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

Tsz Shun Eric CHUNG Yalchin Efendiev Wing Tat Leung Zhiwen Zhang

Numerical Analysis and Scientific Computing mathscidoc:1910.43558

Journal of Computational Physics, 371, 606-617, 2018.10
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
No keywords uploaded!
[ Download ] [ 2019-10-20 20:22:57 uploaded by Tsz_Shun_Eric_CHUNG ] [ 694 downloads ] [ 0 comments ]
@inproceedings{tsz2018cluster-based,
  title={Cluster-based generalized multiscale finite element method for elliptic PDEs with random coefficients},
  author={Tsz Shun Eric CHUNG, Yalchin Efendiev, Wing Tat Leung, and Zhiwen Zhang},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191020202257170042087},
  booktitle={Journal of Computational Physics},
  volume={371},
  pages={606-617},
  year={2018},
}
Tsz Shun Eric CHUNG, Yalchin Efendiev, Wing Tat Leung, and Zhiwen Zhang. Cluster-based generalized multiscale finite element method for elliptic PDEs with random coefficients. 2018. Vol. 371. In Journal of Computational Physics. pp.606-617. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191020202257170042087.
Please log in for comment!
 
 
Contact us: office-iccm@tsinghua.edu.cn | Copyright Reserved