Experimental investigation, numerical modelling and multi-objective optimisation of composite wind turbine blades
Fagan, Edward M.
Leen, Sean B.
de la Torre, Oscar
MetadataShow full item record
This item's downloads: 54 (view details)
Fagan, 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: 10.1080/24705314.2017.1318043
Static 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.
This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. Please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.
The following license files are associated with this item: