Jun-Ya Yang

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

Turbulence closure modeling remains one of the central challenges in computational fluid dynamics. Over the past decade, machine learning (ML) has emerged as a promising paradigm to augment and, in some cases, replace classical turbulence models by leveraging high-fidelity simulation data and advanced neural network ar...