
-    for i in range(len(z_vals) - 1):
-        z_top = z_vals[i]
-        z_bot = z_vals[i+1]
-        val = values[i]
-
-        if soil_type == 'clay':
-            color = plt.cm.Oranges(val / max(values))
-            label = f'Su = {val:.0f} kPa'
-        elif soil_type == 'sand':
-            color = plt.cm.YlOrBr(val / max(values))
-            label = f'ϕ = {val:.0f}°'
-
-        if label not in seen_labels:
-            ax.axhspan(z_bot, z_top, color=color, alpha=0.4, label=label)
-            seen_labels.add(label)
-        else:
-            ax.axhspan(z_bot, z_top, color=color, alpha=0.4)
-
-    # Draw pile geometry
-    x_left = -D/2; x_right = D/2
-    z_top = 0; z_bot = L
-    ax.plot([x_left,  x_left], [z_top, z_bot], color='k', lw=2.0, label='Suction Pile')
-    ax.plot([x_right, x_right], [z_top, z_bot], color='k', lw=2.0)
-    ax.plot([x_left, x_right], [z_top, z_top], color='k', lw=2.0)
-
-    # Reference lines
-    ax.axhline(z_vals[0], color='k', linestyle='--', lw=1.5, label='Mudline')
-    ax.axhline(L, color='b', linestyle='--', lw=1.5, label='Pile Tip')
-
-    # Padeye marker
-    if zlug is not None and 0 <= zlug <= L:
-        ax.plot(x_right, zlug, 'ko', label=f'Padeye (zlug = {zlug:.2f} m)')
-
-    ax.set_xlabel('Horizontal extent (m)')
-    ax.set_ylabel('Depth (m)')
-    ax.set_xlim(-xmax, xmax)
-    ax.set_ylim(L + 2*D, -D)
-    ax.set_title(title)
-    ax.grid()
-    ax.legend()
-    plt.tight_layout()
-    plt.show()
-
-
-def plot_torpedo(profile, soil_type, D1, D2, L1, L2, zlug, title='Torpedo Pile and Soil Layers'):
-    '''Plot the soil layers and geometry of a torpedo pile using absolute depth for soil and pile head at z=0.
-
-    Parameters:
-    ----------
-        profile : 
-            list or array of (z, Su, 'clay')
-        soil_type : str
-            'clay'
-        D1 : float 
-            Wing diameter (at tip) (m)
-        D2 : float
-            Shaft diameter (at head)
-        L1 : float
-            Winged length (m)
-        L2 : float
-            Shaft length (m)
-        title : str
-            Plot title
-    '''
-    fig, ax = plt.subplots(figsize=(7, 7))
-    
-    xmax = 5*max(D1, D2)
-    z1 = zlug + L1            # interface between L1 and L2
-    z_tip = z1 + L2           # pile tip
-
-    # Split numerical values from profile
-    z_vals = [float(row[0]) for row in profile]
-    values = [float(row[1]) for row in profile]
-
-    seen_labels = set()
-    # Plot soil layers as background fills
-    for i in range(len(z_vals) - 1):
-        z_top = z_vals[i]
-        z_bot = z_vals[i+1]
-        val = values[i]
-
-        if soil_type == 'clay':
-            color = plt.cm.Oranges(val/max(values))
-            label = f'Su = {val:.0f} kPa'
-
-        # Only assign label if not already used
-        if label not in seen_labels:
-            ax.axhspan(z_bot, z_top, color=color, alpha=0.4, label=label)
-            seen_labels.add(label)
-        else:
-            ax.axhspan(z_bot, z_top, color=color, alpha=0.4)
-        
-    # Draw winged section (upper)
-    ax.add_patch(plt.Rectangle((-D1/2, zlug), D1, L1, edgecolor='k', facecolor='none', lw=2, label='Winged Section'))
-
-    # Draw shaft section (lower)
-    ax.add_patch(plt.Rectangle((-D2/2, z1), D2, L2, edgecolor='k', facecolor='none', lw=2, label='Shaft Section'))
-   
-    # Reference lines
-    ax.axhline(z_vals[0], color='k', linestyle='--', lw=1.0, label='Mudline')
-    ax.axhline(    z_tip, color='b', linestyle='--', lw=1.0, label='Pile Tip')
-    
-    # Padeye marker
-    if zlug is not None:
-        ax.plot(0, zlug, 'ko', label=f'Padeye (zlug = {zlug:.2f} m)')
-
-
-    ax.set_xlim(-xmax, xmax)
-    ax.set_ylim(max(z_vals) + 0.5*D1, min(zlug - 2*D1, z_vals[0] - 2))
-    ax.set_xlabel('Horizontal extent (m)')
-    ax.set_ylabel('Depth (m)')
-    ax.set_title(title)
-    ax.grid()
-    ax.legend()
-    plt.tight_layout()
-    plt.show()
- 
-def plot_helical(profile, soil_type, D, L, d, zlug, n_helix=1, spacing=1.0, title='Helical Pile and Soil Layers'):
-    '''Plot a helical pile in layered soil, with the pile starting at zlug and the helix near the pile tip.
-
-    Parameters:
-    ----------
-        profile : list or array of (z, Su or phi, ...)
-        soil_type : 
-            'clay' or 'sand'
-        D : float
-            Helix diameter (m)
-        L : float
-            Pile length (m)
-        d : float
-            Shaft diameter (m)
-        zlug : float
-            Embedment depth of pile head (m)
-        n_helix : int 
-            Number of helices (-)
-        spacing : float
-            Vertical spacing between helices (m)
-        title : str
-            Plot title
-    '''
-    fig, ax = plt.subplots(figsize=(5, 5))
-    
-    xmax = 3*max(D, d)
-
-    # Extract soil data
-    z_vals = [float(row[0]) for row in profile]
-    values = [float(row[1]) for row in profile]
-
-    seen_labels = set()
-    # Plot soil layers as background fills
-    for i in range(len(z_vals) - 1):
-        z_top = z_vals[i]
-        z_bot = z_vals[i+1]
-        val = values[i]
-        
-        if soil_type == 'clay':
-            color = plt.cm.Oranges(val/max(values))
-            label = f'Su = {val:.0f} kPa' 
-        elif soil_type == 'sand':
-            color = plt.cm.YlOrBr(val / max(values))
-            label = f'ϕ = {val:.0f}°' 
-
-        # Only assign label if not already used
-        if label not in seen_labels:
-            ax.axhspan(z_bot, z_top, color=color, alpha=0.4, label=label)
-            seen_labels.add(label)
-        else:
-            ax.axhspan(z_bot, z_top, color=color, alpha=0.4)
-
-    # Draw shaft
-    ax.add_patch(plt.Rectangle((-d/2, 0), d, L, edgecolor='k', facecolor='none', lw=2, label='Shaft'))
-
-    # Draw helices
-    z_helix_base = L - D  # Base helix depth
-    for i in range(n_helix):
-        z_helix = z_helix_base - i*spacing
-        if z_helix < zlug:
-            break
-        ax.plot([-D/2, D/2], [z_helix - d/2, z_helix + d/2], color='k', lw=2, label='Helix' if i == 0 else None)
-
-    # Reference lines
-    ax.axhline(z_vals[0], color='k', linestyle='--', lw=1.0, label='Mudline')
-    ax.axhline(        L, color='b', linestyle='--', lw=1.0, label='Pile Tip')
-    
-    # Padeye marker
-    if zlug is not None:
-        ax.plot(d/2, zlug, 'ko', label=f'Padeye (zlug = {zlug:.2f} m)')
-
-    ax.set_xlim(-xmax, xmax)
-    ax.set_ylim(max(z_vals), min(zlug - 0.5*d, z_vals[0] - 2))
-    ax.set_xlabel('Horizontal extent (m)')
-    ax.set_ylabel('Depth (m)')
-    ax.set_title(title)
-    ax.grid()
-    ax.legend()
-    plt.tight_layout()
-    plt.show()
-
-def plot_plate(profile, B, L, zlug, beta, title='Plate Anchor in Clay Profile'):
-    '''Plot soil layers and an inclined plate anchor centered at zlug.
-
-    Parameters:
-    ----------
-        profile : ndarray of shape (n, 3), with (depth, Su, gamma)
-        B : float
-            Plate width (m)
-        L : float
-            Plate length (m) 
-        zlug : float
-            Center embedment of the plate (m)
-        beta : float
-            Inclination angle of plate (deg)
-        title : str
-            Plot title
-    '''
-    fig, ax = plt.subplots(figsize=(5, 5))
-    
-    xmax = 3*B
-
-    # Extract soil data
-    layer_depths = profile[:, 0]
-    layer_depths = np.append(layer_depths, [profile[0][-1]])    
-
-    # Inclined plate geometry
-    dx = (B/2)*np.cos(np.deg2rad(beta))
-    dz = (B/2)*np.sin(np.deg2rad(beta))
-    plate_x = [-dx, dx]
-    plate_z = [zlug - dz, zlug + dz]
-
-    seen_labels = set()
-    # Plot soil layers as background fills
-    for i in range(len(layer_depths) - 1):
-        z_top = layer_depths[i]
-        z_bot = layer_depths[i+1]
-        Su = profile[i][1]
-        color = plt.cm.Oranges(Su/np.max(profile[:, 1]))
-        label = f'Su = {Su:.0f} kPa'
-        
-        # Only assign label if not already used
-        if label not in seen_labels:
-            ax.axhspan(z_bot, z_top, color=color, alpha=0.4, label=label)
-            seen_labels.add(label)
-        else:
-            ax.axhspan(z_bot, z_top, color=color, alpha=0.4)
-
-    # Plot inclined plate
-    ax.plot(plate_x, plate_z, color='k', lw=1.5, label='Plate')
-
-    # Reference lines
-    ax.axhline(0, color='k', linestyle='--', lw=1.0, label='Mudline')
-    
-    # Padeye marker
-    if zlug is not None:
-        ax.plot(0, zlug, 'ko', label=f'Padeye (zlug = {zlug:.2f} m)')
-
-    ax.set_xlim(-xmax, xmax)
-    ax.set_ylim(25, -1)  
-    ax.set_xlabel("Horizontal extent (m)")
-    ax.set_ylabel("Depth (m)")
-    ax.set_title(title)
-    ax.legend(loc='lower right')
-    ax.grid(True)
-    plt.tight_layout()
-    plt.show()
-    
-def plot_load(profile, soil_type, drag_values, depth_values, Tm, thetam, Ta, thetaa, zlug):
-
-        fig, ax = plt.subplots(figsize=(12, 6))
-        n = 2e6
-
-        # Plot the inverse catenary profile
-        ax.plot(drag_values, depth_values, color='b', label='Mooring line')
-
-        # Add load vectors
-        ax.arrow(0, -profile[0][0], Tm*np.cos(np.deg2rad(thetam))/n, Tm*np.sin(np.deg2rad(thetam))/n,
-                 head_width=0.25, head_length=0.5, color='r', label='Mudline Load')
-        ax.arrow(drag_values[-1], depth_values[-1], Ta*np.cos(thetaa)/n, Ta*np.sin(thetaa)/n,
-                 head_width=0.25, head_length=0.5, color='g', label='Padeye Load')
-        
-        #ax.set_aspect('equal', adjustable='datalim')
-
-        # Plot soil layers as background fills
-        for i in range(len(profile) - 1):
-            z_top = -profile[i][0]
-            z_bot = -profile[i+1][0]
-            if soil_type == 'clay':
-                Su = profile[i][1]
-                gamma = profile[i][2]
-                color = plt.cm.Oranges(Su/np.max(profile[:, 1]))
-                label = f'Su = {Su:.0f} kPa'
-            elif soil_type == 'sand':
-                phi = profile[i][1]
-                gamma = profile[i][2]
-                color = plt.cm.YlOrRd(phi/np.max(profile[:, 1]))
-                label = f'ϕ = {phi:.0f}°, γ = {gamma:.1f} kN/m³'
-            ax.axhspan(z_bot, z_top, color=color, alpha=0.4, label=label)
-
-        # Deduplicate legend entries
-        handles, labels = ax.get_legend_handles_labels()
-        unique = dict(zip(labels, handles))
-        ax.legend(unique.values(), unique.keys(), loc='lower left')
-
-        ax.set_xlabel('Drag distance [m]')
-        ax.set_ylabel('Embedded depth [m]')
-        ax.set_title('Inverse Catenary in Layered Soil')
-        ax.grid(True)
-        
-        ax.annotate(f"{Tm/1e6:.2f} MN", (Tm*np.cos(np.deg2rad(thetam))/n, -profile[0][0] + Tm*np.sin(np.deg2rad(thetam))/n), color='r')
-        ax.annotate(f"{Ta/1e6:.2f} MN", (drag_values[-1] + Ta*np.cos(thetaa)/n, depth_values[-1] + Ta*np.sin(thetaa)/n), color='g')
diff --git a/famodel/anchors/anchors_famodel_profile/capacity_pycurves.py b/famodel/anchors/anchors_famodel_profile/capacity_pycurves.py
deleted file mode 100644
index 67eb67f8..00000000
--- a/famodel/anchors/anchors_famodel_profile/capacity_pycurves.py
+++ /dev/null
@@ -1,298 +0,0 @@
-
-import numpy as np
-import matplotlib.pyplot as plt
-from scipy.interpolate import interp1d
-
-def py_Matlock(z, D, zlug, f_Su, f_sigma_v_eff, f_gamma, z0=None, plot=True):
-    ''' Generate Matlock (1970) p–y curve at a given depth in clay.
-
-    Parameters
-    ----------
-    z : float
-        Depth relative to pile head (m)
-    D : float
-        Pile diameter (m)
-    zlug : float
-        Load eccentricity above or below mudline (m)
-    f_Su : function
-        Undrained shear strength (Pa)
-    f_sigma_v_eff : function
-        Effective vertical stress (Pa)
-    f_gamma : function
-        Effective unit weight (kN/m³)
-    z0 : float, optional
-        Mudline depth (m). If provided, disables resistance above this level
-    plot : bool
-        Plot the resulting p–y curve if True
-
-    Returns
-    -------
-    f : interp1d
-        Interpolation function for p–y relationship (N/m vs m)
-    '''
-    
-    Su = f_Su(z)
-    sigma_v_eff = f_sigma_v_eff(z)
-    gamma = f_gamma(z)
-   
-    # Strain at half the strength as defined by Matlock (1970). 
-    # Typically ranges from 0.005 (stiff clay) to 0.02 (soft clay).
-    epsilon_50 = 0.02          
-    J = 0.5
-    
-    # No soil resistance above mudline
-    if z0 is not None and z < z0:
-        return lambda y_val: np.zeros_like(y_val)
-
-    # Calculate ultimate resistance and shape parameters
-    Nc = 3.0 + sigma_v_eff/Su + J*z/D
-    Nc = min(Nc, 9.0)
-    z_cr = 6.0 *D/(gamma*D/Su + J)
-
-    p_ult = Su * Nc * D
-    y_50 = 2.5 * epsilon_50 * D
-
-    # Normalized lateral displacements
-    Y = np.concatenate((-np.logspace(3, -4, 100), [0], np.logspace(-4, 3, 100)))
-    P = 0.5 * np.sign(Y)*np.abs(Y)**(1.0/3.0)
-    P = np.clip(P, -1.0, 1.0)
-
-    # Un-normallized p-y curves
-    y = Y*y_50
-    p = P*p_ult
-    
-    f = interp1d(y, p, kind='linear', bounds_error=False, fill_value=0.0)   # Interpolation function for p-y curve
-
-    # Plot of p-y curve and check if 'k' is calculated correctly
-    if plot:
-        plt.plot(y, p,'-')
-        plt.xlabel('y (m)') 
-        plt.ylabel('p (N/m)')
-        plt.title('PY Curves - Matlock (1970)')
-        plt.grid(True)
-        plt.xlim([-2*D, 2*D])
-
-    return f  
-       
-def py_API(z, D, zlug, f_phi, f_sigma_v_eff, f_Dr, z0=None, plot=True):   
-    ''' Generate API RP2A (1993) p–y curve at a given depth in sand.
-
-    Parameters
-    ----------
