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This thesis presents two aspects of air transportation systems, capacity and efficiency. The first study improved a runway capacity simulation model for estimating the capacity of airports under various conditions. The main contribution of this study was to develop a simulation model which is able to analyze different airports with individual aircraft types. Many air traffic regulations were added to the simulation model to give more realistic results to the potential users of the model. Analysis of different separation systems between aircraft pairs show that the capacity of airports can improve by using more efficient separation systems specially under tough weather conditions. One of the outputs of the study, is an upgraded user interface which can be used by airport authorities for estimating their facilities' available capacity under different scenarios. The second study represents a new method for estimating unimpeded taxi times for taxing airplanes at airports. This study focused specifically on 6 large airports in the United States and the real ground radar data for all of the movements at those facilities. By tracking the real trajectories of every operation, the taxing behavior of each flight was analyzed. A standalone application was designed to summarize the flights information at each airport and represent the taxing behavior. The results show that using the ground radar data at airports can represent the taxing behavior in the highest fidelity. / Master of Science / The federal aviation administration predicts an ongoing growth in aviation industry over the following 20 years. The number of passengers using air transportation systems will increase annually in the next 20 years. Therefore, the airports will be more crowded and a higher number of operations will occur at those facilities. An accurate prediction of airports’ capacities can help the authorities to improve the airports appropriately. This will lead to an efficient aviation system which does not suffer severely from long delays. The contribution of the first study in this thesis was to help the process of predating airports’ capacities under various conditions by utilizing a computer model. As a result, a user interface was designed to help airport planners choosing their desired airports and estimating the maximum capacity under different operational conditions. An accurate prediction of airport capacity, can be useful for future designs and improvement plans. The second part of this thesis, represents a new methodology for analyzing the behavior of airplanes while moving at airports. Every flight operation starts its journey at the origin airport and finishes its journey at the destination airport. It is very important to analyze the behavior of each airplane while it is moving on the ground at the origin or destination airport. Therefore, parameters like taxing duration, waiting duration, average taxi speed can be used to evaluate the taxing performance of the airplanes. This study extracts the critical parameters of airplanes’ behavior at airports to help the planners evaluating the ground performance of each airport.

Effective and efficient air transportation systems are crucial to a nation's economy and connectedness. These systems involve capital-intensive facilities and equipment and move millions of people and tonnes of freight every day. As air traffic has continued to increase, the systems necessary to ensure safe and efficient operation will continue to grow more and more complex. Hence, it is imperative that air transport analysts are equipped with the best tools to properly predict and respond to expected air transportation operations. This dissertation aims to improve on those tools currently available to air transportation analysts, while offering new ones. Specifically, this thesis will offer the following: 1) A model for predicting arrival runway occupancy times (AROT); 2) a model for predicting departure runway occupancy times (DROT); and 3) a flight planning model. This thesis will also offer an exploration of the uses of unmanned aerial vehicles for providing wireless communications services. For the predictive models of AROT and DROT, we fit hierarchical Bayesian regression models to the data, grouped by aircraft type using airport physical and aircraft operational parameters as the regressors. Recognizing that many existing air transportation models require distributions of AROT and DROT, Bayesian methods are preferred since their output are distributions that can be directly inputted into air transportation modeling programs. Additionally, we exhibit how analysts will be able to decouple AROT and DROT predictions from the traditional 4 or 5 groupings of aircraft currently in use. Lastly, for the flight planning model, we present a 2-D model using presently available wind data that provides wind-optimal flight routings. We improve over current models by allowing free-flight unconnected to pre-existing airways and by offering finer resolutions over the current 2.5 degree norm. / Ph. D.

Increased efficiency at airports is necessary to reduce delays and fuel consumption. Many of the busiest airports in the nation have at least one pair of closely spaced parallel runways (CSPRs), defined by a separation of less than 2500 ft, with one runway dedicated to arrivals and the other to departures. CSPRs experience a large decrease in capacity under instrument conditions because they can no longer operate independently. In order to mitigate this decrease in capacity and to increase efficiency, proposed herein is a departure regulator for runways so configured, along with a plan of study to investigate the effects of this regulator. The proposed departure regulator makes use of data from precision tracking systems such as ADS-B to issue automated or semi-automated departure clearances. Assuming sequential departure separations are sufficient for clearance, the regulator will automatically issue, or advise the controller to issue, the departure clearance as soon as the arrival on the adjacent runway has descended below its decision height. By issuing the departure clearance earlier, the departure regulator reduces the gap between a pair of arrivals that is required to clear a departure. By decreasing the gap, the regulator increases the number of opportunities where a departure clearance can be issued, given a particular arrival stream. A simulation models the effects of the regulator and quantifies the resulting increases in capacity. The simulation results indicate that all forms of the regulator would provide significant gains of between 14% and 23% in capacity over the current operating paradigm. The results also indicate that the capacity gains are greatest at high arrival rates. Therefore, implementation of the departure regulator could significantly decrease the congestion at many major airports during inclement weather.

