Application of an Improved Particle Swarm Optimization Algorithm in Hydrodynamic Design

  • Sheng Huang
  • Wanlong Ren
  • Chao Wang
  • Chunyu Guo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7928)


In order to design the hydrofoil section with good lift-drag ratio performance, the airfoil which received by Improved Particle Swarm Optimization algorithm and Particle Swarm Optimization algorithm should be compared to find the best way in accord with the target. Airfoils are represented by analytic functions, and objective function and fitness function are provided by numerical solution of Panel method. In entire optimization process Improved Particle Swarm Optimization algorithm only changed the weight which influences the speed of particles flying, and optimized airfoil that compared to the original airfoil hydrodynamic performance has improved significantly, and has better result than the elementary particle swarm algorithm. Results of Optimization verified the feasibility of the improved Particle Swarm Optimization algorithm in the optimization of airfoil section design, and in the future this algorithm has certain significance.


Hydrofoil section optimization Improved Particle Swarm Optimization algorithm Panel method Optimization design 


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  1. 1.
    Wang, X.: Marine wing theory. National Defence Industry Press, Beijing (1988)Google Scholar
  2. 2.
    Zhou, B.: The study of four paddle two rudder of a large ship’s propeller panel method designed. Harbin, Harbin Engineering University. master’s thesis (2010)Google Scholar
  3. 3.
    Xu, P., Jiang, C.: Aerodynamic Optimization Design of Airfoil Based on Partical Swarm Optimuzation. Aircraft Design 128(15), 6–9 (2008)Google Scholar
  4. 4.
    Gao, S.: Ant colony algorithm theory, application and mixing with other algorithms. Nanjing University of Science and Technology doctoral thesis, NanJing (2005)Google Scholar
  5. 5.
    Kennedy, J., Ebehtart, R., et al.: SwarmIntelligence. Morgan Kuafann publishers, San rnaeiseo (2001)Google Scholar
  6. 6.
    Xu, Q., Liu, S., Liu, Q.: An improved particle swarm algorithm. Hangzhou University of Electronic Technology 28(6), 103–106 (2008)Google Scholar
  7. 7.
    Wang, X., Gao, Z.: Aerodynamic optimization design of airfoil based on genetic algorithm. Acta Aerodynamica Sinica 21(3), 70–75 (2000)Google Scholar
  8. 8.
    Xu, W.-B., Wang, C., Huang, S., Yu, K., Zhou, B.: The application of Particle swarm optimization theory in the hydrofoil design. Journal of SHIP Mechanics 15(6), 598–604 (2011)Google Scholar
  9. 9.
    Chang, X., Guo, C., Meng, X., Zhou, B.: Design of the airfoil section of the particle swarm algorithm. Marine Engineering 32(5), 1–3 (2010)CrossRefGoogle Scholar
  10. 10.
    Su, Y., Huang, S.: Ship propeller theory. Harbin Engineering University Press, Harbin (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Sheng Huang
    • 1
  • Wanlong Ren
    • 1
  • Chao Wang
    • 1
    • 2
  • Chunyu Guo
    • 1
  1. 1.College of Shipbuilding EngineeringHarbin Engineering UniversityHarbinChina
  2. 2.College of Naval Architecture and Marine PowerNaval University of EngineeringWuhanChina

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