32 citations · 98 across the 9 of their papers we have counts for
9 papers
Thermal Model Calibration of a Squirrel-Cage Induction Machine
Leon Blumrich, Christian Bergfried, Armin Galetzka +4
Accurate and efficient thermal simulations of induction machines are indispensable for detecting thermal hot spots and hence avoiding potential material failure in an early design…
Data-driven Modified Nodal Analysis Circuit Solver
Armin Galetzka, Dimitrios Loukrezis, Herbert De Gersem
This work introduces a novel data-driven modified nodal analysis (MNA) circuit solver. The solver is capable of handling circuit problems featuring elements for which solely measur…
An -adaptive multi-element stochastic collocation method for surrogate modeling with information re-use
Armin Galetzka, Dimitrios Loukrezis, Niklas Georg +2
This paper introduces an -adaptive multi-element stochastic collocation method, which additionally allows to re-use existing model evaluations during either - or -refinem…
Three-Dimensional Data-Driven Magnetostatic Field Computation using Real-World Measurement Data
Armin Galetzka, Dimitrios Loukrezis, Herbert De Gersem
This paper presents a practical case study of a data-driven magnetostatic finite element solver applied to a real-world three-dimensional problem. Instead of using a hard-coded phe…
Data-Driven Solvers for Strongly Nonlinear Material Response
Armin Galetzka, Dimitrios Loukrezis, Herbert De Gersem
This work presents a data-driven magnetostatic finite-element solver that is specifically well-suited to cope with strongly nonlinear material responses. The data-driven computing…
Magnetic Field Simulation with Data-Driven Material Modeling
Herbert De Gersem, Armin Galetzka, Ion Gabriel Ion +2
This paper developes a data-driven magnetostatic finite-element (FE) solver which directly exploits measured material data instead of a material curve constructed from it. The dist…
Robust Adaptive Least Squares Polynomial Chaos Expansions in High-Frequency Applications
Dimitrios Loukrezis, Armin Galetzka, Herbert De Gersem
We present an algorithm for computing sparse, least squares-based polynomial chaos expansions, incorporating both adaptive polynomial bases and sequential experimental designs. The…
A multilevel Monte Carlo method for high-dimensional uncertainty quantification of low-frequency electromagnetic devices
Armin Galetzka, Zeger Bontinck, Ulrich Römer +1
This work addresses uncertainty quantification of electromagnetic devices determined by the eddy current problem. The multilevel Monte Carlo (MLMC) method is used for the treatment…
Multilevel Monte Carlo Simulation of the Eddy Current Problem With Random Parameters
Armin Galetzka, Zeger Bontinck, Ulrich Römer +1
The multilevel Monte Carlo method is applied to an academic example in the field of electromagnetism. The method exhibits a reduced variance by assigning the samples to multiple mo…