Fast Numerical Methods for Stochastic Computations: A Review

被引:0
|
作者
Xiu, Dongbin [1 ]
机构
[1] Purdue Univ, Dept Math, W Lafayette, IN 47907 USA
关键词
Stochastic differential equations; generalized polynomial chaos; uncertainty quantification; spectral methods; PARAMETRIC UNCERTAINTY ANALYSIS; GENERALIZED POLYNOMIAL CHAOS; WEIGHTED INTEGRAL METHOD; FINITE-ELEMENTS; DIFFERENTIAL-EQUATIONS; ELLIPTIC PROBLEMS; RESPONSE VARIABILITY; MODELING UNCERTAINTY; RANDOM-FIELDS; SIMULATION;
D O I
暂无
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
This paper presents a review of the current state-of-the-art of numerical methods for stochastic computations. The focus is on efficient high-order methods suitable for practical applications, with a particular emphasis on those based on generalized polynomial chaos (gPC) methodology. The framework of gPC is reviewed, along with its Galerkin and collocation approaches for solving stochastic equations. Properties of these methods are summarized by using results from literature. This paper also attempts to present the gPC based methods in a unified framework based on an extension of the classical spectral methods into multi-dimensional random spaces.
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页码:242 / 272
页数:31
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