The approach exploited within the the EC funded project COSMA (Community Oriented Solutions to Minimize Aircraft Annoyance, FP7) for multi-objective optimization aimed at optimal take-off and landing trajectories (minimizing noise emissions and fuel bum) is presented. The methodology has been recently extended to include aircraft design variables, performing a simultaneous design/procedure optimization. As noise indicator, the area bounded by the SEL 60dBA contour is chosen, whereas the fuel bum refers to the specified procedure. A binary coded multi-objective genetic algorithm (MOGA) is applied to find the front of non-dominated solutions (Pareto front) and an optimal compromise solution is selected. The trajectory is partitioned into segments, and the 3D spatial coordinates of each segment extreme, along with the aircraft speed and high-lift devices settings are taken as optimization variables. Aircraft performance and noise emissions are evaluated through the multidisciplinary simulation, design and optimization tool FRIDA (Framework for Innovative Design in Aeronautics). The approach is applied to three classes of aircraft, from mid to long range and the relevant results for mid range aircraft are presented herein.
Multi-objective, multi-disciplinary optimization of take-off and landing procedures to minimize the environmental impact of commercial aircraft: The noise vs fuel consumption trade-off within the EC project COSMA
Diez M;Leotardi C;
2012
Abstract
The approach exploited within the the EC funded project COSMA (Community Oriented Solutions to Minimize Aircraft Annoyance, FP7) for multi-objective optimization aimed at optimal take-off and landing trajectories (minimizing noise emissions and fuel bum) is presented. The methodology has been recently extended to include aircraft design variables, performing a simultaneous design/procedure optimization. As noise indicator, the area bounded by the SEL 60dBA contour is chosen, whereas the fuel bum refers to the specified procedure. A binary coded multi-objective genetic algorithm (MOGA) is applied to find the front of non-dominated solutions (Pareto front) and an optimal compromise solution is selected. The trajectory is partitioned into segments, and the 3D spatial coordinates of each segment extreme, along with the aircraft speed and high-lift devices settings are taken as optimization variables. Aircraft performance and noise emissions are evaluated through the multidisciplinary simulation, design and optimization tool FRIDA (Framework for Innovative Design in Aeronautics). The approach is applied to three classes of aircraft, from mid to long range and the relevant results for mid range aircraft are presented herein.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
