No description available.

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1991. / Vita. Abstract. Includes bibliographical references (leaves 99-101). Also available via the Internet.

Thesis (M.S.)--Oregon Graduate Institute of Science and Technology, 1992.

Thesis (Ph. D.)--Aerospace Engineering, Georgia Institute of Technology, 2008. / Committee Chair: Pritchett, Amy; Committee Co-Chair: Feron, Eric; Committee Member: Clarke, John-Paul; Committee Member: Tsiotras, Panagiotis; Committee Member: Yang, Bong-Jun

Thesis (Ph. D.)--University of Wisconsin--Madison, 1958. / Typescript. Abstracted in Dissertation abstracts, v. 19 (1959) no. 8, p. 2188-2189. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves [144]-166).

The busiest regions of airspace in the U.S. are congested during much of the day from traffic volume, weather, and other airspace restrictions. The projected growth in demand for airspace is expected to worsen this congestion while reducing system efficiency and safety. This dissertation focuses on providing methods to analyze en route airspace congestion during severe convective weather (i.e. thunderstorms) in an effort to provide more efficient aircraft routes in terms of: en route travel time, air traffic controller workload, aircraft collision potential, and equity between airlines and other airspace users. The en route airspace is generally that airspace that aircraft use between the top of climb and top of descent. Existing en route airspace flight planning models have several important limitations. These models do not appropriately consider the uncertainty in airspace demand associated with departure time prediction and en route travel time. Also, airspace capacity is typically assumed to be a static value with no adjustments for weather or other dynamic conditions that impact the air traffic controller. To overcome these limitations a stochastic demand, stochastic capacity, and an incremental assignment method are developed. The stochastic demand model combines the flight departure uncertainty and the en route travel time uncertainty to achieve better estimates for sector demand. This model is shown to reduce the predictive error for en route sector demand by 20\% at a 30 minute look-ahead time period. The stochastic capacity model analyzes airspace congestion at a more macroscopic level than available in existing models. This higher level of analysis has the potential to reduce computational time and increase the number of alternative routing schemes considered. The capacity model uses stochastic geometry techniques to develop predictions of the distribution of flight separation and conflict potential. A prediction of dynamic airspace capacity is calculated based on separation and conflict potential. The stochastic demand and capacity models are integrated into a graph theoretic framework to generate alternative routing schemes. Validation of the overall integrated model is performed using the fast time airspace simulator RAMS. The original flight plans, the routing obtained from an integer programming method, and the routing obtained from the incremental method developed in this dissertation are compared. Results of this validation simulation indicate that integer programming and incremental routing methods are both able to reduce the average en route travel time per flight by 6 minutes. Other benefits include a reduction in the number of conflict resolutions and weather avoidance maneuvers issued by en route air traffic controllers. The simulation results do not indicate a significant difference in quality between the incremental and integer programming methods of routing flights around severe weather. / Ph. D.

One way to address the need for increased airspace system capacity is to reduce the separation requirements between aircraft in-flight. A key limiting factor to any reduction in separation is wake turbulence. The potential for aircraft to encounter wake turbulence poses a threat to both safety as well as increased efficiency. This research effort seeks to develop a model that can be used to evaluate the potential for wake encounters in today's flight operations, as well as serve as a tool for evaluating future reduced separation scenarios. The wake encounter model (WEM) achieves this goal by integrating results from NASA's TDAWP wake turbulence prediction model with a flight operations model based on radar flight track data. Unique in this model's design, is the ability to evaluate the potential for wake encounters throughout the terminal area versus previous research which has largely been restricted to areas near the runway. Expanding the model's reach provides not only for a more thorough analysis of potential wake encounters, but also creates an effective tool for evaluating future reduced separation scenarios. The WEM model was used to evaluate operations at three metropolitan airspaces in the United States: Atlanta, Los Angeles and New York. The results from these model runs indicated that potential wake encounters in today's operations were few. More importantly, the results from the WEM create a baseline for wake turbulence exposure in today's system, by which future scenarios can be compared against as part of any comprehensive reduced separation safety analysis. / Master of Science

No description available.

At the present time, millions of dollars are being lost by major airlines each year because of the inability of high density air terminals to efficiently service all of the demands placed upon them during peak periods of demand. Up to the present time, studies involving congestion have been aimed primarily at the implementation of computerized techniques to aid the air traffic controller during peak demand periods. By scheduling aircraft in a given system in a different manner, delay, caused by congestion, could possibly be reduced at high density terminals even more than it has been reduced by the results obtained from previous studies. The approach taken in this study involves testing different heuristic scheduling algorithms, based on what has been done previously, to determine what extent total system delay can be reduced. The method of approach which was followed was based on a simulator which models aircraft movement between N major terminals. For each scheduling algorithm developed, hourly statistics related to the number of aircraft demanding service, average departure delay, and average arrival delay were calculated along with total system delay times for arriving and departing aircraft. The results obtained from these algorithms were analyzed and compared with the scheduling algorithm which resulted in a reduction in delay being examined in greater detail to determine whether or not such a schedule would actually be feasible and worthwhile. / Master of Science

This thesis deals with innovative concept of air traffic operations such as Free Flight. First, a baseline is established to determine how controllers operate under the current operation guidelines. Then flight trajectories are developed for different alternatives to the Free Flight operational concept. Finally, a comparison of these Free Flight alternatives with current operational concept is conducted to investigate an impact of Free Flight on Air Traffic Control. With the powerful features of optimization, graphics, and hierarchical modeling, the MATLAB toolboxes proved to be effective in the modeling process involved in this research. / Master of Science