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
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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