具有非均质迪里希勒边界条件的不可压缩流动的三步缺陷校正稳定算法

IF 1.7 3区 数学 Q2 MATHEMATICS, APPLIED
Bo Zheng, Yueqiang Shang
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引用次数: 0

摘要

基于速度和压力近似的双网格离散和二次等阶有限元,我们开发了不可压缩纳维-斯托克斯方程的三步缺陷校正稳定算法,其中考虑了非均质迪里夏特边界条件,并允许高雷诺数。在这一开发的算法中,我们首先在粗网格上通过缺陷步骤求解一个人工粘度稳定非线性问题,然后通过在细网格上通过修正步骤求解两个稳定和线性化问题来修正所产生的残差。细网格修正问题的刚度矩阵相同,只是右侧不同。我们使用变分多尺度方法来稳定系统,使得该算法在高雷诺数流动模拟中具有广泛的应用潜力。在弱唯一性条件下,我们给出了本算法的稳定性分析,分析了近似解的误差边界,并推导出了算法参数标度。最后,我们通过一系列数值示例展示了所提算法的前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A three-step defect-correction stabilized algorithm for incompressible flows with non-homogeneous Dirichlet boundary conditions

Based on two-grid discretizations and quadratic equal-order finite elements for the velocity and pressure approximations, we develop a three-step defect-correction stabilized algorithm for the incompressible Navier-Stokes equations, where non-homogeneous Dirichlet boundary conditions are considered and high Reynolds numbers are allowed. In this developed algorithm, we first solve an artificial viscosity stabilized nonlinear problem on a coarse grid in a defect step and then correct the resulting residual by solving two stabilized and linearized problems on a fine grid in correction steps. While the fine grid correction problems have the same stiffness matrices with only different right-hand sides. We use a variational multiscale method to stabilize the system, making the algorithm has a broad range of potential applications in the simulation of high Reynolds number flows. Under the weak uniqueness condition, we give a stability analysis of the present algorithm, analyze the error bounds of the approximate solutions, and derive the algorithmic parameter scalings. Finally, we perform a series of numerical examples to demonstrate the promise of the proposed algorithm.

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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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