2007.126: Efficient Solvers for a Linear Stochastic Galerkin Mixed Formulation of Diffusion Problems with Random Data
2007.126: O.G. Ernst, C.E Powell, D.J. Silvester and E. Ullmann (2009) Efficient Solvers for a Linear Stochastic Galerkin Mixed Formulation of Diffusion Problems with Random Data. SIAM Journal of Scientific Computing, 31 (2). pp. 1424-1447.
Full text available as:
 | PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader 1643 Kb |
DOI: 10.1137/070705817
Abstract
We introduce a stochastic Galerkin mixed formulation of the steady-state diffusion equation and focus on the efficient iterative solution of the saddle-point systems obtained by combining standard finite element discretisations with two distinct types of stochastic basis functions. So-called mean-based preconditioners, based on fast solvers for scalar diffusion problems, are introduced for use with the minimum residual method. We derive eigenvalue bounds for the preconditioned system matrices and report on the efficiency of the chosen preconditioning schemes with respect to all the discretisation parameters
| Item Type: | Article |
|---|---|
| Subjects: | MSC 2000 > 15 Linear and multilinear algebra; matrix theory MSC 2000 > 65 Numerical analysis |
| MIMS number: | 2007.126 |
| Deposited By: | Dr C.E. Powell |
| Deposited On: | 11 February 2009 |
Download Statistics: last 4 weeks
Repository Staff Only: edit this item