Polynomial Chaos Expansion
Purpose
Provides polynomial chaos expansion methods for efficient uncertainty propagation in computational models.
Capabilities
- Generalized polynomial chaos bases
- Sparse PCE construction
- Adaptive basis selection
- PCE-based sensitivity indices
- Low-rank tensor approximation
- Stochastic Galerkin projection
Usage Guidelines
- Basis Selection: Match basis to input distributions
- Truncation: Choose appropriate polynomial order
- Sparsity: Exploit sparsity for high dimensions
- Sensitivity: Extract Sobol indices from PCE coefficients
Tools/Libraries
- Chaospy
- UQLab
- OpenTURNS