Avrupa hava trafiği ve uzay-zamansal grid salınım modellemede veri analizi ve simulasyonu uygalamaları

With its intrinsic complexity, rapidly growing demand and almost saturated infrastructures, Air Transport Management is one of the most challenging fields of the near future. To be able to respond the need, there are many conducted researches and initiatives as Single European Sky ATM Research (SESAR) programme in Europe and its US counterpart NextGen. Resilience2050.eu is one of the projects carried out in Europe with the purpose of analyzing the current air traffic system's deficiencies in terms of resilience ability. Aimed to design disruption and perturbation adaptive ATM concepts of future beyond SESAR within the boundaries of safety, this research project analyzes the current system dynamics focusing on the propagation of unexpected and undesired events through the whole ATM system which underlies the theme of this thesis. Macro analysis of the European Air Traffic Network system play a key role in pinpointing the elements and events that drive the system which are crucial for a resilient structure. Specifically the air transportation network across the airports, airspaces, subspaces and its segmentation define the structure of the flow network. In addition, scheduled flights, their densities across this network, and corresponding flight patterns define the nature of the flow across the network. The analyses provide an insight about the transportation network system's dynamics and serve to the construction of more accurate models which will enable the application of optimization problems into real world conditions. Accordingly, they form an essential part for the purpose of building a resilient structure and have an utter importance to construct reliable and robust air traffic management and control infrastructures. The analyses in this project have been conducted with two types of data as ALL_FT+ trajectory data and DDR capacity data. Each file of the trajectory data gives the all flights' trajectories with point and airspace profiles over European Air Traffic Network whereas DDR capacity data provides the declared capacities for different entities of air transportation system such as airports, airspaces etc. Among from various flight models and radar data in ALL_FT+ structure, Planned and Actual Data have been extracted with some assumptions. The planned data structure represents the prior determined trajectory that is intended to be flown whereas the actual data is the actual flown trajectory. Since the ALL_FT+ data has a complex structure with many flaws, series of fixing and filtering algorithms have been developed to preclude the wrong computations which may conclude with false deductions. The three parameters that create the infrastructure of analyses are capacity, traffic and delays. As it was mentioned, capacity values are obtained via DDR capacity data and the traffic and delays are extracted from ALL_FT+ data. The first leg of the analyses is to construct the network graph of the European Airspace where each node in the graph may represent airports. This graph does not only depict the interactions between airports, but also provide a framework to work on with traffic data. Each branch (edge) of the graph stands for reciprocal traffic flows between the related nodes. The complete connectivity graph is generated by the ALL_FT+ data itself thanks to continuous airspace profiles of each flight . The analysis is conducted bidirectional in each branches of the graph and the time interval of the whole analysis has been chosen as a month to see daily and weekly pattern and their variations based on flight plans of each day. Additionally, the findings that obtained through the traffic flow graphs regarding the magnitude of sectors also have been confirmed via monitoring the number aircrafts per hour in each sector. As a third parameter of the analyses, delays and their propagation across the network graph have been investigated. Delay is not only a solid merit of quality of service but also a key element which defines resilience in the Air Traffic Network. Individual delays for each phases that all flights experience have been calculated with seeking the differences between planned and actual data's elapsed times for each phase where the possible reasons for these differences may be unexpected events such as bad weather conditions or strikes. Aggregating these individual delays in terms of airspaces yields the delay distributions of airspaces over the European airspace network. Moreover classifying these delays in hourly intervals will depict the propagation of delays, and an example of this approach has been conducted over Frankfurt area. As a secondary approach, instead of using airspace centered analyses, network of airports have been investigated which shifts the focus to the propagation of delays between airport pairs. The approach introduces the examination of airport delays into analyses, hence the delays of Actual Off-Block Times and Taxi phases have been calculated and status of airports are monitored in terms of arrival/departure traffics and declared capacities. Incorporating the airports into the analyses provided the push-back delays and their evolutions through each flight's path which resulted with a complete track of delays. The analyses have been conducted in different perspectives and results of each are given with comments. The events, conditions and procedures that drive the air transportation network system have been identified to get deeper understanding and the comparisons of potential modelling techniques for European Air Transportation Network have been presented holistically. In addition to resilience of the European Air Traffic, emissions and air quality effects of the flights over the Marmara region have been investigated. In the last decade, air traffic has increased dramatically with a significant increase in emissions. Our goal is to quantify the impact of aircraft emissions on regional air quality, especially in regards to HC, NOx, and CO, and ozone. Here the focus is on Marmara Region, which is the busiest region in Turkey in terms of air traffic. First, aircraft HC, NOx, and CO emissions are estimated based on the Smoke Number (SN) by using the ''first order'' method. The Emissions and Dispersion Modeling System (EDMS) is used for gaseous species. HC, NOx, and CO emissions are estimated once based on the characteristic SN and a second time using the mode-specific SN. Further, aircraft emissions are processed in two ways: (1) allocating the emissions at the airport itself, and (2) by accounting for flight paths, mode, and plume rise. When the more conservative emission estimates are used (i.e, the characteristic SN estimates allocated to the region.