Optimization of a supersonic wind tunnel diffuser using genetic algorithm

Abstract

Purpose – The purpose of this paper is to find the optimum design of diffuser of supersonic wind tunnel in order to access the minimum overall pressure drop in wind tunnel, using evolutionary algorithm. Design/methodology/approach – The authors developed a genetic algorithm (GA) code to calculate the shape of a diffuser with flexible walls in order to have the maximum pressure recovery. The two-dimensional turbulent and compressible flow was analyzed numerically using shear-stress transport and Advection Upstream Splitting Method (AUSM)+ turbulence models and its optimization with GA. Findings – The results of this study indicate that elitist GA promises a powerful method for optimization of the wind tunnel diffuser. Separation zone is reduced by 22.2 percent at the convergent part of diffuser and 56 percent at the divergent part of diffuser. The efficiency of new optimized wind tunnel diffuser increased by 83 percent in comparison to the sample of supersonic wind tunnel. Originality/value – It has been observed that AUSM+ method and shape design optimization using GA are robust and efficient technique to optimize wind tunnel diffuser.

Supersonic Multi-Objective Optimization of a Rocket Based Combined Cycle Inlet by Differential Evolution

“…An example of this, was the use of a GA for the subsonic optimization of the exchange inlet by Chorkawy [43]. Other examples of aerospace engineering GA applications range from wind tunnels [44], to injector systems [45,46] and scramjet inlets [47].…”