Mengyu Feng

A physics-informed relaxation-decomposed neural collision model for discrete Boltzmann dynamics

A relaxation-decomposed network (RDN) is proposed for learning collision operators in discrete Boltzmann equations and achieves better interface preservation, smaller deviations in macroscopic quantities, and improved long-time stability during multiphase-flow evolution.