Article (Scientific journals)
Hybrid Sampling/Spectral Method for Solving Stochastic Coupled Problems
Arnst, Maarten; Soize, Christian; Ghanem, Roger
2013In SIAM/ASA Journal on Uncertainty Quantification, 1 (1), p. 218-243
Peer reviewed
 

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Keywords :
coupled problems; multiphysics; hybrid method; Monte Carlo; polynomial chaos
Abstract :
[en] In this paper, we present a hybrid method that combines Monte Carlo sampling and spectral methods for solving stochastic coupled problems. After partitioning the stochastic coupled problem into subsidiary subproblems, the proposed hybrid method entails iterating between these subproblems in a way that enables the use of the Monte Carlo sampling method for subproblems that depend on a very large number of uncertain parameters and the use of spectral methods for subproblems that depend on only a small or moderate number of uncertain parameters. To facilitate communication between the subproblems, the proposed hybrid method shares between the subproblems a reference representation of all the solution random variables in the form of an ensemble of samples; for each subproblem solved by a spectral method, it uses a dimension-reduction technique to transform this reference representation into a subproblem-specific reduced-dimensional representation to facilitate a computationally efficient solution in a reduced-dimensional space. After laying out the theoretical framework, we provide an example relevant to microelectomechanical systems.
Disciplines :
Mechanical engineering
Author, co-author :
Arnst, Maarten ;  Université de Liège - ULiège > Département d'aérospatiale et mécanique > Computational and stochastic modeling
Soize, Christian;  Universite Paris-Est > Laboratoire de Modelisation et Simulation Multi Echelle
Ghanem, Roger;  University of Southern California > Department of Civil and Environmental Engineering
Language :
English
Title :
Hybrid Sampling/Spectral Method for Solving Stochastic Coupled Problems
Publication date :
2013
Journal title :
SIAM/ASA Journal on Uncertainty Quantification
eISSN :
2166-2525
Publisher :
Society for Industrial and Applied Mathematics
Volume :
1
Issue :
1
Pages :
218-243
Peer reviewed :
Peer reviewed
Funders :
F.R.S.-FNRS - Fonds de la Recherche Scientifique [BE]
ULiège - Université de Liège [BE]
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