A numerical twin model for the coupled field analysis of TEAM workshop problem 36
A numerical twin model for the coupled field analysis of TEAM workshop problem 36
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.
billets, computational modeling, convolutional neural networks, coupled problems, databases, heating systems, inductors, TEAM problem, temperature distribution, convolutional neural network, testing electromagnetic analysis method (TEAM) problem, Convolutional neural network (CNN)
Di Barba, P.
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Mognaschi, M. E.
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Cavazzini, A. M.
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Ciofani, M.
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Dughiero, F.
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Forzan, M.
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Lazzarin, M.
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Marconi, A.
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Lowther, D. A.
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Sykulski, J. K.
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1 May 2023
Di Barba, P.
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Mognaschi, M. E.
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Cavazzini, A. M.
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Ciofani, M.
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Dughiero, F.
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Forzan, M.
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Lazzarin, M.
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Marconi, A.
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Lowther, D. A.
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Sykulski, J. K.
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Di Barba, P., Mognaschi, M. E., Cavazzini, A. M., Ciofani, M., Dughiero, F., Forzan, M., Lazzarin, M., Marconi, A., Lowther, D. A. and Sykulski, J. K.
(2023)
A numerical twin model for the coupled field analysis of TEAM workshop problem 36.
IEEE Transactions on Magnetics, 59 (5), [7000904].
(doi:10.1109/TMAG.2023.3238767).
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.
Text
A_Numerical_Twin_Model_for_the_Coupled_Field_Analysis_of_TEAM_Workshop_Problem_36
- Accepted Manuscript
More information
e-pub ahead of print date: 23 April 2023
Published date: 1 May 2023
Additional Information:
Publisher Copyright:
© 1965-2012 IEEE.
Keywords:
billets, computational modeling, convolutional neural networks, coupled problems, databases, heating systems, inductors, TEAM problem, temperature distribution, convolutional neural network, testing electromagnetic analysis method (TEAM) problem, Convolutional neural network (CNN)
Identifiers
Local EPrints ID: 477379
URI: http://eprints.soton.ac.uk/id/eprint/477379
ISSN: 0018-9464
PURE UUID: 18fb82f4-dbdc-4471-a154-21d76ff559ee
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Date deposited: 05 Jun 2023 16:53
Last modified: 17 Mar 2024 02:33
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Contributors
Author:
P. Di Barba
Author:
M. E. Mognaschi
Author:
A. M. Cavazzini
Author:
M. Ciofani
Author:
F. Dughiero
Author:
M. Forzan
Author:
M. Lazzarin
Author:
A. Marconi
Author:
D. A. Lowther
Author:
J. K. Sykulski
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