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cs.CE2026

Simplification of the Isotropic Generalized Stop-Type Prandtl-Ishlinskii Vector Hysteresis Operator Using Analytical Return-Point Mapping

Arvinth Shankar, Klaus Kuhnen, Iryna Kulchytska-Ruchka +1

While the thermodynamically formulated generalized Prandtl-Ishlinskii stop-type operator effectively captures hysteresis nonlinearities, it requires a local iterative procedure to…

cs.CE2026

Accelerating Industrial Finite Element Simulations of Electric Machines based on Runtime Analysis

Arvinth Shankar, Iryna Kulchytska-Ruchka, Sebastian Schöps

The simulation of electric machines plays a significant role in the design of efficient and competitive products. Faster simulations reduce computational costs, such as CPU hours,…

cs.CE2026

The CREATOR Project: Towards a Computational Electric Machine Laboratory

Sebastian Schöps, Annette Muetze, Herbert De Gersem +3

The Collaborative Research Centre TRR 361/F90 CREATOR (2022-2030) aims at establishing a new paradigm for the simulation-driven design of electric machines. Increasing demands on e…

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 der…

cs.CE2026

A non-intrusive approach to index-aware learning

Peter Förster, Idoia Cortes Garcia, Wil Schilders +1

We present a non-intrusive version of the index-aware learning framework introduced in arXiv:2309.00958. Index-aware learning itself is an approach for learning the time and parame…