On the dynamic properties of statistically-independent nonlinear normal modes

Champneys, M.D. orcid.org/0000-0002-3037-7584, Tsialiamanis, G., Rogers, T.J. orcid.org/0000-0002-3433-3247 et al. (2 more authors) (2022) On the dynamic properties of statistically-independent nonlinear normal modes. Mechanical Systems and Signal Processing, 181. 109510. ISSN 0888-3270

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Nonlinear normal modes; Nonlinear system identification; Machine learning; cycle-GAN; Higher-order frequency-response functions
Dates:
  • Accepted: 27 June 2022
  • Published (online): 5 July 2022
  • Published: 1 December 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield)
Funding Information:
FunderGrant number
Engineering and Physical Sciences Research CouncilEP/R006768/1; EP/L016257/1
European Commission - HORIZON 2020764547
Depositing User: Symplectic Sheffield
Date Deposited: 15 Jul 2022 11:23
Last Modified: 15 Jul 2022 11:23
Status: Published
Publisher: Elsevier BV
Refereed: Yes
Identification Number: https://doi.org/10.1016/j.ymssp.2022.109510

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