关于应用于高对比度多尺度介质中平流-扩散的广义多尺度有限元方法的时间积分器

IF 2.1 2区 数学 Q1 MATHEMATICS, APPLIED
Wei Xie , Juan Galvis , Yin Yang , Yunqing Huang
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引用次数: 0

摘要

尽管最近在处理高对比度多尺度环境下的平流-扩散问题方面取得了进展,但仍然需要在不影响精度的前提下加快计算速度的方法。在本文中,我们考虑了存在多尺度高对比度介质的非稳态扩散-平流问题所面临的挑战。我们使用广义多尺度法(GMsFEM)作为空间离散化方法,并对时间求解器给予了特别关注。传统有限差分法的精度和稳定性在高对比度和平流项的情况下会下降。继 Contreras 等人(2023 年)之后,我们使用指数积分器来处理时间依赖性,充分发挥了广义多尺度方法的优势。对于以扩散为主的情况,我们的方法与之前的工作一致。但是,在平流开始占主导地位的情况下,我们引入了一个不同的局部广义特征值问题来构建多尺度基础函数。由于基函数保留了更多与平流项相关的信息,因此这一调整提高了效率。我们将通过实验来证明我们提出的方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On time integrators for Generalized Multiscale Finite Element Methods applied to advection–diffusion in high-contrast multiscale media
Despite recent progress in dealing with advection–diffusion problems in high-contrast multiscale settings, there is still a need for methods that speed up calculations without compromising accuracy. In this paper, we consider the challenges of unsteady diffusion–advection problems in the presence of multiscale high-contrast media. We use the Generalized Multiscale Method (GMsFEM) as the space discretization and pay extra attention to the time solver. Traditional finite-difference methods’ accuracy and stability deteriorate in the presence of high contrast and also with an advection term. Following Contreras et al. (2023), we use exponential integrators to handle the time dependence, fully utilizing the advantages of the generalized multiscale method. For situations dominated by diffusion, our approach aligns with previous work. However, in cases where advection starts to dominate, we introduce a different local generalized eigenvalue problem to build the multiscale basis functions. This adjustment makes things more efficient since the basis functions retain more information related to the advection term. We present experiments to demonstrate the effectiveness of our proposed method.
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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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