Sudheer Mishra, E. Natarajan, Sundararajan Natarajan
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引用次数: 0
摘要
本文研究了在一般多边形网格上利用等阶虚元对稳定不可压缩流体Navier-Stokes方程的方法。我们提出了一个基于残差的类supg稳定项来解决导致压力不稳定的离散不稳定条件的违反,并减轻对流主导状态的影响。此外,我们还采用了梯度稳定项来解决无发散约束的违反问题。我们推广了(López-Marcos和Sanz-Serna, IMA J. number中导出的非线性稳定性的概念。数学学报。8(1),71-84,1998)。根据Lopez-Marcos & Sanz-Serna的结果,我们利用非奇异解的分支建立了能量范数的适定性和最优收敛估计。我们进行了几个数值实验来验证理论结果。
A SUPG-stabilized virtual element method for the Navier–Stokes equation: approximations of branches of non-singular solutions
In this paper, we investigate a stabilization technique for the Navier–Stokes equations for incompressible fluid flow using equal-order virtual element pairs on general polygonal meshes. We propose a residual-based SUPG-like stabilization term to address the violation of the discrete inf-sup condition, which leads to pressure instability, and to mitigate the effects of the convection-dominated regime. Additionally, we employ a grad-div stabilization term to address the violation of divergence-free constraints. We extend the concept of nonlinear stability derived in (López-Marcos and Sanz-Serna, IMA J. Numer. Anal. 8(1), 71–84, 1998) to a stabilized virtual element framework. Following the results of Lopez-Marcos & Sanz-Serna, we establish the well-posedness and optimal convergence estimates in the energy norm using the branches of non-singular solutions. We perform several numerical experiments to validate the theoretical findings.
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.