| name | orcaflex-mooring-iteration |
| description | Iterate mooring line lengths to achieve target pretensions using scipy optimization, Newton-Raphson, or EA-based methods. Use for mooring system design, pretension optimization, and CALM/SALM buoy configuration. |
| type | reference |
| version | 1.0.0 |
| updated | "2026-01-17T00:00:00.000Z" |
| category | engineering |
| triggers | ["mooring tension iteration","pretension optimization","line length adjustment","mooring design","target tension","tension matching","mooring optimization","CALM mooring","SALM mooring"] |
| capabilities | [] |
| requires | [] |
| tags | [] |
| scripts_exempt | true |
Orcaflex Mooring Iteration
When to Use
- Achieving target mooring line pretensions
- Optimizing line lengths for design loads
- CALM/SALM buoy mooring configuration
- Spread mooring system design
- Turret mooring optimization
- Multi-line tension balancing
- Mooring system verification
Prerequisites
- OrcaFlex license (for simulation)
- Python environment with
digitalmodel package installed
- Initial mooring model (close to target configuration)
- Target pretensions for each line
Python API
Basic Usage
from digitalmodel.orcaflex.mooring_tension_iteration import (
MooringTensionIterator,
IterationConfig,
LineConfig,
ConvergenceConfig
)
config = IterationConfig(
*See sub-skills for full details.*
```python
from digitalmodel.orcaflex.mooring_tension_iteration import (
MooringTensionIterator,
IterationConfig,
VesselConfig
)
config = IterationConfig(
method="scipy",
vessel_config=VesselConfig(
*See sub-skills for full details.*
```python
result = iterator.iterate_to_targets()
for i, error in enumerate(result.convergence_history):
print(f"Iteration {i+1}: Max error = {error:.2f}%")
import matplotlib.pyplot as plt
*See sub-skills for full details.*
```python
report = iterator.generate_report(output_path="iteration_report.txt")
(report)