On the detection and quantification of nonlinearity via statistics of the gradients of a black-box model

Tsialiamanis, G. orcid.org/0000-0002-1205-4175 and Farrar, C.R. (2024) On the detection and quantification of nonlinearity via statistics of the gradients of a black-box model. In: Brake, M.R.W., Renson, L., Kuether, R.J. and Tiso, P., (eds.) Nonlinear Structures & Systems, Volume 1: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023. 41st IMAC, A Conference and Exposition on Structural Dynamics 2023, 13-16 Feb 2023, Austin, TX United States. Conference Proceedings of the Society for Experimental Mechanics Series (CPSEMS) . Springer Nature Switzerland , pp. 1-9. ISBN 9783031369988

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
Editors:
  • Brake, M.R.W.
  • Renson, L.
  • Kuether, R.J.
  • Tiso, P.
Copyright, Publisher and Additional Information:

© 2024 The Society for Experimental Mechanics, Inc. This is an author-produced version of a paper subsequently published in Nonlinear Structures & Systems, Volume 1: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023. Uploaded in accordance with the publisher's self-archiving policy.

Keywords: Structural health monitoring (SHM); Structural dynamics; Nonlinear dynamics; Machine learning; Neural networks
Dates:
  • Published: 14 October 2024
  • Published (online): 19 June 2023
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 08 Feb 2024 11:03
Last Modified: 19 Jun 2024 00:13
Status: Published
Publisher: Springer Nature Switzerland
Series Name: Conference Proceedings of the Society for Experimental Mechanics Series (CPSEMS)
Refereed: Yes
Identification Number: 10.1007/978-3-031-36999-5_1
Open Archives Initiative ID (OAI ID):

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