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cs.CE2026

Subdivision-based isogeometric analysis for axisymmetric electromagnetic problems

Devin Balian, Sebastian Schöps, Melina Merkel

This paper applies a subdivision-based isogeometric method to solve the axisymmetric Maxwell eigenvalue problem. The reduction to an -formulation allows to use a Catmull-Clark…

cs.CE2026

On the Application of Hybrid Mixed Domain Decomposition Methods to Permanent Magnet Synchronous Machines

Timon Seibel, Sebastian Schöps, Kersten Schmidt

In this work, we study the application of a hybrid mixed domain decomposition (HMDD) method for the rotor-stator coupling of a permanent magnet synchronous machine. For this, we de…

cs.CE2026

Multivariate Sensitivity Analysis of Electric Machine Efficiency Maps and Profiles Under Design Uncertainty

Aylar Partovizadeh, Sebastian Schöps, Dimitrios Loukrezis

This work introduces the use of multivariate global sensitivity analysis for assessing the impact of uncertain electric machine design parameters on efficiency maps and profiles. C…

cs.CE2026

Homogenization of HTS coils with the h, h-phi, and t-omega foil conductor model

Elias Paakkunainen, Louis Denis, Benoît Vanderheyden +3

Efficient numerical models are required for the design of systems with high temperature superconductor (HTS) coils, as fully resolved finite element simulations of individual coate…

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…

cs.CE2026

Multi-Level Monte Carlo sampling with Parallel-in-Time Integration for Uncertainty Quantification in Electric Machine Simulation

Robert Hahn, Sebastian Schöps

While generally considered computationally expensive, Uncertainty Quantification using Monte Carlo sampling remains beneficial for applications with uncertainties of high dimension…