7 citations · 12 across the 10 of their papers we have counts for
3 papers · 1 filter
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…
Isogeometric Analysis for 2D Magnetostatic Computations with Multi-level Bézier Extraction for Local Refinement
Andreas Grendas, Michael Wiesheu, Sebastian Schöps +1
Local refinement is vital for efficient numerical simulations. In the context of Isogeometric Analysis (IGA), hierarchical B-splines have gained prominence. The work applies the me…