-    z : float
-        Depth relative to pile head (m)
-    D : float
-        Pile diameter (m)
-    zlug : float
-        Load eccentricity above or below mudline (m)
-    f_phi : function
-        Friction angle (deg)
-    f_sigma_v_eff : function
-        Effective vertical stress (Pa)
-    f_Dr : function
-        Relative density (-)
-    z0 : float, optional
-        Mudline depth (m). If provided, disables resistance above this level
-    plot : bool
-        Plot the resulting p–y curve if True
-
-    Returns
-    -------
-    f : interp1d
-        Interpolation function for p–y relationship (N/m vs m)
-    '''
-    
-    phi = f_phi(z)
-    sigma_v_eff = f_sigma_v_eff(z)
-    Dr = f_Dr(z)
-         
-    # Interpolate coefficients depending on the effective friction angle
-    phi_ref = [  20,   25,   30,   35,   40]
-    C1_ref  = [0.80, 1.25, 1.90, 3.00, 4.50]
-    C2_ref  = [1.60, 2.10, 2.60, 3.40, 4.30]
-    C3_ref  = [  10,   15,   30,   55,  105]
-    
-    C1 = np.interp(phi, phi_ref, C1_ref)
-    C2 = np.interp(phi, phi_ref, C2_ref)
-    C3 = np.interp(phi, phi_ref, C3_ref)
-    
-    # Disable p–y curve above mudline
-    if z0 is not None and z < z0:
-        return lambda y_val: np.zeros_like(y_val)
-    
-    # Compute ultimate lateral resistance
-    p_ult = min(C1*z + C2*D, C3*D) * sigma_v_eff
-    
-    # Compute initial stiffness k (kN/m3 → N/m3)
-    k = (54.6*Dr**2 + 0.8*Dr + 1.8)*1e3
-    
-    # Normalized displacement range
-    N = 20
-    y = np.concatenate((-np.logspace(3, -4, N), [0], np.logspace(-4, 3, N)))
-    
-    # Shape coefficient A
-    A = max(3 - 0.8*z/D, 0.9)
-    
-    # Apply API p–y formulation
-    ε = 1e-6  # prevent division by zero
-    p = A * p_ult * np.tanh(k*z*y/(A*p_ult + ε))
-    
-    f = interp1d(y, p, kind='linear', bounds_error=False, fill_value=0.0)
-    
-    if plot:
-        # Plot of p-y curve and check if 'k' is calculated correctly
-        plt.plot(y, p,'-') 
-        plt.xlabel('y (m)') 
-        plt.ylabel('p (N/m)')
-        plt.title('PY Curves - API (1993)')
-        plt.grid(True)
-        plt.xlim([-0.10*D, 0.10*D])
-        
-    return f  
-
-def py_Reese(z, D, zlug, f_UCS, f_Em, z0=None, plot=True):
-    ''' Generate Reese (1997) p–y curve at a given depth in weak rock.
-
-    Parameters
-    ----------
-    z : float
-        Depth relative to pile head (m)
-    D : float
-        Pile diameter (m)
-    zlug : float
-        Load eccentricity above or below mudline (m)
-    f_UCS : function
-        Unconfined compressive strength UCS(z) (Pa)
-    f_Em : function
-        Young's modulus Em(z) (Pa)
-    z0 : float, optional
-        Mudline depth (m). If provided, disables resistance above this level
-    plot : bool
-        Plot the resulting p–y curve if True
-
-    Returns
-    -------
-    f : interp1d
-        Interpolation function for p–y relationship (N/m vs m)
-    '''
-    
-    UCS = f_UCS(z)
-    Em = f_Em(z)
-  
-    RQD = 52                     # Assumed fair rock quality (moderately weathered rocks) 
-    Dref = 0.305; nhu = 0.3; E = 200e9
-    t = (6.35 + D*20)/1e3        # Pile wall thickness (m), API RP2A-WSD
-    I  = np.pi*(D**4 - (D - 2*t)**4)/64.0
-    EI = E*I
-    alpha = -0.00667*RQD + 1
-    krm = 0.0005
-
-    if z < z0:
-        # Above mudline, no resistance
-        p_ur = 0
-    else:
-        if z < 3*D:
-            p_ur = alpha*UCS*D*(1 + 1.4*z/D)
-            #kir = (100 +400*z/(3*D))
-        else:
-            p_ur = 5.2*alpha*UCS*D
-            #kir = 500
-        
-    kir = (D/Dref)*2**(-2*nhu)*(EI/(Em*D**4))**0.284
-    Kir = kir*Em     
-    y_rm = krm*D
-    y_a = (p_ur/(2*y_rm**0.25*Kir))**1.333    
-   
-    # Normalized lateral displacement
-    N = 20
-    y = np.concatenate((-np.logspace(4,-3,N),[0],np.logspace(-3,4,N)))
-    
-    p = []
-    for val in y:
-        if abs(val) < y_a:
-            p_val = np.sign(val) * Kir * val
-        else:
-            p_val = np.sign(val)*min((p_ur/2)*(abs(val)/y_rm)**0.25, p_ur)
-        p.append(p_val)                                  
-    
-    f = interp1d(y, p, kind='linear', bounds_error=False, fill_value=0.0)
-    
-    if plot:    
-        plt.plot(y, p) 
-        plt.xlabel('y (m)') 
-        plt.ylabel('p (N/m)'),
-        plt.title('PY Curves - Reese (1997)')
-        plt.grid(True)
-        plt.xlim([-0.03*D, 0.03*D])
-        #plt.ylim([min(p), max(p)])      
-        
-    return f      
-
-def py_Lovera(z, D, f_UCS, f_Em, zlug, z0, plot=True):
-    ''' Generate Lovera (2019) p–y curve at a given depth for layered rock interfaces.
-
-    Parameters
-    ----------
-    z : float
-        Depth relative to pile head (m)
-    D : float
-        Pile diameter (m)
-    f_UCS : function
-        Unconfined compressive strength UCS(z) (Pa)
-    f_Em : function
-        Young's modulus Em(z) (Pa)
-    zlug : float
-        Load eccentricity (m)
-    z0 : float
-        Mudline depth (m). If provided, disables resistance above this level
-    delta_grout : float, optional
-        Grout annulus thickness (m) (default value: delta_grout=0.075)
-    E_grout : float, optional
-        Grout elastic modulus (Pa) (default value: E_grout=20e9)
-    delta_crushed : float, optional
-        Crushed rock annulus thickness (m) (default value: delta_crushed=0.025)
-    plot : bool
-        Plot the resulting p–y curve if True
-
-    Returns
-    -------
-    f : interp1d
-        Interpolation function for p–y relationship (N/m vs m)
-    '''
-     
-    # Default values
-    delta_grout = 0.075
-    E_grout = 20e9
-    delta_crushed = 0.025
- 
-    if z < z0:
-        return lambda y: np.zeros_like(y)
-
-    # Retrieve elastic modulus at depth
-    Em = f_Em(z)
-    nu = 0.3  # Typical Poisson's ratio for rock
-    G_rock = Em/(2*(1 + nu))
-    k_rock = 4*G_rock
-    
-    # Set E_crushed as 25% of intact rock modulus if not given
-    E_crushed = 0.25*Em
-
-    # Compute total stiffness from linear components
-    k_eq = 1.0/(0.4*delta_grout/E_grout + delta_crushed/E_crushed + 1.0/k_rock)
-
-    y = np.linspace(-0.03*D, 0.03*D, 200)
-    p = k_eq*y
-    f = interp1d(y, p, fill_value="extrapolate")
-
-    if plot:
-        plt.plot(y, p, '-')
-        plt.xlabel('y (m)')
-        plt.ylabel('p (N/m)')
-        plt.title('PY Curves - Lovera (2019)')
-        plt.grid(True)
-        plt.xlim([-0.1*D, 0.1*D])
-        plt.ylim([min(p), max(p)]) 
-        plt.show()
-
-    return f
-
diff --git a/famodel/anchors/anchors_famodel_profile/capacity_soils.py b/famodel/anchors/anchors_famodel_profile/capacity_soils.py
deleted file mode 100644
index 93d4ae19..00000000
--- a/famodel/anchors/anchors_famodel_profile/capacity_soils.py
+++ /dev/null
@@ -1,176 +0,0 @@
-
-import numpy as np
-from scipy.interpolate import interp1d
-
-def clay_profile(profile):
-    ''' Create interpolated functions for a clay soil profile.
-    Calculates Su, effective vertical stress, unit weight and adhesion factor.
-    
-    Parameters
-    ----------
-    profile : array
-        Clay profile as 2D array: (z, Su, gamma)
-        Depth (m), undrained shear strength Su (kPa) and effective unit weight gamma (kN/m³)
-    
-    Returns
-    -------
-    z0 : float
-        Depth of mudline relative to pile head (m)
-    f_Su : interp1d
-        Undrained shear strength, Su(z) (Pa)
-    f_sigma_v_eff : interp1d
-        Effective vertical stress, σ'v(z) (Pa)
-    f_gamma : interp1d
-        Effective unit weight of the soil, γ'(z) (N/m³)
-    f_alpha : function
-        Adhesion factor from API correlation, α (-)
-    '''
-
-    # Depth of mudline relative to pile head
-    z0 = float(profile[0][0])
-
-    # Extract data from profile array and zero strength virtual soil layer
-    # from the pile head down to the mudline
-    depth = np.concatenate([np.array([z0]),np.array([row[0] for row in profile],dtype=float)]) # m
-    Su    = np.concatenate([np.array([0]), np.array([row[1] for row in profile],dtype=float)]) # kPa
-    gamma = np.concatenate([np.array([0]), np.array([row[2] for row in profile],dtype=float)]) # kN/m3
-
-    # Calculate sigma_v_eff at each depth
-    sigma_v_eff = np.zeros(len(depth))
-
-    for i in range(1, len(depth)):
-        sigma_v_eff[i] = sigma_v_eff[i-1] + gamma[i-1]*(depth[i] - depth[i-1])
-
-    # Define interpolation functions
-    f_Su          = interp1d(depth, Su*1e3, kind='linear')           # Pa
-    f_sigma_v_eff = interp1d(depth, sigma_v_eff*1e3, kind='linear')  # Pa
-    f_gamma       = interp1d(depth, gamma*1e3, kind='linear')        # N/m3
-    
-    # Calculate f_psi and f_alpha at each depth (not as a scalar)
-    f_psi = lambda z: f_Su(z)/np.maximum(f_sigma_v_eff(z), 1.0)  
-    
-    def calc_alpha(psi):
-        # Avoid divide-by-zero or log(0) by setting a floor
-        psi = np.maximum(psi, 1e-6)
-        if np.ndim(psi) == 0:
-            psi = float(psi)
-            # API-style adhesion factor: two regimes
-            return min(0.5*psi**-0.50, 1) if psi <= 1.0 else min(0.5*psi**-0.25, 1)
-        else:
-            return np.where(
-                psi <= 1.0,
-                np.minimum(0.5*psi**-0.50, 1),
-                np.minimum(0.5*psi**-0.25, 1)
-            )
-     
-    # Create an interpolated adhesion factor function
-    # Create an interpolated adhesion factor function
-    def f_alpha(z):
-        psi_val = f_psi(z)
-        alpha_val = calc_alpha(psi_val)
-        return np.atleast_1d(alpha_val)[0] if np.ndim(alpha_val) == 0 else alpha_val
-
-    return z0, f_Su, f_sigma_v_eff, f_gamma, f_alpha
-
-def sand_profile(profile):
-    ''' Create interpolated functions for a sand soil profile.
-    Calculates phi, effective stress, unit weight, relative density, and skin friction factor.
-
-    Parameters
-    ----------
-    profile : array
-        Sand profile as 2D array: (z, phi, gamma, Dr)
-        Depth (m), friction angle, phi (deg), effective unit weight, gamma (kN/m³) and relative density, Dr (%)
-
-    Returns
-    -------
-    z0 : float
-        Depth of mudline relative to pile head (m)
-    f_phi : interp1d
-        Friction angle, φ(z) (deg)
-    f_sigma_v_eff : interp1d
-        Effective vertical stress, σ'v(z) (Pa)
-    f_gamma : interp1d
-        Effective unit weight of the soil, γ'(z) (N/m³)
-    f_Dr : interp1d
-        Relative density, Dr(z) (-)
-    f_delta : interp1d
-        Skin friction factor, δ(z) (-)
-    '''
-
-    # Depth of mudline relative to pile head
-    z0 = float(profile[0][0])
-
-    # Extract data from profile array and zero strength virtual soil layer
-    # from the pile head down to the mudline
-    depth = np.concatenate([np.array([z0]),np.array([row[0] for row in profile],dtype=float)]) # m
-    phi   = np.concatenate([np.array([0]), np.array([row[1] for row in profile],dtype=float)]) # deg
-    gamma = np.concatenate([np.array([0]), np.array([row[2] for row in profile],dtype=float)]) # kN/m3
-    Dr    = np.concatenate([np.array([0]), np.array([row[3] for row in profile],dtype=float)]) # -
-   
-    # Calculate sigma_v_eff and static loading factor at each depth
-    sigma_v_eff = np.zeros(len(depth))
-
-    for i in range(1, len(depth)):  
-        sigma_v_eff[i] = sigma_v_eff[i-1] + gamma[i-1]*(depth[i] - depth[i-1])
-
-    # Define interpolation functions
-    f_phi         = interp1d(depth, phi, kind='linear')              # deg
-    f_sigma_v_eff = interp1d(depth, sigma_v_eff*1e3, kind='linear')  # Pa
-    f_gamma       = interp1d(depth, gamma*1e3, kind='linear')        # N/m3
-    f_Dr          = interp1d(depth, Dr, kind='linear')               # -
-    
-    # Define delta as a function of Dr
-    def calc_delta(Dr_val):
-        if 35 <= Dr_val < 50:
-            return 0.29
-        elif 50 <= Dr_val < 65:
-            return 0.37
-        elif 65 <= Dr_val < 85:
-            return 0.46
-        elif Dr_val >= 85:
-            return 0.56
-        else:
-            return 0  # Default or error value for very low Dr values
-        
-    # Apply delta calculation to Dr profile
-    delta_values = np.array([calc_delta(Dr_val) for Dr_val in Dr])
-    f_delta      = interp1d(depth, delta_values, kind='linear')  # Interpolated delta values
-    
-    return z0, f_phi, f_sigma_v_eff, f_gamma, f_Dr, f_delta
-    
-def rock_profile(profile):
-    ''' Create interpolated functions for a weak rock profile.
-    Calculates unconfined compressive strength (UCS) and Young’s modulus (Em).
-
-    Parameters
-    ----------
-    profile : array
-        Rock profile as 2D array: (z, UCS, Em)
-        Depth (m), unconfined compressive strength, UCS (MPa), Young's modulus, Em (MPa)
-
-    Returns
-    -------
-    z0 : float
-        Depth of rockline relative to pile head (m)
-    f_UCS : interp1d
-        Unconfined compressive strength, UCS(z) (Pa)
-    f_Em : interp1d
-        Young's modulus, Em(z) (Pa)
-    '''
-
-    # Depth of rockline relative to pile head
-    z0 = float(profile[0][0])
-
-    # Extract data from soil_profile array and zero strength virtual soil layer
-    # from the pile head down to the mudline
-    depth = np.concatenate([np.array([z0]),np.array([row[0] for row in profile],dtype=float)]) # m  
-    UCS   = np.concatenate([np.array([0]), np.array([row[1] for row in profile],dtype=float)]) # MPa
-    Em    = np.concatenate([np.array([0]), np.array([row[2] for row in profile],dtype=float)]) # MPa
-
-    # Define interpolation functions
-    f_UCS = interp1d(depth, UCS*1e6, kind='linear')  # Pa
-    f_Em  = interp1d(depth, Em*1e6, kind='linear')   # Pa
