Aerodynamic Optimization of High Speed Propellers

Abstract

The fact that fuel costs accounts for 29% of all airlines cost [1] and the increase in environmental awareness is driving the aviation industry to reach for more efficient engines. One of the promising technologies to tackle this problem is the open-rotor, which combines the fuel efficiency of turboprops together with the high cruise Mach number of turbofans. More specifically, counter rotating open-rotors (CROR), which are expected to bring fuel savings in the order of 20% − 35% [2]. A new type of propeller blades was invented by Richard Avellán and Anders Lundbladh, the Boxprop (patent filed in 2009 [3]). Its highly 3 dimensional geometry together with the complexity of the flow, make the optimization challenging for conventional design methods, thus necessitating a different approach. In this thesis work a generic optimization framework in Python that can handle both single-objective and multi-objective optimization problems by means of genetic algorithms is presented. Moreover, the parametrization of the Boxprop is also carried out, together with the automation of the geometry creation and mesh generation processes using Python and ICEM CFD scripting.