Differential evolution in aerodynamic optimization

Abstract

Aerodynamic design algorithms require an optimization strategy to search for the best design. The object of this paper is to compare the performance of Differential Evolution, a recently developed genetic algorithm, with other more traditional optimization strategies. An inverse design technique is developed to design fan blade profiles. The design objective in this case is the surface pressure distribution. Three different optimizers are integrated into the inverse design algorithm in order to compare their performance. Differential Evolution is shown to be the most effective of the three - finding solutions even when the other optimizers are unable to do so. However, genetic algorithms are not efficient, and Differential Evolution requires a high number of function evaluations to converge to a solution.