Yan Shang

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

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 hydrocarbon fuel in three-dimensional Kagome lattice structures, offering guidance for the prediction of flow and thermal fields under applied thermal bound...