H. Kazmi

A Neural Network-Based Model Order Reduction Methodology With Harmonic Forecasting for Parametric Nonlinear Magnetodynamic Simulations

High-fidelity parametric simulations of nonlinear magnetodynamic systems are computationally demanding, making real-time and many-query applications impractical with conventional finite element methods (FEMs). While model order reduction (MOR) techniques address this challenge, extending them to nonlinear, time-depende...