Aircraft propeller design using deep learning models and genetic algorithms

Abstract

The use of MLP-based surrogate aerodynamics modelsreduced the computational time by a factor of 50 whilemaintaining the computational accuracy. This advantage canbe further effectively used for solving optimization problemsbecause the high computational speed will allow theconsideration of a significantly larger number of combinationsof design variables and increase the design accuracy.