Collaborative Optimization of Aerodynamics and Wind Turbine Blades
This paper explores the application of multidisciplinary design optimization to the blades in horizontal-axis wind turbines. The aerodynamics and structural performance of blades are considered in the optimization framework. In the aerodynamic discipline, class function/shape function transformation...
Saved in:
Main Authors: | , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/15/2/834 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
_version_ | 1832589190321143808 |
---|---|
author | Fushan He Xingsheng Zheng Weilin Luo Jianfeng Zhong Yunhua Huang Aili Ye Rongrong Qiu Huafu Ma |
author_facet | Fushan He Xingsheng Zheng Weilin Luo Jianfeng Zhong Yunhua Huang Aili Ye Rongrong Qiu Huafu Ma |
author_sort | Fushan He |
collection | DOAJ |
description | This paper explores the application of multidisciplinary design optimization to the blades in horizontal-axis wind turbines. The aerodynamics and structural performance of blades are considered in the optimization framework. In the aerodynamic discipline, class function/shape function transformation-based parameterized modeling is used to express the airfoil. The Wilson method is employed to obtain the aerodynamic shape of the blade. Computational fluid dynamics numerical simulation is performed to analyze the aerodynamics of the blade. In the structural discipline, the materials and ply lay-up design are studied. Finite element method-based modal analysis and static structural analysis are conducted to verify the structural design of the blade. A collaborative optimization framework is set up on the Isight platform, employing a genetic algorithm to find the optimal solution for the blade’s aerodynamics and structural properties. In the optimization framework, the design variables refer to the length of the blade chord, twist angle, and lay-up thickness. Additionally, Kriging surrogate models are constructed to reduce the numerical simulation time required during optimization. An optimal Latin hypercube sampling method-based experimental design is employed to determine the samples used in the surrogate models. The optimized blade exhibits improved performance in both the aerodynamic and the structural disciplines. |
format | Article |
id | doaj-art-6f7cdd9ef4ba42038026e715cf0bc63a |
institution | Kabale University |
issn | 2076-3417 |
language | English |
publishDate | 2025-01-01 |
publisher | MDPI AG |
record_format | Article |
series | Applied Sciences |
spelling | doaj-art-6f7cdd9ef4ba42038026e715cf0bc63a2025-01-24T13:21:00ZengMDPI AGApplied Sciences2076-34172025-01-0115283410.3390/app15020834Collaborative Optimization of Aerodynamics and Wind Turbine BladesFushan He0Xingsheng Zheng1Weilin Luo2Jianfeng Zhong3Yunhua Huang4Aili Ye5Rongrong Qiu6Huafu Ma7College of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, ChinaCollege of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, ChinaCollege of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, ChinaCollege of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, ChinaSansteel Minguang Co., Ltd., Sanming 365000, ChinaSansteel Minguang Co., Ltd., Sanming 365000, ChinaSansteel Minguang Co., Ltd., Sanming 365000, ChinaSansteel Minguang Co., Ltd., Sanming 365000, ChinaThis paper explores the application of multidisciplinary design optimization to the blades in horizontal-axis wind turbines. The aerodynamics and structural performance of blades are considered in the optimization framework. In the aerodynamic discipline, class function/shape function transformation-based parameterized modeling is used to express the airfoil. The Wilson method is employed to obtain the aerodynamic shape of the blade. Computational fluid dynamics numerical simulation is performed to analyze the aerodynamics of the blade. In the structural discipline, the materials and ply lay-up design are studied. Finite element method-based modal analysis and static structural analysis are conducted to verify the structural design of the blade. A collaborative optimization framework is set up on the Isight platform, employing a genetic algorithm to find the optimal solution for the blade’s aerodynamics and structural properties. In the optimization framework, the design variables refer to the length of the blade chord, twist angle, and lay-up thickness. Additionally, Kriging surrogate models are constructed to reduce the numerical simulation time required during optimization. An optimal Latin hypercube sampling method-based experimental design is employed to determine the samples used in the surrogate models. The optimized blade exhibits improved performance in both the aerodynamic and the structural disciplines.https://www.mdpi.com/2076-3417/15/2/834wind turbine bladesaerodynamic characteristicsstructural characteristicsmultidisciplinary design optimizationnumerical simulation |
spellingShingle | Fushan He Xingsheng Zheng Weilin Luo Jianfeng Zhong Yunhua Huang Aili Ye Rongrong Qiu Huafu Ma Collaborative Optimization of Aerodynamics and Wind Turbine Blades Applied Sciences wind turbine blades aerodynamic characteristics structural characteristics multidisciplinary design optimization numerical simulation |
title | Collaborative Optimization of Aerodynamics and Wind Turbine Blades |
title_full | Collaborative Optimization of Aerodynamics and Wind Turbine Blades |
title_fullStr | Collaborative Optimization of Aerodynamics and Wind Turbine Blades |
title_full_unstemmed | Collaborative Optimization of Aerodynamics and Wind Turbine Blades |
title_short | Collaborative Optimization of Aerodynamics and Wind Turbine Blades |
title_sort | collaborative optimization of aerodynamics and wind turbine blades |
topic | wind turbine blades aerodynamic characteristics structural characteristics multidisciplinary design optimization numerical simulation |
url | https://www.mdpi.com/2076-3417/15/2/834 |
work_keys_str_mv | AT fushanhe collaborativeoptimizationofaerodynamicsandwindturbineblades AT xingshengzheng collaborativeoptimizationofaerodynamicsandwindturbineblades AT weilinluo collaborativeoptimizationofaerodynamicsandwindturbineblades AT jianfengzhong collaborativeoptimizationofaerodynamicsandwindturbineblades AT yunhuahuang collaborativeoptimizationofaerodynamicsandwindturbineblades AT ailiye collaborativeoptimizationofaerodynamicsandwindturbineblades AT rongrongqiu collaborativeoptimizationofaerodynamicsandwindturbineblades AT huafuma collaborativeoptimizationofaerodynamicsandwindturbineblades |