NeuroSEM: A hybrid framework for simulating multiphysics problems by coupling PINNs and spectral elements

Understand

Multiphysics problems that are characterized by complex interactions among fluid dynamics, heat transfer, structural mechanics, and electromagnetics, are inherently challenging due to their coupled nature.

• While experimental data on certain state variables may be available, integrating these data with numerical solvers remains a significant challenge.
• Physics-informed neural networks (PINNs) have shown promising results in various engineering disciplines, particularly in handling noisy data and solving inverse problems in partial differential equations (PDEs).
• However, their effectiveness in forecasting nonlinear phenomena in multiphysics regimes, particularly involving turbulence, is yet to be fully established.