Towards the Development of a Multi-Disciplinary Flight Trajectory Optimization Tool: GATAC

Abstract

Reducing the impact on the environment and the associated commercial implications are two major challenges that the global commercial aviation industry is addressing with significant commitment today. In this respect, Clean Sky, which is a €1.6 billion Joint Technology Initiative part funded by the European Commission is the largest ever programme addressing the greening of air transportation in response to the Advisory Council for Aeronautics Research in Europe (ACARE) goals of reducing CO2 and perceived noise emissions by 50% and NOx by 80% by 2020 compared to 2000 condition. This paper presents research work carried out within the Systems for Green Operations Integrated Technology Demonstrator (ITD) of Clean Sky that is associated with GATAC, a trajectory and route planning tool to enable the multi-objective optimization of flight trajectories and missions. The design and operational methodology of the tool, the optimization algorithms and models are discussed and the results of a preliminary application for a long-range commercial flight are presented.

Multi-objective optimisation of aircraft flight trajectories in the ATM and avionics context

“…The most desired quality of EA is therefore that they are natively suitable for the research of the global optima, since the method produces an arbitrary number of non-deterministic initial guesses and the algorithm itself is not restricted on the concept of the search scope. Among other research activities, EA were exploited as part of the research within the Systems for Green Operations Integrated Technology Demonstrator (SGO-ITD) of Clean Sky by the Green Systems for Aircraft Foundation (GSAF) academic cluster [122][123][124][125][126][127][128][129][130][131][132][133].…”

Novel flight management system for improved safety and sustainability in the CNS+A context

“…The NG-FMS generates 4DT intents composed by groups of single trajectories t belonging to the global set T. A number of algorithms have been adopted for trajectory generation and avoidance manoeuvres [14][15][16][17]. The consecutive Trajectory Change Points (TCP) along the path are defined with respect to the previous waypoints by conditional probability and generate fly-by and fly-over waypoints for each flight segment up to the destination.…”

Generic Framework for Multi-Disciplinary Trajectory Optimization of Aircraft and Power Plant Integrated Systems

“…In this way, the user effectively defines (formulates) the optimization problem. The optimization process takes place in the GATAC Core, which accesses an optimization function chosen from a suite by the user [2,3].…”

“…The data exchange between components carried out through Ethernet LAN. The Figure 2 illustrates the architecture and operating network of the GATAC distributed system [2,3].…”

“…New generations are created using different methods such as stochastic universal sampling, random selection and genetic operators (crossover and mutation). In the case of single objective optimization the result is the best-case while for a multi-objective optimization, the final result is a Pareto Front [3].…”