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Abstract
The fluid-structure interaction (FSI) technique has been extensively used and developed in the past decades. Commonly, the reduced-order models are used in FSI analyses to assure the numerical robustness and efficiency. However, due to the increasing demand for higher numerical resolutions in modern wind turbine composite blade applications, intrinsic limitations of reduced-order models, such as their inability to account for complex aerodynamic flow interactions, multi-motion couplings, and sophisticated composite properties, have become the weaknesses in existing reduced-order FSI approaches. In this study, we propose a general FSI framework, which combines the advantages of high-fidelity Computational Fluid Dynamics (CFD) and robust Multi-Body Dynamics (MBD) methods, and detailed Finite Element Analysis (FEA) for analysing the detailed stress distributions on the composite structures. The results of predicted dynamics and the Von Mises stress on the composite blade structures under given operation condition are compared and reasonably agreed with the literature results, with a significant computational cost reduction by nearly 25% is achieved. The proposed FSI framework can be a general approach to investigate the multi-physical interactions where the composite structure specifications are involved, coupling with complex dynamic motions in three-dimensional space.
Original language | English |
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Article number | 116412 |
Number of pages | 20 |
Journal | Ocean Engineering |
Volume | 291 |
Early online date | 27 Nov 2023 |
DOIs | |
Publication status | Published - 1 Jan 2024 |
Keywords
- FSI
- CFD
- FEA
- composite blades
- stress analysis
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Dive into the research topics of 'A general FSI framework for an effective stress analysis on composite wind turbine blades'. Together they form a unique fingerprint.Projects
- 1 Finished
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Composite material offshore wind turbine blade fluid-structure-interaction analysis
Xiao, Q. (Principal Investigator), Deng, Z. (Researcher) & Yang, L. (Co-investigator)
1/10/19 → 1/05/24
Project: Research