A rotational pressure-correction discontinuous Galerkin scheme for the Cahn-Hilliard-Darcy-Stokes system

IF 1.7 3区 数学 Q2 MATHEMATICS, APPLIED Advances in Computational Mathematics Pub Date : 2024-05-30 DOI:10.1007/s10444-024-10151-6
Meiting Wang, Guang-an Zou, Jian Li
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Abstract

This paper is devoted to the numerical approximations of the Cahn-Hilliard-Darcy-Stokes system, which is a combination of the modified Cahn-Hilliard equation with the Darcy-Stokes equation. A novel discontinuous Galerkin pressure-correction scheme is proposed for solving the coupled system, which can achieve the desired level of linear, fully decoupled, and unconditionally energy stable. The developed scheme here is implemented by combining several effective techniques, including by adding an additional stabilization term artificially in Cahn-Hilliard equation for balancing the explicit treatment of the coupling term, the stabilizing strategy for the nonlinear energy potential, and a rotational pressure-correction scheme for the Darcy-Stokes equation. We rigorously prove the unique solvability, unconditional energy stability, and optimal error estimates of the proposed scheme. Finally, a number of numerical examples are provided to demonstrate numerically the efficiency of the present formulation.

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卡恩-希利亚德-达西-斯托克斯系统的旋转压力校正非连续伽勒金方案
本文致力于 Cahn-Hilliard-Darcy-Stokes 系统的数值近似,该系统是修正的 Cahn-Hilliard 方程与 Darcy-Stokes 方程的组合。为求解该耦合系统,提出了一种新颖的非连续 Galerkin 压力校正方案,该方案可达到理想的线性、完全解耦和无条件能量稳定水平。本文开发的方案是通过结合几种有效技术实现的,包括在卡恩-希利亚德方程中人为添加额外的稳定项以平衡耦合项的显式处理、非线性能量势的稳定策略以及达西-斯托克斯方程的旋转压力校正方案。我们严格证明了所提方案的唯一可解性、无条件能量稳定性和最优误差估计。最后,我们提供了一些数值示例,从数值上证明了本方案的效率。
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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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