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

IF 2.1 2区 数学 Q1 MATHEMATICS, APPLIED Journal of Computational and Applied Mathematics Pub Date : 2024-09-13 DOI:10.1016/j.cam.2024.116275
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引用次数: 0

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.

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离散网络(图)模型的广义多尺度有限元法
在本文中,我们考虑了一个具有高度变化连接性的随时间变化的离散网络模型。时间近似采用隐式方案。我们提出了基于广义多尺度有限元法的网络模型粗尺度近似构造。通过求解子网络中的局部谱问题,生成精确的粗尺度近似值。对半离散和离散网络模型进行了收敛分析。我们建立了多尺度离散网络的稳定性。还给出了结构化和随机异构网络的数值结果。
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来源期刊
CiteScore
5.40
自引率
4.20%
发文量
437
审稿时长
3.0 months
期刊介绍: The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.
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