An Efficient Solver for the Stokes equations with Random Inputs

DOI

10.2991/citcs.2012.208How to use a DOI?

Keywords

Random inputs; Wiener-Askey polynomial chaos; Spectral methods; Exponential error convergence

Abstract

In this paper we present a high order method to solve the Stokes equations with random coefficients numerically. A stochastic Galerkin approach, based on the truncated Karhunen- Loeve decomposition technique for the stochastic inputs, is used to reduce the original stochastic Stokes equations into a set of deterministic equations for the expansion coefficients. Then a spectral collocation method, together with a block Jacobi iteration is applied to solve the resulting problem. The efficiency of the solver is verified in each model problem by numerical tests, against Monte Carlo simulations.

Copyright

© 2012, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Dong Qu
AU  - Jing Yang
PY  - 2012/11
DA  - 2012/11
TI  - An Efficient Solver for the Stokes equations with Random Inputs
BT  - Proceedings of the 2012 National Conference on Information Technology and Computer Science
PB  - Atlantis Press
SP  - 819
EP  - 822
SN  - 1951-6851
UR  - https://doi.org/10.2991/citcs.2012.208
DO  - 10.2991/citcs.2012.208
ID  - Qu2012/11
ER  -