Orcaflex Extreme Analysis
by vamseeachanta
Extract extreme response values with linked statistics from OrcaFlex
Skill Details
Repository Files
1 file in this skill directory
name: orcaflex-extreme-analysis description: Extract extreme response values with linked statistics from OrcaFlex simulations. Use for design load identification, max/min extraction with associated values, and extreme event characterization. version: 1.0.0 updated: 2026-01-17 category: offshore-engineering triggers:
- extreme analysis
- max tension
- linked statistics
- extreme values
- design loads
- maximum response
- associated values
- peak extraction
OrcaFlex Extreme Analysis Skill
Extract extreme response values with linked statistics for design load identification and extreme event characterization.
Version Metadata
version: 1.0.0
python_min_version: '3.10'
dependencies:
orcaflex-modeling: '>=2.0.0,<3.0.0'
orcaflex-post-processing: '>=1.0.0,<2.0.0'
orcaflex_version: '>=11.0'
compatibility:
tested_python:
- '3.10'
- '3.11'
- '3.12'
- '3.13'
os:
- Windows
- Linux
- macOS
Changelog
[1.0.0] - 2026-01-17
Added:
- Initial release with linked statistics extraction
- Max/min value extraction with timestamps
- Associated variable extraction at extremes
- Batch processing across multiple simulations
When to Use
- Extracting maximum/minimum values from simulations
- Identifying design loads for structural analysis
- Finding associated values at extreme events
- Characterizing vessel motions at peak tensions
- Riser curvature at maximum tension conditions
- Wave conditions at extreme responses
- Multi-variable correlation at extremes
Prerequisites
- OrcaFlex simulation results (.sim files)
- Python environment with
digitalmodelpackage installed - Knowledge of variables to extract (object names, variable names)
Key Concepts
Linked Statistics
Linked statistics capture what other variables were doing when a primary variable reached its extreme:
At time T_max when Line1.Tension = MAX:
- Vessel.Heave = ?
- Vessel.Pitch = ?
- Line1.Curvature = ?
- Wave.Elevation = ?
This enables understanding of the physical conditions that caused the extreme.
Extreme Types
| Statistic | Description |
|---|---|
Max |
Maximum value during simulation |
Min |
Minimum value during simulation |
TimeOfMax |
Time when maximum occurred |
TimeOfMin |
Time when minimum occurred |
ValueAtMax |
Primary variable's max value |
ValueAtMin |
Primary variable's min value |
LinkedValueAtMax |
Secondary variable value at primary's max time |
LinkedValueAtMin |
Secondary variable value at primary's min time |
Configuration
Basic Extreme Extraction
# configs/extreme_analysis.yml
orcaflex:
postprocess:
linked_statistics:
flag: true
# Primary variable (extremes will be found for this)
primary:
object: "Mooring_Line_1"
variable: "Effective Tension"
# Linked variables (values at primary's extremes)
linked:
- object: "Vessel"
variable: "Heave"
- object: "Vessel"
variable: "Pitch"
- object: "Vessel"
variable: "Roll"
- object: "Vessel"
variable: "X"
# Statistics to extract
statistics:
- "Max"
- "Min"
- "TimeOfMax"
- "TimeOfMin"
- "LinkedValueAtMax"
- "LinkedValueAtMin"
output:
format: csv
directory: "results/extremes/"
Multi-Object Analysis
# configs/extreme_multi_object.yml
orcaflex:
postprocess:
linked_statistics:
flag: true
# Analyze multiple primary objects
groups:
- name: "mooring_tensions"
primaries:
- object: "Leg_1"
variable: "Effective Tension"
- object: "Leg_2"
variable: "Effective Tension"
- object: "Leg_3"
variable: "Effective Tension"
linked:
- object: "CALM_Buoy"
variable: "X"
- object: "CALM_Buoy"
variable: "Y"
- name: "vessel_motions"
primaries:
- object: "Tanker"
variable: "Heave"
- object: "Tanker"
variable: "Pitch"
linked:
- object: "Hawser"
variable: "Effective Tension"
output:
format: csv
directory: "results/extremes/"
separate_files: true
Python API
Basic Linked Statistics
from digitalmodel.modules.orcaflex.opp_linkedstatistics import OPPLinkedStatistics
# Initialize extractor
extractor = OPPLinkedStatistics()
# Configure extraction
config = {
"primary": {
"object": "Mooring_Line_1",
"variable": "Effective Tension"
},
"linked": [
{"object": "Vessel", "variable": "Heave"},
{"object": "Vessel", "variable": "Pitch"},
{"object": "Vessel", "variable": "Roll"}
]
}
# Extract from simulation
results = extractor.extract_linked_statistics(
sim_file="results/mooring_analysis.sim",
config=config
)
# Access results
print(f"Max Tension: {results['Max']:.1f} kN")
print(f"Time of Max: {results['TimeOfMax']:.2f} s")
print(f"Heave at Max Tension: {results['LinkedValueAtMax']['Heave']:.2f} m")
print(f"Pitch at Max Tension: {results['LinkedValueAtMax']['Pitch']:.2f} deg")
Direct OrcFxAPI Usage
import OrcFxAPI
from pathlib import Path
def extract_extremes_with_linked(sim_file: str, config: dict) -> dict:
"""
Extract extreme values with linked statistics.
