2 papers
cond-mat.mtrl-sci2026
PINN-Phase: Physics-informed neural integration for accurate, generalizable and scalable multiphase-field evolution
Seifallah Elfetni, Peter H. Seeberger, Sascha Thinius +1
Polycrystal phase-field simulations are repeated for many related initial conditions, calling for integrators trained once and reused without retraining. We introduce PINN-Phase, a…
cond-mat.mtrl-sci2024
PINNs-MPF: A Physics-Informed Neural Network Framework for Multi-Phase-Field Simulation of Interface Dynamics
Seifallah Elfetni, Reza Darvishi Kamachali
We present an application of Physics-Informed Neural Networks to handle MultiPhase-Field simulations of microstructure evolution. It has been showcased that a combination of optimi…