可压缩壁有界流DNS的自然网格拉伸

Alessandro Ceci, Sergio Pirozzoli
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引用次数: 0

摘要

我们提出了一种用于可压缩湍流壁有界流直接数值模拟(DNS)的物理驱动拉伸函数,该函数将均匀的近壁间距与外壁层中半局部Kolmogorov单元的均匀分辨率相结合。给定目标马赫数、雷诺数和壁温,我们的程序为网格点的数量及其分布提供了一个明确的处方,同时保证了数值精度和计算资源的合理利用。使用高速湍流边界层的DNS来评估所提出的拉伸函数的质量,这表明可以获得与通用拉伸函数相同的结果,但效率要高得多。提供了一个Python脚本来促进所提出的网格拉伸的实现。
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Natural grid stretching for DNS of compressible wall-bounded flows

We propose a physics-driven stretching function for direct numerical simulation (DNS) of compressible turbulent wall-bounded flows, which blends uniform near-wall spacing with uniform resolution in terms of semi-local Kolmogorov units in the outer wall layer. Given target Mach number, Reynolds number and wall temperature, our procedure yields a well-defined prescription for the number of grid points and their distribution which guarantee at the same time numerical accuracy and judicious exploitation of computational resources. DNS of high-speed turbulent boundary layers are used to evaluate the quality of the proposed stretching function, which show that one can achieve identical results as with general-purpose stretching functions, however with substantially higher efficiency. A Python script is provided to facilitate implementation of the proposed grid stretching.

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来源期刊
Journal of Computational Physics: X
Journal of Computational Physics: X Physics and Astronomy-Physics and Astronomy (miscellaneous)
CiteScore
6.10
自引率
0.00%
发文量
7
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