Distributions of fatigue damage from data-driven strain prediction using Gaussian process regression

Gibson, S.J. orcid.org/0000-0003-1247-6471, Rogers, T.J. orcid.org/0000-0002-3433-3247 and Cross, E.J. (2023) Distributions of fatigue damage from data-driven strain prediction using Gaussian process regression. Structural Health Monitoring. ISSN 1475-9217

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Authors/Creators:
Copyright, Publisher and Additional Information: © The Author(s) 2023. 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 properly attributed.
Keywords: Gaussian process; probabilistic; fatigue assessment; posterior sampling; uncertainty; propagation; data-driven; strain prediction
Dates:
  • Published (online): 6 January 2023
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 SCIENCE RESEARCH COUNCILEP/S001565/1
Depositing User: Symplectic Sheffield
Date Deposited: 22 Feb 2023 15:51
Last Modified: 22 Feb 2023 15:51
Status: Published online
Publisher: SAGE Publications
Refereed: Yes
Identification Number: https://doi.org/10.1177/14759217221140080
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