Hydrodynamics Skill

Hydrodynamics Skill

Manage hydrodynamic coefficients, wave spectra, and environmental loading for vessel and floater response analysis.

Version Metadata

version: 1.0.0
python_min_version: '3.10'
compatibility:
  tested_python:
  - '3.10'
  - '3.11'
  - '3.12'
  - '3.13'
  os:
  - Windows
  - Linux
  - macOS

Changelog

[1.0.0] - 2026-01-07

Added:

• Initial version metadata and dependency management
• Semantic versioning support
• Compatibility information for Python 3.10-3.13

Changed:

• Enhanced skill documentation structure

When to Use

• 6×6 added mass and damping matrix management
• Wave spectrum modeling (JONSWAP, Bretschneider, PM)
• OCIMF wind and current loading calculations
• RAO interpolation and frequency-dependent coefficients
• Hydrodynamic coefficient database management
• Kramers-Kronig causality validation

Prerequisites

• Python environment with digitalmodel package installed
• Hydrodynamic coefficient data (from AQWA, WAMIT, etc.)
• Environmental data for wave/​wind/​current loading

Analysis Types

1. Coefficient Database Management

Store and retrieve hydrodynamic coefficients.

hydrodynamics:
  coefficient_database:
    flag: true
    vessel_name: "FPSO"
    source_file: "data/​hydro_coefficients.json"
    coefficients:
      - added_mass
      - damping
      - wave_excitation
    output:
      database_file: "results/​coefficient_db.json"

2. Wave Spectra Modeling

Generate and analyze wave spectra.

hydrodynamics:
  wave_spectra:
    flag: true
    spectrum_type: "jonswap"  # jonswap, bretschneider, pm, custom
    parameters:
      hs: 3.5  # Significant wave height (m)
      tp: 10.0  # Peak period (s)
      gamma: 3.3  # JONSWAP peakedness
    frequency_range:
      min: 0.02
      max: 0.5
      n_points: 100
    output:
      spectrum_file: "results/​wave_spectrum.csv"
      plot_file: "results/​spectrum_plot.html"

3. OCIMF Environmental Loading

Calculate wind and current loads per OCIMF guidelines.

hydrodynamics:
  ocimf_loading:
    flag: true
    vessel:
      length: 300.0
      beam: 50.0
      draft: 20.0
      displacement: 200000
    environment:
      wind_speed: 25.0
      wind_direction: 45.0
      current_speed: 1.5
      current_direction: 90.0
    output:
      loads_file: "results/​ocimf_loads.json"

4. RAO Interpolation

Interpolate RAOs across frequencies and directions.

hydrodynamics:
  rao_interpolation:
    flag: true
    input_raos: "data/​vessel_raos.csv"
    target_frequencies: [0.05, 0.1, 0.15, 0.2, 0.25]
    target_directions: [0, 30, 60, 90, 120, 150, 180]
    method: "cubic"  # linear, cubic, spline
    output:
      interpolated_file: "results/​interpolated_raos.csv"

5. Displacement RAO Quality Checks

Validate displacement RAO data for physical correctness and consistency.

hydrodynamics:
  rao_quality_check:
    flag: true
    input_file: "data/​vessel_raos.yml"  # OrcaFlex format
    vessel_type: auto  # auto, ship, fpso, semi_submersible, spar, barge
    tolerances:
      amplitude: 0.05  # 5% tolerance
      phase: 10.0      # 10 degrees tolerance
    checks:
      - long_period_phase  # Phase angles at T → infinity
      - peak_detection     # Natural period validation
      - vessel_type_detection
    output:
      html_report: "reports/​rao_qa/​quality_report.html"
      csv_summary: "reports/​rao_qa/​quality_summary.csv"

Quality Checks:

• Long Period Phase: Validates phase angles approach expected values as period → infinity (Orcina convention)
• Peak Detection: Identifies resonance peaks and validates against vessel type natural period ranges
• Vessel Type Detection: Auto-detects vessel type from RAO characteristics with confidence score
• Active DOF Validation: Checks appropriate DOFs are active for each wave heading

