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A Numerical Twin Model for the Coupled Field Analysis of TEAM Workshop Problem 36

Articolo
Data di Pubblicazione:
2023
Abstract:
A numerical twin model for the magneto-thermal analysis of an induction heating device is proposed. The non-linearity of magnetic permeability against temperature - which characterizes the workpiece - is captured by the model, while the use of a convolutional neural network (CNN), trained by a number of finite-element (FE) analyses, makes it possible to solve the following inverse problem: given a temperature map in the workpiece section, identify current and relevant frequency in the inductor coil, as well as the time instant at which the map refers to. The testing electromagnetic analysis method (TEAM) problem 36 is considered as the case study.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
Convolutional neural network (CNN); coupled problems; testing electromagnetic analysis method (TEAM) problem
Elenco autori:
Di Barba, P.; Mognaschi, M. E.; Cavazzini, A. M.; Ciofani, M.; Dughiero, F.; Forzan, M.; Lazzarin, M.; Marconi, A.; Lowther, D. A.; Sykulski, J. K.
Autori di Ateneo:
DI BARBA PAOLO
MOGNASCHI MARIA EVELINA
Link alla scheda completa:
https://iris.unipv.it/handle/11571/1477337
Pubblicato in:
IEEE TRANSACTIONS ON MAGNETICS
Journal
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