Title
Iterative Solvers for the Stochastic Finite Element Method
Abstract
This paper presents an overview and comparison of iterative solvers for linear stochastic partial differential equations (PDEs). A stochastic Galerkin finite element discretization is applied to transform the PDE into a coupled set of deterministic PDEs. Specialized solvers are required to solve the very high-dimensional systems that result after a finite element discretization of the resulting set. This paper discusses one-level iterative methods, based on matrix splitting techniques; multigrid methods, which apply a coarsening in the spatial dimension; and multilevel methods, which make use of the hierarchical structure of the stochastic discretization. Also Krylov solvers with suitable preconditioning are addressed. A local Fourier analysis provides quantitative convergence properties. The efficiency and robustness of the methods are illustrated on two nontrivial numerical problems. The multigrid solver with block smoother yields the most robust convergence properties, though a cheaper point smoother performs as well in most cases. Multilevel methods based on coarsening the stochastic dimension perform in general poorly due to a large computational cost per iteration. Moderate size problems can be solved very quickly by a Krylov method with a mean-based preconditioner. For larger spatial and stochastic discretizations, however, this approach suffers from its nonoptimal convergence properties.
Year
DOI
Venue
2010
10.1137/080727026
SIAM J. Scientific Computing
Keywords
Field
DocType
krylov solvers,iterative solvers,nonoptimal convergence property,finite element discretization,stochastic galerkin finite element,stochastic discretization,stochastic discretizations,linear stochastic partial differential,stochastic finite element method,multilevel method,stochastic dimension,polynomial chaos,preconditioning,multigrid
Discretization,Mathematical optimization,Preconditioner,Mathematical analysis,Iterative method,Stochastic partial differential equation,Partial differential equation,Multigrid method,Domain decomposition methods,Numerical linear algebra,Mathematics
Journal
Volume
Issue
ISSN
32
1
1064-8275
Citations 
PageRank 
References 
9
0.64
10
Authors
2
Name
Order
Citations
PageRank
Eveline Rosseel1473.31
Stefan Vandewalle250162.63