3 papers
cs.LG2026
Architecture-Optimization Co-Design for Physics-Informed Neural Networks Via Attentive Representations and Conflict-Resolved Gradients
Pancheng Niu, Jun Guo, Qiaolin He +2
Physics-Informed Neural Networks (PINNs) provide a learning-based framework for solving partial differential equations (PDEs) by embedding governing physical laws into neural netwo…
physics.plasm-ph2025
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…
physics.flu-dyn2025
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…