Jin-Zhao Wang

Flow and heat transfer predictions of supercritical pressure hydrocarbon fuel in three-dimensional Kagome lattice structures using physics-informed neural network

Classical computational fluid dynamics faces prohibitive computational costs due to complex cooling structures and variable operating conditions. This study developed a physics-informed neural network (PINN) driven by Reynolds-averaged Navier–Stokes data to predict the flow and heat transfer of supercritical hydrocarbo...