New methodology for calculating flight parameters with neural network - Extended Great Deluge method applied on a reduced scale wind tunnel model of an ATR-42 wing

Abstract

The determination of flight parameters such as pressure distributions and aerodynamic coefficients (lift, drag and moment) from the known parameters (angle of attack, Mach number ...) in real time is still not achievable easily by methods of numerical analysis in aerodynamics and aeroelasticity domains. For this reason, we propose a flight parameters control system. This approach is based on new optimization methodologies with neural networks (NN) and extended great deluge (EGD). The validation of this new method is realized by experimental tests using a model installed in the wind tunnel to determine the pressure distribution. For lift, drag and moment coefficient, the results of our approach are compared to the XFoil results for different angles of attack. The main purpose of this control system is to improve the aircraft aerodynamic performance.