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首页> 外文期刊>Bulletin of the American Physical Society >APS -70th Annual Meeting of the APS Division of Fluid Dynamics- Event - Modeling rough-wall turbulent channel flow with principal component analysis enhanced amplitude modulation
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APS -70th Annual Meeting of the APS Division of Fluid Dynamics- Event - Modeling rough-wall turbulent channel flow with principal component analysis enhanced amplitude modulation

机译：APS -70TH流体动力学APS划分的年会 - 事件 - 建模粗壁湍流通道流，具有主要成分分析增强幅度调制

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Direct numerical simulation of turbulent channel flows over rough surfaces, formed from hexagonally-packed arrays of hemispheres on both walls, were performed at friction Reynolds numbers $Re_au = 200$, $400$, and $600$. The inner normalized roughness height $k^+=20$ was maintained for all Reynolds numbers while the spacing between hemispheres was varied from $d/k=2-4$. The interactions between the near-wall small-scale fluctuations and outer layer large-scale turbulence were studied by amplitude modulation (AM) analysis that has been modified to include principal component analysis (PCA). Based on these interactions, a PCA-adapted predictive inner--outer model was developed to address the modeling of anisotropic effects near the roughness and effectively predict the near-wall statistics up to $4^{th}$ order moments of all velocity fluctuations, including cross terms. The predictions based on the PCA-adapted model were shown to agree excellently with the original statistics from the DNS with better predictions of the statistics of $v$ compared to model without the PCA.
机译：湍流通道的直接数值模拟在粗糙的表面上流动，由两个墙壁上的六角包装阵列形成，在摩擦雷诺数$ re_au = 200 $，400美元和600美元上进行。所有雷诺数的内部归一化粗糙度高度$ k ^ + = 20 $，而半球之间的间距从$ d / k = 2-4 $之间变化。通过修饰为包括主成分分析（PCA）的幅度调制（AM）分析，研究了近壁小规模波动和外层大规模湍流之间的相互作用。基于这些相互作用，开发了一种PCA适应的预测内外模型，以解决粗糙度附近的各向异性效应的建模，有效地预测所有速度波动的$ 4 ^ {th} $ 4 ^ {th} $ 4美元的统计数据，包括横向术语。基于PCA适应模型的预测显示，与DNS的原始统计数据相加，具有更好的预测，与无需PCA的模型相比，与型号相比的统计数据。

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