Cluster-based generalized multiscale finite element method for elliptic PDEs with random coefficients

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Original languageEnglish
Pages (from-to)606-617
Journal / PublicationJournal of Computational Physics
Publication statusPublished - 15 Oct 2018
Externally publishedYes


We propose a generalized multiscale finite element method (GMsFEM) based on clustering algorithm to study the elliptic PDEs with random coefficients in the multi-query setting. Our method consists of offline and online stages. In the offline stage, we construct a small number of reduced basis functions within each coarse grid block, which can then be used to approximate the multiscale finite element basis functions. In addition, we coarsen the corresponding random space through a clustering algorithm. In the online stage, we can obtain the multiscale finite element basis very efficiently on a coarse grid by using the pre-computed multiscale basis. The new GMsFEM can be applied to multiscale SPDE starting with a relatively coarse grid, without requiring the coarsest grid to resolve the smallest-scale of the solution. The new method offers considerable savings in solving multiscale SPDEs. Numerical results are presented to demonstrate the accuracy and efficiency of the proposed method for several multiscale stochastic problems without scale separation.

Research Area(s)

  • Clustering algorithm, Generalized multiscale finite element method (GMsFEM), Karhunen–Loève expansion, Multiscale basis functions, Stochastic partial differential equations (SPDEs), Uncertainty quantification (UQ)

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