Adaptive multiscale model reduction with Generalized Multiscale Finite Element Methods

被引：163

作者：

Chung, Eric ^{[1
]}

Efendiev, Yalchin ^{[2
]}

Hou, Thomas Y. ^{[3
]}

机构：

[1] Chinese Univ Hong Kong, Dept Math, Shatin, Hong Kong, Peoples R China

[2] Texas A&M Univ, Dept Math, College Stn, TX 77843 USA

[3] CALTECH, Appl & Computat Math 9 94, Pasadena, CA 91125 USA

来源：

JOURNAL OF COMPUTATIONAL PHYSICS | 2016年 / 320卷

基金：

美国国家科学基金会;

关键词：

Multiscale; Multiscale finite element method; Heterogeneous media; Porous media; Numerical homogenization; DOMAIN DECOMPOSITION PRECONDITIONERS; ELLIPTIC PROBLEMS; EMPIRICAL INTERPOLATION; FLOW; HOMOGENIZATION;

D O I：

10.1016/j.jcp.2016.04.054

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, we discuss a general multiscale model reduction framework based on multiscale finite element methods. We give a brief overview of related multiscale methods. Due to page limitations, the overview focuses on a few related methods and is not intended to be comprehensive. We present a general adaptive multiscale model reduction framework, the Generalized Multiscale Finite Element Method. Besides the method's basic outline, we discuss some important ingredients needed for the method's success. We also discuss several applications. The proposed method allows performing local model reduction in the presence of high contrast and no scale separation. (C) 2016 Elsevier Inc. All rights reserved.

引用

页码：69 / 95

页数：27

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