Grid and basis adaptive polynomial chaos techniques for sensitivity and uncertainty analysis

DOI10.1016/j.jcp.2013.12.025zbMath1349.65027OpenAlexW2072640958MaRDI QIDQ348759

Luca Gilli, Zoltán Perkó, Jan Leen Kloosterman, Danny Lathouwers

Publication date: 5 December 2016

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jcp.2013.12.025

zbMATH Keywords

sensitivity analysisuncertainty quantificationpolynomial chaos expansiongeneralized polynomial chaosadaptive sparse gridsbasis adaptivity

Mathematics Subject Classification ID

Probabilistic models, generic numerical methods in probability and statistics (65C20) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35)

Related Items (12)

Adaptive weighted least-squares polynomial chaos expansion with basis adaptivity and sequential adaptive sampling ⋮ Classifier-based adaptive polynomial chaos expansion for high-dimensional uncertainty quantification ⋮ A nonintrusive reduced order modelling approach using proper orthogonal decomposition and locally adaptive sparse grids ⋮ An efficient adaptive forward-backward selection method for sparse polynomial chaos expansion ⋮ Variance-based adaptive sequential sampling for polynomial chaos expansion ⋮ On the parametric uncertainty quantification of the Rothermel's rate of spread model ⋮ Convergence Analysis and Adaptive Order Selection for the Polynomial Chaos Approach to Direct Optimal Control under Uncertainties ⋮ Sequential Stochastic Response Surface Method Using Moving Least Squares-Based Sparse Grid Scheme for Efficient Reliability Analysis ⋮ Extreme value oriented random field discretization based on an hybrid polynomial chaos expansion -- Kriging approach ⋮ Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark ⋮ Efficient aerodynamic analysis and optimization under uncertainty using multi-fidelity polynomial chaos-Kriging surrogate model ⋮ Multigroup-like MC resolution of generalised polynomial chaos reduced models of the uncertain linear Boltzmann equation (+discussion on hybrid intrusive/non-intrusive uncertainty propagation)

Uses Software

• Matlab

Cites Work

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