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physics.flu-dyn2025
A features-embedded-learning immersed boundary model for large-eddy simulation of turbulent flows with complex boundaries
Zhideng Zhou, Fengshun Zhang, Xiaolei Yang
The hybrid wall-modeled large-eddy simulation (WMLES) and immersed boundary (IB) method offers significant flexibility for simulating high Reynolds number flows involving complex b…
physics.flu-dyn2024★ 18 cited
A wall model for separated flows: embedded learning to improve a posteriori performance
Zhideng Zhou, Xin-lei Zhang, Guo-wei He +1
The development of a wall model using machine learning methods for the large-eddy simulation (LES) of separated flows is still an unsolved problem. Our approach is to leverage the…
physics.flu-dyn2020★ 4 cited
A wall model based on neural networks for LES of turbulent flows over periodic hills
Zhideng Zhou, Guowei He, Xiaolei Yang
In this work, a data-driven wall model for turbulent flows over periodic hills is developed using the feedforward neural network (FNN) and wall-resolved LES (WRLES) data. To develo…