Genetic algorithm based design of transonic airfoils using Euler equations

Minsung Jang, Jongsoo Lee

Research output: Contribution to journalConference article

7 Citations (Scopus)

Abstract

The paper describes the adaptation of genetic algorithms (GA's) in design of inviscid transonic airfoils. GA's are effective optimization strategies in designing of transonic airfoils where the nonlinear aerodynamic phenomenon such as shock wave results in flow discontinuity. Euler equations are discretized through flux vector splitting method with Poisson's equation based grid generation. Advanced strategies in GA's such as directed crossover and multistage searches are used to overcome drawbacks in computational fluid dynamics based direct optimization under the global optimization environment. The objective is to determine the best combination of weighted parameters of analytic functions for airfoil surface, by maximizing the L/D ratio. The paper first covers the optimization of transonic airfoils to enhance the baseline design of NACA0012. Multiobjective design problem is also conducted to accommodate both transonic and subsonic regimes represented by Mach number and angle of attack. The optimized airfoils have shown improved aerodynamic performance for both flight regimes.

All Science Journal Classification (ASJC) codes

  • Architecture
  • Materials Science(all)
  • Aerospace Engineering
  • Mechanics of Materials
  • Mechanical Engineering

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