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Development of an efficient aerodynamic shape optimization framework

Author

Listed:
  • Kim, Jong-Eun
  • Rao, Vinay N.
  • Koomullil, Roy P.
  • Ross, Doug H.
  • Soni, Bharat K.
  • Shih, Alan M.

Abstract

Although many efforts have been made to develop an aerodynamic shape optimization (ASO) framework, iterative grid generation of the complex configuration within the optimization loop has still been a critical barrier. In this paper, an efficient ASO framework is developed by integrating a parametric grid generator, an optimization toolkit, and a flow solver. A geometry-grid template toolkit is developed to address the need to produce a large number of grids in a timely manner for the parametric design study. An object-oriented optimization toolkit that allows a flexible and extensible interfacing with user-specific codes is used. An in-house full Navier–Stokes flow solver is developed and used in the framework. Code integration is achieved using a black-box interface with script files. Two ASO applications and their optimum solutions are presented to demonstrate the success of this framework.

Suggested Citation

  • Kim, Jong-Eun & Rao, Vinay N. & Koomullil, Roy P. & Ross, Doug H. & Soni, Bharat K. & Shih, Alan M., 2009. "Development of an efficient aerodynamic shape optimization framework," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2373-2384.
    • Handle: RePEc:eee:matcom:v:79:y:2009:i:8:p:2373-2384
    DOI: 10.1016/j.matcom.2009.01.012
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    Cited by:

    1. Zhu, Ping & Pan, Feng & Chen, Wei & Zhang, Siliang, 2012. "Use of support vector regression in structural optimization: Application to vehicle crashworthiness design," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 86(C), pages 21-31.

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