Python API

Coefficient Database

from digitalmodel.modules.hydrodynamics.coefficient_database import CoefficientDatabase

# Initialize database
db = CoefficientDatabase()

# Store coefficients
db.store(
    vessel_name="FPSO",
    frequency=0.1,
    added_mass=added_mass_matrix,  # 6x6 numpy array
    damping=damping_matrix         # 6x6 numpy array
)

# Retrieve coefficients
A, B = db.get_matrices(vessel_name="FPSO", frequency=0.1)

# Get all frequencies
frequencies = db.get_frequencies("FPSO")

Frequency-Dependent Matrices

from digitalmodel.modules.hydrodynamics.freq_dependent import FrequencyDependentMatrix

# Initialize with frequency-dependent data
fdm = FrequencyDependentMatrix()
fdm.load("hydro_data.json")

# Interpolate to specific frequency
A_interp = fdm.interpolate_added_mass(frequency=0.15)
B_interp = fdm.interpolate_damping(frequency=0.15)

# Get infinite frequency added mass
A_inf = fdm.get_infinite_frequency_added_mass()

Wave Spectra

from digitalmodel.modules.hydrodynamics.wave_spectra import WaveSpectra

# Create JONSWAP spectrum
spectrum = WaveSpectra()
frequencies, S = spectrum.jonswap(
    hs=3.5,       # Significant wave height (m)
    tp=10.0,      # Peak period (s)
    gamma=3.3,    # Peakedness parameter
    freq_min=0.02,
    freq_max=0.5,
    n_points=100
)

# Alternative spectra
freq, S_pm = spectrum.pierson_moskowitz(hs=3.5, tp=10.0)
freq, S_bs = spectrum.bretschneider(hs=3.5, tp=10.0)

# Calculate spectral moments
m0 = spectrum.spectral_moment(frequencies, S, n=0)
m2 = spectrum.spectral_moment(frequencies, S, n=2)
Tz = np.sqrt(m0/​m2)  # Zero-crossing period

OCIMF Loading

from digitalmodel.modules.hydrodynamics.ocimf_loading import OCIMFLoading

# Initialize calculator
ocimf = OCIMFLoading()

# Define vessel
vessel = {
    "length": 300.0,
    "beam": 50.0,
    "draft": 20.0,
    "displacement": 200000
}

# Calculate wind load
wind_load = ocimf.wind_load(
    vessel=vessel,
    wind_speed=25.0,
    wind_direction=45.0  # degrees from bow
)
# Returns: {"Fx": ..., "Fy": ..., "Mz": ...}

# Calculate current load
current_load = ocimf.current_load(
    vessel=vessel,
    current_speed=1.5,
    current_direction=90.0
)

Coefficient Interpolation

from digitalmodel.modules.hydrodynamics.interpolator import CoefficientsInterpolator

# Initialize interpolator
interp = CoefficientsInterpolator()

# Load RAO data
interp.load_raos("vessel_raos.csv")

# Interpolate to new frequencies
new_freqs = [0.05, 0.1, 0.15, 0.2]
interpolated = interp.interpolate_frequencies(new_freqs, method="cubic")

# Interpolate to new directions
new_dirs = [0, 45, 90, 135, 180]
interpolated = interp.interpolate_directions(new_dirs)

Causality Validation

from digitalmodel.modules.hydrodynamics.validation import HydroValidator

# Initialize validator
validator = HydroValidator()

# Load frequency-dependent coefficients
validator.load_coefficients("hydro_data.json")

# Kramers-Kronig check
kk_result = validator.kramers_kronig_check()
if not kk_result["passed"]:
    print(f"Causality issues at: {kk_result['violations']}")

# Check matrix properties
sym_check = validator.check_symmetry()
pd_check = validator.check_positive_definite()

Displacement RAO Quality Checks

import yaml
from digitalmodel.modules.marine_analysis import (
    RAODataValidators,
    VesselType,
    DisplacementRAOQualityReport
)
from digitalmodel.modules.marine_analysis.rao_quality_report import RAOQualityReportGenerator