Args:
sim_file: Path to .sim file
config: Configuration dictionary
Returns:
Dictionary with extreme values and linked values
"""
model = OrcFxAPI.Model(sim_file)
# Get primary object
primary_obj = model[config["primary"]["object"]]
primary_var = config["primary"]["variable"]
# Get time history
time_history = primary_obj.TimeHistory(primary_var, period=None)
times = primary_obj.SampleTimes(period=None)
# Find extremes
max_idx = time_history.argmax()
min_idx = time_history.argmin()
results = {
"Max": float(time_history[max_idx]),
"Min": float(time_history[min_idx]),
"TimeOfMax": float(times[max_idx]),
"TimeOfMin": float(times[min_idx]),
"LinkedValueAtMax": {},
"LinkedValueAtMin": {}
}
# Extract linked values at extreme times
for linked_config in config["linked"]:
linked_obj = model[linked_config["object"]]
linked_var = linked_config["variable"]
linked_history = linked_obj.TimeHistory(linked_var, period=None)
results["LinkedValueAtMax"][linked_var] = float(linked_history[max_idx])
results["LinkedValueAtMin"][linked_var] = float(linked_history[min_idx])
return results
# Example usage
config = {
"primary": {"object": "Line1", "variable": "Effective Tension"},
"linked": [
{"object": "Vessel", "variable": "Heave"},
{"object": "Vessel", "variable": "Pitch"}
]
}
results = extract_extremes_with_linked("simulation.sim", config)
Batch Extreme Analysis
from digitalmodel.modules.orcaflex.opp_linkedstatistics import OPPLinkedStatistics
from pathlib import Path
import pandas as pd
def batch_extreme_analysis(sim_directory: str, config: dict) -> pd.DataFrame:
"""
Extract extremes from multiple simulations.
