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Comparative study of projection schemes for stochastic finite element analysis

Comparative study of projection schemes for stochastic finite element analysis
Comparative study of projection schemes for stochastic finite element analysis
We present a comparison of subspace projection schemes for stochastic finite element analysis in terms of accuracy and computational efficiency. More specifically, we compare the polynomial chaos projection scheme with reduced basis projection schemes based on the preconditioned stochastic Krylov subspace. Numerical studies are presented for two problems: (1) static analysis of a plate with random Young’s modulus and (2) settlement of a foundation supported on a randomly heterogeneous soil. Monte Carlo simulation results based on exact structural analysis are used to generate benchmark results against which the projection schemes are compared. We show that stochastic reduced basis methods require significantly less computer memory and execution time compared to the polynomial chaos approach, particularly for large-scale problems with many random variables. For the class of problems considered, we find that stochastic reduced basis methods can be up to orders of magnitude faster, while providing results of comparable or better accuracy.
stochastic finite element analysis, projection schemes, polynomial chaos, stochastic reduced basis methods
0045-7825
2371-2392
Sachdeva, Sachin K.
40692b50-50e3-4e78-a464-86475be62053
Nair, Prasanth B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Keane, Andy J.
26d7fa33-5415-4910-89d8-fb3620413def
Sachdeva, Sachin K.
40692b50-50e3-4e78-a464-86475be62053
Nair, Prasanth B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Keane, Andy J.
26d7fa33-5415-4910-89d8-fb3620413def

Sachdeva, Sachin K., Nair, Prasanth B. and Keane, Andy J. (2006) Comparative study of projection schemes for stochastic finite element analysis. Computer Methods in Applied Mechanics and Engineering, 195 (19-22), 2371-2392. (doi:10.1016/j.cma.2005.05.010).

Record type: Article

Abstract

We present a comparison of subspace projection schemes for stochastic finite element analysis in terms of accuracy and computational efficiency. More specifically, we compare the polynomial chaos projection scheme with reduced basis projection schemes based on the preconditioned stochastic Krylov subspace. Numerical studies are presented for two problems: (1) static analysis of a plate with random Young’s modulus and (2) settlement of a foundation supported on a randomly heterogeneous soil. Monte Carlo simulation results based on exact structural analysis are used to generate benchmark results against which the projection schemes are compared. We show that stochastic reduced basis methods require significantly less computer memory and execution time compared to the polynomial chaos approach, particularly for large-scale problems with many random variables. For the class of problems considered, we find that stochastic reduced basis methods can be up to orders of magnitude faster, while providing results of comparable or better accuracy.

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Published date: 2006
Keywords: stochastic finite element analysis, projection schemes, polynomial chaos, stochastic reduced basis methods

Identifiers

Local EPrints ID: 23315
URI: http://eprints.soton.ac.uk/id/eprint/23315
ISSN: 0045-7825
PURE UUID: ec1e8d6f-8560-4514-aadb-e9ecec410c76
ORCID for Andy J. Keane: ORCID iD orcid.org/0000-0001-7993-1569

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Date deposited: 15 Mar 2006
Last modified: 16 Mar 2024 02:53

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Contributors

Author: Sachin K. Sachdeva
Author: Prasanth B. Nair
Author: Andy J. Keane ORCID iD

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