采用双压缩方案对可压缩混合层进行数值建模

Q3 Mathematics
M. D. Bragin
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引用次数: 0

摘要

摘要 在可压缩导热流体的情况下,考虑了 Navier-Stokes 方程的双紧凑方案。该方案采用物理过程分割法构建,在空间上具有四阶近似性,在时间上具有二阶近似性。针对双曲方程和抛物方程的双紧凑方案,推导出了两种不同数值解表示之间转换的新保守公式。测试了双紧凑方案的并行执行是否具有很强的可扩展性。双约束方案应用于对流马赫数为 0.4 和 0.8 的混合层的三维直接数值模拟。在计算的流动中,湍流混合区得到了详细的解析,并充分再现了实验中观察到的现象。计算结果与其他学者的模拟结果在数量上有很好的一致性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Numerical Modeling of Compressible Mixing Layers with a Bicompact Scheme

Numerical Modeling of Compressible Mixing Layers with a Bicompact Scheme

Abstract

A bicompact scheme for the Navier–Stokes equations is considered in the case of a compressible heat-conducting fluid. The scheme is constructed using splitting by physical processes and it has the fourth order of approximation in space and the second order of approximation in time. New, conservative formulas are derived for transitions between two different representations of the numerical solution in bicompact schemes for hyperbolic and parabolic equations. The parallel implementation of the bicompact scheme is tested for strong scalability. The bicompact scheme is applied to the three-dimensional direct numerical simulation of the mixing layer with convective Mach numbers of 0.4 and 0.8. In the calculated flows, the zone of turbulent mixing is resolved in detail, and the phenomena observed in experiments are adequately reproduced. Good quantitative agreement is demonstrated with the simulations carried out by other authors.

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来源期刊
Mathematical Models and Computer Simulations
Mathematical Models and Computer Simulations Mathematics-Computational Mathematics
CiteScore
1.20
自引率
0.00%
发文量
99
期刊介绍: Mathematical Models and Computer Simulations  is a journal that publishes high-quality and original articles at the forefront of development of mathematical models, numerical methods, computer-assisted studies in science and engineering with the potential for impact across the sciences, and construction of massively parallel codes for supercomputers. The problem-oriented papers are devoted to various problems including industrial mathematics, numerical simulation in multiscale and multiphysics, materials science, chemistry, economics, social, and life sciences.
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