PhD, University of Cincinnati, 2007, Engineering : Aerospace Engineering

The research presented in this dissertation is motivated by the need for new, efficient algorithms for the solution of two important problems currently faced by the air-traffic control community: (i) optimal scheduling of aircraft arrivals at congested airports, and (ii) optimal National Airspace System (NAS) wide traffic flow management. In the first part of this dissertation, we present an optimal airport arrival scheduling algorithm, which works within a hierarchical scheduling structure. This structure consists of schedulers at multiple points along the arrival-route. Schedulers are linked through acceptance-rate constraints, which are passed up from downstream metering-points. The innovation in this scheduling algorithm is that these constraints are computed by using an Eulerian model-based optimization scheme. This rate computation removes inefficiencies introduced in the schedule through ad hoc acceptance-rate computations. The scheduling process at every metering-point uses its optimal acceptance-rate as a constraint and computes optimal arrival sequences by using a combinatorial search-algorithm. We test this algorithm in a dynamic air-traffic environment, which can be customized to emulate different arrival scenarios. In the second part of this dissertation, we introduce a novel two-level control system for optimal traffic-flow management. The outer-level control module of this two-level control system generates an Eulerian-model of the NAS by aggregating aircraft into interconnected controlvolumes. Using this Eulerian model of the airspace, control strategies like Model Predictive Control are applied to find the optimal inflow and outflow commands for each control-volume so that efficient flows are achieved in the NAS. Each control-volume has its separate innerlevel control-module. The inner-level control-module takes in the optimal inflow and outflow commands generated by the outer control-module as reference inputs and uses hybrid aircraft models to sea (open full item for complete abstract)

Committee: Dr. Gary Slater (Advisor) Subjects: Engineering, Aerospace

Doctor of Philosophy, The Ohio State University, 2024, Industrial and Systems Engineering

Sociotechnical systems in safety-critical domains are distributed and contain interdependencies between the different elements, including human and automated roles that need to coordinate and synchronize their activities with dynamic events in the environment. The advancement of technology and the introduction of machines capable of acting at a higher level of autonomy has increased the complexity of such Distributed Work Systems (DWSs). An envisioned DWS is described by a set of static paper-based documents and will be deployed in the next few years. The short-range low-altitude air mobility system is one very good example of an envisioned DWS. Interactions between human and automated roles and their environment are dynamic, evolve, and change over time, causing emergent effects like taskload peaks and coordination breakdowns. A well-designed DWS will be able to keep pace with the work environment dynamics (like the dynamics of aircraft governed by laws of flight in a short-range low-altitude air mobility system) and succeed in responding to the disturbance. This creates the need to understand the dynamics of envisioned DWS, such as how a DWS performs in high-paced situations like anomaly response. Assessing the feasibility and robustness of an envisioned DWS comes with challenges: the physical system does not yet exist, its design and operations are often underspecified, and multiple versions may exist within a designer community about what future operations will look like. Therefore, as a part of this dissertation, an exploratory early-stage computational modeling and simulation technique is described and demonstrated to evaluate an envisioned DWS. Using functional modeling and computational simulation capabilities, the dissertation shows a technique that can help evaluate envisioned DWS by discovering things that are not uncovered by traditional normative simulations. The primary advantage of the technique is the ability to evaluate the dynamics of work in (open full item for complete abstract)

Committee: Martijn Ijtsma (Advisor); Michael Rayo (Committee Member); David Woods (Committee Member) Subjects: Industrial Engineering; Systems Design

Master of Science in Engineering, University of Akron, 2019, Mechanical Engineering

Essential components of a new scenario-based air traffic control (ATC) training platform whose effectiveness was analyzed are outlined with respect to its use in the decision making skills of trainees when confronted with emergency situations. Actual previous extreme weather incidences were used in the creation of the weather display. Further, two separate weather displays were designed for the training platform. The traditional weather display depicted the precipitation levels present during the scenario. A new, exploratory weather display was also created using the concept of probabilistic hazard information (PHI). The PHI tool indicated the one-hour movement of areas of severe precipitation present during the scenario. Testing of the platform was completed with ATC students from Kent State University. Data from subjective pre- and post-questionnaires as well as objective decision parameters were collected. Preliminarily, it was shown that probabilistic forecasts present on the weather display may have corresponded with faster aircraft deviation from the participants. However, with this added information in the form of PHI, participants subjectively rated their task workload as higher.

