Poly-Sinc Solution of Stochastic Elliptic Differential Equations

被引:0
|
作者
Maha Youssef
Roland Pulch
机构
[1] University of Greifswald,Institute of Mathematics and Computer Science
来源
Journal of Scientific Computing | 2021年 / 87卷
关键词
Poly-Sinc methods; Collocation method; Galerkin method; Stochastic differential equations; Polynomial chaos; Legendre polynomials; 65N35; 65N12; 65N30; 65C20; 35R60;
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摘要
In this paper, we introduce a numerical solution of a stochastic partial differential equation (SPDE) of elliptic type using polynomial chaos along side with polynomial approximation at Sinc points. These Sinc points are defined by a conformal map and when mixed with the polynomial interpolation, it yields an accurate approximation. The first step to solve SPDE is to use stochastic Galerkin method in conjunction with polynomial chaos, which implies a system of deterministic partial differential equations to be solved. The main difficulty is the higher dimensionality of the resulting system of partial differential equations. The idea here is to solve this system using a small number of collocation points in space. This collocation technique is called Poly-Sinc and is used for the first time to solve high-dimensional systems of partial differential equations. Two examples are presented, mainly using Legendre polynomials for stochastic variables. These examples illustrate that we require to sample at few points to get a representation of a model that is sufficiently accurate.
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