-    
-    return z0, f_UCS, f_Em
-
diff --git a/famodel/anchors/anchors_famodel_profile/capacity_suction.py b/famodel/anchors/anchors_famodel_profile/capacity_suction.py
deleted file mode 100644
index e322048a..00000000
--- a/famodel/anchors/anchors_famodel_profile/capacity_suction.py
+++ /dev/null
@@ -1,293 +0,0 @@
-   
-import numpy as np
-import matplotlib.pyplot as plt
-from scipy.optimize import fsolve
-from scipy.optimize import root_scalar
-from .capacity_soils import clay_profile, sand_profile
-from .capacity_plots import plot_suction
-
-def getCapacitySuction(profile, soil_type, D, L, zlug, Ha, Va, plot=True):    
-    '''Calculate the inclined load capacity of a suction pile in sand or clay following S. Kay methodology.
-    The calculation is based on the soil profile, anchor geometry and inclined load.  
-    
-    Parameters
-    ----------
-    profile : array
-        Soil profile as a 2D array: (z, parameters)
-            Clay soil profile (z (m), Su (kPa), gamma (kN/m³))
-            Sand soil profile (z (m), phi (deg), gamma (kN/m³), Dr (%))
-    soil_type : string
-        Select soil condition, 'clay' or 'sand'
-    D : float 
-        Suction pile diameter (m)
-    L : float 
-        Suction pile length from pile head (m)
-    zlug: float
-        Embedded depth of the main padeye (m)
-    thetalug: float
-        Angle of tilt misaligment (deg) (default value: 5.0)
-    psilug: float
-        Angle of twist misaligment (deg) (default value: 7.5)
-    Ha : float       
-        Horizontal load at pile lug elevation (N)
-    Va : float          
-        Vertical load at pile lug elevation (N)
-    plot : bool
-        Plot the capacity envelope if True
-                    
-    Returns
-    -------
-    Dictionary with capcity, weigths and UC.
-    ''' 
-    
-    z0 = profile[0][0]      
-    lambdap = (L - z0)/D; m = 2/3;   # Suction pile slenderness ratio
-    t = (6.35 + D*20)/1e3            # Suction pile wall thickness (m), API RP2A-WSD
-    rlug = D/2                       # Radial position of the lug
-    thetalug = 5                     # Angle of tilt misaligment, default is 5. (deg)
-    psilug = 7.5                     # Angle of twist misaligment, default is 7.5. (deg)
-    rhows = 66.90e3                  # Submerged steel specific weight (N/m3)
-    rhow = 10e3                      # Water specific weight (N/m3) 
-    
-    # Outer and inner surface of the pile skirt
-    def PileSurface(Len, Dia):
-        Sp = np.pi*Dia*Len
-        return Sp    
-    # Dry and wet mass of the pile    
-    def PileWeight(Len, Dia, tw, rho):
-        Wp = ((np.pi/4)*((Dia**2 - (Dia - 2*tw)**2)*Len + (np.pi/4)*Dia**2*tw))*rho
-        return Wp 
-    # Mass of the soil plug      
-    def SoilWeight(Len, Dia, tw, gamma_soil): 
-        Wsoil =(np.pi/4)*(Dia - 2*tw)**2*Len*gamma_soil
-        return Wsoil
-    # Tilt and twist effects due to installation misaligments
-    def rlugTilt(r, z, theta):
-        R = r*np.cos(np.deg2rad(theta)) - z*np.sin(np.deg2rad(theta))
-        return R   
-    def zlugTilt(r, z, theta):
-        Z = r*np.sin(np.deg2rad(theta)) + z*np.cos(np.deg2rad(theta))
-        return Z    
-    
-    if soil_type == 'clay':
-        z0, f_Su, f_sigma_v_eff, f_gamma, f_alpha = clay_profile(profile)
-        z_vals = np.linspace(z0, L, 10)
-
-        Su_vals = f_Su(z_vals)
-        ez = np.trapz(z_vals*Su_vals, z_vals)/np.trapz(Su_vals, z_vals); 
-        ez_soil = ez; print(f"ez_soil = {ez_soil:.2f} m")
-        gamma_vals = f_gamma(z_vals)
-
-        Su_av_L = f_Su(ez_soil)
-        Su_tip = f_Su(L); # print(f"Su_tip = {Su_tip:.2f} Pa")
-        sigma_v_eff = f_sigma_v_eff(ez_soil)
-        gamma_av = np.trapz(gamma_vals, z_vals)/(L - z0); # print(f"gamma_av = {gamma_av:.2f} kN/m³")
-        alpha_av = float(f_alpha(ez_soil))
-                
-        Nc = min(6.2*(1 + 0.34*np.arctan(lambdap)), 9)
-        Np_fixed = 10.25; Np_free = 4 
-        Hmax = Np_fixed*(L - z0)*D*Su_av_L; print(f'Su_av_L = {Su_av_L:.2f} Pa')
-        print(f'Hmax = {Hmax:.2f} N')
-        
-        M = -Va*rlugTilt(rlug, zlug, thetalug) - Ha*(zlugTilt(rlug, zlug, thetalug) - ez_soil)
-        # print(f"rlug_eff = {rlugTilt(rlug, zlug, thetalug):.2f} m")
-        # print(f"zlug_eff = {zlugTilt(rlug, zlug, thetalug):.2f} m")
-        print(f"M = {M:.2f} Nm")
-
-        # --- MH Ellipse Parameters for Clay (Kay 2014) ---
-        # ΔφMH (piecewise based on L/D)
-        if 0.5 <= lambdap < 1.125:
-            delta_phi = 0.32 + 4.32*lambdap; # print(delta_phi)
-        elif 1.125 <= lambdap < 2.0:
-            delta_phi = 7.13 - 1.71*lambdap; # print(delta_phi)
-        elif 2.0 <= lambdap <= 8.0:
-            delta_phi = 4.55 - 0.425*lambdap; # print(delta_phi)
-        else:
-            raise ValueError('L/D ratio out of bounds for MH ellipse formulation.')
-
-        phi_MH = -np.arctan(ez_soil/(L -z0)) - np.deg2rad(delta_phi)
-        a_MH = Np_fixed/np.cos(phi_MH)
-        delta_bMH = 0.45*(lambdap)**(-0.9) if lambdap <= 1.5 else 0
-        b_MH = -Np_free*np.sin(phi_MH) + delta_bMH
-        print('M cos(phi)/a_MH =', (M*np.cos(phi_MH))/a_MH)
-        print('M sin(phi)/b_MH =', (M*np.sin(phi_MH))/b_MH)
-
-        # Solve MH ellipse for Hmax
-        def f(Hmax):
-            term1 = ((M*np.cos(phi_MH) + Hmax*np.sin(phi_MH))/a_MH)**2
-            term2 = ((M*np.sin(phi_MH) - Hmax*np.cos(phi_MH))/b_MH)**2
-            return term1 + term2 - 1
-
-        try:
-            Hmax = max(fsolve(f, Hmax*0.8)[0], 0.0)
-        except:
-            Hmax = 0.0
-            
-        print(f'Hmax (MH ellipse) = {Hmax:.2f} N')
-
-        To = PileSurface((L - z0), D)*alpha_av*Su_av_L
-        Ti = PileSurface((L - z0), D - 2*t)*alpha_av*Su_av_L
-        Tbase = np.pi*D**3*Su_tip/12
-        Tmax = min(To + Ti, To + Tbase)
-
-        T = Ha*rlug*np.sin(np.deg2rad(psilug))
-        nhuT = T/Tmax
-        nhuV = Ha/To
-        nhuVstar = np.sqrt(nhuV**2 - nhuT**2)
-        alphastar = alpha_av*(nhuVstar/nhuV); print(f"alphastar   = {alphastar:.3f}")
-        
-        Vmax1 = PileWeight(L, D, t, rhows) + PileSurface((L - z0), D)*alphastar*Su_av_L + Nc*Su_tip*(np.pi/4)*D**2
-        Vmax2 = PileWeight(L, D, t, rhows) + PileSurface((L - z0), D)*alphastar*Su_av_L + PileSurface((L - z0), D - 2*t)*alphastar*Su_av_L
-        Vmax3 = PileWeight(L, D, t, rhows) + PileSurface((L - z0), D)*alphastar*Su_av_L + SoilWeight((L - z0), D, t, gamma_av)
-        Vmax = min(Vmax1, Vmax2, Vmax3)
-        
-        print(f"Vmax1    = {Vmax1:.2f} N"); print(f"Vmax2    = {Vmax2:.2f} N"); print(f"Vmax3    = {Vmax3:.2f} N")
-        
-
-    elif soil_type == 'sand':
-        z0, f_phi, f_sigma_v_eff, f_gamma, f_Dr, f_delta = sand_profile(profile)
-        z_vals = np.linspace(z0, L, 10)
-
-        sigma_v_vals = f_sigma_v_eff(z_vals)
-        ez = np.trapz(z_vals*sigma_v_vals, z_vals) / np.trapz(sigma_v_vals, z_vals)
-        ez_soil = ez - z0        
-
-        phi_vals = f_phi(z_vals)
-        gamma_vals = f_gamma(z_vals)
-        sigma_v_vals = f_sigma_v_eff(z_vals)
-        Dr_vals = f_Dr(z_vals)
-        delta_vals = f_delta(z_vals)
-
-        phi_av = np.trapz(phi_vals, z_vals)/(L - z0)
-        gamma_av = np.trapz(gamma_vals, z_vals)/(L - z0)
-        delta_av = np.trapz(delta_vals, z_vals)/(L - z0)
-        sigma_av_L = np.trapz(sigma_v_vals, z_vals)/(L - z0)
-        sigma_tip = f_sigma_v_eff(L)
-
-        Nq = np.e**(np.pi*np.tan(np.radians(phi_av)))*(np.tan(np.radians(45) + np.radians(phi_av)/2))**2
-        Hmax = 0.5*D*Nq*gamma_av*(L - z0)**2
-        Np_free = 3.0  
-
-        M = -Va*rlugTilt(rlug, zlug, thetalug) - Ha*(zlugTilt(rlug, zlug, thetalug) - ez_soil)
-
-        # --- MH Ellipse Parameters for Clay (Kay 2014) ---
-        # ΔφMH (piecewise based on L/D)
-        if 0.5 <= lambdap < 1.125:
-            delta_phi = 0.32 + 4.32*lambdap
-        elif 1.125 <= lambdap < 2.0:
-            delta_phi = 7.13 - 1.71*lambdap
-        elif 2.0 <= lambdap <= 6.0:
-            delta_phi = 4.55 - 0.425*lambdap
-        else:
-            raise ValueError('L/D ratio out of bounds for MH ellipse formulation.')
-
-        phi_MH = -np.arctan(ez_soil/(L - z0)) - np.deg2rad(delta_phi)
-        a_MH = Nq/np.cos(phi_MH)     
-        delta_bMH = 0.45*(lambdap)**(-0.9) if lambdap <= 1.5 else 0
-        b_MH = -Nq*np.sin(phi_MH) + delta_bMH
-
-        # Solve MH ellipse for Hmax
-        def f(Hmax):
-            term1 = ((M*np.cos(phi_MH) + Hmax*np.sin(phi_MH))/a_MH)**2
-            term2 = ((M*np.sin(phi_MH) - Hmax*np.cos(phi_MH))/b_MH)**2
-            return term1 + term2 - 1
-
-        Hmax = fsolve(f, 0.8*Hmax)[0]
-        print(f'Hmax (MH ellipse) = {Hmax:.2f} N')
-
-        To = PileSurface((L - z0), D)*delta_av*sigma_av_L
-        Ti = PileSurface((L - z0), D - 2*t)*delta_av*sigma_av_L
-        Tbase = np.pi*D**3*sigma_tip/12
-        Tmax = min(To + Ti, To + Tbase)
-
-        T = Ha*rlug*np.sin(np.deg2rad(psilug))
-        Fo = delta_av*sigma_av_L*L*np.pi*D
-        nhuT = T/Tmax
-        nhuV = Ha/Fo
-        nhuVstar = np.sqrt(nhuV**2 - nhuT**2)
-        deltastar = delta_av*(nhuVstar/nhuV)
-
-        Vmax2 = PileWeight(L, D, t, rhows) + PileSurface((L - z0), D)*deltastar*sigma_av_L + PileSurface((L - z0), D - 2*t)*deltastar*sigma_av_L
-        Vmax3 = PileWeight(L, D, t, rhows) + PileSurface((L - z0), D)*deltastar*sigma_av_L + SoilWeight((L - z0), D, t, gamma_av)
-        Vmax = min(Vmax2, Vmax3)
-        
-    # Pile weight (inc. stiffening plus vent) assessed as a factor
-    Wp = 1.10*PileWeight(L, D, t, (rhows + rhow)) 
-    # Submerged weight of the soil plug
-    Wsoil = SoilWeight((L - z0), D, t, gamma_av)
-    
-    # Capacity envelope
-    aVH = 0.5 + lambdap; bVH = 4.5 + lambdap/3 
-    # print('Env. exp = ' +str(aVH)+'   '+str(bVH))
-    UC = (Ha/Hmax)**aVH + (Va/Vmax)**bVH      
-    x = np.cos(np.linspace (0, np.pi/2, 100))
-    y = (1 - x**bVH)**(1/aVH)
-    X = Hmax*x; Y = Vmax*y
-    
-    if plot:
-        plt.figure(figsize=(6, 5))
-        plt.plot(X, Y, color = 'b', label='VH Envelope')
-        plt.plot(Ha, Va, 'o', color = 'r', label='Load Point')
-            
-        # Set labels and title
-        plt.xlabel('Horizontal capacity (N)')
-        plt.ylabel('Vertical capacity (N)')
-        plt.suptitle('VH suction pile capacity envelope')
-        plt.axis([0, 1.3*max(X[0], Ha), 0, 1.3*max(Y[-1], Va)]) 
-        plt.legend()
-        plt.grid(True)
-        plt.show()
-    
-    resultsSuction = {
-        'Horizontal max.': Hmax,
-        'Vertical max.': Vmax,
-        'Unity check': UC,
-        'Weight pile': Wp,
-        'Weight soil': Wsoil,
-        't': t
-    }
-    
-    return resultsSuction
-    
-if __name__ == '__main__':
-
-    # Clay profile: [depth (m), Su (kPa), gamma (kN/m³)]
-    profile_clay = np.array([
-        [ 2.0,  25,  8.5],
-        [ 4.0,  25,  8.5],
-        [ 6.0,  25,  8.5],
-        [20.0,  25,  8.5]
-    ])
-    
-    # Sand profile: [depth (m), phi (deg), gamma (kN/m³), Dr(%)]
-    profile_sand = np.array([
-        [ 1.0, 28, 8.0, 75],
-        [ 5.0, 35, 8.5, 75],
-        [ 8.0, 38, 9.0, 75],
-        [20.0, 42, 9.5, 75]
-    ])
-
-    D = 3.0             # Diameter (m)
-    L = 10.0            # Length (m)
-    zlug = 8.0          # Padeye depth (m)
-    Ha = 2.0e6          # Horizontal load (N)
-    Va = 3.0e6          # Vertical load (N)
-
-    # === CLAY ===
-    resultsSuction_clay = getCapacitySuction(profile_clay, 'clay', D, L, zlug, Ha, Va, plot=True)
-    for key, val in resultsSuction_clay.items(): 
-        print(f"{key}: {val:.2f}")
-        
-    # Plot suction pile with the clay profile
-    profile_clay_plot = [(float(z), float(Su), 'clay') for z, Su, _ in profile_clay]
-    plot_suction(profile_clay_plot, 'clay', L, D, zlug)
-      
-    # === SAND ===
-    # resultsSuction_sand = getCapacitySuction(profile_sand, 'sand', D, L, zlug, Ha, Va, plot=True)
-    # for key, val in resultsSuction_sand.items(): 
-    #     print(f"{key}: {val:.2f}") 
-    
-    # # Sand profile formatted for plotting
-    # profile_sand_plot = [(float(z), float(phi), 'sand') for z, phi, _, _ in profile_sand]
-    # plot_suction(profile_sand_plot, 'sand', L, D, zlug, title='Suction Pile in Sand Profile')
-
diff --git a/famodel/anchors/anchors_famodel_profile/capacity_torpedo.py b/famodel/anchors/anchors_famodel_profile/capacity_torpedo.py
deleted file mode 100644
index 5495a956..00000000
--- a/famodel/anchors/anchors_famodel_profile/capacity_torpedo.py
+++ /dev/null
@@ -1,159 +0,0 @@
-  
-import numpy as np
-import matplotlib.pyplot as plt
-from .capacity_soils import clay_profile
-from .capacity_plots import plot_torpedo
-
-def getCapacityTorpedo(profile, soil_type, D1, D2, L1, L2, zlug, ballast, Ha, Va, plot=True):
-    '''Calculate the inclined load capacity of a torpedo pile in clay following S. Kay methodology.
-    The calculation is based on the soil profile, anchor geometry and inclined load.  
-
-    Parameters
-    ----------
-    profile : array
-        Clay soil profile (z, Su, gamma)
-            Clay soil profile (z (m), Su (kPa), gamma (kN/m³))
-    soil_type : string
-        Select soil condition, 'clay' 
-    D1 : float 
-        Wing diameter (m)
-    D2 : float    
-        Shaft diameter (m)
-    L1 : float 
-        Winged section length (m)
-    L2 : float 
-        Shaft section length (m)
-    zlug : float 
-        Padeye embedment depth (m)       
-    Ha : float       
-        Horizontal load at pile lug elevation (N)
-    Va : float          
