No more conflicts: the development of a generic airport model in a sequence-optimization framework

International audienceComponents of the airport airside such as runways, taxiways and aprons, have a significant impact in the total capacity of the airport system, where capacity is usually considered as maximum number of air traffic movements or number of passengers accommodated in a given period of time. Operations on the airside impact in the propagation of delay and consequently in the perceived level of service by passengers the terminal buildings. This paper put the focus on the airside operations at airports. A methodology for modelling operations on the ground and the successive optimization is proposed. The methodology presented in this paper is generic enough in the sense that it can be applied to any airport. The objective of this work is to come up with a generic tool that can be used by air traffic controllers in order to minimize conflicts on the ground and consequently increase the airport capacit

Tackling Uncertainty for the Development of Efficient Decision Support System in Air Traffic Management

International audienceAirport capacity has become a constraint in the air transportation networks, due to the growth of air traffic demand and the lack of resources able to accommodate this demand. This paper presents the algorithmic implementations of a decision support system for making a more efficient use of the airspace and ground capacity. The system would be able to provide support for air traffic controllers in handling large amount of flights while reducing to a minimum the potential conflicts. In this framework, airspace together with ground airport operations are considered. Conflicts are defined as separation minima violation between aircraft for what concerns airspace and runways, and as capacity overloads for taxiway network and terminals. The methodology proposed in this work consists of an iterative approach that couples optimization and simulation to find solutions that are resilient to perturbations due to the uncertainty present in different phases of the arrival and departure process. An optimization model was employed to find a (sub)optimal solution while a discrete event-based simulation model evaluated the objective function. By coupling simulation with optimization, we generate more robust solutions resilient to variability in the operations, this is supported by a case study of Paris Charles de Gaulle Airport

Tackling Uncertainty for the Development of Efficient Decision Support System in Air Traffic Management

International audienceAirport capacity has become a constraint in the air transportation networks, due to the growth of air traffic demand and the lack of resources able to accommodate this demand. This paper presents the algorithmic implementations of a decision support system for making a more efficient use of the airspace and ground capacity. The system would be able to provide support for air traffic controllers in handling large amount of flights while reducing to a minimum the potential conflicts. In this framework, airspace together with ground airport operations are considered. Conflicts are defined as separation minima violation between aircraft for what concerns airspace and runways, and as capacity overloads for taxiway network and terminals. The methodology proposed in this work consists of an iterative approach that couples optimization and simulation to find solutions that are resilient to perturbations due to the uncertainty present in different phases of the arrival and departure process. An optimization model was employed to find a (sub)optimal solution while a discrete event-based simulation model evaluated the objective function. By coupling simulation with optimization, we generate more robust solutions resilient to variability in the operations, this is supported by a case study of Paris Charles de Gaulle Airport

Integrated optimization of terminal maneuvering area and airport at the macroscopic level

Airports and surrounding airspaces are limited in terms of capacity and represent the major bottlenecks of the air traffic management system. This paper addresses the problems of terminal airspace management and airport congestion management at the macroscopic level through the integrated control of arrivals and departures. Conflict detection and resolution methods are applied to a predefined terminal route structure. Different airside components are modeled using network abstraction. Speed, arrival and departure times, and runway assignment are managed by using an optimization method. An adapted simulated annealing heuristic combined with a time decomposition approach is proposed to solve the corresponding problem. Computational experiments performed on case studies of Paris Charles De-Gaulle airport show some potential improvements: First, when the airport capacity is decreased, until a certain threshold, the overload can be mitigated properly by adjusting the aircraft entry time in the Terminal Maneuvering Area and the pushback time. Second, landing and take-off runway assignments in peak hours with imbalanced runway throughputs can significantly reduce flight delays. A decrease of 37% arrival delays and 36% departure delays was reached compared to baseline case

Modelling and Simulation of APOC Operations

International audienceThis work aims at developing an agent-based platform that allows to model and analyze decisions made by different stakeholders in an Airport Operations Centre. We will develop a methodology combining agent-based modelling and field/lab behavioral experiments for identifying the incentives behind the decisions of the stakeholders in an Airport Operations Centre environment. Once, the causal relationships have been identified, these will be translated into an agent-based environment so, it will be possible to have a virtual environment for identifying which incentives are the best for aligning the objectives of the center, considering the diversity of objectives present in the system. The causal-relationships identified in the study will be validated with a human-in-the-loop environment already developed under the SESAR program. This study is an interdisciplinary one which integrates simulation, decision making and behavioral science in the airport operations center environment

Extended enantiopure ortho-phenylene ethylene (o-OPE)-based helical systems as scaffolds for supramolecular architectures: a study of chiroptical response and its connection to the CISS effect

A novel synthetic strategy based on a bifunctional stapled chiral nucleus from which segments of different lengths can be added to both ends of o-phenylene ethynylenes (o-OPEs) has been developed to obtain a new type of foldamer and a novel chiral Pd2L2 metallacycle. For the first time, an enantiopure fully conjugated helical foldamer having 14 phenyl rings and 13 alkynes is reported. The folded structure has four complete loops and is able to host three Ag(i) cations in their cavity with high binding constants. The complete photophysical and chiroptical (ECD, CPL and VCD) characterization of these foldamers has shown that these molecules show intense chiroptical responses with dissymmetry ratios in the range of 10(-2). Theoretical modeling of these systems reveals the origin of these remarkable responses and points out a potential connection with the chiral induced spin selectivity (CISS) effect. The magnetic dipole moment is proposed as a key physical variable connecting the chiroptical properties and CISS-based spin filtering properties observed in chiral compounds