Physics-integrated neural network modeling of heat and mass transfer in cryogenic liquid storage under static and dynamic conditions

Accurate system-level prediction of cryogenic liquid storage remains challenging because reduced-order models rely on regime-dependent closures for unresolved heat and mass transfer, particularly under sloshing. We present a physics-integrated neural-network framework that combines a conservation-ba