Predicting strain and stress fields in self-sensing nanocomposites using deep learned electrical tomography

Chen, L., Hassan, H., Tallman, T.N. et al. (2 more authors) (2022) Predicting strain and stress fields in self-sensing nanocomposites using deep learned electrical tomography. Smart Materials and Structures, 31 (4). 045024. ISSN 0964-1726

Abstract

Metadata

Item Type: Article
Authors/Creators:
  • Chen, L.
  • Hassan, H.
  • Tallman, T.N.
  • Huang, S.-S.
  • Smyl, D.J.
Copyright, Publisher and Additional Information:

© 2022 IOP Publishing Ltd. This Accepted Manuscript is available for reuse under a CC BY-NC-ND 3.0 licence (https://creativecommons.org/licences/by-nc-nd/3.0).

Keywords: Deep learning; electrical resistance tomography; nanocomposites; piezoresistivity
Dates:
  • Published: April 2022
  • Published (online): 24 February 2022
  • Accepted: 24 February 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 03 Mar 2022 10:22
Last Modified: 24 Feb 2023 01:13
Status: Published
Publisher: IOP Publishing
Refereed: Yes
Identification Number: 10.1088/1361-665x/ac585f
Open Archives Initiative ID (OAI ID):

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