Galetzka, Armin (2024)
Data-Driven Model-Free Electromagnetic Simulation.
Technische Universität Darmstadt
doi: 10.26083/tuprints-00027532
Ph.D. Thesis, Primary publication, Publisher's Version
Text
data-driven-electromagnetic-sim.pdf Copyright Information: CC BY 4.0 International - Creative Commons, Attribution. Download (3MB) |
Item Type: | Ph.D. Thesis | ||||
---|---|---|---|---|---|
Type of entry: | Primary publication | ||||
Title: | Data-Driven Model-Free Electromagnetic Simulation | ||||
Language: | English | ||||
Referees: | De Gersem, Prof. Dr. Herbert ; Römer, Prof. Dr. Ulrich | ||||
Date: | 20 June 2024 | ||||
Place of Publication: | Darmstadt | ||||
Collation: | vii, 80 Seiten | ||||
Date of oral examination: | 10 November 2023 | ||||
DOI: | 10.26083/tuprints-00027532 | ||||
Abstract: | This work addresses the simulation of magnetostatic field problems using measured material data exclusively, rather than using material models constructed from the data. The work introduces a data-driven computing framework for field problems and adapts its formulation to the case of magnetostatics. The data-driven field problem is developed in continuous form utilizing the Euler-Lagrange equations and subsequently solved with the finite element method. A hybrid solver is introduced to handle magnetostatic problems that involve domains with known material relations in combination with domains where solely data are available. Adaptively adjusted weighting factors are introduced to adapt the norm in the material phase space to changing operating points. The properties of the data-driven problem and the computational complexity of the solver are discussed. The findings are illustrated with several numerical experiments covering both academic and real-world problems, including an example that is solved with real-world measurement data only. |
||||
Alternative Abstract: |
|
||||
Uncontrolled Keywords: | electromagnetic field simulation, data-driven computing, material model free | ||||
Status: | Publisher's Version | ||||
URN: | urn:nbn:de:tuda-tuprints-275325 | ||||
Classification DDC: | 600 Technology, medicine, applied sciences > 621.3 Electrical engineering, electronics | ||||
Divisions: | 18 Department of Electrical Engineering and Information Technology > Institute for Accelerator Science and Electromagnetic Fields > Electromagnetic Field Theory (until 31.12.2018 Computational Electromagnetics Laboratory) | ||||
Date Deposited: | 20 Jun 2024 12:23 | ||||
Last Modified: | 21 Jun 2024 07:07 | ||||
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/27532 | ||||
PPN: | 519289072 | ||||
Export: |
View Item |