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Okenyi, V. 
ORCID: 0000-0001-6489-2675, Bodaghi, M. ORCID: 0000-0002-0707-944X, Mansfield, N. ORCID: 0000-0001-6769-1721, Afazov, S. ORCID: 0000-0001-5346-1933 and Siegkas, P.,
2022.
A review of challenges and framework development for corrosion fatigue life assessment of monopile-supported horizontal-axis offshore wind turbines.
Ships and Offshore Structures.
ISSN 1744-5302
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Text
1619734_Bodaghi.pdf - Published version Download (2MB) | Preview |
Abstract
Digital tools such as machine learning and the digital twins are emerging in asset management of offshore wind structures to address their structural integrity and cost challenges due to manual inspections and remote sites of offshore wind farms. The corrosive offshore environments and salt-water effects further increase the risk of fatigue failures in offshore wind turbines. This paper presents a review of corrosion fatigue research in horizontal-axis offshore wind turbines (HAOWT) support structures, including the current trends in using digital tools that address the current state of asset integrity monitoring. Based on the conducted review, it has been found that digital twins incorporating finite element analysis, material characterisation and modelling, machine learning using artificial neural networks, data analytics, and internet of things (IoT) using smart sensor technologies, can be enablers for tackling the challenges in corrosion fatigue (CF) assessment of offshore wind turbines in shallow and deep waters.
| Item Type: | Journal article | ||||||
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| Publication Title: | Ships and Offshore Structures | ||||||
| Creators: | Okenyi, V., Bodaghi, M., Mansfield, N., Afazov, S. and Siegkas, P. | ||||||
| Publisher: | Informa UK Limited | ||||||
| Date: | 4 November 2022 | ||||||
| ISSN: | 1744-5302 | ||||||
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| Rights: | © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. | ||||||
| Divisions: | Schools > School of Science and Technology | ||||||
| Record created by: | Laura Ward | ||||||
| Date Added: | 21 Nov 2022 11:31 | ||||||
| Last Modified: | 21 Nov 2022 11:31 | ||||||
| URI: | https://irep.ntu.ac.uk/id/eprint/47445 |
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