Acceleration method for evolutionary optimization of variable cycle engine

Variable cycle engine (VCE) is considered as one of the best options for advanced military or commercial supersonic propulsion system. Variable geometries enable the engine to adjust performance over the entire the flight envelope but add complexity to the engine. Evolutionary algorithms (EAs) have been widely used in the design of VCE. The initial guesses of the engine model are generally set using design point information during evolutionary optimization. However, the design point information is not suitable for all situations. Without suitable initial guesses, the Newton-Raphson solver will not be able to reach the solution quickly, or even get a convergent solution. In this paper, a new method is proposed to obtain suitable initial guesses of VCE model during evolutionary optimization. Differential evolution (DE) algorithm is used to verify our method through a series of optimization cases of a double bypass VCE. The result indicates that the method can significantly reduce the VCE model call number during evolutionary optimization, which means a dramatic reduction in terms of evolution time. And the robustness of the optimization is not affected by the method. The method can also be used in the evolutionary optimization of other engines.