Performance enhancement of axial fan blade through multi-objective optimization techniques

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

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

This paper presents an axial fan blade design optimization method incorporating a hybrid multi-objective evolutionary algorithm (hybrid MOEA). In flow analyses, Reynolds-averaged Navier-Stokes (RANS) equations were solved using the shear stress transport turbulence model. The numerical results for the axial and tangential velocities were validated by comparing them with experimental data. Six design variables relating to the blade lean angle and the blade profile were selected through Latin hypercube sampling of design of experiments (DOE) to generate design points within the selected design space. Two objective functions, namely, total efficiency and torque, were employed, and multi-objective optimization was carried out, to enhance the performance. A surrogate model, Response Surface Approximation (RSA), was constructed for each objective function based on the numerical solutions obtained at the specified design points. The Non-dominated Sorting of Genetic Algorithm (NSGA-II) with local search was used for multi-objective optimization. The Pareto-optimal solutions were obtained, and a trade-off analysis was performed between the two conflicting objectives in view of the design and flow constraints. It was observed that, by the process of multi-objective optimization, the total efficiency was enhanced and the torque reduced. The mechanisms of these performance improvements were elucidated by analysis of the Pareto-optimal solutions.

Original languageEnglish
Pages (from-to)2059-2066
Number of pages8
JournalJournal of Mechanical Science and Technology
Volume24
Issue number10
DOIs
Publication statusPublished - Oct 2010

Fingerprint

Multiobjective optimization
Fans
Torque
Turbulence models
Sorting
Evolutionary algorithms
Design of experiments
Navier Stokes equations
Shear stress
Genetic algorithms
Sampling

Keywords

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

ASJC Scopus subject areas

  • Mechanical Engineering
  • Mechanics of Materials

Cite this

Performance enhancement of axial fan blade through multi-objective optimization techniques. / Kim, Jin Hyuk; Choi, Jae Ho; Husain, Afzal; Kim, Kwang Yong.

In: Journal of Mechanical Science and Technology, Vol. 24, No. 10, 10.2010, p. 2059-2066.

Research output: Contribution to journalArticle

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