Physics-Informed Transformation Toward Improving the Machine-Learned
NLTE Models of ICF Simulations
Physics-Informed Transformation Toward Improving the Machine-Learned
NLTE Models of ICF Simulations
The integration of machine learning techniques into Inertial Confinement Fusion (ICF) simulations has emerged as a powerful approach for enhancing computational efficiency. By replacing the costly Non-Local Thermodynamic Equilibrium (NLTE) model with machine learning models, significant reductions in calculation time have been achieved. However, determining how to optimize machine learning-based …