WIAS Preprint No. 1911, (2013)

A convergent adaptive stochastic Galerkin finite element method with quasi-optimal spatial meshes



Authors

  • Eigel, Martin
    ORCID: 0000-0003-2687-4497
  • Gittelson, Claude Jeffrey
  • Schwab, Christoph
  • Zander, Elmar

2010 Mathematics Subject Classification

  • 65N30

Keywords

  • generalized polynomial chaos, adaptive Finite Element Methods, contraction property, residual a-posteriori error estimation, uncertainty quantification

DOI

10.20347/WIAS.PREPRINT.1911

Abstract

We analyze a-posteriori error estimation and adaptive refinement algorithms for stochastic Galerkin Finite Element methods for countably-parametric elliptic boundary value problems. A residual error estimator which separates the effects of gpc-Galerkin discretization in parameter space and of the Finite Element discretization in physical space in energy norm is established. It is proved that the adaptive algorithm converges, and to this end we establish a contraction property satisfied by its iterates. It is shown that the sequences of triangulations which are produced by the algorithm in the FE discretization of the active gpc coefficients are asymptotically optimal. Numerical experiments illustrate the theoretical results.

Appeared in

  • ESAIM Math. Model. Numer. Anal., 49 (2015) pp. 1367--1398.

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