Over the past few years, great concern has been raised about the impact of commercial aviation on the environment. In a Business As Usual approach, the expected growth in air traffic is going to affect climate change even more unless mitigation policies are devised and implemented. Although there is a tendency to focus on long-term technological solutions and breakthroughs, short-term improvements applicable to existing aircraft/engine configurations are also very important to fully realise the benefits of new technologies. Aircraft trajectory optimisation presents the opportunity to effectively reduce fuel consumption and pollutants emitted providing a feasible short-term strategy to be applied to the existing aircraft fleet. The present study focuses on preliminary results obtained using a multi-disciplinary aircraft trajectory optimisation simulation framework. Three in-house computational models are implemented in the framework to model the aircraft and engine performance, as well as to predict the level of gaseous emissions produced. A commercially available optimiser is integrated within the framework to analyse and optimise single flight path elements (e.g., climb), as well as the entire flight profile. For the purpose of this study, the climb and the whole flight profile are divided in four and eight segments respectively. Trajectory optimisation processes are then carried out in order to minimise three different objective functions: flight time, fuel burned, and mass of oxides of nitrogen (NOx) emitted. The results of the trajectory optimisation processes performed confirm the validity, effectiveness, and flexibility of the methodology proposed. In future, it is expected that these types of approaches are utilised to efficiently compute complete, optimum and ‘greener’ aircraft trajectories, which help to minimise the impact of commercial aviation on the environment. Other computational models that simulate several other aspects such as aircraft and engine noise, weather conditions and contrails formation, among others, need to be also included in the optimisation processes.

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