斯托克斯-达西耦合问题的基于局部投影的统一稳定虚拟元素法

IF 1.7 3区 数学 Q2 MATHEMATICS, APPLIED
Sudheer Mishra, E. Natarajan
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引用次数: 0

摘要

在这项工作中,我们针对多边形网格上带有 Beavers-Joseph-Saffman 接口条件的斯托克斯-达西耦合问题提出并分析了一种新的稳定虚拟元素方法。我们推导出了耦合斯托克斯-达西问题的两种局部投影稳定方法。基于局部投影的稳定项的重要意义在于,它们能对斯托克斯流的压力分量进行合理控制,而不涉及高阶导数项。针对涉及速度、水头和压力的等阶虚拟元素三元组,建立了斯托克斯-达西耦合问题的离散 inf-sup 条件。在能量和(L^2\)规范中使用等阶虚拟元素得出了最优误差估计值。所提出的方法有以下几个优点:质量保证、避免了求解成分的耦合、更易于实现、可在混合多边形元素上高效执行。我们进行了数值实验来描述所提方法的灵活性,验证了理论结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A unified local projection-based stabilized virtual element method for the coupled Stokes-Darcy problem

In this work, we propose and analyze a new stabilized virtual element method for the coupled Stokes-Darcy problem with Beavers-Joseph-Saffman interface condition on polygonal meshes. We derive two variants of local projection stabilization methods for the coupled Stokes-Darcy problem. The significance of local projection-based stabilization terms is that they provide reasonable control of the pressure component of the Stokes flow without involving higher-order derivative terms. The discrete inf-sup condition of the coupled Stokes-Darcy problem is established for the equal-order virtual element triplets involving velocity, hydraulic head, and pressure. The optimal error estimates are derived using the equal-order virtual elements in the energy and \(L^2\) norms. The proposed methods have several advantages: mass conservative, avoiding the coupling of the solution components, more accessible to implement, and performing efficiently on hybrid polygonal elements. Numerical experiments are conducted to depict the flexibility of the proposed methods, validating the theoretical results.

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来源期刊
CiteScore
3.00
自引率
5.90%
发文量
68
审稿时长
3 months
期刊介绍: Advances in Computational Mathematics publishes high quality, accessible and original articles at the forefront of computational and applied mathematics, with a clear potential for impact across the sciences. The journal emphasizes three core areas: approximation theory and computational geometry; numerical analysis, modelling and simulation; imaging, signal processing and data analysis. This journal welcomes papers that are accessible to a broad audience in the mathematical sciences and that show either an advance in computational methodology or a novel scientific application area, or both. Methods papers should rely on rigorous analysis and/or convincing numerical studies.
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