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ENCIT 2020
18th Brazilian Congress of Thermal Sciences and Engineering
A SIMPLIFIED GENETIC ALGORITHM FOR OPTIMIZING DIFFUSER-AUGMENTED HYDROKINETIC BLADES
Submission Author:
Jerson Vaz , PA , Canada
Co-Authors:
Marilza dos santos Viana, Déborah do Rio Vaz, Jerson Vaz
Presenter: Jerson Vaz
doi://10.26678/ABCM.ENCIT2020.CIT20-0195
Abstract
The main objective of this work is to develop a simplified genetic algorithm to optimize chord and twist angle distributions of diffuser-augmented hydrokinetic turbine blades. The methodology comprises a genetic algorithm coupled to an extended blade element momentum model, which is able to take into account diffuser effect. The approach optimizes hydrokinetic blades through maximizing turbine power coefficient, which is dependent on the axial induction factor at the rotor plane of the turbine. The proposed genetic algorithm uses the local power coefficient of the turbine as an evaluation function (fitness). The results are compared with the classical optimization method developed by Glauert. The main contribution of this work is the development of a simple and efficient approach for designing hydrokinetic rotors for harnessing kinetic energy from water streams.
Keywords
Diffuser, genetic algorithm, hydrokinetic turbine
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