Conference item : Abstract
A novel machine learning model to fast predict nonlinear waveforces on monopile-type offshore wind turbine foundations
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 372.2KB, Terms of use)
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Authors
+ Engineering and Physical Sciences Research Council
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- Funder identifier:
- https://ror.org/0439y7842
- Grant:
- EP/V050079/1
- Publisher:
- CADE School of Engineering, University of Bristol
- Host title:
- Proceedings of PRIMaRE 2025
- Pages:
- 31
- Publication date:
- 2025-07-03
- Acceptance date:
- 2025-05-07
- Event title:
- 12th PRIMaRE conference 2025
- Event location:
- Bristol, UK
- Event website:
- https://www.bristol.ac.uk/science-engineering/schools/civil-aero-design/12th-primare-conference/
- Event start date:
- 2025-07-02
- Event end date:
- 2025-07-03
- Language:
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English
- Subtype:
-
Abstract
- Pubs id:
-
2122496
- Local pid:
-
pubs:2122496
- Deposit date:
-
2025-05-09
- ARK identifier:
Terms of use
- Copyright holder:
- Ding et al.
- Copyright date:
- 2025
- Rights statement:
- © 2025 the Authors.
- Notes:
- The author accepted manuscript (AAM) of this paper has been made available under the University of Oxford's Open Access Publications Policy, and a CC BY public copyright licence has been applied.
- Licence:
- CC Attribution (CC BY)
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