Marshak Wave

Marshak waves, a phenomenon of radiative heat transfer crucial in high-energy density physics, are currently being investigated using advanced computational methods to improve prediction accuracy and efficiency. Research focuses on applying machine learning techniques, particularly physics-informed neural networks (PINNs) and Fourier Neural Operators (FNOs), to model these waves across diverse material properties and conditions, often leveraging existing analytical approximations as a starting point. These advancements have implications for inertial fusion energy design and analysis, as well as broader applications in areas like wave propagation modeling in other physical systems.