Knowledge-integrated additive learning for consistent near-wall modelling of turbulent flows

Journal of Fluid Mechanics, Journal Year: 2025, Volume and Issue: 1011

Published: May 13, 2025

Developing a consistent near-wall turbulence model remains an unsolved problem. The machine learning method has the potential to become workhorse for modelling. However, learned suffers from limited generalisability, especially flows without similarity laws (e.g. separated flows). In this work, we propose knowledge-integrated additive (KIA) approach wall models in large-eddy simulations. proposed integrates knowledge simplified thin-boundary-layer equation with data-driven forcing term non-equilibrium effects induced by pressure gradients and flow separations. capability each dataset is encapsulated using basis functions corresponding weights approximated neural networks. fusion of capabilities various datasets enabled distance function, way that preserved generalisability other cases allowed. demonstrated via training sequentially data gradient but no separation, data. preserve previously tested turbulent channel cases. periodic hill 2-D Gaussian bump showcase different surface curvatures Reynolds numbers. Good agreements references are obtained all test

Language: Английский

Non-Linear Super-Stencils for turbulence model corrections

Communications Physics, Journal Year: 2025, Volume and Issue: 8(1)

Published: June 4, 2025

Language: Английский