"""
extractor = OPPLinkedStatistics()
sim_files = list(Path(sim_directory).glob("*.sim"))
all_results = []
for sim_file in sim_files:
try:
results = extractor.extract_linked_statistics(
sim_file=str(sim_file),
config=config
)
results["file"] = sim_file.stem
all_results.append(results)
except Exception as e:
print(f"Error processing {sim_file}: {e}")
# Convert to DataFrame
df = pd.DataFrame(all_results)
# Find overall extremes
overall_max = df.loc[df["Max"].idxmax()]
overall_min = df.loc[df["Min"].idxmin()]
print(f"Overall Max: {overall_max['Max']:.1f} kN in {overall_max['file']}")
print(f"Overall Min: {overall_min['Min']:.1f} kN in {overall_min['file']}")
return df
# Run batch analysis
results_df = batch_extreme_analysis(
sim_directory="results/.sim/",
config=config
)
results_df.to_csv("extreme_summary.csv", index=False)
Range Graph Extremes
from digitalmodel.modules.orcaflex.opp_range_graph import OPPRangeGraph
# Extract range graph (min/max/mean along arc length)
range_extractor = OPPRangeGraph()
config = {
"object": "Riser",
"variables": ["Effective Tension", "Curvature", "Bend Moment"],
"arc_length_range": [0, 1500] # meters
}
range_data = range_extractor.extract_range_graph(
sim_file="riser_analysis.sim",
config=config
)
# Find critical location
max_curvature_idx = range_data["Curvature"]["Max"].argmax()
critical_arc_length = range_data["arc_length"][max_curvature_idx]
print(f"Maximum curvature at arc length: {critical_arc_length:.1f} m")
print(f"Curvature value: {range_data['Curvature']['Max'][max_curvature_idx]:.6f} 1/m")
Output Formats
Linked Statistics CSV
File,Primary_Object,Primary_Variable,Max,Min,TimeOfMax,TimeOfMin,Heave_AtMax,Pitch_AtMax,Roll_AtMax,Heave_AtMin,Pitch_AtMin,Roll_AtMin
case_001,Mooring_Line_1,Effective Tension,2450.5,320.1,1823.4,2156.7,3.2,-1.5,0.8,-2.1,0.9,-0.3
case_002,Mooring_Line_1,Effective Tension,2380.2,345.6,1567.2,1890.3,2.8,-1.2,0.5,-1.8,0.7,-0.2
Extreme Summary Report
{
"simulation": "mooring_100yr.sim",
"primary": {
"object": "Mooring_Line_1",
"variable": "Effective Tension",
"units": "kN"
},
"extremes": {
"maximum": {
"value": 2450.5,
"time": 1823.4,
"linked_values": {
"Vessel.Heave": 3.2,
"Vessel.Pitch": -1.5,
"Vessel.Roll": 0.8
}
},
"minimum": {
"value": 320.1,
"time": 2156.7,
"linked_values": {
"Vessel.Heave": -2.1,
"Vessel.Pitch": 0.9,
"Vessel.Roll": -0.3
}
}
}
}
Common Use Cases
1. Design Load Identification
# Find maximum tension for structural design
config = {
"primary": {"object": "Riser", "variable": "Wall Tension"},
"linked": [
{"object": "Riser", "variable": "Curvature"},
{"object": "Riser", "variable": "Bend Moment"}
]
}
results = extractor.extract_linked_statistics(sim_file, config)
design_tension = results["Max"] * 1.1 # Add 10% margin
2. VIV Characterization
# Characterize conditions at maximum amplitude
config = {
"primary": {"object": "Riser", "variable": "Max Amplitude"},
"linked": [
{"object": "Environment", "variable": "Current Velocity"},
{"object": "Riser", "variable": "Inline Frequency"}
]
}
3. Mooring Load Case
# Extract design load case for mooring
config = {
"primary": {"object": "Hawser", "variable": "Effective Tension"},
"linked": [
{"object": "Tanker", "variable": "X"},
{"object": "Tanker", "variable": "Y"},
{"object": "Tanker", "variable": "Heading"}
]
}
# Results define the design load case
Best Practices
Variable Selection
- Primary variable - Choose the most critical response
- Linked variables - Include relevant causative factors
- Physical correlation - Select variables that explain the extreme
Time Range
- Exclude ramp-up - Skip initial transient period
- Statistical period - Use 3-hour simulation for design
- Multiple seeds - Consider seed variability
Reporting
- Context - Include simulation parameters
- Units - Always specify units
- Uncertainty - Note seed sensitivity if applicable
Error Handling
try:
results = extractor.extract_linked_statistics(sim_file, config)
except OrcFxAPI.OrcaFlexError as e:
print(f"OrcaFlex error: {e}")
print("Check object names and variable specifications")
except FileNotFoundError:
print("Simulation file not found")
Related Skills
- orcaflex-post-processing - General post-processing
- orcaflex-operability - Multi-sea-state analysis
- orcaflex-results-comparison - Compare multiple results
- fatigue-analysis - Fatigue from time histories
References
- OrcaFlex Results: Linked Statistics
- OrcFxAPI Documentation
- Source:
src/digitalmodel/modules/orcaflex/opp_linkedstatistics.py - Source:
src/digitalmodel/modules/orcaflex/opp_range_graph.py
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