Design optimization of an axial fan blade through multi-objective evolutionary algorithm

Jin Hyuk Kim, Jae Ho Choi, Afzal Husain, Kwang Yong Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents design optimization of an axial fan blade with hybrid multi-objective evolutionary algorithm (hybrid MOEA). Reynolds-averaged Navier-Stokes equations with shear stress transport turbulence model are discretized by the finite volume approximations and solved on hexahedral grids for the flow analyses. The validation of the numerical results was performed with the experimental data for the axial and tangential velocities. Six design variables related to the blade lean angle and blade profile are selected and the Latin hypercube sampling of design of experiments is used to generate design points within the selected design space. Two objective functions namely total efficiency and torque are employed and the multi-objective optimization is carried out to enhance total efficiency and to reduce the torque. The flow analyses are performed numerically at the designed points to obtain values of the objective functions. The Non-dominated Sorting of Genetic Algorithm (NSGA-II) with ε -constraint strategy for local search coupled with surrogate model is used for multi-objective optimization. The Pareto-optimal solutions are presented and trade-off analysis is performed between the two competing objectives in view of the design and flow constraints. It is observed that total efficiency is enhanced and torque is decreased as compared to the reference design by the process of multi-objective optimization. The Pareto-optimal solutions are analyzed to understand the mechanism of the improvement in the total efficiency and reduction in torque.

Original languageEnglish
Title of host publicationAIP Conference Proceedings
Pages696-703
Number of pages8
Volume1225
DOIs
Publication statusPublished - 2010
Event10th Asian International Conference on Fluid Machinery, AICFM - Kuala Lumpur, Malaysia
Duration: Oct 21 2010Oct 23 2010

Other

Other10th Asian International Conference on Fluid Machinery, AICFM
CountryMalaysia
CityKuala Lumpur
Period10/21/1010/23/10

Fingerprint

fan blades
design optimization
torque
blades
optimization
experiment design
turbulence models
classifying
genetic algorithms
Navier-Stokes equation
shear stress
sampling
grids
profiles
approximation

Keywords

  • Axial fan
  • Evolutionary algorithm
  • Pareto-optimal solutions
  • Surrogate model
  • Torque
  • Total efficiency

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Kim, J. H., Choi, J. H., Husain, A., & Kim, K. Y. (2010). Design optimization of an axial fan blade through multi-objective evolutionary algorithm. In AIP Conference Proceedings (Vol. 1225, pp. 696-703) https://doi.org/10.1063/1.3464918

Design optimization of an axial fan blade through multi-objective evolutionary algorithm. / Kim, Jin Hyuk; Choi, Jae Ho; Husain, Afzal; Kim, Kwang Yong.

AIP Conference Proceedings. Vol. 1225 2010. p. 696-703.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kim, JH, Choi, JH, Husain, A & Kim, KY 2010, Design optimization of an axial fan blade through multi-objective evolutionary algorithm. in AIP Conference Proceedings. vol. 1225, pp. 696-703, 10th Asian International Conference on Fluid Machinery, AICFM, Kuala Lumpur, Malaysia, 10/21/10. https://doi.org/10.1063/1.3464918
Kim, Jin Hyuk ; Choi, Jae Ho ; Husain, Afzal ; Kim, Kwang Yong. / Design optimization of an axial fan blade through multi-objective evolutionary algorithm. AIP Conference Proceedings. Vol. 1225 2010. pp. 696-703
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