Jia-Hao Hu

Bridging physics and data: A review of machine learning approaches for turbulence closure modeling

It is concluded that aligning data-driven methods with physical constraints—and the training objective with deployment—is the path toward reliable, generalizable, and computationally efficient turbulence models for engineering applications.