Automate OrcaFlex marine simulations via Python API for mooring, riser,
Scanned 9/9/2026
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---
name: orcaflex-specialist
version: 1.0.0
category: engineering
description: Automate OrcaFlex marine simulations via Python API for mooring, riser,
and installation analysis
type: reference
capabilities: []
requires: []
tags: []
scripts_exempt: true
---
# Orcaflex Specialist
## When to Use This Skill
Use this skill when you need to:
- Automate OrcaFlex model creation and analysis
- Build parametric OrcaFlex models via Python API
- Perform batch simulations with varying parameters
- Extract and process time series results
- Validate OrcaFlex models against design criteria
- Integrate OrcaFlex with external tools and workflows
- Optimize mooring and riser configurations
- Conduct sensitivity studies and Monte Carlo simulations
## Core Knowledge Areas
### 1. OrcaFlex Python API Basics
Connecting to OrcaFlex and basic model operations:
```python
import OrcFxAPI
import numpy as np
from pathlib import Path
from typing import List, Dict, Optional
def create_new_model(
general_data: dict,
*See sub-skills for full details.*
### 2. Building Models Programmatically
Create complex models via Python API:
```python
def create_vessel_model(
vessel_params: dict,
mooring_config: dict,
environment: dict
) -> OrcFxAPI.Model:
"""
Create complete vessel model with moorings and environment.
*See sub-skills for full details.*
### 3. Results Extraction and Post-Processing
Extract time series and perform analysis:
```python
def extract_time_series(
model: OrcFxAPI.Model,
object_name: str,
variable_name: str,
object_extra: OrcFxAPI.OrcaFlexObjectExtra = OrcFxAPI.oeEndA,
period: OrcFxAPI.SpecifiedPeriod = OrcFxAPI.SpecifiedPeriod(OrcFxAPI.pnWholeSimulation)
) -> tuple:
*See sub-skills for full details.*
### 4. Batch Simulation and Parametric Studies
Automate multiple simulation runs:
```python
def batch_simulation(
base_model_path: Path,
parameter_sets: List[dict],
output_dir: Path,
parallel: bool = False
) -> List[dict]:
"""
*See sub-skills for full details.*
### 5. Model Validation and QA
Automated model checking:
```python
def validate_model(
model: OrcFxAPI.Model,
checks: List[str] = None
) -> dict:
"""
Comprehensive model validation checks.
*See sub-skills for full details.*
### 6. Advanced Analysis Techniques
```python
def extreme_response_analysis(
model_path: Path,
sea_states: List[dict],
response_variable: tuple,
method: str = 'most_probable_maximum'
) -> dict:
"""
Extreme response analysis using irregular wave simulations.
*See sub-skills for full details.*
## Complete Examples
### Example 1: Automated Mooring Analysis Workflow
```python
from pathlib import Path
import OrcFxAPI
import numpy as np
import pandas as pd
def complete_mooring_analysis_workflow(
vessel_params: dict,
mooring_config: dict,
environment: dict,
*See sub-skills for full details.*
## Resources
### OrcaFlex Documentation
- **OrcaFlex Help**: Built-in help system (F1 in OrcaFlex)
- **Python API Reference**: OrcaFlex installation → Python folder → OrcFxAPIDocumentation.html
- **Example Scripts**: OrcaFlex → Examples → Python folder
- **Orcina Website**: https://www.orcina.com/resources/
### Training and Support
- **Orcina Training Courses**: Official OrcaFlex training
- **User Forum**: https://www.orcina.com/forums/
- **Technical Support**: support@orcina.com
### Related Standards
- **DNV-RP-C205**: Environmental Conditions and Environmental Loads
- **DNV-RP-F205**: Global Performance Analysis of Deepwater Floating Structures
- **API RP 2SM**: Recommended Practice for Design, Manufacture, Installation, and Maintenance of Synthetic Fiber Ropes
- **API RP 2SK**: Design and Analysis of Stationkeeping Systems for Floating Structures
### Additional Resources
- Noble Denton (2013). *OrcaFlex Training Manual*
- Orcina (2023). *OrcaFlex Manual Version 11.4*
- Various industry webinars and tutorials on YouTube
---
**Use this skill for:** Expert-level OrcaFlex modeling, automation, and analysis for offshore marine simulations with full Python API integration.
## Sub-Skills
- [1. Model Organization (+2)](1-model-organization/SKILL.md)
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