Generalized Multiscale Finite Element Method for discrete network (graph) models

In this paper, we consider a time-dependent discrete network model with highly varying connectivity. The approximation by time is performed using an implicit scheme. We propose the coarse scale approximation construction of network models based on the Generalized Multiscale Finite Element Method . An accurate coarse-scale approximation is generated by solving local spectral problems in sub-networks. Convergence analysis of the proposed method is presented for semi-discrete and discrete network models. We establish the stability of the multiscale discrete network. Numerical results are presented for structured and random heterogeneous networks .

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Publication Details

Journal
Journal of Computational and Applied Mathematics
Published
2024-09-13
DOI
https://doi.org/10.1016/j.cam.2024.116275
Citations
5
Primary Topic
Advanced Mathematical Modeling in Engineering
Type
article
Field-Weighted Citation Impact
1.81
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article

Generalized Multiscale Finite Element Method for discrete network (graph) models

Maria Vasilyeva
5 citations
Journal of Computational and Applied Mathematics
Advanced Mathematical Modeling in Engineering
1.81
article

Generalized Multiscale Finite Element Method for discrete network (graph) models

Maria Vasilyeva
article en
5 citations

Abstract

In this paper, we consider a time-dependent discrete network model with highly varying connectivity. The approximation by time is performed using an implicit scheme. We propose the coarse scale approximation construction of network models based on the Generalized Multiscale Finite Element Method . An accurate coarse-scale approximation is generated by solving local spectral problems in sub-networks. Convergence analysis of the proposed method is presented for semi-discrete and discrete network models. We establish the stability of the multiscale discrete network. Numerical results are presented for structured and random heterogeneous networks .

Journal of Computational and Applied MathematicsVol. 457
Texas A&M University – Corpus Christi (US)
Openalex Percentile: Top 13%
Advanced Mathematical Modeling in Engineering
1.81
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