Abstracts Category : Other

New methodologies for calculation of flight parameters on reduced scale wings models in wind tunnel

by Mosbah Abdallah Ben

In order to improve the qualities of wind tunnel tests, and the tools used to perform aerodynamic tests on aircraft wings in the wind tunnel, new methodologies were developed and tested on rigid and flexible wings models. A flexible wing concept is consists in replacing a portion (lower and/or upper) of the skin with another flexible portion whose shape can be changed using an actuation system installed inside of the wing. The main purpose of this concept is to improve the aerodynamic performance of the aircraft, and especially to reduce the fuel consumption of the airplane. Numerical and experimental analyses were conducted to develop and test the methodologies proposed in this thesis.To control the flow inside the test sections of the Price-Padoussis wind tunnel of LARCASE, numerical and experimental analyses were performed. Computational fluid dynamics calculations have been made in order to obtain a database used to develop a new hybrid methodology for wind tunnel calibration. This approach allows controlling the flow in the test section of the Price-Padoussis wind tunnel.For the fast determination of aerodynamic parameters, new hybrid methodologies were proposed. These methodologies were used to control flight parameters by the calculation of the drag, lift and pitching moment coefficients and by the calculation of the pressure distribution around an airfoil. These aerodynamic coefficients were calculated from the known airflow conditions such as angles of attack, the mach and the Reynolds numbers.In order to modify the shape of the wing skin, electric actuators were installed inside the wing to get the desired shape. These deformations provide optimal profiles according to different flight conditions in order to reduce the fuel consumption. A controller based on neural networks was implemented to obtain desired displacement actuators.A metaheuristic algorithm was used in hybridization with neural networks, and support vector machine approaches and their combination was optimized, and very good results were obtained in a reduced computing time.The validation of the obtained results has been made using numerical data obtained by the XFoil code, and also by the Fluent code. The results obtained using the mthodologies presented in this thesis have been validated with experimental data obtained using the subsonic Price-Padoussis blow down wind tunnel.