3 citations · 4 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
Solving Electromagnetic Scattering Problems by Isogeometric Analysis with Deep Operator Learning
Merle Backmeyer, Stefan Kurz, Matthias Möller +1
We present a hybrid approach combining isogeometric analysis with deep operator networks to solve electromagnetic scattering problems. The neural network takes a computer-aided des…
Modeling non-planar coils in a full-scale stellarator
Merle Backmeyer, Nicolo Riva, Mika Lyly +2
Design and modeling of a stellarator fusion reactor is a multidisciplinary effort that requires a tight integration between simulation of highly nonlinear multi-physics and represe…