-        Vertical load at pile lug elevation (N)
-    plot : bool
-        Plot the capacity envelope if True
-
-    Returns
-    -------
-    Dictionary with capcity, weigth and UC.
-    '''
-
-    t = (6.35 + D2*20)/1e3           # Torpedo pile wall thickness (m), API RP2A-WSD
-    rhows = 66.90e3                  # Submerged steel specific weight (N/m3)
-    rhow = 10e3                      # Water specific weight (N/m3) 
-    
-    # Average effective width
-    L = L1 + L2
-    A_wing_plane_1 = (D1 - D2)*L1
-    A_wing_plane_2 = (D1 - D2)*np.cos(np.deg2rad(45))/2*L1
-    A_shaft = D2*L
-    
-    # Choose based on direction:
-    plane = '1'  # or '2'
-    
-    if plane == '1':
-        Dstar = (A_wing_plane_1 + A_shaft)/L
-    elif plane == '2':
-        Dstar = (A_wing_plane_2 + A_shaft)/L
-     
-    z0, f_Su, f_sigma_v_eff, f_gamma, f_alpha = clay_profile(profile)
-
-    a = zlug
-    c = zlug + L1 + L2
-    profile_depth = profile[-1, 0]
-
-    if c > profile_depth:
-        raise ValueError(
-            f'Soil profile does not cover the full pile length.\n'
-            f'   → Pile tip depth: {c:.2f} m\n'
-            f'   → Soil profile depth: {profile_depth:.2f} m\n'
-            f'Extend the soil profile to at least the pile tip depth to run the capacity model.'
-        )
-
-    z_vals = np.linspace(a, c, 100)
-    Su_vals = f_Su(z_vals)
-    alpha_vals = np.array([f_alpha(z) for z in z_vals])
-
-    ez_soil = np.trapz(z_vals*Su_vals, z_vals)/np.trapz(Su_vals, z_vals)
-    Su_e = f_Su(ez_soil)
-    alpha_e = f_alpha(ez_soil)
-    print(f"Su_e = {Su_e:.2f} kPa, ez_soil = {ez_soil:.2f} m, alpha_e = {alpha_e:.2f}")
-
-    def PileWeight(Len1, Len2, Dia1, Dia2, tw, rho):
-        return ((np.pi/4)*(Dia1**2 - (Dia1 - 2*tw)**2)*(Len1 + Len2) + 4*Len2*Dia2*tw)*rho
-
-    def PileSurface(Len1, Len2, Dia1, Dia2):
-        return np.pi*Dia1*(Len1 + Len2) + 8*Len2*Dia2*0.9
-
-    Np_free = 3.45
-    Hmax = Np_free*L*Dstar*Su_e
-    Vmax = PileSurface(L1, L2, D1, D2)*alpha_e*Su_e + PileWeight(L1, L2, D1, D2, t, rhows) + ballast
-    
-    # Pile weight (inc. auxiliary elements) assessed as a factor
-    Wp = 1.10*PileWeight(L1, L2, D1, D2, t, (rhows + rhow)) + ballast
-
-    # Calculate actual ez_su to L ratio
-    ez_ratio = (ez_soil - zlug)/L; print(f"ez_ratio = {ez_ratio:.2f} m")
-
-    # Assign aVH and bVH based on ez_su/L
-    if np.isclose(ez_ratio, 2/3, atol=0.05):
-        aVH = 0.5 + L/Dstar
-        bVH = 4.5 - L/(3*Dstar)
-        mode = 'deep mobilization (2/3)'
-    elif 0.45 <= ez_ratio <= 0.75:
-        aVH = 4.5 + L/(2*Dstar)
-        bVH = 3.5 - L/(4*Dstar)
-        mode = 'moderate mobilization (1/2 – 3/4)'
-    print(f'Interaction exponents set to aVH = {aVH:.2f}, bVH = {bVH:.2f} [{mode}]')
-    
-    UC = (Ha/Hmax)**aVH + (Va/Vmax)**bVH
-
-    deg = np.linspace(0, 90, 20)
-    x = np.cos(np.deg2rad(deg))
-    y = (1 - x**bVH)**(1/aVH)
-    X = Hmax*x; Y = Vmax*y
-
-    if plot:
-        plt.plot(X, Y, color='blue', label='VH Envelope')
-        plt.plot(H, V, 'o', color='red', label='Load Point')
-        plt.xlabel('Horizontal Load (N)')
-        plt.ylabel('Vertical Load (N)')
-        plt.title('VH torpedo pile capacity envelope')
-        plt.grid(True)
-        plt.legend()
-        plt.axis([0, 1.3*max(X[0], H), 0, 1.3*max(Y[-1], V)])
-        plt.show()
-
-    resultsTorpedo = {
-        'Horizontal max.': Hmax,
-        'Vertical max.': Vmax,
-        'Unity check': UC,
-        'Weight pile': Wp
-    }
-
-    return resultsTorpedo
-
-if __name__ == '__main__':
-    
-    profile_clay = np.array([
-        [ 0.0, 50, 8.0],
-        [20.0, 50, 8.5],
-        [25.0, 50, 8.5],
-        [50.0, 50, 9.0]
-    ])
-
-    D1 = 3.0             # Wing diameter (m)
-    D2 = 1.5             # Shaft diamter (m)
-    L1 = 11.0            # Winged section length (m) 
-    L2 = 10.0             # Shaft section length (m)
-    zlug = 15.0          # Padeye depth (m)
-    ballast = 10000      # Ballast load (N)
-    H = 6.0e6            # Horizontal load (N)
-    V = 8.0e6            # Vertical load (N)
-
-    results = getCapacityTorpedo(profile_clay, 'clay', D1, D2, L1, L2, zlug, ballast, H, V, plot=True)
-    print("\n--- Torpedo Pile Capacity Results ---")
-    for key, val in results.items():
-        print(f"{key}: {val:.2f}")
-        
-    plot_torpedo(profile_clay, 'clay', D1, D2, L1, L2, zlug, title='Torpedo Pile in Clay Profile')
-
diff --git a/famodel/anchors/getCapacityAnchor_profile.py b/famodel/anchors/getCapacityAnchor_profile.py
deleted file mode 100644
index 4e7cf491..00000000
--- a/famodel/anchors/getCapacityAnchor_profile.py
+++ /dev/null
@@ -1,94 +0,0 @@
-
-from famodel.anchors.anchor_profile import Anchor
-from famodel.anchors.anchors_famodel_profile.capacity_plots import plot_load
-import numpy as np  
-
-# Define the soil profile
-soil_profile = np.array([
-    [ 1.0,  10, 8.0],
-    [ 2.0,  25, 8.5],
-    [ 8.0,  50, 9.0],
-    [16.0, 100, 9.5],
-    [25.0, 100, 9.5]
-])
-
-# Create Anchor object
-anchor = Anchor(
-    dd={
-        'type': 'suction',
-        'design': {'D': 2.5, 'L': 10.0, 'zlug': 6.0, 'soil_type': 'clay'},
-        'soil_properties': {'clay': soil_profile}
-    },
-    ms=None,
-    r=[0.0, 0.0, 0.0],
-    aNum=0,
-    id='A1',
-    g=9.81,
-    rho=1025
-)
-
-# Assign loads manually
-anchor.loads = {
-    'Hm': 3e6,     # Horizontal mudline load (N)
-    'Vm': 1e6      # Vertical mudline load (N)
-}
-
-# Also assign mooring line properties manually
-anchor.line_type = 'chain'
-anchor.d = 0.16    # Chain diameter (m)
-anchor.w = 5000.0  # Nominal submerged weight (N/m)
-
-# --- Step 1: Compute Lug Forces ---
-Ha, Va = anchor.getLugForces(
-    ground_conds=anchor.dd['soil_properties'],
-    Hm=anchor.loads['Hm'],
-    Vm=anchor.loads['Vm'],
-    thetam=np.degrees(np.arctan2(anchor.loads['Vm'], anchor.loads['Hm'])),
-    zlug=anchor.dd['design']['zlug'],
-    line_type=anchor.line_type,
-    d=anchor.d,
-    w=anchor.w,
-    plot=True  
-)
-
-# Print Lug Forces
-print('\nLug Forces Computed:')
-print(f'Ha = {Ha:.2f} N')
-print(f'Va = {Va:.2f} N')
-
-# --- Step 2: Compute Anchor Capacity ---
-anchor.getCapacityAnchor(
-    ground_conds=anchor.dd['soil_properties'],
-    Hm=anchor.loads['Hm'],
-    Vm=anchor.loads['Vm'],
-    thetam=np.degrees(np.arctan2(anchor.loads['Vm'], anchor.loads['Hm'])),
-    zlug=anchor.dd['design']['zlug'],
-    line_type=anchor.line_type,
-    d=anchor.d,
-    w=anchor.w,
-    plot=True  
-)
-
-# Print Capacity Results
-print('\nCapacity Results:')
-for key, value in anchor.capacity_results.items():
-    print(f'{key}: {value:.2f}')
-    
-# --- Step 3: Optimize Anchor Geometry ---
-anchor.getSizeSuction(
-    geom=[anchor.dd['design']['L'], anchor.dd['design']['D']],
-    geomKeys=['L', 'D'],
-    geomBounds=[(5.0, 15.0), (2.0, 6.0)],
-    loads=None,
-    minfs={'Ha': 1.0, 'Va': 1.0},
-    lambdap_con=[3, 6],
-    zlug_fix=False,
-    plot=True
-)
-
-print('\nFinal Optimized Anchor:')
-print('Design:', anchor.dd['design'])
-print('Capacity Results:', anchor.capacity_results)
-
-# --- Step 4: Visualize Anchor Geometry ---
-anchor.getCombinedPlot()
\ No newline at end of file
diff --git a/famodel/anchors/getCapacityHelical_map.py b/famodel/anchors/getCapacityHelical_map.py
deleted file mode 100644
index 1710e413..00000000
--- a/famodel/anchors/getCapacityHelical_map.py
+++ /dev/null
@@ -1,70 +0,0 @@
-
-from anchor_map import Anchor
-
-# --- Define soil profile ---
-profile_map = [
-    {
-        'name': 'CPT_H1',
-        'x': 0.0, 'y': 0.0,
-        'layers': [
-            {'top':  1.0, 'bottom': 10.0, 'soil_type': 'sand', 'gamma_top': 10.0, 'gamma_bot': 11.0, 'phi_top': 30, 'phi_bot': 32, 'Dr_top': 60, 'Dr_bot': 60},
-            {'top': 10.0, 'bottom': 20.0, 'soil_type': 'sand', 'gamma_top': 11.0, 'gamma_bot': 11.5, 'phi_top': 36, 'phi_bot': 38, 'Dr_top': 60, 'Dr_bot': 80}
-        ]
-    }
-]
-
-# --- Create helical anchor object ---
-anchor = Anchor(
-    dd = {
-        'type': 'helical',
-        'design': {
-            'D': 1.7,         # Helix diameter (m)
-            'L': 12.0,        # Depth (m)
-            'd': 0.3,         # Shaft diameter (m)
-            'zlug': 4.0       # Padeye depth (m)
-        }
-    },
-    r = [0.0, 0.0, 0.0]
-)
-
-# Assign loads and mooring info
-anchor.loads = {
-    'Hm': 8.8e6,
-    'Vm': 1.2e6
-}
-anchor.line_type = 'chain'
-anchor.d = 0.16
-anchor.w = 5000.0
-
-# Assign local soil
-anchor.setSoilProfile(profile_map)
-
-# --- Step 1: Lug Forces ---
-layers, Ha, Va = anchor.getLugForces(
-    Hm = anchor.loads['Hm'],
-    Vm = anchor.loads['Vm'],
-    zlug = anchor.dd['design']['zlug'],
-    line_type = anchor.line_type,
-    d = anchor.d,
-    w = anchor.w,
-    plot = True
-)
-
-print('\nLug Forces Computed:')
-print(f'Ha = {Ha:.2f} N')
-print(f'Va = {Va:.2f} N')
-
-# --- Step 2: Capacity ---
-anchor.getCapacityAnchor(
-    Hm = anchor.loads['Hm'],
-    Vm = anchor.loads['Vm'],
-    zlug = anchor.dd['design']['zlug'],
-    line_type = anchor.line_type,
-    d = anchor.d,
-    w = anchor.w,
-    plot = True
-)
-
-print('\nCapacity Results:')
-for key, val in anchor.capacity_results.items():
-    print(f'{key}: {val:.2f}')
diff --git a/famodel/anchors/getCapacityHelical_sand.py b/famodel/anchors/getCapacityHelical_sand.py
deleted file mode 100644
index 1710e413..00000000
--- a/famodel/anchors/getCapacityHelical_sand.py
+++ /dev/null
@@ -1,70 +0,0 @@
-
-from anchor_map import Anchor
-
-# --- Define soil profile ---
-profile_map = [
-    {
-        'name': 'CPT_H1',
-        'x': 0.0, 'y': 0.0,
-        'layers': [
-            {'top':  1.0, 'bottom': 10.0, 'soil_type': 'sand', 'gamma_top': 10.0, 'gamma_bot': 11.0, 'phi_top': 30, 'phi_bot': 32, 'Dr_top': 60, 'Dr_bot': 60},
-            {'top': 10.0, 'bottom': 20.0, 'soil_type': 'sand', 'gamma_top': 11.0, 'gamma_bot': 11.5, 'phi_top': 36, 'phi_bot': 38, 'Dr_top': 60, 'Dr_bot': 80}
-        ]
-    }
-]
-
-# --- Create helical anchor object ---
-anchor = Anchor(
-    dd = {
-        'type': 'helical',
-        'design': {
-            'D': 1.7,         # Helix diameter (m)
-            'L': 12.0,        # Depth (m)
-            'd': 0.3,         # Shaft diameter (m)
-            'zlug': 4.0       # Padeye depth (m)
-        }
-    },
-    r = [0.0, 0.0, 0.0]
-)
-
-# Assign loads and mooring info
-anchor.loads = {
-    'Hm': 8.8e6,
-    'Vm': 1.2e6
-}
-anchor.line_type = 'chain'
-anchor.d = 0.16
-anchor.w = 5000.0
-
-# Assign local soil
-anchor.setSoilProfile(profile_map)
-
-# --- Step 1: Lug Forces ---
-layers, Ha, Va = anchor.getLugForces(
-    Hm = anchor.loads['Hm'],
-    Vm = anchor.loads['Vm'],
-    zlug = anchor.dd['design']['zlug'],
-    line_type = anchor.line_type,
-    d = anchor.d,
-    w = anchor.w,
-    plot = True
-)
-
-print('\nLug Forces Computed:')
-print(f'Ha = {Ha:.2f} N')
-print(f'Va = {Va:.2f} N')
-
-# --- Step 2: Capacity ---
-anchor.getCapacityAnchor(
-    Hm = anchor.loads['Hm'],
-    Vm = anchor.loads['Vm'],
-    zlug = anchor.dd['design']['zlug'],
-    line_type = anchor.line_type,
-    d = anchor.d,
-    w = anchor.w,
-    plot = True
-)
-
-print('\nCapacity Results:')
-for key, val in anchor.capacity_results.items():
-    print(f'{key}: {val:.2f}')
diff --git a/famodel/anchors/images/Drilledandgroutedpiles/Drilled.png b/famodel/anchors/images/Drilledandgroutedpiles/Drilled.png
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index 00000000..38f4ae2b
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diff --git a/famodel/anchors/images/Drivenpiles/Clay - deformed pile.png b/famodel/anchors/images/Drivenpiles/Clay - deformed pile.png
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diff --git a/famodel/anchors/images/Drivenpiles/Driven.png b/famodel/anchors/images/Drivenpiles/Driven.png
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index 00000000..953d7c1a
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diff --git a/famodel/anchors/images/Drivenpiles/pycurves - Lovera.png b/famodel/anchors/images/Drivenpiles/pycurves - Lovera.png
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index 00000000..88214936
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diff --git a/famodel/anchors/images/Suctionpiles/Clay - suction envelope.png b/famodel/anchors/images/Suctionpiles/Clay - suction envelope.png
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index 00000000..b96e863b
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diff --git a/famodel/anchors/images/Torpedopiles/Clay - torpedo envelope.png b/famodel/anchors/images/Torpedopiles/Clay - torpedo envelope.png
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index 00000000..a633fdb1
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diff --git a/famodel/anchors/images/Torpedopiles/Torpedo.png b/famodel/anchors/images/Torpedopiles/Torpedo.png
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index 00000000..1ed223cf
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diff --git a/famodel/geography.py b/famodel/geography.py
index 5e92c5d6..0929f849 100644
--- a/famodel/geography.py
+++ b/famodel/geography.py
@@ -3,22 +3,17 @@
 import os
 import numpy as np
 import matplotlib.pyplot as plt
-
 import moorpy as mp
 from moorpy.helpers import set_axes_equal
 import yaml
-
 import pandas as pd
 import geopandas as gpd
 from shapely.geometry import Point, Polygon, LineString
-
 import famodel.seabed_tools as sbt
-
 from pyproj import CRS
 from pyproj.aoi import AreaOfInterest
 from pyproj.database import query_utm_crs_info
 
