Optimization design of a compressor cascade airfoil using a Navier-Stokes solver and genetic algorithms

This paper presents the multiobjective aerodynamic design of a compressor cascade using a Navier-Stokes sower and genetic algorithms (GAs). The design goal of a compressor cascade optimization is to maximize the pressure rise and minimize the total pressure loss at the given flow condition on the basis of the controlled diffusion airfoil (CDA). A two-branch Boltzmann selection and Pareto optimal solution criteria method are applied to GAs for the multiobjective optimization design. The optimization performance of the present multiobjective GAs is demonstrated by the typical test function. Bezier curves are adopted to represent the geometry of the cascade shape. The aerodynamic performance of design candidates is evaluated using a two-dimensional Navier-Stokes solver. The obtained results of the compressor cascade design provide many Pareto optimal solutions. A certain Pareto optimal solution with higher pressure rise and lower total pressure loss is demonstrated to have improved aerodynamic performance than the existed CDA.