OrcaFlex Riser Sensitivity Automation
Method notes for engineering and data workflows.
The challenge
Organise the inputs, calculations and reporting into a repeatable workflow with checks.
Our Solution: OrcaFlex Batch Automation
Parametric Model Generation
Python scripts read the design matrix Excel file and automatically generated all 50 OrcaFlex model files with correct geometry, buoyancy distribution, and environmental loading combinations.
Batch Processing
Simulations are queued for batch execution.
Automated Results Extraction
Post-processing scripts extracted all required outputs (max stress, fatigue damage, effective tension, curvature) and populated standardized comparison tables automatically.
Report Generation
Final deliverable compiled automatically with sensitivity plots, optimization recommendations, and configuration comparison matrix ready for client review.
Automation Workflow
# Batch OrcaFlex Sensitivity Analysis
import orcaflex_batch as ofx
# Load design matrix from Excel
design_matrix = ofx.load_matrix("sensitivity_matrix.xlsx")
# Generate model configurations
for config in design_matrix:
model = ofx.generate_model(
base_model="SCR_baseline.dat",
tdp_offset=config['tdp_offset'],
hangoff_angle=config['hangoff_angle'],
buoyancy_length=config['buoyancy_length'],
current_profile=config['current']
)
ofx.queue_simulation(model)
# Run overnight batch
ofx.run_batch(parallel_jobs=8)
# Extract results and generate report
results = ofx.extract_all_results()
ofx.generate_sensitivity_report(results)
Technical Details
Output Parameters Extracted
- Maximum von Mises stress at critical locations
- Effective tension envelope along riser length
- Minimum bend radius and curvature
- Dynamic amplification factors
- Touch-down point excursion range
- Hang-off angle variation
- Fatigue damage at welds (per DNV-RP-C203)
Technical References
Related methods
Summary
Review the inputs, assumptions and calculation results for the stated scope.
Engineering workflows ยท Technical articles
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