Runway detection in long wavelength infrared (LWIR) video could potentially increase the number of successful landings by increasing the situational awareness of pilots and verifying a correct approach. A method for detecting runways in LWIR video was therefore proposed and evaluated for robustness, speed and FPGA acceleration. The proposed algorithm improves the detection probability by making assumptions of the runway appearance during approach, as well as by using a modified Hough line transform and a symmetric search of peaks in the accumulator that is returned by the Hough line transform. A video chain was implemented on a Xilinx ZC702 Development card with input and output via HDMI through an expansion card. The video frames were buffered to RAM, and the detection algorithm ran on the CPU, which however did not meet the real-time requirement. Strategies were proposed that would improve the processing speed by either acceleration in hardware or algorithmic changes.

The principal aim of this thesis is to design two possible options for the steel structure of a new multibay industrial hall located in Slavkov u Brna. An overhead crane with load capacity of 12.5 metric tons will by situated in one of the bays. The hall has a rectangular shape with dimensions of 63x48 meters, each of the two bays has dimensions of 63x24 meters, a height of 11.5 meters and a saddle roof with an angle of slope 10°. Both of the options have the same layout design, the only difference is that option 1 has columns with truss girders while option 2 has a transversal frame with a haunch. The first option was selected because it is more economical due to material savings and is design developed in a greater detail. The permanent load on the building is considered and includes the weight of the steel structure, panels and the weight of crane runway. The variable load is also considered due to the live load, snow load, wind load, the crane, and their combination. Steel S235 is used as the construction material.

This thesis discusses the capacity of airport subsystems and describes various assessment methods of capacity including factors that affect it. The first part contains theoretical analysis of assessment methods for airport subsystems especially runway and terminal. The practical part deals with experimentation using the simulation software Visual Simmod. The objective of these experiments is to evaluate the effect of certain factors to runway operations and observe the change of aircraft delay over the capacity. In the end all simulation results are analyzed and shown in graphs.

The diploma thesis contains design of steel one-aisle industrial hall with span 24 m, length 63 m and height of the holder of a crane track girder 8,7 m. In hall are two overhead cranes, first with load capacity 50 tons and second with load capacity 32 tons. Main structural material is steel S 450. Is processed several versions and one is processed in detail. Drawings contain platform and section of hall and manufacturing drawings of crane runway.

<p> This study deals with applied research in the field of environmentai noise problems, specifically the measuring of noise patterns near Mount Hope Airport originating from subsonic jet aircraft using the present runway facilities. Based on actual measurements the results have been analyzed and reduced to simple contour lines. </p> <p> An attempt has been made in this study to relate the concept of community noise in the vicinity of the airport to specific runway configurations, traffic density and patterns, and to provide a comparison between the noise levels due to the existing operations and those which may result due to the proposed expansion. Versatile computer programs have been developed in this study to simulate an airport model, compute and construct the noise contours for any combination of design requirements such as runway orientation, flight procedure, type of aircraft, etc </p> / Thesis / Master of Engineering (MEngr)

This dissertation represents the methodologies used to develop an aircraft landing database and predictive models for estimating arrival flight runway occupancy times. In the second chapter, all the algorithms developed for analyzing the airport surface radar data are explained, and detailed statistical information about various airports in the United States in terms of landing behavior is studied. In the third chapter a novel data-driven approach for modeling aircraft landing behavior is represented. The outputs of the developed approach are runway occupancy time distributions and runway exit utilizations. The represented hybrid approach in the third chapter is a combination of machine learning and Monte Carlo simulation methods. This novel approach was calibrated based on two years of airport radar data. The study's output is a computer application, which is currently being used by the Federal Aviation Administration and various airport consulting firms for analyzing and designing optimum runway exits to optimize runway occupancy times at airports. In the fourth chapter, four real-world case scenarios were analyzed to show the power of the developed model in solving real-world challenges in airport capacity. In the fifth chapter, pilot motivational behaviors were introduced, and three methodologies were used to replicate motivated pilot behaviors on the runway. Finally, in the sixth chapter, a neural network approach was used as an alternative model for estimating runway occupancy time distributions. / Doctor of Philosophy / The federal aviation administration predicts ongoing growth in the aviation industry over the following 20 years. Therefore, the airports will be more crowded, and a higher number of operations will occur at those facilities. An accurate prediction of airports' capacities can help the authorities to improve the airports appropriately. Due to significant reductions in in-trail aircraft separations, runway occupancy times will become more significant in airport arrival procedures. In this study, a landing event database was developed to represent the accurate distributions of runway occupancy times. Also, it is essential to have computer applications capable of replicating runway occupancy time distributions. In this dissertation, a novel approach was developed to replicate aircraft runway occupancy times. A massive amount of airport surface radar data was utilized to create all the mentioned computer applications. The results of the final products were validated against real data. Real-world case scenarios were discussed as part of this study to showcase the strengths of the final developed product in solving challenging problems related to airport capacity. Finally, extreme cases of motivated landing behavior from airline pilots were studied, and multiple methodologies were introduced to replicate pilot motivational behavior while landing on runway.