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dc.contributor.authorFagan, Edward M.
dc.contributor.authorLeen, Sean B.
dc.contributor.authorde la Torre, Oscar
dc.contributor.authorJamie, Goggins
dc.identifier.citationFagan, Edward M., Leen, Sean B., de la Torre, Oscar, & Goggins, Jamie. (2017). Experimental investigation, numerical modelling and multi-objective optimisation of composite wind turbine blades. Journal of Structural Integrity and Maintenance, 2(2), 109-119. doi: 10.1080/24705314.2017.1318043en_IE
dc.description.abstractStatic load and modal testing of two blades from a 15 kW wind turbine is presented. The two blades are made from glass fibre-reinforced polypropylene, one of which has been reinforced with additional carbon fibre plies. Static testing is performed with a Whiffle tree test rig to determine the structural response of the blades. Blade mass, deflections, strains and natural frequencies are reported. The following objectives are undertaken: (i) evaluate and compare the test results of the two wind turbine blade designs, (ii) use the results to validate finite element models of the blades and (iii) utilise the validated models in a design optimisation study. Parametric blade models are generated using the Python programming language and are based on manufacturing specifications for the blades. The models show good correspondence with the experimental results. The goal of the optimisation study is to maximise the stiffness and reduce the mass of the glass fibre blade. A multi-objective genetic algorithm is used to determine the optimum laminate thicknesses along the length of the blades. The optimisation study produced a set of Pareto efficient blade designs with up to 17% improvement in stiffness and 30% reduction in mass for the glass fibre blade design.en_IE
dc.description.sponsorshipThis material is in part based upon works supported by the Science Foundation Ireland Marine Renewable Energy Ireland (MaREI) research centre under Grant No. 12/RC/2302. It was also funded by a fellowship from the College of Engineering and Informatics, NUI Galway, and was supported by an NUI Travelling Studentship, 2014. The last author would like to acknowledge the support of Science Foundation Ireland through the Career Development Award programme (Grant No. 13/CDA/2200). Additional thanks are given to the technical staff at NUI Galway and the group of mechanical engineering Masters students for their efforts on the testing of the wind turbine blades. Thanks also to Dr Jonathan Byrne for his guidance on the implementation of the NSGA-II algorithm.en_IE
dc.publisherTaylor & Francisen_IE
dc.relation.ispartofJournal of Structural Integrity and Maintenanceen
dc.subjectFinite element modellingen_IE
dc.subjectNon-dominated Sorting Genetic Algorithm-II (NSGA-II)en_IE
dc.subjectstructural testingen_IE
dc.subjectwind turbine bladeen_IE
dc.titleExperimental investigation, numerical modelling and multi-objective optimisation of composite wind turbine bladesen_IE
dc.contributor.funderScience Foundation Irelanden_IE
dc.contributor.funderCollege of Engineering and Informatics, National University of Ireland, Galwayen_IE
dc.contributor.funderScience Foundation Irelanden_IE
dc.local.contactSean Leen, Mechanical & Biomedical Eng, Eng-2051, New Engineering Building, Nui Galway. 5955 Email:
dcterms.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2302/IE/Marine Renewable Energy Ireland (MaREI) - The SFI Centre for Marine Renewable Energy Research/en_IE
dcterms.projectinfo:eu-repo/grantAgreement/SFI/SFI Career Development Award/13/CDA/2200/IE/Achieving nearly zero energy buildings - A life cycle assessment approach to retrofitting existing buildings (acronym: nZEB-RETROFIT)/en_IE

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