Physics-informed regularisation procedure in neural networks : an application in blast protection engineering

Pannell, J.J. orcid.org/0000-0003-2136-2150, Rigby, S.E. orcid.org/0000-0001-6844-3797 and Panoutsos, G. orcid.org/0000-0002-7395-8418 (2022) Physics-informed regularisation procedure in neural networks : an application in blast protection engineering. International Journal of Protective Structures, 13 (3). pp. 555-578. ISSN 2041-4196

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Item Type: Article
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© 2022 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).

Keywords: machine learning; physics-guided neural network; deep learning; blast; computational fluid dynamics; data-driven modelling
Dates:
  • Published: September 2022
  • Published (online): 13 April 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 29 Apr 2022 08:41
Last Modified: 28 Jun 2024 11:32
Status: Published
Publisher: SAGE Publications
Refereed: Yes
Identification Number: 10.1177/20414196211073501
Open Archives Initiative ID (OAI ID):

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