-
 # =============================================================================
 # COORDINATE REFERENCE SYSTEMS & TRANSFORMATIONS
 # =============================================================================
@@ -89,7 +84,6 @@ def getTargetCRS(longitudes, latitudes):
 
     return target_crs
 
-
 def getCustomCRS(long, lat):
     '''Seemingly way too simple of a method to create a pyproj CRS centered around a custom geographical point
 
@@ -110,8 +104,6 @@ def getCustomCRS(long, lat):
 
     return custom_crs
 
-
-
 def getLeaseCoords(lease_name):
 
     # read in the BOEM shapefile that contains all Wind Energy Lease Areas (can use other shapefiles for aliquots)
@@ -137,17 +129,17 @@ def getLeaseCoords(lease_name):
         raise ValueError(f"The lease area name '{lease_area}' is not supported yet")
     
     # extract the longitude and latitude coordinates of the lease area
-    area_longs, area_lats = lease_area.geometry.unary_union.exterior.coords.xy
+    #area_longs, area_lats = lease_area.geometry.unary_union.exterior.coords.xy
+    area_longs, area_lats = lease_area.geometry.union_all().exterior.coords.xy
+
 
     # calculate the centroid of the lease area
     centroid = ( lease_area.geometry.centroid.values.x[0], lease_area.geometry.centroid.values.y[0] )
 
-    return area_longs, area_lats, centroid
-        
-
-
 
 
+    return area_longs, area_lats, centroid
+        
 def convertLatLong2Meters(longs, lats, centroid, latlong_crs, target_crs, return_centroid=False):
     '''input longs/lats need to be in EPSG:4326 CRS
     Longs and Lats need to be in pairs, i.e., the first entry to longs and 
@@ -203,7 +195,6 @@ def convertLatLong2Meters(longs, lats, centroid, latlong_crs, target_crs, return
     else:
         return xs, ys
 
-
 def convertMeters2LatLong(xs, ys, centroid, latlong_crs, target_crs, mesh=False):
     '''Input xs and ys need to be in the target CRS
     Xs and Ys need to be in pairs, i.e. the first entry to xs and the 
@@ -275,7 +266,6 @@ def getMapBathymetry(gebcofilename):
 
     return longs, lats, depths, ncols, nrows
 
-
 def convertBathymetry2Meters(longs, lats, depths, centroid, centroid_utm, 
                              latlong_crs, target_crs, ncols, nrows,
                              xs=[], ys=[]):
@@ -329,8 +319,6 @@ def convertBathymetry2Meters(longs, lats, depths, centroid, centroid_utm,
 
     return bathXs, bathYs, bath_depths
 
-        
-        
 def writeBathymetryFile(moorpy_bathymetry_filename, bathXs, bathYs, bath_depths, soil=False):
     '''Write a MoorDyn/MoorPy-style bathymetry text file based on provided
     x and y grid line values and a 2D array of depth values.'''
@@ -366,7 +354,6 @@ def writeBathymetryFile(moorpy_bathymetry_filename, bathXs, bathYs, bath_depths,
     f.close()
 
 
-
 def getLeaseAndBathymetryInfo(lease_name, bathymetry_file, bath_ncols=100, bath_nrows=100, write_bathymetry=True):
 
     # initialize the conventional lat/long CRS
@@ -379,7 +366,8 @@ def getLeaseAndBathymetryInfo(lease_name, bathymetry_file, bath_ncols=100, bath_
     custom_crs = getCustomCRS(centroid[0], centroid[1])
     
     # convert the lease boundary to meters
-    lease_xs, lease_ys, centroid_utm = convertLatLong2Meters(lease_longs, lease_lats, centroid, latlong_crs, custom_crs, return_centroid=True)
+    lease_xs, lease_ys, centroid_utm = convertLatLong2Meters(lease_longs, lease_lats, centroid, 
+                                                             latlong_crs, custom_crs, return_centroid=True)
 
     if write_bathymetry:
         # get bathymetry information from a GEBCO file (or other)
@@ -545,8 +533,6 @@ def getSoilType(x, y, centroid, latlong_crs, custom_crs, soil_file):
 
     return soil_type
 
-
-
 def getSoilGrid(centroid, latlong_crs, custom_crs, soil_file, nrows=100, ncols=100, xbound=None, ybound=None):
     """Note: can make the outer shapely shape have 'holes' of the inner shapely shapes"""
     
@@ -592,6 +578,7 @@ def getSoilGrid(centroid, latlong_crs, custom_crs, soil_file, nrows=100, ncols=1
         ys = np.linspace(ybound[0], ybound[-1], nrows)
     else:
         ys = np.linspace( np.min([np.min(soil_ys[i]) for i in range(len(soil_shapes))]),  np.max([np.max(soil_ys[i]) for i in range(len(soil_shapes))]),  nrows)
+    
     soil_grid = np.zeros([len(ys), len(xs)])
 
     # for each manmade grid point, loop through all the polygons and determine whether that grid point is within the shape or not
@@ -613,13 +600,10 @@ def getSoilGrid(centroid, latlong_crs, custom_crs, soil_file, nrows=100, ncols=1
     soil_grid = np.array(soil_grid_list)        # saving to list and then changing to np.array because I couldn't figure out how else to do it with strings
 
     return xs, ys, soil_grid
-
-
         
 
 
 
-
 if __name__ == '__main__':
 
