3 papers
cs.CE2026
Gradient-Informed Machine Learning in Electromagnetics
Matteo Zorzetto, Merle Backmeyer, Michael Wiesheu +3
Simulation techniques such as the finite element method are essential for designing electrical devices, but their computational cost can be prohibitive for repeated or real-time co…
math.NA2026
A Reduced Magnetic Vector Potential Approach with Higher-Order Splines
Merle Backmeyer, Laura A. M. D'Angelo, Brahim Ramdane +1
This work presents a high-order isogeometric formulation for magnetoquasistatic eddy-current problems based on a decomposition into Biot-Savart-driven source fields and finite-elem…
cs.CE2026
Learning electromagnetic fields based on finite element basis functions
Merle Backmeyer, Michael Wiesheu, Sebastian Schöps
Parametric surrogate models of electric machines are widely used for efficient design optimization and operational monitoring. Addressing geometry variations, spline-based computer…