论文标题
数据驱动的封闭了三维流动围绕虚张声势的封闭
Data-driven RANS closures for three-dimensional flows around bluff bodies
论文作者
论文摘要
在此简短的说明中，我们应用了最近提出的数据驱动的Rans封闭建模框架，Schmelzer等人。 （2020年）到达全三维，高雷诺数流量：re = 40,000时，即壁挂式的立方体和立方体，以及一个RE = 140,000的圆柱体。对于每种流，使用基于LES或DES参考数据的稀疏符号回归生成新的RANS闭合。该新模型是在CFD求解器中实现的，随后应用于其他流的预测。与基线$ k-ω$ SST模型相比，我们看到一致的改进，以预测完整流量域中的均值。
In this short note we apply the recently proposed data-driven RANS closure modelling framework of Schmelzer et al. (2020) to fully three-dimensional, high Reynolds number flows: namely wall-mounted cubes and cuboids at Re=40,000, and a cylinder at Re=140,000. For each flow, a new RANS closure is generated using sparse symbolic regression based on LES or DES reference data. This new model is implemented in a CFD solver, and subsequently applied to prediction of the other flows. We see consistent improvements compared to the baseline $k-ω$ SST model in predictions of mean-velocity in the complete flow domain.