     """
@@ -661,7 +645,7 @@ def getSoilGrid(centroid, latlong_crs, custom_crs, soil_file, nrows=100, ncols=1
     # get bathymetry information from a GEBCO file (or other)
     bath_longs, bath_lats, bath_depths, ncols, nrows = getMapBathymetry('bathymetry/gebco_2023_n41.3196_s40.3857_w-125.2881_e-123.9642.asc')
     # convert bathymetry to meters
-    ncols = 500
+    ncols = 500C:/Users/fmoreno/Downloads/GEBCO_25_Jun_2025_3c682d73375c/GEBCO_25_Jun_2025_3c682d73375c/gebco_2024_n44.2_s44.0_w12.5_e12.8.asc
     nrows = 500
     bath_xs, bath_ys, bath_depths = convertBathymetry2Meters(bath_longs, bath_lats, bath_depths, centroid, centroid_utm, latlong_crs, custom_crs, ncols, nrows)
     # export to MoorPy-readable file
@@ -677,12 +661,75 @@ def getSoilGrid(centroid, latlong_crs, custom_crs, soil_file, nrows=100, ncols=1
     __location__ = os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(__file__)))
     lease_name = 'GulfofMaine_ResearchArray'
     gebco_file = __location__+'\\..\\geography\\gebco_2024_n44.1458_s41.4761_w-70.9497_e-66.2146.asc'
-    info = getLeaseAndBathymetryInfo(lease_name, bathymetry_file)
+    info = getLeaseAndBathymetryInfo(lease_name, gebco_file)
+    
+    x_center = np.mean(info['lease_xs'])
+    y_center = np.mean(info['lease_ys'])
+    
+    zoom = 8000  
+
+
+    xbounds = [x_center - zoom, x_center + zoom]
+    ybounds = [y_center - zoom, y_center + zoom]
+    
+    fig, ax = plot3d(info['lease_xs'], info['lease_ys'], 'bathymetry_100x100.txt',
+        area_on_bath=True, args_bath={'cmap': 'gist_earth', 'zlim': [-500, 50]},
+        xbounds=xbounds, ybounds=ybounds)
+    
+    plt.show()
+    
+    # Load bathymetry data manually
+    with open('GulfOfMaine_bathymetry_100x100.txt', 'r') as f:
+        lines = f.readlines()
+    
+    nGridX = int(lines[1].split()[1])
+    nGridY = int(lines[2].split()[1])
+    x_vals = np.array([float(val) for val in lines[3].split()])
+    y_vals = []
+    z_matrix = []
+    
+    for line in lines[4:4+nGridY]:
+        parts = line.split()
+        y_vals.append(float(parts[0]))
+        z_matrix.append([float(z) for z in parts[1:]])
+
+    
+    # Extract y and z
+    z_vals = np.array(z_matrix)
+    y_vals = np.array(y_vals)
+
+    
+    # Now crop using xbounds and ybounds
+    xmask = (x_vals >= xbounds[0]) & (x_vals <= xbounds[1])
+    ymask = (y_vals >= ybounds[0]) & (y_vals <= ybounds[1])
+    
+    x_crop = x_vals[xmask]
+    y_crop = y_vals[ymask]
+    z_crop = z_vals[ymask][:, xmask]
+    
+    # Plot manually using Axes3D
+    X, Y = np.meshgrid(x_crop, y_crop)
+    fig = plt.figure()
+    ax = fig.add_subplot(111, projection='3d')
+    ax.plot_surface(X, Y, z_crop, cmap='gist_earth')
+    ax.set_title('Zoomed Bathymetry')
+    
+    lease_xs = info['lease_xs']
+    lease_ys = info['lease_ys']
 
+    ax.plot(lease_xs, lease_ys, zs=200, zdir='z', color='r', linewidth=2, label='Lease Area')
+    ax.legend()
 
     plt.show()
 
-    a = 2
+
+ 
+    # plot3d(info['lease_xs'], info['lease_ys'], 'bathymetry_100x100.txt', area_on_bath=False, args_bath={'zlim':[-3000, 500], 'cmap': 'gist_earth'})
+           # xbounds=(info['bath_xs'].min(), info['bath_xs'].min()),
+           # ybounds=(info['bath_ys'].min(), info['bath_ys'].min()),
+           # zbounds=(info['bath_depths'].min(), info['bath_depths'].min())
+
+
 
 
 
diff --git a/famodel/project.py b/famodel/project.py
index d4f846cc..234c3880 100644
--- a/famodel/project.py
+++ b/famodel/project.py
@@ -1157,7 +1157,6 @@ def seabedIntersect(self, r, u):
         
         return r_i
 
-
     def projectAlongSeabed(self, x, y):
         '''Project a set of x-y coordinates along a seabed surface (grid),
         returning the corresponding z coordinates.'''
@@ -1177,206 +1176,207 @@ def projectAlongSeabed(self, x, y):
             
         return z
 
-
-
     # METHODS TO USE WITH ANCHOR TOOLS
-
-    def loadSoil(self, filename=None, yaml=None):
+    def loadSoil(self, filename=None, yaml=None, soil_mode='uniform', profile_source=None):
         '''
-        Load geoetechnical information from an input file (format TBD), convert to
-        a rectangular grid, and save the grid to the floating array object (TBD).
-        
-        The input file should provide rows with the following entries:
-        - x coordinate
-        - y coordinate
-        - class  - soil classification name ('clay', 'sand', or 'rock' with optional modifiers)
-        - gamma* - soil effective unit weight [kPa] (all soils)
-        - Su0*   - undrained shear strength at mudline [kPa] (clay 
-        - K*     - undrained shear strength gradient [kPa/m] (clay 
-        - alpha* - soil skin friction coefficient [-] (clay soils)
-        - phi*   - angle of internal friction [deg] (sand soils)
-        
-        Some (*) parameters are optional depending on the soil class and mode.   
+        Load geotechnical information from input file or YAML.
+        Supports two soil modes: 'uniform' and 'layered'.
 
-        Irregular sampling points will be supported and interpolated to a 
-        rectangular grid.
-        
-        Paramaters
+        Parameters
         ----------
-        filename : path
-            path/name of file containing soil data
+        filename : str, optional
+            Path to .txt/.dat file with soil labels/profile IDs and coordinates
+        yaml : dict, optional
+            Dictionary containing soil data and properties (used when filename is None)
+        soil_mode : str
+            Either 'uniform' or 'layered'
+        profile_source : str, optional
+            Path to YAML file with layered profile definitions (only used if soil_mode='layered')
         '''
         xs = None
         ys = None
         soil_names = None
-        if filename is not None:    # if the filename option was selected, then that means there is at least a grid in the file, and maybe soil type information
-            if filename[-3:]=='shp':
-                raise ValueError("Geography-related operations not directly supported in Project class")
-            
-            elif filename[-3:]=='txt' or filename[-3:]=='dat':
+        soilProps = None
 
-                # load in the grid portion of the soil input file
-                xs, ys, soil_names = sbt.readBathymetryFile(filename, dtype=str)  # read MoorDyn-style file
+        # Case 1: File input (grid + properties)
+        if filename is not None:
+            if filename.endswith('.shp'):
+                raise ValueError("Shapefiles not supported in Project class")
 
-                soilProps = sbt.getSoilTypes(filename)     # load in the soil property information (if there is any)
-            
-            # regardless of whether there is soil type information in the file, if there is soil information in the yaml, read that in
-            if yaml:
-                soilProps = yaml['soil_types']     # if there is a yaml file as input, load in the soil props that way (overwrites the other one)
+            elif filename.endswith('.txt') or filename.endswith('.dat'):
+                # Load label/profile_id grid
+                xs, ys, soil_names = sbt.readBathymetryFile(filename, dtype=str)
+
+                # Load soil properties
+                soilProps = sbt.getSoilTypes(filename, soil_mode=soil_mode, profile_source=profile_source)
 
+            if yaml:
+                soilProps = yaml.get('soil_types', soilProps)  # allow overwriting via YAML
 
-        elif filename is None:  # if the filename option was not selected
-            if yaml:            # and if there was a yaml option selected, simply read in that yaml information
+        # Case 2: YAML only (no filename)
+        elif filename is None:
+            if yaml:
                 xs = yaml['x']
                 ys = yaml['y']
                 soil_names = yaml['type_array']
-                soilProps = yaml['soil_types']
-            else:               # but if there was no yaml option selected (and no file option selected) -> set default values
-                print('Warning: No soil grid nor soil properties were selected, but this function ran -> use preprogrammed default values')
+                raw_soil_types = yaml['soil_types']
+        
+                # Ensure all soil types have a 'layers' field
+                soilProps = {}
+                for key, entry in raw_soil_types.items():
+                    if 'layers' in entry:
+                        soilProps[key] = entry 
+                    else:
+                        # Wrap old flat format into single-layer profile (optional fallback)
+                        layer = dict(entry)
+                        layer.setdefault('top', 0)
+                        layer.setdefault('bottom', 50)
+                        layer.setdefault('soil_type', key)
+                        soilProps[key] = {'layers': [layer]}
+            else:
+                print('[Warning] No soil input provided — using default values')
                 xs = [0]
                 ys = [0]
-                soil_names = ['mud']
-                soilProps = dict(mud={'Su0':[2.39], 'k':[1.41], 'gamma':[10], 'depth':[0]},
-                                rock={'UCS':[5], 'Em':[7], 'depth':[0]})
-        
+                soil_names = [['mud']]  # note: should be 2D to match grid structure
+                soilProps = {
+                    'mud': {'layers': [{
+                        'soil_type': 'clay',
+                        'top': 0, 'bottom': 50,
+                        'gamma_top': 10, 'gamma_bot': 10,
+                        'Su_top': 2.39, 'Su_bot': 59.39
+                    }]},
+                    'rock': {'layers': [{
+                        'soil_type': 'rock',
+                        'top': 0, 'bottom': 50,
+                        'UCS_top': 5, 'UCS_bot': 5,
+                        'Em_top': 7, 'Em_bot': 7
+                    }]}
+                }
+
+
         else:
-            raise ValueError("Something is wrong")
-        
-        '''
-        # check that correct soil properties are being provided for the different soil types
-        for soil in soilProps:
-            if 'rock' in soil or 'hard' in soil:
-                if not 'UCS' in soilProps[soil] or not 'Em' in soilProps[soil]:
-                    raise ValueError('Rock soil type requires UCS and Em values')
-            elif 'sand' in soil:
-                if not 'phi' in soilProps[soil] or not 'gamma' in soilProps[soil]:
-                    raise ValueError('Sand soil type requires phi and gamma values')
-            elif 'clay' in soil:
-                if not 'Su0' in soilProps[soil] or not 'k' in soilProps[soil]:
-                    raise ValueError('Clay soil type requires Su0 and k values')
-            elif 'mud' in soil or 'mud_soft':
-                if not 'Su0' in soilProps[soil] or not 'k' in soilProps[soil]:
-                    raise ValueError('Mud soil type requires Su0 and k values')
-            else:
-                raise ValueError(f'Soil type {soil} not recognized. Soil type key must contain one of the following keywords: rock, sand, clay, mud')
-        '''
-        
-        # make sure the soilProps dictionary has all the required information (should be updated later with exact properties based on anchor capacity functions)
-        # setting each soil type dictionary with all the values, just in case they need them for whatever reason - here are the default values
-        # the default types (and values) are set if there is no other information provided
-        for key,props in soilProps.items():
-            props['Su0']   = getFromDict(props, 'Su0'  , shape=-1, dtype=list, default=[2.39], index=None)
-            props['k']     = getFromDict(props, 'k'    , shape=-1, dtype=list, default=[1.41], index=None)
-            props['alpha'] = getFromDict(props, 'alpha', shape=-1, dtype=list, default=[0.7] , index=None)
-            props['gamma'] = getFromDict(props, 'gamma', shape=-1, dtype=list, default=[4.7] , index=None)
-            props['phi']   = getFromDict(props, 'phi'  , shape=-1, dtype=list, default=[0.0] , index=None)
-            props['UCS']   = getFromDict(props, 'UCS'  , shape=-1, dtype=list, default=[7.0] , index=None)
-            props['Em']    = getFromDict(props, 'Em'   , shape=-1, dtype=list, default=[50.0], index=None)
-            
-            for k,prop in props.items():
-                if 'array' in type(prop).__name__:
-                    # clean up property type
-                    props[k] = np.array(prop)
-        
-        
+            raise ValueError("Invalid combination of filename/yaml inputs")
+
+        # --- Set defaults only for uniform mode ---
+        if soil_mode == 'uniform':
+            for key, props in soilProps.items():
+                props['Su0']   = getFromDict(props, 'Su0',   shape=-1, dtype=list, default=[2.39])
+                props['k']     = getFromDict(props, 'k',     shape=-1, dtype=list, default=[1.41])
+                props['alpha'] = getFromDict(props, 'alpha', shape=-1, dtype=list, default=[0.7])
+                props['gamma'] = getFromDict(props, 'gamma', shape=-1, dtype=list, default=[8.7])
+                props['phi']   = getFromDict(props, 'phi',   shape=-1, dtype=list, default=[0.0])
+                props['UCS']   = getFromDict(props, 'UCS',   shape=-1, dtype=list, default=[7.0])
+                props['Em']    = getFromDict(props, 'Em',    shape=-1, dtype=list, default=[50.0])
+
+                # ensure no array-like leftovers
+                for k, prop in props.items():
+                    if hasattr(prop, '__array__'):
+                        props[k] = np.array(prop)
+
+        # --- Store to project ---
         self.soilProps = soilProps
 
-
-        
-        
         if xs is not None:
             self.soil_x = np.array(xs)
             self.soil_y = np.array(ys)
             self.soil_names = np.array(soil_names)
-        
-        
-        # update soil info for anchor if needed
+
+        self.soil_mode = soil_mode
+        print(f"Loaded soilProps keys: {list(soilProps.keys())}")
+
+        # --- Update anchor objects if available ---
         if self.anchorList:
-            for anch in self.anchorList.values():
-                name, props = self.getSoilAtLocation(anch.r[0],anch.r[1])
-                anch.soilProps = {name:props}
-        
-        # load data from file
-        
-        # interpolate onto grid defined by grid_x, grid_y
-        
-        # save
-        '''
-        self.soil_class
-        self.soil_gamma
-        self.soil_Su0  
-        self.soil_K    
-        self.soil_alpha
-        self.soil_phi  
-        '''
-        pass
-        
+            for anchor in self.anchorList.values():
+                name, props = self.getSoilAtLocation(anchor.r[0], anchor.r[1])
+                anchor.soilProps = {name: props}
 
     def getSoilAtLocation(self, x, y):
         '''
-        Interpolate soil properties at specified location from the soil
-        properties grid and return a dictionary of soil properties that
-        can be used in anchor capacity calculations.
-        
-        Parameters
-        ----------        
-        x : float
-            x coordinate in array reference frame [m].        
-        y : float
-            y coordinate in array reference frame [m].
+        Retrieve the soil information at a specific location, supporting both uniform and layered modes.
 
