Fully coupled aero-hydrodynamic analysis of a semi-submersible FOWT using a dynamic fluid body interaction approach
- Authors
- Tran, Thanh Toan; Kim, Dong-Hyun
- Issue Date
- Jul-2016
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Keywords
- Dynamic fluid body interaction; 6-DOF solver; Fully coupled aero-hydrodynamics; OC4 DeepCWind; Overset grid; FAST code
- Citation
- RENEWABLE ENERGY, v.92, pp 244 - 261
- Pages
- 18
- Indexed
- SCIE
SCOPUS
- Journal Title
- RENEWABLE ENERGY
- Volume
- 92
- Start Page
- 244
- End Page
- 261
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/15408
- DOI
- 10.1016/j.renene.2016.02.021
- ISSN
- 0960-1481
1879-0682
- Abstract
- In the design phase of a floating offshore wind turbine, the influence of aero-hydro-structure dynamic coupling needs to be fully considered to yield reliable analysis results. In this study, a highly elaborated computational model based on a dynamic fluid body interaction method with a superimposed motion and catenary mooring solver is applied and compared with common engineering approaches. An overset-based technique is also utilized to effectively handle large movements of a full floating wind turbine body due to the coupled influence of wind-wave loads. The DeepCwind semi-submersible, floating platform mounted by the NREL 5-MW baseline wind turbine is used to obtain validation and verification of the new computational model with the experimental test data and the NREL FAST code. Various computational results for unsteady aerodynamics, hydrodynamics, and fully coupled aero-hydrodynamics including mooring line loads are compared stage by stage with the test data and numerical results calculated by the NREL FAST code. Overall, the predicted results of the aerodynamic performances, platform dynamic responses, and mooring line tensions show good agreements with the presented numerical solutions and the FAST solutions. In addition, multi-phase unsteady flow fields with complex inference effects in the blade-tip vortices, shedding vortices, and turbulent wakes are numerically visualized and investigated in detail. (C) 2016 Elsevier Ltd. All rights reserved.
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