Kinematic Optimization of Energy Extraction Efficiency for Flapping Airfoil by using Response Surface Method and Genetic Algorithm

Document Type : Regular Article

Authors

1 Aeronautics and Propulsive Systems Laboratory, Faculty of Mechanical Engineering, Department of Mechanics, University of Sciences and Technology of Oran Mohamed Boudiaf, BP. 1505 Oran El M'Naouer, 31000 Oran, Algeria

2 LMF, Ecole Militaire Polytechnique (EMP), B.P 17 Bordj-el-Bahri, 16111, Algiers, Algeria

3 IUSTI Laboratory, UMR 7343 CNRS-University of Aix-Marseille Technopole de Chateau-Gombert, 5 rue Enrico Fermi 13453 MARSEILLE, Cedex 13, France

Abstract

In this paper, numerical simulations have been performed to study the performance of a single fully activated flapping wing serving as energy harvester. The aims of the paper are predicting and maximizing the energy extraction efficiency by using optimization methodology. The metamodeling and the genetic algorithms are applied in order to find the optimal configuration improving the efficiency. A response surface method (RSM) based on Box–Behnken experimental design and genetic algorithm has been chosen to solve this problem. Three optimization factors have been manipulated, i.e. the dimensionless heaving amplitude h0, the pitching amplitude θ0 and the flapping frequency f. The ANSYS FLUENT 14 commercial software has been used to compute the governing flow equations at a Reynolds number of 1100, while the flapping movement combined from heaving and pitching of the NACA0015 foil has been carried out by using an in house user-defined function (UDF). A maximum predicted efficiency of 34.02% has been obtained with high accuracy of optimal kinematic factors of dimensionless heaving amplitude around the chord, high pitching amplitude and low flapping frequency of 0.304 hertz. Results have also showed that the interaction effect between optimization factors is important and the quadratic effect of the frequency is strong confirming the great potential of the applied optimization methodology.

Keywords

References

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History

  • Received: 10 November 2022
  • Revised: 12 January 2023
  • Accepted: 20 January 2023
  • Available online: 01 May 2023

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