         Returns
-        -------            
-        soilProps : dictionary
-            Dictionary of standard MoorPy soil properties.
+        -------
+        (str, dict or list): soil name or profile ID, and associated soil properties or layered profile
         '''
-        
-        # NEW: finds the specific soil grid point that the xy point is closest to and assigns it that soil type
         if self.soil_x is not None:
-            ix = np.argmin([abs(x-soil_x) for soil_x in self.soil_x])
-            iy = np.argmin([abs(y-soil_y) for soil_y in self.soil_y])
-    
-            soil_name = self.soil_names[iy, ix]
-    
-            soil_info = self.soilProps[soil_name]
-    
-            return soil_name, soil_info
+            ix = np.argmin([abs(x - sx) for sx in self.soil_x])
+            iy = np.argmin([abs(y - sy) for sy in self.soil_y])
+            soil_id = self.soil_names[iy, ix]  # could be label or profile_id
+
+            if self.soil_mode == 'uniform':
+                soil_info = self.soilProps[soil_id]
+                return soil_id, soil_info
+
+            elif self.soil_mode == 'layered':
+                profile_layers = self.soilProps[soil_id]  # list of layer dicts
+                return soil_id, profile_layers
+
+            else:
+                raise ValueError(f"Unknown soil_mode: {self.soil_mode}")
+
+            print(f"[DEBUG] soil_id at location ({x}, {y}) is: {soil_id}")
+            print(f"[DEBUG] Available soilProps keys: {list(self.soilProps.keys())}")
         else:
-            pass
-        
-        '''
-        # SIMPLE HACK FOR NOW        
-        rocky, _,_,_,_ = sbt.interpFromGrid(x, y, self.soil_x, self.soil_y, self.soil_rocky)
-        
-        return rocky
+            raise ValueError("No soil grid defined")
+            
+    def convertUniformToLayered(self, default_layer=50.0):
         '''
+        Converts self.soilProps (uniform format) into profile_map (layered format)
+        using a default thickness and assuming uniform clay profile.
+        Matches the structure of layered CPT-based soil profiles.
         '''
-        soilProps = {}
-        
-
-        if self.seabed_type == 'clay':
+        self.profile_map = {}
+
+        for name, props in self.soilProps.items():
+            name = str(name)
+            gamma = float(props['gamma'][0])
+            Su0 = float(props['Su0'][0])
+            k = float(props['k'][0])
+
+            layer = {
+                'soil_type': 'clay',
+                'top': 0.0,
+                'bottom': default_layer,
+                'gamma_top': gamma,
+                'gamma_bot': gamma,
+                'Su_top': Su0,
+                'Su_bot': Su0 + k * default_layer}
+
+            self.profile_map[name] = [layer]  # just layers!
             
-            soilProps['class'] = 'clay'
-            soilProps['gamma'] = interp2d(x, y, self.seabed_x, self.seabed_y, self.soil_gamma)
-            soilProps['Su0'  ] = interp2d(x, y, self.seabed_x, self.seabed_y, self.soil_Su0  )
-            soilProps['k'    ] = interp2d(x, y, self.seabed_x, self.seabed_y, self.soil_k    )
-            soilProps['alpha'] = interp2d(x, y, self.seabed_x, self.seabed_y, self.soil_alpha)
-            soilProps['phi'  ] = None
-        
-        elif self.seabed_type == 'sand':
-            soilProps['class'] = 'sand'
-            soilProps['gamma'] = interp2d(x, y, self.seabed_x, self.seabed_y, self.soil_gamma)
-            soilProps['Su0'  ] = None
-            soilProps['k'    ] = None
-            soilProps['alpha'] = None
-            soilProps['phi'  ] = interp2d(x, y, self.seabed_x, self.seabed_y, self.soil_phi  )
-            
-            # note: for sand, can assume homogeneous angle of internal fricton
-        else:
-            raise ValueError(f"Unsupported seabed type '{self.seabed_type}'.")
-            
-        return soilProps
+    def convertLayeredToUniform(self):
         '''
+        Converts self.profile_map (layered format) into soilProps (uniform format)
+        assuming a single clay layer with linear Su(z) = Su0 + k*z.
+        Matches the structure expected by uniform soil models.
+        '''
+        self.soilProps = {}
+
+        for name, layers in self.profile_map.items():
+            if not layers or len(layers) != 1:
+                raise ValueError('convertLayeredToUniform only supports a single-layer profile')
+
+            layer = layers[0]
+            if str(layer.get('soil_type', '')).lower() != 'clay':
+                raise ValueError('convertLayeredToUniform only supports clay')
+
+            top = float(layer['top'])
+            bot = float(layer['bottom'])
+            Su_top = float(layer['Su_top'])
+            Su_bot = float(layer['Su_bot'])
+            gamma = float(layer['gamma_top'])  # gamma_top == gamma_bot in your format
+
+            if bot <= top:
+                raise ValueError('Invalid layer thickness (bottom <= top)')
+
+            thickness = bot - top
+            k = (Su_bot - Su_top)/thickness
+            Su0 = Su_top - k*top
+
+            self.soilProps[name] = {
+                'gamma': [gamma],
+                'Su0': [Su0],
+                'k': [k]}
 
     # # ----- Anchor 
     def updateAnchor(self,anch='all',update_loc=True):
@@ -1407,39 +1407,20 @@ def updateAnchor(self,anch='all',update_loc=True):
                 name, props = self.getSoilAtLocation(x,y) # update soil
                 anchor.soilProps = {name:props}
             
-
-
-    # def calcAnchorCapacity(self, anchor):
-    #     '''Compute holding capacity of a given anchor based on the soil
-    #     info at its position. The anchor object's anchor properties and
-    #     location will be used to determine the holding capacity, which
-    #     will be saved to the anchor object.
-        
-    #     Parameters
-    #     ----------
-    #     anchor : MoorPy Anchor object (derived from Point)
-    #         The anchor object in question.
-    #     '''
-
-    #     # interpolate soil properties/class based on anchor position
-    #     anchor.soilProps = self.getSoilAtLocation(anchor.r[0], anchor.r[1])
-        
-    #     # fill in generic anchor properties if anchor info not provided
-    #     if not type(anchor.anchorProps) == dict:
-    #         anchor.anchorProps = dict(type='suction', diameter=6, length=12)
-        
-    #     # apply anchor capacity model
-    #     capacity, info = anchorCapacity(anchorProps, soilProps)
-        
-    #     # save all information to the anchor (attributes of the Point)
-    #     anchor.soilProps = soilProps
-    #     anchor.anchorCapacity = capacity
-    #     anchor.anchorInfo = info
-        
-    #     # also return it
-    #     return capacity
-
+    def setSoilAtLocation(self, anchor):
+        name, props = self.getSoilAtLocation(anchor.r[0], anchor.r[1])
+    
+        # Add required metadata
+        layer = dict(props)  # shallow copy of props
+        layer['soil_type'] = name  # or force to 'clay'/'rock' if needed
+        layer['top'] = props.get('top', 0)
+        layer['bottom'] = props.get('bottom', 50)  
     
+        # Wrap in expected profile_map format
+        profile_map = [{'name': name, 'layers': [layer]}]
+        anchor.setSoilProfile(profile_map)
+
+   
     def setCableLayout(self):
 
         # 2-D
diff --git a/famodel/seabed_tools.py b/famodel/seabed_tools.py
index 6baeffb6..afeb868e 100644
--- a/famodel/seabed_tools.py
+++ b/famodel/seabed_tools.py
@@ -4,6 +4,7 @@
 import os
 import matplotlib.pyplot as plt
 import numpy as np
+import yaml
 
 
 
@@ -43,31 +44,77 @@ def readBathymetryFile(filename, dtype=float):
     return bathGrid_Xs, bathGrid_Ys, bathGrid
 
             
-def getSoilTypes(filename):
-    '''function to read in a preliminary input text file format of soil type information'''
+def getSoilTypes(filename, soil_mode='layered', profile_source=None):
+    '''
+    Load soil properties or layered profiles depending on soil_mode.
 
+    Parameters
+    ----------
+    filename : str
+        Path to .txt file containing grid and profile/soil label definitions
+    soil_mode : str
+        'uniform' or 'layered'
+    profile_source : str or None
+        Path to YAML file with layered soil profiles (used only for 'layered')
+
+    Returns
+    -------
+    soilProps : dict
+        Dictionary of soil type properties (uniform) or layered profiles (layered)
+    '''
     soilProps = {}
+    used_labels = []
 
-    f = open(filename, 'r')
-    
-    for line in f:
-        if line.count('---') > 0 and (line.upper().count('SOIL TYPES') > 0):
-            line = next(f) # skip this header line, plus channel names and units lines
-            var_names = line.split()
-            line = next(f)
-            line = next(f)
-            while line.count('---') == 0:
-                entries = line.split()
-                soilProps[entries[0]] = {}
-                for iv,var in enumerate(var_names[1:]):
-                    # convert entries to strings unless there is 
-                    if entries[iv+1] == '-':
-                        soilProps[entries[0]][var] = [0]
-                    else:
-                        soilProps[entries[0]][var] = [float(entries[iv+1])]
-                line = next(f)
-    
-    f.close()
+    with open(filename, 'r') as f:
+        lines = f.readlines()
+
+    for i, line in enumerate(lines):
+        if line.strip().startswith('---') and 'SOIL TYPES' in line.upper():
+            break
+
+    # Extract used labels from the SOIL TYPES section
+    for line in lines[i+3:]:
+        if '---' in line:
+            break
+        entries = line.strip().split()
+        label = entries[0]
+        used_labels.append(label); print(label)
+
+    if soil_mode == 'uniform':
+        var_names = lines[i+1].split()
+        for line in lines[i+3:]:
+            if '---' in line:
+                break
+            entries = line.strip().split()
+            label = entries[0]
+            soilProps[label] = {}
+            for iv, var in enumerate(var_names[1:]):
+                val = entries[iv+1]
+                soilProps[label][var] = [float(val)] if val != '-' else [0.0]
+
+    elif soil_mode == 'layered':
+        if profile_source is None:
+            raise ValueError("profile_source (path to YAML) is required for layered mode.")
+
+        # Load the full YAML file of profiles
+        with open(profile_source, 'r') as f:
+            all_profiles = yaml.safe_load(f)
+
+        # Reassign each label to the actual layer list directly
+        for label in used_labels:
+            if label not in all_profiles:
+                raise KeyError(f'Profile ID {label} not found in YAML: {profile_source}')
+            soilProps[label] = all_profiles[label]['layers']  # now a list of layer dicts
+
+        print(f"[DEBUG] Loaded profiles from YAML: {list(soilProps.keys())}")
+        if used_labels:
+            print(f"[DEBUG] Example layers for {used_labels[0]}: {soilProps[used_labels[0]]}")
+        else:
+            print("[WARNING] No profile labels were found in the soil grid.")
+
+
+    else:
+        raise ValueError(f"Unrecognized soil_mode '{soil_mode}'")
 
     return soilProps
 
diff --git a/tests/mooring_ontology.yaml b/tests/mooring_ontology.yaml
index aa06dd1d..f5da3059 100644
--- a/tests/mooring_ontology.yaml
+++ b/tests/mooring_ontology.yaml
@@ -152,7 +152,7 @@ mooring_connector_types:
 # Anchor type properties
 anchor_types:
   suction_pile1:
-    type   :  suction_pile
+    type   :  suction
     L      :     16.4  # length of pile [m]
     D      :     5.45  # diameter of pile [m]
     zlug   :     9.32  # embedded depth of padeye [m]
\ No newline at end of file
diff --git a/tests/mooring_ontology_parallels.yaml b/tests/mooring_ontology_parallels.yaml
index e98647ae..92794cd7 100644
--- a/tests/mooring_ontology_parallels.yaml
+++ b/tests/mooring_ontology_parallels.yaml
@@ -170,7 +170,7 @@ mooring_connector_types:
 # Anchor type properties
 anchor_types:
   suction_pile1:
-    type   :  suction_pile
+    type   :  suction
     L      :     16.4  # length of pile [m]
     D      :     5.45  # diameter of pile [m]
     zlug   :     9.32  # embedded depth of padeye [m]
\ No newline at end of file
diff --git a/tests/platform_ontology.yaml b/tests/platform_ontology.yaml
index f43a97a9..be7dd26b 100644
--- a/tests/platform_ontology.yaml
+++ b/tests/platform_ontology.yaml
@@ -1239,7 +1239,7 @@ mooring_line_types:
 # Anchor type properties
 anchor_types:
   suction_pile1:
-    type   :  suction_pile
+    type   :  suction
     L      :     16.4  # length of pile [m]
     D      :     5.45  # diameter of pile [m]
     zlug   :     9.32  # embedded depth of padeye [m]
\ No newline at end of file
diff --git a/tests/simple_farm.yaml b/tests/simple_farm.yaml
index c05945de..db5a46e4 100644
--- a/tests/simple_farm.yaml
+++ b/tests/simple_farm.yaml
@@ -1166,7 +1166,7 @@ platform:
         rB        :  [ 0, 0,  15]              # [m]    and B coordinates
         shape     :  circ                      # [-]    circular or rectangular
         gamma     :  0.0                       # [deg]  twist angle about the member's z-axis
-        potMod    :  True                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
+        potMod    :  False                     # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
         # --- outer shell including hydro---
         stations  :  [0, 1]                    # [-]    location of stations along axis. Will be normalized such that start value maps to rA and end value to rB
         d         :  10.0                      # [m]    diameters if circular or side lengths if rectangular (can be pairs)
@@ -1189,7 +1189,7 @@ platform:
         heading   :  [ 60, 180, 300]           # [deg]  heading rotation of column about z axis (for repeated members)
         shape     :  circ                      # [-]    circular or rectangular
         gamma     :  0.0                       # [deg]  twist angle about the member's z-axis
-        potMod    :  True                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
+        potMod    :  False                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
         # --- outer shell including hydro---
         stations  :  [0, 35]                   # [-]    location of stations along axis. Will be normalized such that start value maps to rA and end value to rB
         d         :  12.5                      # [m]    diameters if circular or side lengths if rectangular (can be pairs)
diff --git a/tests/testOntology.yaml b/tests/testOntology.yaml
index 2c1eb1d0..5f645bb9 100644
--- a/tests/testOntology.yaml
+++ b/tests/testOntology.yaml
@@ -32,27 +32,53 @@ site:
         file:   #'../bathymetry200m_sample.txt'
     
     seabed:
-        x : [-1901,    0,    1900]
-        y : [-1900,     2,  1900 ]
+        x : [-1901,    0,    1900 ]
+        y : [-1900,    2,    1900 ]
         
         type_array:
           - [mud_soft ,  mud_firm ,   mud_soft]  
-          - [mud_soft ,  mud_soft     ,   mud_soft]  
+          - [mud_soft ,  mud_soft ,   mud_soft]  
           - [mud_soft ,  mud_firm ,   mud_soft]  
-
-        soil_types:   # dictionary-based approach
-          mud_soft:
-            Su0 : [2.39]  # [kPa]
-            k : [1.41]    # [kPa/m]
-            depth: [0]    # [m]
-          mud_firm:
-            Su0 : [23.94] # [kPa]
-            k : [2.67]    # [kPa/m]
-            depth: [0]    # [m]
-          rock:
-            UCS : [7]     # [MPa]
-            Em  : [50]    # [MPa]
-            depth: [0]    # [m]   
+    
+        soil_types:  
+           mud_soft:
+            layers: 
+            - soil_type: clay
+              top: 0
+              bottom: 50
+              gamma_top: 10.0
+              gamma_bot: 10.0
+              Su_top: 2.39
+              Su_bot: 59.39
+           mud_firm:
+            layers:
+            - soil_type: clay            
+              top: 0
+              bottom: 50
+              gamma_top: 10.0
+              gamma_bot: 50.0
+              Su_top: 23.4
+              Su_bot: 157.44
+           sand: 
+            layers:
+            - soil_type: sand           
+              top: 1
+              bottom: 50
+              gamma_top: 8.5
+              gamma_bot: 8.5
+              phi_top: 28.0
+              phi_bot: 32.00
+              Dr_top: 50.0
+              Dr_bot: 85.00               
+           weak_rock:
+            layers:
+            - soil_type: rock
+              top: 0
+              bottom: 50
+              UCS_top: 5.0
+              UCS_bot: 5.0
+              Em_top: 7.0
+              Em_bot: 7.0 
     
     metocean:
         extremes:  # extreme values for specified return periods (in years)
@@ -82,7 +108,7 @@ site:
             -  [    10.5,         0,            0.01,    operating,          0,        JONSWAP,         12,         6,         0       ]
 
