hydrodynamic-pipeline-orcawave-execution
Sub-skill of hydrodynamic-pipeline: OrcaWave Execution (+3).
Best use case
hydrodynamic-pipeline-orcawave-execution is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of hydrodynamic-pipeline: OrcaWave Execution (+3).
Teams using hydrodynamic-pipeline-orcawave-execution should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/orcawave-execution/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How hydrodynamic-pipeline-orcawave-execution Compares
| Feature / Agent | hydrodynamic-pipeline-orcawave-execution | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of hydrodynamic-pipeline: OrcaWave Execution (+3).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# OrcaWave Execution (+3)
## OrcaWave Execution
```bash
# OrcaWave runs via OrcFxAPI (same as OrcaFlex)
python3 -c "
import OrcFxAPI
model = OrcFxAPI.Model()
model.LoadData('diffraction_model.owd')
model.CalculateStatics()
model.RunSimulation()
model.SaveSimulation('results.owr')
"
```
## AQWA Execution
```bash
# AQWA runs via ANSYS Workbench or command line
# Typical AQWA-LINE execution:
aqwa_line input.dat output.lis
# AQWA-DRIFT for QTFs:
aqwa_drift input.dat output.lis
```
## Key Outputs from Diffraction Analysis
| Output | Format | Used By | Description |
|--------|--------|---------|-------------|
| **RAOs** | .owd / .lis | OrcaFlex VesselType | Response amplitude operators (6 DOF) |
| **Added mass** | Frequency-dependent | OrcaFlex | Mass added by fluid acceleration |
| **Radiation damping** | Frequency-dependent | OrcaFlex | Energy radiated as waves |
| **Mean drift** | Force per wave amplitude² | OrcaFlex | Steady drift forces |
| **QTFs** | Difference/sum frequency | OrcaFlex | Second-order slow-drift forces |
| **Hydrostatic stiffness** | 6x6 matrix | OrcaFlex | Restoring forces |
## Extracting Results for OrcaFlex
```python
import OrcFxAPI
def extract_diffraction_results(owd_path):
"""Extract hydrodynamic data from OrcaWave for OrcaFlex.
OrcaWave results are accessed via VesselType diffraction data,
not the Vessel instance directly.
"""
model = OrcFxAPI.Model()
model.LoadSimulation(owd_path.replace('.owd', '.owr'))
# Access vessel type (diffraction data lives on VesselType, not Vessel)
vessel_type = model['Vessel Type1']
results = {
"raos": {},
"added_mass": {},
"damping": {},
}
# Extract RAOs via VesselType hydrodynamic database
# RAO data is loaded via VesselType.LoadHydrodynamicData() or
# accessed after OrcaWave populates the vessel type
dof_names = ['Surge', 'Sway', 'Heave', 'Roll', 'Pitch', 'Yaw']
for i, dof in enumerate(dof_names):
results["raos"][dof] = {
"amplitude": [],
"phase": [],
}
# Note: exact accessor depends on OrcaWave version; see
# orcawave-to-orcaflex skill for the canonical extraction pattern
return results
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