Stochastic Galerkin techniques for random ordinary differential equations

F. Augustin, P. Rentrop

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

Over the last decade the stochastic Galerkin method has become an established method to solve differential equations involving uncertain parameters. It is based on the generalized Wiener expansion of square integrable random variables. Although there exist very sophisticated variants of the stochastic Galerkin method (wavelet basis, multi-element approach) convergence for random ordinary differential equations has rarely been considered analytically. In this work we develop an asymptotic upper boundary for the L2-error of the stochastic Galerkin method. Furthermore, we prove convergence of a local application of the stochastic Galerkin method and confirm convergence of the multi-element approach within this context.

Original languageEnglish
Pages (from-to)399-419
Number of pages21
JournalNumerische Mathematik
Volume122
Issue number3
DOIs
StatePublished - Nov 2012
Externally publishedYes

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