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physics.flu-dyn2025
Towards a Generalized SA Model: Symbolic Regression-Based Correction for Separated Flows
Xuxiang Sun, Xianglin Shan, Yilang Liu +1
This study focuses on the numerical simulation of high Reynolds number separated flows and proposes a data-driven approach to improve the predictive capability of the SA turbulence…
physics.flu-dyn2024★ 1 cited
Discovery of knowledge of wall-bounded turbulence via symbolic regression
ZhongXin Yang, XiangLin Shan, WeiWei Zhang
With the development of high performance computer and experimental technology, the study of turbulence has accumulated a large number of high fidelity data. However, few general tu…
physics.flu-dyn2024
New Interpretation for error propagation of data-driven Reynolds stress closures via global stability analysis
Xianglin Shan, Wenbo Cao, Weiwei Zhang
In light of the challenges surrounding convergence and error propagation encountered in Reynolds-averaged Navier-Stokes (RANS) equations with data-driven Reynolds stress closures,…