Multi-criteria Multi-constrained Aerodynamic Optimization of Civil Tiltrotor Empennage Surfaces

The present work describes the overall optimization strategy that has been adopted for the enhancement of the aerodynamic performance of a civil tiltrotor empennage surfaces. The optimization process has been designed around GeDEA-II, a Multi-Objective Evolutionary Algorithm developed at University of Padua. The optimization algorithm has been used in two different cases: A two-dimensional optimization of the empennage airfoil and a three-dimensional optimization of the empennage winglets, patented by Leonardo Helicopters under the name of finlets. Results demonstrate the effectiveness of the optimization strategies for both the cases. A parametric study of the empennage planform has also been conducted with the aid of an artificial neural network, in order to assess the variations in aerodynamic performance for different geometries.