2017
DOI: 10.1051/rees/2017006
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A method to optimise the materials layout of small wind turbine blades

Abstract: Abstract. This paper presents a method to optimise the material layout of a fibreglass-reinforced composite constructed small wind turbine blade. The method was developed with the intent of reducing blade mass without compromising the blade's structural performance or longevity. The bi-directional evolutionary layout optimisation method utilises finite element analysis to redesign the composite lay of the blade structure based on a strain energy criterion. Details of the procedure of this method are documented… Show more

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Cited by 4 publications
(1 citation statement)
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“…Wind turbine rotor blade is a key element that converts wind kinetic energy into mechanical energy, hence the blade of the wind turbine must be stiff and should have sufficient strength to withstand alternating loads, making material selection for small wind turbine blades a complex problem. Costa MS et al (2017) have presented a bidirectional evolutionary layout optimization (BELO) method to optimize the material layout of a 2.5 m composite blade of a 5 kW wind turbine. Pourrajabian A et al (2016) have performed optimization of small wind turbine blade aerodynamically and structurally using genetic algorithm optimization technique.…”
Section: Introductionmentioning
confidence: 99%
“…Wind turbine rotor blade is a key element that converts wind kinetic energy into mechanical energy, hence the blade of the wind turbine must be stiff and should have sufficient strength to withstand alternating loads, making material selection for small wind turbine blades a complex problem. Costa MS et al (2017) have presented a bidirectional evolutionary layout optimization (BELO) method to optimize the material layout of a 2.5 m composite blade of a 5 kW wind turbine. Pourrajabian A et al (2016) have performed optimization of small wind turbine blade aerodynamically and structurally using genetic algorithm optimization technique.…”
Section: Introductionmentioning
confidence: 99%