Publication:
Simultaneous aerodynamic and structural optimisation of a low-speed horizontal-axis wind turbine blade using metaheuristic algorithms

dc.contributor.authorSabangban, Numchoak
dc.contributor.authorPanagant, Natee
dc.contributor.authorBureerat, Sujin
dc.contributor.authorWansasueb, Kittinan
dc.contributor.authorKuma, Sumit
dc.contributor.authorYıldız, Ali Riza
dc.contributor.authorPholdee, Nantiwat
dc.contributor.buuauthorYILDIZ, ALİ RIZA
dc.contributor.departmentBursa Uludağ Üniversitesi/Makine Mühendisliği Bölümü
dc.contributor.researcheridF-7426-2011
dc.date.accessioned2024-11-08T08:16:50Z
dc.date.available2024-11-08T08:16:50Z
dc.date.issued2023-04-12
dc.description.abstractThis work presents a concurrent design and multi-objective optimisation framework of horizontal axis wind turbine blades, made of composite material, for low wind speed. The optimisation model aims to minimise the structural mass of the blade whilst simultaneously maximising the turbine power output, subjected to three constraints viz. blade tip deflection, and Tsai-Hill and von Mises criteria. The design variables are blade shape and details of the internal blade structure. The control points and polynomial interpolation technique were adopted to determine the blade shape while the airfoil types at blade sections remained fixed. The internal blade structure design variables include the thickness of ribs and spars and the carbon fibre thickness and orientations. The blade element momentum approach is utilised to calculate turbine power and structural loads, whereas a finite element method is employed for structural analysis. Twelve multi-objective metaheuristics algorithms are used to solve the proposed multi-objective optimisation problem while their performance is investigated. The results obtained show that the multi-objective cuckoo search algorithm is the most efficient method. This study is said to be the baseline for a future study on multi-objective optimisation which combines two design stages of the composite low-speed wind turbine blades.
dc.description.sponsorshipResearch Fund for Supporting Lecturer to Admit High Potential Student to Study and Research on His Expert Program Year -2019 - 621T226
dc.description.sponsorshipNational Research Council of Thailand (NRCT) - N42A650549
dc.identifier.doi10.1515/mt-2022-0308
dc.identifier.eissn2195-8572
dc.identifier.endpage714
dc.identifier.issn0025-5300
dc.identifier.issue5
dc.identifier.startpage699
dc.identifier.urihttps://doi.org/10.1515/mt-2022-0308
dc.identifier.urihttps://www.degruyter.com/document/doi/10.1515/mt-2022-0308/html
dc.identifier.urihttps://hdl.handle.net/11452/47620
dc.identifier.volume65
dc.identifier.wos000970284100001
dc.indexed.wosWOS.SCI
dc.language.isoen
dc.publisherWalter de Gruyter Gmbh
dc.relation.journalMaterials Testing
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectDesign optimization
dc.subjectShape optimization
dc.subjectSearch
dc.subjectAlternative energy resources
dc.subjectEvolutionary algorithms
dc.subjectLow-speed wind turbine
dc.subjectMulti-objective optimisation
dc.subjectWind turbine blades optimisation
dc.subjectScience & technology
dc.subjectTechnology
dc.subjectMaterials science, characterization & testing
dc.subjectMaterials science
dc.titleSimultaneous aerodynamic and structural optimisation of a low-speed horizontal-axis wind turbine blade using metaheuristic algorithms
dc.typeArticle
dspace.entity.typePublication
relation.isAuthorOfPublication89fd2b17-cb52-4f92-938d-a741587a848d
relation.isAuthorOfPublication.latestForDiscovery89fd2b17-cb52-4f92-938d-a741587a848d

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