Thesis
Aeroelastic analysis and optimizations for composite blades on floating offshore wind turbine
- Creator
- Rights statement
- Awarding institution
- University of Strathclyde
- Date of award
- 2025
- Thesis identifier
- T17555
- Person Identifier (Local)
- 201978673
- Qualification Level
- Qualification Name
- Department, School or Faculty
- Abstract
- Modern wind energy industry has embraced larger turbine solutions with ultra-long blades that has reached a 100-150 meter scale for maximising the amount of power extraction and increasing the levelized cost of energy (LCOE) of the wind turbines. One key driving factor of this technological advancement is the necessity for in-depth understandings of the blade aeroelastic behaviour and its structural responses of the composite blades, particularly under complex operational conditions such as those experienced by floating offshore wind turbines (FOWTs). However, analysing the aeroelastic responses of such composite structures can encounter significant computational challenges, such as the difficulties in capturing global-local coupled behaviours and anisotropic material effects due to the excessive computational expenses. This thesis is structured in two main parts: (1) the development of a high-fidelity aeroelastic analysis framework for composite FOWT blades via fluid–structure interaction (FSI); and (2) multi-objective structural optimization of composite blades using surrogate-assisted algorithms. In the first part, an FSI framework aiming for the structural response investigations of composite wind turbine blade on FOWT is developed. This work is a further development based on previous developed FSI framework established by Yuanchuan Liu (2018) who integrated the open-source computational fluid dynamics (CFD) code OpenFOAM and the multibody dynamics (MBD) method MBDyn for the flexible structure aeroelastic predictions. In parallel, the fully-resolved finite element analysis (FEA) for the composite blade is conducted using the commercial package Abaqus CAE, where the blade aeroelastics being resolved in FSI can be applied explicitly for the field recovery for stress inspections on the blade. This FSI framework is used for FOWT blade aeroelastic investigations with consideration of anisotropic composite material properties. To reasonably account for the influence of platform motions, a prescribed sinusoidal motion function resembling the FOWT platform motions under a regular wave condition is applied, allowing a realistic reproduction of the dynamics on the FOWT blades. The present FSI framework performs more computationally efficient than existing FSI strategies by reducing nearly 25% of core-hours of computing resources while offering detailed multi-hierarchy composite structural insights into the non-uniform stress behaviour across the blade under dynamic loading conditions. In the second part of this work, we presented a further extension based on the established FSI framework for blade structural optimizations, aiming to achieve higher strength-weight ratio blade designs to support the upscaling trend of the future wind turbine blades. A nondominated sorting genetic algorithm II (NSGA-II), is integrated with a machine learning (ML) based artificial neural network (ANN) surrogate model for approximating the objective outputs (i.e. blade weight and max. Von Mises stress). This approach streamlined the conventional FEA approach so that a significant reduction in computational expenses is achieved. A notable challenge of the distribution drifting issue of the surrogate model is identified and addressed, improving the generalisability and predictive accuracy of the ANN during iterative optimization. The framework demonstrates its robustness and effectiveness in highdimensional design spaces, achieving substantial blade weight reduction without compromising structural integrity. This work systematically introduced a numerical FSI analysing and optimization workflow by taking the advantages of CFD, MBD and FEA, for the FSI investigations for the flexible composite structures. The novelty of this work is that we provide a general-purpose FSI-driven surrogate-assist structural optimization framework for designing flexible composite structures with higher strength-to-weight performance. The proposed framework in this work is also capable of handling applications beyond wind turbines to other complex systems that are prone to interactive environments between the fluid and structure physical fields accompany with different forms of dynamic motions, offering detailed insights in aero- or hydroelastics terms and has a great potential in the light-weight designs for composite structures.
- Advisor / supervisor
- Yang, Liu
- Xiao, Qing
- Resource Type
- DOI
- Alternative Title
- Aeroelastic analysis and optimisations for composite blades on floating offshore wind turbine
关系
项目
| 缩略图 | 标题 | 上传日期 | 公开度 | 行动 |
|---|---|---|---|---|
|
|
PDF of thesis T17555 | 2026-01-09 | 公开 | 下载 |