# Load OrcaFlex RAO data
with open("vessel_raos.yml", 'r') as f:
    rao_data = yaml.safe_load(f)

# Initialize validators
validators = RAODataValidators()

# Run quality check (auto-detects vessel type)
report = validators.validate_displacement_rao_quality(
    rao_data,
    source_file="vessel_raos.yml",
    vessel_type=None,  # Auto-detect, or specify VesselType.SHIP
    amplitude_tolerance=0.05,  # 5%
    phase_tolerance=10.0       # degrees
)

# Access results
print(f"Vessel Type: {report.vessel_type.value}")
print(f"Confidence: {report.vessel_type_confidence:.1%}")
print(f"Overall Status: {report.overall_status}")
print(f"Pass Rate: {report.pass_rate:.1f}%")
print(f"Total/​Passed/​Warnings/​Failed: {report.total_checks}/​{report.passed_checks}/​{report.warning_checks}/​{report.failed_checks}")

# Check phase results
for check in report.phase_checks:
    if check.status == 'FAIL':
        print(f"FAIL: {check.dof} @ {check.heading}° - {check.message}")

# Check peak detection results
for check in report.peak_checks:
    print(f"{check.dof}: Peak at {check.peak_period:.1f}s (expected {check.expected_range[0]:.1f}-{check.expected_range[1]:.1f}s)")

# Generate HTML report
generator = RAOQualityReportGenerator(output_dir="reports/​rao_qa")
html_path = generator.generate_html_report(report, report_name="vessel_quality")
print(f"HTML report: {html_path}")

# Export CSV summary
csv_path = generator.export_csv_summary(report, report_name="vessel_summary")
print(f"CSV summary: {csv_path}")

# Get active DOFs for a heading
active_dofs = RAODataValidators.get_active_dofs_for_heading(180.0)
print(f"Active DOFs at head seas: {active_dofs}")
# Output: ['surge', 'heave', 'pitch']

Wave Direction Convention:

• 0° = Head seas (waves from bow, approaching vessel)
• 90° = Beam seas from starboard
• 180° = Following seas (waves from stern)
• 270° = Beam seas from port

Expected Long Period Values (Orcina Convention):

Phase Convention Support:

• PhaseConvention.ORCINA - Phase lag from wave crest (OrcaFlex, OrcaWave)
• PhaseConvention.ISO_6954 - Phase lead over wave (AQWA, WAMIT)
• Auto-detection based on file extension (.yml → Orcina, .lis → ISO)

Key Classes

Wave Spectrum Types

Output Formats

Coefficient Database JSON

{
  "vessel_name": "FPSO",
  "frequencies_rad_s": [0.1, 0.2, 0.3],
  "added_mass": {
    "0.1": [[1.2e6, 0, 0, 0, 1.5e7, 0], ...],
    "0.2": [[1.1e6, 0, 0, 0, 1.4e7, 0], ...]
  },
  "damping": {
    "0.1": [[2.5e5, 0, 0, 0, 3.2e6, 0], ...],
    "0.2": [[2.8e5, 0, 0, 0, 3.5e6, 0], ...]
  }
}

Wave Spectrum CSV

frequency_rad_s,frequency_hz,period_s,spectral_density
0.314,0.050,20.0,0.123
0.628,0.100,10.0,2.456
0.942,0.150,6.67,1.234

Best Practices

1. Frequency range - Cover full wave spectrum of interest (typically 0.02-0.5 rad/​s)
2. Direction convention - Use consistent direction convention (from/​to, bow=0°)
3. Unit consistency - Verify units (rad/​s vs Hz, degrees vs radians)
4. Causality check - Validate coefficients with Kramers-Kronig before use
5. Matrix symmetry - Verify added mass symmetry for physical consistency

Related Skills

• diffraction-analysis - Master skill for all diffraction workflows
• aqwa-analysis - Extract coefficients from AQWA
• bemrosetta - AQWA → OrcaFlex conversion with QTF and mesh support
• orcaflex-modeling - Apply in OrcaFlex models
• viv-analysis - Hydrodynamic coefficient usage

References

• DNV-RP-C205: Environmental Conditions and Environmental Loads
• OCIMF: Mooring Equipment Guidelines
• Newman, J.N.: Marine Hydrodynamics