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Aerodynamic Shape Optimization Using Improved Territorial Particle Swarm Algorithm

[+] Author Affiliations
Amir Nejat, Pooya Mirzabeygi, Masoud Shariat-Panahi

University of Tehran, Tehran, Iran

Paper No. IMECE2012-88828, pp. 509-517; 9 pages
doi:10.1115/IMECE2012-88828
From:
  • ASME 2012 International Mechanical Engineering Congress and Exposition
  • Volume 1: Advances in Aerospace Technology
  • Houston, Texas, USA, November 9–15, 2012
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4517-2
  • Copyright © 2012 by ASME

abstract

In this paper, a new robust optimization technique with the ability of solving single and multi-objective constrained design optimization problems in aerodynamics is presented. This new technique is an improved Territorial Particle Swarm Optimization (TPSO) algorithm in which diversity is actively preserved by avoiding overcrowded clusters of particles and encouraging broader exploration. Adaptively varying “territories” are formed around promising individuals to prevent many of the lesser individuals from premature clustering and encouraged them to explore new neighborhoods based on a hybrid self-social metric. Also, a new social interaction scheme is introduced which guided particles towards the weighted average of their “elite” neighbors’ best found positions instead of their own personal bests which in turn helps the particles to exploit the candidate local optima more effectively. The TPSO algorithm is developed to take into account multiple objective functions using a Pareto-Based approach. The non-dominated solutions found by swarm are stored in an external archive and nearest neighbor density estimator method is used to select a leader for the individual particles in the swarm. Efficiency and robustness of the proposed algorithm is demonstrated using multiple traditional and newly-composed optimization benchmark functions and aerodynamic design problems. In final airfoil design obtained from the Multi Objective Territorial Particle Swarm Optimization algorithm, separation point is delayed to make the airfoil less susceptible to stall in high angle of attack conditions. The optimized airfoil also reveals an evident improvement over the test case airfoil across all objective functions presented.

Copyright © 2012 by ASME

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