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首页> 外文期刊>Physics of fluids >Successive inverse polynomial interpolation to optimize Smagorinsky's model for large-eddy simulation of homogeneous turbulence
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Successive inverse polynomial interpolation to optimize Smagorinsky's model for large-eddy simulation of homogeneous turbulence

机译:连续逆多项式插值可优化Smagorinsky模型,用于大涡模拟均质湍流

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We propose the successive inverse polynomial interpolation method to optimize model parameters in subgrid parameterization for large-eddy simulation. This approach is illustrated for the Smagorinsky eddy-viscosity model used in homogeneous decaying turbulence. The optimal Smagorinsky parameter is resolution dependent and provides minimal total error in the resolved kinetic energy. It is approximated by starting with a "bracketing interval" that is obtained from separate "no-model" and "dynamic eddy-viscosity" large-eddy simulations. The total error level is reduced 3-6 times compared to the maximal initial errors. The computational overhead of the full optimization at resolution N-3 is comparable to a single simulation at (3N/2)(3) grid cells. The increased accuracy is higher than obtained with dynamic modeling at a resolution of (4N)(3). (c) 2006 American Institute of Physics.
机译:我们提出了连续逆多项式插值方法来优化大涡流仿真的子网格参数化中的模型参数。对于在均质衰减湍流中使用的Smagorinsky涡粘性模型,已说明了该方法。最佳Smagorinsky参数取决于分辨率,并且在解析动能方面提供了最小的总误差。通过从单独的“无模型”和“动态涡流-粘度”大涡流模拟获得的“包围间隔”开始进行近似。与最大初始错误相比,总错误级别减少了3到6倍。分辨率为N-3时,完全优化的计算开销可与(3N / 2)(3)网格单元处的单个模拟相比。在(4N)(3)的分辨率下,提高的精度比通过动态建模获得的精度更高。 (c)2006年美国物理研究所。

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