Aerodynamic shape optimization of aircraft components using an advanced multi-objective evolutionary approach
In this paper, a fast and effective CFD-based automatic loop for optimization of rotorcraft components is presented. The automatic loop is strictly designed around an innovative Multi Objective Evolutionary Algorithm (MOEA) developed at University of Padua, namely the GeDEA-II. This algorithm allows performing multi-objective, multi-point optimization works in a fast and robust way. It combines novel crossover and mutation operators when compared to other state-of-the-art MOEA. Recent papers show its excellent performance when tested on state-of-the-art problems. In order to test the performance of this algorithm, two test cases are presented, each having peculiar characteristics making them even harder to solve. Test cases regard the aerodynamic shape optimization of ERICA components, that is an innovative tilt-rotor concept conceived and designed recently. The first problem regards the single-objective, multi-constrained aerodynamic optimization of the ERICA tilt-rotor cockpit region. The second one is a multi-objective multi-constrained optimization of the ERICA landing gear sponsons. Results demonstrate the effectiveness of this automatic optimization loop in tackling real-world engineering problems.
aerodynamics optimization multi objective evolutionary algorithm aircraft optimization