15 citations · 16 across the 2 of their papers we have counts for
5 papers
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…