Optimization of aspirated airfoil based on artificial bee colony algorithm and NURBS

To improve the optimization design quality of aspirated airfoil of axial compressor, an automatic optimization system was developed based on artificial bee colony (ABC) algorithm and non-uniform rational B-splines (NURBS). The mechanism of ABC algorithm was researched and the performance was compared with genetic algorithm (GA) commonly used at present. The comparison indicated that ABC algorithm can obtain better global optimum and the convergence speed was 50% higher than GA. NURBS was applied to parameterize the airfoil and distortion problems in the process were studied. The optimization system was validated by optimizing an aspirated cascade, both parameters of the profile and the suction settings were treated as optimization variables. Results show that the best suction location which could bring the most performance improvement is at about 58.44% axial chord length. 64.8% decrease of the flow loss is obtained if compared with the initial cascade and the separation of the flow is restrained.