Design and Multi Objective Optimization of an Axisymmetric Air Intake for Specific Mass Flow Rate and Design Mach Number

Air intakes play an important role in the operation of aircrafts, so their optimal performance can have a significant effect on the performance of the propulsion system. The purpose of this study was to design and optimize an axisymmetric air intake for a mass flow rate of 10 kg / sec in a free-stream Mach number of 2.5 at sea-level conditions. In the present study, pressure recovery and flow distortion coefficients are selected as functional parameters for optimization. Initially, the parametric design of the intake and the selection of geometric parameters were dealt with, and then the interval of the parameter changes was determined. In this research, the NSGA-II multi-objective genetic algorithm was used as an optimization algorithm; artificial neural network was used to predict intake performance in the optimization loop; for training neural networks 243 Initial geometry has been designed and numerically solved. The genetic algorithm that used has 20 population per generation and 1000 generations. After 1000 generations, the resulting population is selected as optimal geometries. At the end of the optimization, the pressure recovery and flow distortion were improved by 4.4% and 49%, which indicates the efficiency of the optimization process.