Physics-constrained machine learning for generalisable turbulence modelling across flow regimes
Abstract Content of image described in text. In this work we propose a physics-constrained machine learning approach to enhance the generalisability of neural-network-represented turbulence models across different flow regimes. Machine learning-augmented turbulence modelling has emerged to improve the predictive accura...