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.

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

Ponza R.;Benini E.;
2021

Abstract

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.
2021
AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2021
978-1-62410-610-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3443453
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