     RAFT_settings:   
-        min_freq     :  0.001    #  [Hz]       lowest frequency to consider, also the frequency bin width     
+        min_freq     :  0.001   #  [Hz]       lowest frequency to consider, also the frequency bin width     
         max_freq     :  0.10    #  [Hz]       highest frequency to consider
         XiStart      :   0      # sets initial amplitude of each DOF for all frequencies
         nIter        :   4      # sets how many iterations to perform in Model.solveDynamics()
@@ -1220,7 +1246,7 @@ platforms:
         rB        :  [ 0, 0,  15]              # [m]    and B coordinates
         shape     :  circ                      # [-]    circular or rectangular
         gamma     :  0.0                       # [deg]  twist angle about the member's z-axis
-        potMod    :  True                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
+        potMod    :  False                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
         # --- outer shell including hydro---
         stations  :  [0, 1]                    # [-]    location of stations along axis. Will be normalized such that start value maps to rA and end value to rB
         d         :  10.0                      # [m]    diameters if circular or side lengths if rectangular (can be pairs)
@@ -1243,7 +1269,7 @@ platforms:
         heading   :  [ 60, 180, 300]           # [deg]  heading rotation of column about z axis (for repeated members)
         shape     :  circ                      # [-]    circular or rectangular
         gamma     :  0.0                       # [deg]  twist angle about the member's z-axis
-        potMod    :  True                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
+        potMod    :  False                      # [bool] Whether to model the member with potential flow (BEM model) plus viscous drag or purely strip theory
         # --- outer shell including hydro---
         stations  :  [0, 35]                   # [-]    location of stations along axis. Will be normalized such that start value maps to rA and end value to rB
         d         :  12.5                      # [m]    diameters if circular or side lengths if rectangular (can be pairs)
@@ -1492,17 +1518,17 @@ mooring_connector_types:
 # Anchor type properties
 anchor_types:
   suction_pile1:
-    type   :  suction_pile
+    type   :  suction
     L      :     16.4  # length of pile [m]
     D      :     5.45  # diameter of pile [m]
     zlug   :     9.32  # embedded depth of padeye [m]
   d-g_pile1:
-    type   :  dandg_pile
+    type   :  dandg
     L      :     50 # length of pile [m]
     D      :     3 # diameter of pile [m]
     zlug   :     0 # embedded depth [m]
   driven_pile1:
-    type   :  driven_pile
+    type   :  driven
     L      :     20 # pile length [m]
     D      :     1.5 # pile diameter [m]
     zlug   :     3 # embedded depth [m
@@ -1512,14 +1538,14 @@ anchor_types:
     zlug : 10
     #beta: 30
   torpedo_pile1:
-    type: torpedo_pile 
+    type: torpedo 
     D1 : 3
     D2: 1.1
     L1: 10
     L2: 4
     zlug: 16
   helical_pile1:
-    type: helical_pile
+    type: helical
     L : 25.1
     d : 1
     D : 5.01
diff --git a/tests/test_anchors.py b/tests/test_anchors.py
index ae177770..d97e57c2 100644
--- a/tests/test_anchors.py
+++ b/tests/test_anchors.py
@@ -5,6 +5,20 @@
 import matplotlib.pyplot as plt
 import pytest
 
+# --- Helper goes at module level ---
+def assign_soil(anchor, soil_label, project):
+    soil_def = project.soilProps[soil_label]
+    layers = soil_def['layers']
+    # print('[DEBUG] assign_soil: soil_label =', soil_label)
+    # print('[DEBUG] assign_soil: soil_def =', soil_def)
+    profile_map = [{
+        'name': 'CPT_Assigned',
+        'x': 0, 'y': 0,
+        'layers': layers}]
+    
+    anchor.setSoilProfile(profile_map)
+    anchor.profile_name = 'CPT_Assigned'
+
 @pytest.fixture
 def project():
     dir = os.path.dirname(os.path.realpath(__file__))
@@ -14,91 +28,135 @@ def test_anchor_loads(project):
     # load in famodel project 
     project.getMoorPyArray(cables=1)
     anch = project.anchorList['FOWT1a']
+   
+    assign_soil(anch, 'mud_soft', project)
     
-    # get lug loads on anchor
-    anch.getLugForces(plot=False)
+    # Force calculation
+    anch.getMudlineForces(max_force=False)
     
-    assert('Ha' in anch.loads)
-    assert('Hm' in anch.loads)
-    assert(anch.loads['Ha'] != anch.loads['Hm'])
+    # Extract mudline loads
+    Hm = anch.loads.get('Hm')
+    Vm = anch.loads.get('Vm')
+    zlug = anch.dd['design']['zlug']
+
+    # Compute lug loads
+    _, Ha, Va = anch.getLugForces(Hm, Vm, zlug, plot=False)
+    anch.loads['Ha'] = Ha
+    anch.loads['Va'] = Va
 
+    # Assertions
+    assert 'Ha' in anch.loads
+    assert 'Hm' in anch.loads
+    assert anch.loads['Ha'] != anch.loads['Hm']
+    
 def test_anchor_capacities(project):
     # load in famodel project (suction pile anchor)
     project.getMoorPyArray(cables=1)
     anch = project.anchorList['FOWT1a']
+
+    assign_soil(anch, 'mud_firm', project)
     
     # fill in load dictionary to skip watch circle run
-    loads = {'Ha':4522222,'Va':3948278}
+    loads = {'Ha':4.5e6, 'Va':1.9e6}
     # get capacity and safety factor
-    anch.getAnchorCapacity(loads=loads, plot=False)
-    anch.getFS(loads=loads)
-    
-    # try suction pile with sand
-    soil = anch.soilProps
-    soil['sand'] = soil.pop(next(iter(soil.keys())))
-    soil['sand']['phi'] = 33
-    soil['sand']['Dr'] = 50
+    Ha = loads['Ha']
+    Va = loads['Va']
+    zlug = anch.dd['design']['zlug']
+    anch.getCapacityAnchor(Ha, Va, zlug=zlug, plot=False)
+    anch.getSafetyFactor()
+
+    # try SUCTION PILE with sand
+    assign_soil(anch, 'sand', project)
     # get capacity and safety factor
-    anch.getAnchorCapacity(loads=loads, plot=False)
-    anch.getFS(loads=loads)
-    
-    # check plate anchor type   
-    newdd = anch.dd
-    newdd['type'] = 'plate'
-    newdd['design'] = {'type':'plate','A':20,'zlug':10,'beta':10}
-    anch.soilProps['clay'] = anch.soilProps.pop('sand')
-    # new loads
-    loads['Ha'] = 1000000
+    Ha = loads['Ha']
+    Va = loads['Va']
+    zlug = anch.dd['design']['zlug']
+    anch.getCapacityAnchor(Ha, Va, zlug=zlug, plot=False)
+    anch.getSafetyFactor()
+    
+    # check PLATE ANCHOR type   
+    anch.dd['type'] = 'plate'
+    anch.dd['design'] = {'B':5, 'L':2, 'zlug':10, 'beta':10}
+    assign_soil(anch, 'mud_soft', project)
+    # new horizontal load
+    loads['Ha'] = 2e6
     loads['Va'] = 0
+    Ha = loads['Ha']
+    Va = loads['Va']
+    zlug = anch.dd['design']['zlug']
     # get capacity and safety factor
-    anch.getAnchorCapacity(loads=loads, plot=False)
-    anch.getFS(loads=loads)
-    
-    # check drilled and grouted anchor type (need to change material to rock)
-    loads = {'Ha':4522222,'Va':3948278} # go back to original loads    
-    newdd['type'] = 'dandg_pile'
-    newdd['design'] = {'type':'dandg_pile','L':50,'D':3,'zlug':0}
-    soil['rock'] = soil.pop('clay') # soil_properties has default rock info in there already, just change name
-    anch.getAnchorCapacity(loads=loads, plot=False)
-    anch.getFS(loads=loads)
-    
-    # check driven pile anchor in rock and clay
-    newdd['type'] = 'driven'
-    soil['weak_rock'] = soil.pop('rock')
-    newdd['design'] = {'type':'driven','L':20,'D':1.5,'zlug':-3}
-    anch.getAnchorCapacity(loads=loads, plot=False)
-    anch.getFS(loads=loads)
-    
-    soil['clay'] = soil.pop('weak_rock')
-    newdd['design'] = {'type':'driven','L':30,'D':2,'zlug':3}
-    anch.getAnchorCapacity(loads=loads, plot=False)
-    anch.getFS(loads=loads)
-    
-    soil['sand'] = soil.pop('clay')
-    anch.getAnchorCapacity(loads=loads, plot=False)
-    anch.getFS(loads=loads)
-    soil['sand']['Dr'] = 50
-    
-    # check helical pile anchor with sand
-    newdd['type'] = 'helical_pile'
-    newdd['design'] = {'type':'helical_pile','L':25.1,'d':1,'D':5.01,'zlug':5}
-    anch.getAnchorCapacity(loads=loads, plot=False)
-    anch.getFS(loads=loads)
-    
-    # check helical pile anchor with clay
-    soil['clay'] = soil.pop('sand')
-    newdd['type'] = 'helical_pile'
-    newdd['design'] = {'type':'helical_pile','L':25.1,'d':1,'D':5.01,'zlug':5}
-    anch.getAnchorCapacity(loads=loads, plot=False)
-    anch.getFS(loads=loads)
-    
-    # check torpedo anchor
-    newdd['type'] = 'torpedo_pile'
-    newdd['design'] = {'type':'torpedo_pile','D1':3,'D2':1.1,'L1':10,'L2':4,'zlug':16}
-    anch.getAnchorCapacity(loads=loads, plot=False)
-    anch.getFS(loads=loads)
-    
+    anch.getCapacityAnchor(Ha, Va, zlug=zlug, plot=False)
+    anch.getSafetyFactor()
+       
+    # check DRILLED & GROUTED PILE (need to change material to rock)
+    loads = {'Ha':4.5e5, 'Va':1.9e5} # again assign new loads    
+    anch.dd['type'] = 'drilled'
+    anch.dd['design'] = {'L':10, 'D':3, 'zlug':0}
+    assign_soil(anch, 'weak_rock', project)
+    Ha = loads['Ha']
+    Va = loads['Va']
+    zlug = anch.dd['design']['zlug']
+    anch.getCapacityAnchor(Ha, Va, zlug=zlug, plot=False)
+    anch.getSafetyFactor()
+    
+    # check DRIVEN PILES in soils and rock
+    anch.dd['type'] = 'driven'
+    anch.dd['design'] = {'L':20, 'D':1.5, 'zlug': 3}
+    assign_soil(anch, 'mud_firm', project)
+    Ha = loads['Ha']
+    Va = loads['Va']
+    zlug = anch.dd['design']['zlug']
+    anch.getCapacityAnchor(Ha, Va, zlug=zlug, plot=False)
+    anch.getSafetyFactor()
+    
+    anch.dd['design'] = {'L':30, 'D':2, 'zlug':3}
+    assign_soil(anch, 'sand', project)
+    Ha = loads['Ha']
+    Va = loads['Va']
+    zlug = anch.dd['design']['zlug']
+    anch.getCapacityAnchor(Ha, Va, zlug=zlug, plot=False)
+    anch.getSafetyFactor()
+    
+    assign_soil(anch, 'weak_rock', project)
+    Ha = loads['Ha']
+    Va = loads['Va']
+    # change the padeye back to mudline elevation in rock
+    anch.dd['design']['zlug'] = 0
+    zlug = anch.dd['design']['zlug'] 
+    anch.getCapacityAnchor(Ha, Va, zlug=zlug, plot=False)
+    anch.getSafetyFactor()
+       
+    # check HELICAL PILE with sand
+    anch.dd['type'] = 'helical'
+    anch.dd['design'] = {'L':15, 'd':1.25, 'D':2.00, 'zlug':3}
+    assign_soil(anch, 'sand', project)
+    Ha = loads['Ha']
+    Va = loads['Va']
+    zlug = anch.dd['design']['zlug']
+    anch.getCapacityAnchor(Ha, Va, zlug=zlug, plot=False)
+    anch.getSafetyFactor()
+    
+    # check HELICAL PILE with clay
+    anch.dd['type'] = 'helical'
+    anch.dd['design'] = {'L':12, 'd':0.5, 'D':1.5, 'zlug':3}
+    assign_soil(anch, 'mud_firm', project)
+    Ha = loads['Ha']
+    Va = loads['Va']
+    zlug = anch.dd['design']['zlug']
+    anch.getCapacityAnchor(Ha, Va, zlug=zlug, plot=False)
+    anch.getSafetyFactor()
+    
+    # check TORPEDO PILE
+    anch.dd['type'] = 'torpedo'
+    anch.dd['design'] = {'D1':3, 'D2':1.1, 'L1':10, 'L2':4, 'zlug':16}
+    assign_soil(anch, 'mud_soft', project)
+    Ha = loads['Ha']
+    Va = loads['Va']
+    zlug = anch.dd['design']['zlug']
+    anch.getCapacityAnchor(Ha, Va, zlug=zlug, plot=False)
+    anch.getSafetyFactor()
     
+