--- 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. type: reference version: 1.0.0 updated: 2026-01-17 category: engineering triggers: - extreme analysis - max tension - linked statistics - extreme values - design loads - maximum response - associated values - peak extraction capabilities: [] requires: [] tags: [] scripts_exempt: true --- # Orcaflex Extreme Analysis ## 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 `digitalmodel` package installed - Knowledge of variables to extract (object names, variable names) ## Python API ### Basic Linked Statistics ```python from digitalmodel.orcaflex.opp_linkedstatistics import OPPLinkedStatistics # Initialize extractor extractor = OPPLinkedStatistics() # Configure extraction config = { "primary": { "object": "Mooring_Line_1", *See sub-skills for full details.* ### Direct OrcFxAPI Usage ```python 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 *See sub-skills for full details.* ### Batch Extreme Analysis ```python from digitalmodel.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() *See sub-skills for full details.* ### Range Graph Extremes ```python from digitalmodel.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 *See sub-skills for full details.* ## Related Skills - [orcaflex-post-processing](../orcaflex-post-processing/SKILL.md) - General post-processing - [orcaflex-operability](../orcaflex-operability/SKILL.md) - Multi-sea-state analysis - [orcaflex-results-comparison](../orcaflex-results-comparison/SKILL.md) - Compare multiple results - [fatigue-analysis](../fatigue-analysis/SKILL.md) - 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` ## Sub-Skills - [Basic Extreme Extraction (+1)](basic-extreme-extraction/SKILL.md) - [Variable Selection (+2)](variable-selection/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) - [Linked Statistics (+1)](linked-statistics/SKILL.md) - [Linked Statistics CSV (+1)](linked-statistics-csv/SKILL.md) - [1. Design Load Identification (+2)](1-design-load-identification/SKILL.md)