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Auteurs principaux: Wan, Xiaoliang, Yu, Haijun
Format: Preprint
Publié: 2018
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Accès en ligne:https://arxiv.org/abs/1810.04849
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_version_ 1866913130910580736
author Wan, Xiaoliang
Yu, Haijun
author_facet Wan, Xiaoliang
Yu, Haijun
contents In this work, we consider a non-standard preconditioning strategy for the numerical approximation of the classical elliptic equations with log-normal random coefficients. In \cite{Wan_model}, a Wick-type elliptic model was proposed by modeling the random flux through the Wick product. Due to the lower-triangular structure of the uncertainty propagator, this model can be approximated efficiently using the Wiener chaos expansion in the probability space. Such a Wick-type model provides, in general, a second-order approximation of the classical one in terms of the standard deviation of the underlying Gaussian process. Furthermore, when the correlation length of the underlying Gaussian process goes to infinity, the Wick-type model yields the same solution as the classical one. These observations imply that the Wick-type elliptic equation can provide an effective preconditioner for the classical random elliptic equation under appropriate conditions. We use the Wick-type elliptic model to accelerate the Monte Carlo method and the stochastic Galerkin finite element method. Numerical results are presented and discussed.
format Preprint
id arxiv_https___arxiv_org_abs_1810_04849
institution arXiv
publishDate 2018
record_format arxiv
spellingShingle Numerical approximation of elliptic problems with log-normal random coefficients
Wan, Xiaoliang
Yu, Haijun
Numerical Analysis
60H35, 65N30
In this work, we consider a non-standard preconditioning strategy for the numerical approximation of the classical elliptic equations with log-normal random coefficients. In \cite{Wan_model}, a Wick-type elliptic model was proposed by modeling the random flux through the Wick product. Due to the lower-triangular structure of the uncertainty propagator, this model can be approximated efficiently using the Wiener chaos expansion in the probability space. Such a Wick-type model provides, in general, a second-order approximation of the classical one in terms of the standard deviation of the underlying Gaussian process. Furthermore, when the correlation length of the underlying Gaussian process goes to infinity, the Wick-type model yields the same solution as the classical one. These observations imply that the Wick-type elliptic equation can provide an effective preconditioner for the classical random elliptic equation under appropriate conditions. We use the Wick-type elliptic model to accelerate the Monte Carlo method and the stochastic Galerkin finite element method. Numerical results are presented and discussed.
title Numerical approximation of elliptic problems with log-normal random coefficients
topic Numerical Analysis
60H35, 65N30
url https://arxiv.org/abs/1810.04849