用于时变平流扩散方程的 SUPG 稳定时间-DG 有限元和虚拟元

IF 6.9 1区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Computer Methods in Applied Mechanics and Engineering Pub Date : 2025-01-14 DOI:10.1016/j.cma.2024.117722
L. Beirão da Veiga , F. Dassi , S. Gómez
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引用次数: 0

摘要

将有限元或虚元空间离散化与逆风不连续Galerkin时间步进相结合,对时变平流扩散方程的完全离散格式进行了稳定性和收敛性分析。利用时空流线逆风彼得罗夫-伽辽金项稳定该方法。更准确地说,我们证明了该方法是稳定的,常数与扩散系数无关,这保证了该方法在对流和扩散占主导地位的情况下的鲁棒性。此外,对于能量范数误差,我们证明了两种情况下的最优收敛速率。所提出的分析的一个重要特征是控制在完整的L2(0,T;L2(Ω))范数中,而不需要在模型中引入人工反应项。最后给出了(3+1)维的数值实验,验证了我们的理论结果。
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SUPG-stabilized time-DG finite and virtual elements for the time-dependent advection–diffusion equation
We carry out a stability and convergence analysis for the fully discrete scheme obtained by combining a finite or virtual element spatial discretization with the upwind-discontinuous Galerkin time-stepping applied to the time-dependent advection–diffusion equation. A space–time streamline-upwind Petrov–Galerkin term is used to stabilize the method. More precisely, we show that the method is inf–sup stable with constant independent of the diffusion coefficient, which ensures the robustness of the method in the convection- and diffusion-dominated regimes. Moreover, we prove optimal convergence rates in both regimes for the error in the energy norm. An important feature of the presented analysis is the control in the full L2(0,T;L2(Ω)) norm without the need of introducing an artificial reaction term in the model. We finally present some numerical experiments in (3+1)-dimensions that validate our theoretical results.
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来源期刊
CiteScore
12.70
自引率
15.30%
发文量
719
审稿时长
44 days
期刊介绍: Computer Methods in Applied Mechanics and Engineering stands as a cornerstone in the realm of computational science and engineering. With a history spanning over five decades, the journal has been a key platform for disseminating papers on advanced mathematical modeling and numerical solutions. Interdisciplinary in nature, these contributions encompass mechanics, mathematics, computer science, and various scientific disciplines. The journal welcomes a broad range of computational methods addressing the simulation, analysis, and design of complex physical problems, making it a vital resource for researchers in the field.
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