Aircraft shape design using artificial neural network

Abstract

To date, the aerodynamic coefficient of an aircraft has been obtained by computational fluid dynamics (CFD) or wind tunnel experiments, which have a high cost. To reduce the cost and period of analysis, we adopt big data analysis and AI techniques to build an artificial neural network (ANN) and perform learning and training based on historical flight and wind tunnel experiment parameters, so as to predict the aerodynamic coefficient of aircraft. Experimental results show that the values obtained by the proposed method are close to those obtained by wind tunnel experiments. Consequently, the proposed method can effectively reduce the amount of simulation analysis by CFD and wind tunnel experiments.