Parekh, Vivek ; Flore, Dominik ; Schöps, Sebastian
(2022):
Performance analysis of Electrical Machines based on Electromagnetic System Characterization using Deep Learning.
Cornell University, ARXIV: 2201.09603.
[Preprint].
Parekh, Vivek ; Flore, Dominik ; Schöps, Sebastian
(2022):
Variational Autoencoder based Metamodeling for Multi-Objective Topology Optimization of Electrical Machines.
In: IEEE Transactions on Magnetics, ISSN: 0018-9464, DOI: 10.1109/TMAG.2022.3163972, ARXIV: 2201.08877.
[Article]
Parekh, Vivek ; Flore, Dominik ; Schöps, Sebastian
(2022):
Multi-objective topology optimization of electrical machines using variational autoencoder.
In: 23rd Conference on the Computation of Electromagnetic Fields (COMPUMAG 2021), Cancun, Mexico. International Compumag Society.
URL: http://www.compumag2021.com.
[Talk]
Parekh, Vivek
(2021):
Multi-objective Topology Optimization of Electrical Machines Using Variational Autoencoder.
In: Workshop on Advances in Electromagnetic Research – KWT 2021, Virtual Conference.
URL: http://maxwell-in-motion.org.
[Talk]
Parekh, Vivek ; Flore, Dominik ; Schöps, Sebastian
(2021):
Deep Learning-based Prediction of Key Performance Indicators for Electrical Machine.
In: IEEE Access, ISSN: 2169-3536, DOI: 10.1109/ACCESS.2021.3053856, ARXIV: 2012.11299.
[Article]
Parekh, Vivek ; Flore, Dominik ; Schöps, Sebastian
(2020):
Deep Learning-based Prediction of Key Performance Indicators for Electrical Machine.
In: Workshop on Advances in Electromagnetic Research – KWT 2020, Virtual Conference.
URL: http://maxwell-in-motion.org.
[Talk]