Leveraging unstructured grids for direct numerical simulations of wall turbulence
利用非结构网格进行壁湍流直接数值模拟
Amirreza Rouhi, Vishal Kumar, Wen Wu, Melissa Kozul, Oriol Lehmkuhl
AI总结 本文提出了一种非结构网格生成框架η-grid,用于壁湍流的直接数值模拟,通过将壁法向和跨度方向的网格尺寸与局部柯尔莫戈洛夫尺度η成比例,实现了更高效的网格生成和计算。
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我们提出了一种非结构网格生成框架,用于直接数值模拟(DNSs)的壁湍流,称为η-grid,其基于将壁法向(y)和跨度方向(z)的网格尺寸与局部柯尔莫戈洛夫尺度η成比例。该框架包括一个内层,厚度约为50个粘性单位,其粘性缩放的网格尺寸类似于传统DNS网格;0.3 < Δy+ < 4,Δz+ ~ 5在光滑壁面上,而l+/30 < Δy+, Δz+ < 4在非光滑表面,其中l+是表面最小波长。在内层之上,Δy+~ Δz+ ~ 2η+。我们使用有限体积法(FVM)代码和谱元法(SEM)代码测试η-grid,并进行了湍流通道流和光滑壁面及各种肋条几何形状(如沿流线对齐的微沟槽)的DNS测试,直到摩擦雷诺数δ+0= 1000。我们评估了η-grid与传统笛卡尔网格的精度,以及参考DNS和实验数据。我们发现η-grid与笛卡尔网格在皮肤摩擦系数、平均速度、湍流应力及其频谱图上差异小于1%。在δ+0 ~ 104范围内,η-grid的网格点数(Nη)在光滑壁面上按δ+02.5比例增长,在肋条上按δ+02.0比例增长,而笛卡尔网格和双曲正切y网格(NTanh)的网格点数按δ+03.0比例增长。这导致了巨大的网格节省;当δ+0= 6000时,Nη / NTanh在光滑壁面上约为0.1,在典型降阻三角肋条(尖角60o,粘性缩放间距15)上约为0.03。
We formulate an unstructured grid-generation framework for direct numerical simulations (DNSs) of wall turbulence, termed η-grid, based on setting the wall-normal (y) and spanwise (z) grid sizes proportional to the local Kolmogorov scale η. The framework consists of an inner layer, with a thickness ~50 viscous units, with viscous-scaled grid sizes similar to a conventional DNS grid; 0.3 < Δy+ < 4, Δz+ ~ 5 over a smooth wall, and l+/30 < Δy+, Δz+ < 4 over a non-smooth surface, where l+ is the smallest surface wavelength. Above the inner layer, Δy+~ Δz+ ~ 2η+. We test η-grid with a finite volume method (FVM) code, as well as a spectral element method (SEM) code, and conduct a campaign of DNSs of turbulent channel flow and turbulent boundary layer over smooth wall and various riblet geometries (as streamwise-aligned microgrooves), up to friction Reynolds number δ+0= 1000. We assess the accuracy of the η-grid against the conventional Cartesian grids, as well as the reference DNS and experimental data. We obtain less than 1% difference between the η-grid and the Cartesian grids, in terms of skin-friction coefficient, mean velocity, turbulent stresses, and their spectrograms. Up to δ+0 ~ 104, the number of grid points with the η -grid (Nη) scales proportional to δ+02.5 over smooth wall, and proportional to δ+02.0 over riblets, whereas the number of grid points with a Cartesian grid and hyperbolic tangent y-gird (NTanh) scales proportional to δ+03.0. This leads to an enormous grid saving with the η-grid; by δ+0 = 6000, Nη / NTanh ~ 0.1 over smooth wall, and Nη / NTanh ~ 0.03 over typical drag-reducing triangular riblets with tip angle 60o, and viscous-scaled spacing 15.