5 papers
DeSyR: A Decoupled Symbolic Recovery Framework with PINN-Guided Structure Search and Physics-Informed Coefficient Refinement
Pancheng Niu, Jun Guo, Qiaolin He +2
Recovering compact explicit solutions from neural approximations is challenging when imperfect teacher data guide symbolic topology search and coefficient estimation. We present De…
A Regularized Framework and Admissible Solutions for Liquid-Vapor Phase Transitions in Steady Compressible Flows
Yazhou Chen, Qiaolin He, Dongjuan Niu +2
We investigate the well-posedness of the periodic boundary value problem for the steady compressible isentropic Navier-Stokes system under the van der Waals equation of state. The…
Architecture--Optimization Co-Design for Physics-Informed Neural Networks via Layer-wise Coordinate Adaptation and Gradient Conflict Resolution
Pancheng Niu, Jun Guo, Qiaolin He +2
Physics-informed neural networks (PINNs) can be limited by coordinate representations and conflicting gradients from heterogeneous physical constraints. We propose Architecture--Co…
Thermodynamically consistent modeling and simulation of two-fluid magnetohydrodynamic equations
Ting Xiao, Qiaolin He
Based on a rigorous thermodynamic framework, this work develops a two-fluid magnetohydrodynamic model grounded in the Helmholtz free energy formalism. The model maintains full ther…
Thermodynamically consistent modelling and simulation of the moving contact line problem in non-isothermal compressible two-phase flows
Junkai Wang, Qiaolin He
According to the dynamic van der Waals theory, we propose a thermodynamically consistent model for non-isothermal compressible two-phase flows with contact line motion. In this mod…