Stochastic finite elements: a spectral approach
Stochastic finite elements: a spectral approach
Sparse matrices in matlab: design and implementation
SIAM Journal on Matrix Analysis and Applications
An improved incomplete Cholesky factorization
ACM Transactions on Mathematical Software (TOMS)
A comparative study of sparse approximate inverse preconditioners
IMACS'97 Proceedings on the on Iterative methods and preconditioners
Incomplete Cholesky Factorizations with Limited Memory
SIAM Journal on Scientific Computing
Advances in Engineering Software - Special issue on large-scale analysis, design and intelligent synthesis environments
Iterative solution of linear systems in the 20th century
Journal of Computational and Applied Mathematics - Special issue on numerical analysis 2000 Vol. III: linear algebra
A stochastic projection method for fluid flow. I: basic formulation
Journal of Computational Physics
Computer Solution of Large Sparse Positive Definite
Computer Solution of Large Sparse Positive Definite
A stochastic projection method for fluid flow II.: random process
Journal of Computational Physics
Modeling uncertainty in flow simulations via generalized polynomial chaos
Journal of Computational Physics
Journal of Computational Physics - Special issue: Uncertainty quantification in simulation science
General purpose software for efficient uncertainty management of large finite element models
Finite Elements in Analysis and Design
Uncertainty quantification for algebraic systems of equations
Computers and Structures
Hi-index | 0.00 |
Iterative solvers and preconditioners are widely used for handling the linear system of equations arising from stochastic finite element method (SFEM) formulations, e.g. galerkin-based polynomial chaos (G-P-C) Expansion method. Especially, Preconditioned Conjugate Gradient (PCG) solver and the Incomplete Cholesky (IC) preconditioner are shown to be adequate choices within this context. In this study, approaches for the automated adjustment of the input parameters for these tools are to be introduced. The proposed algorithms aim to enable the use of the PCG solver and IC preconditioner in a black-box fashion. As a result, the requirement of the expertise for using these tools is removed to a certain extend. Furthermore, these algorithms can be used also for the implementation purposes of SFEM's within general purpose software by increasing the ease of the use of these tools and hence leading to an improved user-comfort.