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Τίτλος: Development and application of an aero-hydro-servo-elastic coupling framework for analysis of floating offshore wind turbine
Συγγραφείς: Yang, Yang 
Bashir, Musa 
Michailides, Constantine 
Li, Chun 
Wang, Jin 
Major Field of Science: Engineering and Technology
Field Category: Environmental Engineering
Λέξεις-κλειδιά: Floating offshore wind turbines;AQWA;FAST;Aero-hydro-servo-elastic coupling framework
Ημερομηνία Έκδοσης: Δεκ-2020
Πηγή: Renewable Energy, 2020, vol. 161, pp. 606-625
Volume: 161
Start page: 606
End page: 625
Περιοδικό: Renewable Energy 
Περίληψη: In order to enhance simulation capabilities of existing numerical tools for the design of floating offshore wind turbines (FOWTs), this study has developed and implemented a coupling framework (F2A) that is capable of predicting nonlinear dynamics of a FOWT subjected to wind, wave and current loadings. F2A integrates all the advantages of FAST in efficiently examining aero-servo-elastic effects with all the numerical capabilities of AQWA (e. g. nonlinear hydrodynamics, mooring dynamics and material nonlinearity) for the dynamic analysis of a FOWT. The verification of F2A is carried out by comparing it with OpenFAST through the case study of a 5 MW wind turbine supported by the OC3-Hywind spar platform. The results show excellent agreements between F2A and OpenFAST in predicting dynamic responses of the blades, tower, platform and station-keeping system under both steady and turbulent winds combined with wave conditions. This implies that the simulation capabilities of FAST are well implemented within AQWA. Further advantages and capabilities of F2A in examining the dynamics of a FOWT are investigated via a case study of a multi-body platform concept connected by flexible elements. Some unique phenomena can only be observed from the results obtained using F2A as opposed to conventional tools. The results indicate that the newly-developed F2A coupling framework can be used for the analysis of FOWTs and it has been released to the public.
URI: https://hdl.handle.net/20.500.14279/19248
ISSN: 09601481
DOI: 10.1016/j.renene.2020.07.134
Rights: © Elsevier
Attribution-NonCommercial-NoDerivatives 4.0 International
Type: Article
Affiliation: Liverpool John Moores University 
University of Shanghai for Science and Technology 
Cyprus University of Technology 
Publication Type: Peer Reviewed
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