... especially at off-design conditions. To enable intensive modeling and optimization of complete vehicle powertrains for different drive cycles, the current piece of work seeks to combine the advantages of machine learning techniques and physical meanline modeling to facilitate faster, more accurate...

... machine learning film cooling single hole adiabatic efficiency convolutional neural network distribution prediction heat transfer National Natural Science Foundation of China 10.13039/501100001809 52076053 Natural Science Foundation of Heilongjiang Province 10.13039/501100005046...

...Harshal D. Akolekar; Yaomin Zhao; Richard D. Sandberg; Roberto Pacciani This paper presents the development of accurate turbulence closures for low-pressure turbine (LPT) wake mixing prediction by integrating a machine-learning approach based on gene expression programming (GEP), with Reynolds...

... turbulent Prandtl number (Pr t ), fail to accurately predict heat transfer in film cooling flows. In the present work, machine learning models are trained to predict a non-uniform Pr t field using various datasets as training sets. The ability of these models to generalize beyond the flows on which...