Demand & Capacity Management solutions are key SESAR (Single European Sky ATM Research) research projects to adapt future airspace to the expected high air traffic growth in a Trajectory Based Operations (TBO) environment. These solutions rely on processes, methods and metrics regarding the complexity assessment of traffic flows. However, current complexity methodologies and metrics do not properly take into account the impact of trajectories’ uncertainty to the quality of complexity predictions of air traffic demand. This paper proposes the development of several Bayesian network (BN) models to identify the impacts of TBO uncertainties to the quality of the predictions of complexity of air traffic demand for two particular Demand Capacity Balance (DCB) solutions developed by SESAR 2020, i.e., Dynamic Airspace Configuration (DAC) and Flight Centric Air Traffic Control (FCA). In total, seven BN models are elicited covering each concept at different time horizons. The models allow evaluating the influence of the “complexity generators” in the “complexity metrics”. Moreover, when the required level for the uncertainty of complexity is set, the networks allow identifying by how much uncertainty of the input variables should improve.
Performing Continuous Climb Operation (CCO) procedures enable the reduction of the environmental footprint and the improvement of the trajectory efficiency when individually operated. However, its operation may affect negatively the overall operational efficiency at Terminal Manoeuvring Areas (TMAs). The estimation of capacity is a matter of paramount importance to all airport planning and analyzing the capacity effects of this particular operational technique on a certain scenario will definitely help on evaluating its potential applicability. In this paper, departure runway capacity at the Adolfo Suárez Madrid-Barajas airport was operationally evaluated when introducing CCOs. The considered trajectories consisted of multiobjective optimized CCOs based on the optimal control theory, using the pseudospectral direct numerical method. These scenarios allowed addressing of the incremental variations of CCOs versus conventional departures, through fast time simulation, with the objective to assess the effects on the operations.
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