Polynomial chaos expansion for sensitivity analysis

Thierry Crestaux*, Olivier Le Maître, Jean Marc Martinez

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

439 Scopus citations

Abstract

In this paper, the computation of Sobol's sensitivity indices from the polynomial chaos expansion of a model output involving uncertain inputs is investigated. It is shown that when the model output is smooth with regards to the inputs, a spectral convergence of the computed sensitivity indices is achieved. However, even for smooth outputs the method is limited to a moderate number of inputs, say 10-20, as it becomes computationally too demanding to reach the convergence domain. Alternative methods (such as sampling strategies) are then more attractive. The method is also challenged when the output is non-smooth even when the number of inputs is limited.

Original languageEnglish (US)
Pages (from-to)1161-1172
Number of pages12
JournalReliability Engineering and System Safety
Volume94
Issue number7
DOIs
StatePublished - Jul 2009
Externally publishedYes

Keywords

  • Polynomial chaos
  • Sensitivity analysis
  • Sobol's decomposition
  • Uncertainty quantification

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering
  • Applied Mathematics

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