Sweep Blade Design for an Axial Wind Turbine using a Surrogate-assisted Differential Evolution Algorithm
This paper presents an optimal design of a sweep blade for the axial wind turbine using a hybrid surrogate-assisted optimizer. The design problem is defined to maximize the ratio of the torque coefficient to the thrust coefficient of a turbine blade at a low wind velocity of 10 m/s. Pitch angle and...
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| Format: | Article |
| Language: | English |
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Shahid Chamran University of Ahvaz
2023-01-01
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| Series: | Journal of Applied and Computational Mechanics |
| Subjects: | |
| Online Access: | https://jacm.scu.ac.ir/article_17704_d89260320160df166cdc017c585dd2d3.pdf |
| _version_ | 1811195244367052800 |
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| author | Nantiwat Pholdee Sumit Kumar Sujin Bureerat Weerapon Nuantong Watcharin Dongbang |
| author_facet | Nantiwat Pholdee Sumit Kumar Sujin Bureerat Weerapon Nuantong Watcharin Dongbang |
| author_sort | Nantiwat Pholdee |
| collection | DOAJ |
| description | This paper presents an optimal design of a sweep blade for the axial wind turbine using a hybrid surrogate-assisted optimizer. The design problem is defined to maximize the ratio of the torque coefficient to the thrust coefficient of a turbine blade at a low wind velocity of 10 m/s. Pitch angle and leading-edge blade curve are considered as the design variables. For the aerodynamic analysis of the wind turbine blade, computational fluid dynamics has been used as a high-fidelity simulation. While the surrogate models including, the Kriging model (KG), the radial basis function model (RBF), and the proposed hybrid of KG and RBF (HyKG-RBF) models are applied for function approximation or low-fidelity simulation. In this study, to obtain a set of sampling points and surrogate models development, an optimal Latin Hypercube sampling (OLHS) technique is utilized in the design of the experiment (DOE). A differential evolutionary (DE) algorithm is used to solve the proposed design problem. The performance of the proposed hybrid surrogate assisted optimization method is contrasted with two conventional surrogate assisted optimization techniques. Results demonstrate that the proposed hybrid surrogate model viz. HyKG-RBF is the most efficient surrogate-assisted optimization method for solving the sweep blade optimization problem. |
| first_indexed | 2024-04-12T00:40:09Z |
| format | Article |
| id | doaj.art-ec50172a7e6d49da8dcb57cf159f2dcb |
| institution | Directory Open Access Journal |
| issn | 2383-4536 |
| language | English |
| last_indexed | 2024-04-12T00:40:09Z |
| publishDate | 2023-01-01 |
| publisher | Shahid Chamran University of Ahvaz |
| record_format | Article |
| series | Journal of Applied and Computational Mechanics |
| spelling | doaj.art-ec50172a7e6d49da8dcb57cf159f2dcb2022-12-22T03:55:03ZengShahid Chamran University of AhvazJournal of Applied and Computational Mechanics2383-45362023-01-019121722510.22055/jacm.2022.40974.368217704Sweep Blade Design for an Axial Wind Turbine using a Surrogate-assisted Differential Evolution AlgorithmNantiwat Pholdee0Sumit Kumar1Sujin Bureerat2Weerapon Nuantong3Watcharin Dongbang4Sustainable and Infrastructure Research and Development Center, Department of Mechanical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, 40002, ThailandAustralian Maritime College, College of Science and Engineering, University of Tasmania, Launceston, 7248, AustraliaSustainable and Infrastructure Research and Development Center, Department of Mechanical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, 40002, ThailandDepartment of Mechatronics Engineering, Faculty of Engineering, Rajamangala University of Technology Isan, Khon Kaen Campus, Khon Kaen, 40000, ThailandDepartment of Energy Technology and Management, Faculty of Science, Energy and Environment, King Mongkut’s University of Technology North Bangkok, Rayong, 21120, ThailandThis paper presents an optimal design of a sweep blade for the axial wind turbine using a hybrid surrogate-assisted optimizer. The design problem is defined to maximize the ratio of the torque coefficient to the thrust coefficient of a turbine blade at a low wind velocity of 10 m/s. Pitch angle and leading-edge blade curve are considered as the design variables. For the aerodynamic analysis of the wind turbine blade, computational fluid dynamics has been used as a high-fidelity simulation. While the surrogate models including, the Kriging model (KG), the radial basis function model (RBF), and the proposed hybrid of KG and RBF (HyKG-RBF) models are applied for function approximation or low-fidelity simulation. In this study, to obtain a set of sampling points and surrogate models development, an optimal Latin Hypercube sampling (OLHS) technique is utilized in the design of the experiment (DOE). A differential evolutionary (DE) algorithm is used to solve the proposed design problem. The performance of the proposed hybrid surrogate assisted optimization method is contrasted with two conventional surrogate assisted optimization techniques. Results demonstrate that the proposed hybrid surrogate model viz. HyKG-RBF is the most efficient surrogate-assisted optimization method for solving the sweep blade optimization problem.https://jacm.scu.ac.ir/article_17704_d89260320160df166cdc017c585dd2d3.pdfevolutionary algorithmmeta modelblade optimization designhybrid surrogate modellow-fidelity simulation |
| spellingShingle | Nantiwat Pholdee Sumit Kumar Sujin Bureerat Weerapon Nuantong Watcharin Dongbang Sweep Blade Design for an Axial Wind Turbine using a Surrogate-assisted Differential Evolution Algorithm Journal of Applied and Computational Mechanics evolutionary algorithm meta model blade optimization design hybrid surrogate model low-fidelity simulation |
| title | Sweep Blade Design for an Axial Wind Turbine using a Surrogate-assisted Differential Evolution Algorithm |
| title_full | Sweep Blade Design for an Axial Wind Turbine using a Surrogate-assisted Differential Evolution Algorithm |
| title_fullStr | Sweep Blade Design for an Axial Wind Turbine using a Surrogate-assisted Differential Evolution Algorithm |
| title_full_unstemmed | Sweep Blade Design for an Axial Wind Turbine using a Surrogate-assisted Differential Evolution Algorithm |
| title_short | Sweep Blade Design for an Axial Wind Turbine using a Surrogate-assisted Differential Evolution Algorithm |
| title_sort | sweep blade design for an axial wind turbine using a surrogate assisted differential evolution algorithm |
| topic | evolutionary algorithm meta model blade optimization design hybrid surrogate model low-fidelity simulation |
| url | https://jacm.scu.ac.ir/article_17704_d89260320160df166cdc017c585dd2d3.pdf |
| work_keys_str_mv | AT nantiwatpholdee sweepbladedesignforanaxialwindturbineusingasurrogateassisteddifferentialevolutionalgorithm AT sumitkumar sweepbladedesignforanaxialwindturbineusingasurrogateassisteddifferentialevolutionalgorithm AT sujinbureerat sweepbladedesignforanaxialwindturbineusingasurrogateassisteddifferentialevolutionalgorithm AT weeraponnuantong sweepbladedesignforanaxialwindturbineusingasurrogateassisteddifferentialevolutionalgorithm AT watcharindongbang sweepbladedesignforanaxialwindturbineusingasurrogateassisteddifferentialevolutionalgorithm |