Low rank solution of unsteady diffusion equations with stochastic coefficients / Peter Benner, Akwum Onwunta, Martin Stoll
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870492039
URN
urn:nbn:de:gbv:3:2-64248
DOI
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Autorin / Autor
Beiträger
Erschienen
Magdeburg : Max Planck Institute for Dynamics of Complex Technical Systems, August 12, 2013
Umfang
1 Online-Ressource (23 Seiten = 0,44 MB)
Ausgabevermerk
Sprache
eng
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Inhaltliche Zusammenfassung
Abstract: We study the solution of linear systems resulting from the discreitization of unsteady diffusion equations with stochastic coefficients. In particular, we focus on those linear systems that are obtained using the so-called stochastic Galerkin finite element method (SGFEM). These linear systems are usually very large with Kronecker product structure and, thus, solving them can be both time- and computer memory-consuming. Under certain assumptions, we show that the solution of such linear systems can be approximated with a vector of low tensor rank. We then solve the linear systems using low rank preconditioned iterative solvers. Numerical experiments demonstrate that these low rank preconditioned solvers are effective.
Schriftenreihe
Max Planck Institute Magdeburg Preprints ; 13-13 ppn:870173030