An iterative projection method for unsteady Navier–Stokes equations with high Reynolds numbers

IF 2.1 3区 数学 Q2 MATHEMATICS, APPLIED
Xiaoming Zheng, Kun Zhao, Jiahong Wu, Weiwei Hu, Dapeng Du
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引用次数: 0

Abstract

A new iterative projection method is proposed to solve the unsteady Navier–Stokes equations with high Reynolds numbers. The convectional projection method attempts to project the intermediate velocity to the divergence-free space only once per time step. However, such a velocity is not genuinely divergence-free in general practice, which can yield large errors when the Reynolds number is high. The new method has several important features: the BDF2 time discretization, the skew-symmetric convection in a semi-implicit form, two modulating parameters, and the iterative projections in each time step. A major difficulty in the proof of iteration convergence is the nonlinear convection. We solve this problem by first analyzing the non-convective scheme with a focus on the spectral properties of the iterative matrix and then employing a delicate perturbation analysis for the convective scheme. The work achieves the weakly divergence-free velocity (strongly divergence-free for divergence-free finite element spaces) and the rigorous stability and error analysis when the iterations converge The three-dimensional numerical tests confirm that this new method can effectively treat high Reynolds numbers with only a few iterations per time, where the convectional projection method and the iterative projection method with the explicit convection would fail.

高雷诺数非定常Navier-Stokes方程的迭代投影法
提出了一种新的求解高雷诺数非定常Navier-Stokes方程的迭代投影法。对流投影法试图将中间速度每时间步长只投影一次到无散度空间。然而,在一般实践中,这样的速度并不是真正无散度的,当雷诺数很高时,散度会产生很大的误差。该方法具有BDF2时间离散化、半隐式偏对称对流、两个调制参数和每个时间步长的迭代投影等重要特点。证明迭代收敛性的一个主要困难是非线性对流。我们首先分析了非对流格式,重点分析了迭代矩阵的谱性质,然后对对流格式进行了精细的微扰分析,从而解决了这个问题。本文实现了弱无散度速度(无散度有限元空间为强无散度)和迭代收敛时严格的稳定性和误差分析。三维数值试验证实,该方法可以有效地处理每次迭代次数很少的高雷诺数,而对流投影法和带显对流的迭代投影法在这方面是失败的。
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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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