Abstract
This work describes initial results obtained from an ongoing research involving the development of optimization algorithms which are capable of performing multi-disciplinary aircraft trajectory optimization processes. A short description of both the rationale behind the initial selection of a suitable optimization technique and the status of the optimization algorithms is firstly presented. The optimization algorithms developed are subsequently utilized to analyze different case studies involving one or more flight phases present in actual aircraft flight profiles. Several optimization processes focusing on the minimization of total flight time, fuel burned and oxides of nitrogen (NO x ) emissions are carried out and their results are presented and discussed. When compared with others obtained using commercially available optimizers, results of these optimization processes show satisfactory level of accuracy (average discrepancies ~2%). It is expected that these optimization algorithms can be utilized in future to efficiently compute realistic, optimal and 'greener' aircraft trajectories, thereby minimizing the environmental impact of commercial aircraft operations.
Highlights
In this globalized world, where the efficient transportation of people and goods greatly contributes to the development of a given region or country, the aviation industry has found the ideal conditions for its development
The critical nature of this problem means that currently several organizations worldwide are focusing their efforts towards large collaborative projects whose main objective is to identify the best alternatives or routes to reduce the environmental impact of aircraft operations
Two different approaches used within the commercial package were (i) a pattern search algorithm called mesh adaptive search (MADS), and (ii) genetic algorithms (GAs)
Summary
In this globalized world, where the efficient transportation of people and goods greatly contributes to the development of a given region or country, the aviation industry has found the ideal conditions for its development. Flight Profiles It is clear that in order to demonstrate the suitability of an optimizer for optimizing aircraft trajectories, an extensive validation process of the algorithms that are implemented needs to be carried out using different analytical problems with known optimal values. The lower and upper bounds of the range of permissible values of the design variables were in general defined in a way to reduce the computational time of the optimization processes, to take into account typical air traffic control (ATC) restrictions, and/or to avoid the aircraft losing (gaining) altitude during climb (descent) processes. Below 10,000 ft, the EAS lower and upper bounds usually correspond to, respectively, the aircraft stall speed
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
