orcaflex-rao-import

Import RAO (Response Amplitude Operator) data from external sources including AQWA, OrcaFlex, and CSV files. Includes validation, interpolation, and conversion for OrcaFlex vessel type creation.

5 stars

Best use case

orcaflex-rao-import is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Import RAO (Response Amplitude Operator) data from external sources including AQWA, OrcaFlex, and CSV files. Includes validation, interpolation, and conversion for OrcaFlex vessel type creation.

Teams using orcaflex-rao-import 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

$curl -o ~/.claude/skills/rao-import/SKILL.md --create-dirs "https://raw.githubusercontent.com/vamseeachanta/workspace-hub/main/.agents/skills/engineering/marine-offshore/orcaflex/rao-import/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/rao-import/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How orcaflex-rao-import Compares

Feature / Agentorcaflex-rao-importStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Import RAO (Response Amplitude Operator) data from external sources including AQWA, OrcaFlex, and CSV files. Includes validation, interpolation, and conversion for OrcaFlex vessel type creation.

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

# Orcaflex Rao Import

## When to Use

- Import RAOs from ANSYS AQWA analysis
- Extract RAOs from existing OrcaFlex models
- Import RAOs from experimental data (CSV/Excel)
- Validate RAO data quality
- Interpolate RAOs to new frequency/heading grids
- Create OrcaFlex vessel types with imported RAOs

## Python API

### Basic RAO Import

```python
from digitalmodel.marine_ops.marine_analysis.rao_processor import RAOProcessor

# Initialize processor
processor = RAOProcessor()

# Import from AQWA
rao_data = processor.import_from_aqwa(
    file_path="data/vessel.lis",
    vessel_name="FPSO"

*See sub-skills for full details.*
### AQWA File Reading

```python
from digitalmodel.marine_ops.marine_analysis.aqwa_reader import AQWAReader

# Initialize reader
reader = AQWAReader()

# Read AQWA .lis file
aqwa_data = reader.read_lis_file("data/vessel_aqwa.lis")

# Extract motion RAOs

*See sub-skills for full details.*
### OrcaFlex RAO Reading

```python
from digitalmodel.marine_ops.marine_analysis.orcaflex_reader import OrcaFlexRAOReader

# Initialize reader
reader = OrcaFlexRAOReader()

# Read from OrcaFlex model
rao_data = reader.read_from_model("models/vessel_model.yml")

# Or read from vessel type definition
rao_data = reader.read_vessel_type("data/vessel_types/fpso_type.yml")
```
### RAO Validation

```python
from digitalmodel.marine_ops.marine_analysis.rao_validators import RAOValidator

# Initialize validator
validator = RAOValidator()

# Define validation limits
limits = {
    "surge": 10.0,
    "sway": 10.0,

*See sub-skills for full details.*
### RAO Interpolation

```python
from digitalmodel.marine_ops.marine_analysis.rao_interpolator import RAOInterpolator

# Initialize interpolator
interpolator = RAOInterpolator()

# Define target grid
target_frequencies = np.linspace(0.02, 2.0, 100)
target_headings = np.arange(0, 181, 15)


*See sub-skills for full details.*
### Export to OrcaFlex Format

```python
from digitalmodel.marine_ops.marine_analysis.rao_processor import RAOProcessor

processor = RAOProcessor()

# Export to OrcaFlex YAML format
processor.export_to_orcaflex(
    rao_data,
    output_file="vessel_type.yml",
    vessel_name="FPSO_RAOs",

*See sub-skills for full details.*
### Complete Workflow

```python
from digitalmodel.marine_ops.marine_analysis.rao_processor import RAOProcessor
from digitalmodel.marine_ops.marine_analysis.rao_validators import RAOValidator
from digitalmodel.marine_ops.marine_analysis.rao_interpolator import RAOInterpolator

# 1. Import RAOs
processor = RAOProcessor()
raw_raos = processor.import_from_aqwa("data/vessel.lis")

# 2. Validate

*See sub-skills for full details.*

## Related Skills

- [orcaflex-modeling](../orcaflex-modeling/SKILL.md) - Apply imported RAOs
- [orcawave/analysis](../orcawave/analysis/SKILL.md) - Generate RAOs from diffraction
- [aqwa-analysis](../aqwa-analysis/SKILL.md) - AQWA-specific processing
- [hydrodynamics](../hydrodynamics/SKILL.md) - Hydrodynamic coefficient management

## References

- OrcaFlex: Vessel Type RAO Data
- ANSYS AQWA: Output File Formats
- Source: `src/digitalmodel/modules/marine_analysis/rao_processor.py`
- Source: `src/digitalmodel/modules/marine_analysis/aqwa_reader.py`
- Source: `src/digitalmodel/modules/marine_analysis/orcaflex_reader.py`
- User Story: `.ai/specs/modules/user-story-rao-data-import-processing-2025.md`

## Sub-Skills

- [Basic Import Configuration (+1)](basic-import-configuration/SKILL.md)
- [Data Quality (+2)](data-quality/SKILL.md)

## Sub-Skills

- [Error Handling](error-handling/SKILL.md)

## Sub-Skills

- [Version Metadata](version-metadata/SKILL.md)
- [[1.0.0] - 2026-01-17](100-2026-01-17/SKILL.md)
- [Supported Formats](supported-formats/SKILL.md)
- [6-DOF Motion RAOs](6-dof-motion-raos/SKILL.md)
- [OrcaFlex YAML Format (+2)](orcaflex-yaml-format/SKILL.md)
- [AQWA Import (+1)](aqwa-import/SKILL.md)

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