A time-evolving digital twin tool for engineering dynamics applications

Edington, L., Dervilis, N. orcid.org/0000-0002-5712-7323, Ben Abdessalem, A. et al. (1 more author) (2023) A time-evolving digital twin tool for engineering dynamics applications. Mechanical Systems and Signal Processing, 188. 109971. ISSN 0888-3270

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Item Type: Article
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© 2022 Elsevier. This is an author produced version of a paper subsequently published in Mechanical Systems and Signal Processing. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Digital twin; Time-evolving; Approximate bayesian computation; Optimisation; Dynamics
Dates:
  • Published: 1 April 2023
  • Published (online): 5 December 2022
  • Accepted: 18 November 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > School of Mechanical, Aerospace and Civil Engineering
Funding Information:
Funder
Grant number
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL
EP/R006768/1
Depositing User: Symplectic Sheffield
Date Deposited: 16 Jan 2025 09:31
Last Modified: 17 Jan 2025 09:07
Status: Published
Publisher: Elsevier BV
Refereed: Yes
Identification Number: 10.1016/j.ymssp.2022.109971
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Licence: CC-BY-NC-ND 4.0

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