Genetic algorithm-based design of transonic aerofoils using Euler equations

The paper describes the adaptation of genetic algorithms (GA) to the design of inviscid transonic aerofoils. GA is effective in optimization strategies for designing transonic aerofoils where the non-linear aerodynamic phenomenon of shock wave results in flow discontinuity. The Euler equations are discretized through the flux-vector splitting method with Poisson's equation-based grid generation. Advanced strategies in the GA such as directed crossover and multi-stage searches are employed in the context of function-based global optimization. The objective is to determine the best combination of weighted parameters of a analytic function for the aerofoil surface, by maximizing the L/D ratio. The paper first covers the optimization of transonic aerofoils to enhance the baseline design of NACA0012. A two-point design problem is also conducted to accommodate both transonic and subsonic regimes represented by the Mach number and angle of attack. The optimized aerofoils have shown improved aerodynamic performance for both flight regimes.