Committee: Chen Ling (Advisor); Shengyong Wang (Committee Member); Robert Priestley (Committee Member) Subjects: Engineering

Master of Science (MS), Ohio University, 2019, Electrical Engineering & Computer Science (Engineering and Technology)

Bird strikes represent a serious economic and safety risk to aircraft operations, especially near airports where aircraft are in critical stages of flight with little room for error. The United States Federal Aviation Administration (FAA) continues to research ways of mitigating the risk to aircraft posed by bird targets which include surveillance of birds with specialized radar systems. This thesis presents an algorithm that can utilize data from an avian radar, Automatic Dependent Surveillance – Broadcast (ADS-B) aircraft positioning data, and other sources to determine which birds constitute a significant risk to aircraft. It is envisioned that this algorithm could be added into a system which then alerts air traffic control (ATC) and/or pilots through communication protocols such as ADS-B and the ATC ground network. For this thesis, avian radar and ADS-B data was analyzed and tested through the prototype algorithm with a simulated aircraft track to illustrate example scenarios of this algorithm working. Additionally, multiple scenarios with a single simulated bird and simulated aircraft track were tested to verify operation of the algorithm when a known collision occurs.

Committee: Chris Bartone Ph.D. (Advisor); Michael Braasch Ph.D. (Committee Member); Frank van Graas Ph.D. (Committee Member); Donald Miles Ph.D. (Committee Member) Subjects: Aerospace Engineering; Electrical Engineering; Engineering; Systems Design

MS, Kent State University, 0, College of Arts and Sciences / Department of Computer Science

Basic tasks for Air Traffic Control will be implemented using NVIDIA's CUDA language on a NVIDIA device and compared to the performance of an Associative SIMD processor doing the same tasks. To do this, we create a simulation of an airfield with constantly moving aircrafts. The tasks that will be used in the evaluation are: tracking and correlation, collision detection, and collision resolution. These are the most compute intensive of the Air Traffic Control tasks, so they will give us a good measure of the capabilities of the NVIDIA device. The first task is tracking and correlation of the aircrafts in a 256 nautical mile by 256 nautical mile bounding area on a 2D plane with varying altitudes. This task is executed once each half second during each 8 second major cycle period and uses radar to correlate the exact location of the aircraft and its flight records. During every 8 second cycle, Batcher's algorithm is used to check if any aircraft's projected path has a possibility for collision. If a potential collision is possible within the next 20 minutes, we first locate a collision free path for one of them and then have it switch to this path. In previous research, the ability of a multicore system to perform basic ATC tasks was investigated. The graph showing its performance increased rapidly as the number of aircraft increased, which is consistent with the general belief that all large real-time systems require exponential time. In contrast, in our earlier research, an associative SIMD system was shown to be able to execute these basic tasks in linear time with a graph that had a very small slope. Additionally, the multicore regularly missed a large number of deadlines while the SIMD system did not miss a single deadline. Our goal here was to determine whether we could get SIMD-like results using a CUDA implementation of the same real-time system involving basic ATC tasks on a NVIDIA accelerator. Our research shows that our NVIDIA accelerators can provide a SIM (open full item for complete abstract)

Committee: Johnnie Baker Dr. (Advisor); Gokarna Sharma Dr. (Committee Member); Ye Zhao Dr. (Committee Member) Subjects: Computer Science

Doctor of Philosophy, The Ohio State University, 1975, Graduate School

Committee: Not Provided (Other) Subjects: Operations Research

Doctor of Philosophy, The Ohio State University, 1971, Graduate School

Committee: Not Provided (Other) Subjects: Engineering

Doctor of Philosophy, The Ohio State University, 1958, Graduate School

Committee: Not Provided (Other) Subjects: Psychology

Doctor of Philosophy, The Ohio State University, 1955, Graduate School

Committee: Not Provided (Other) Subjects: Psychology

Doctor of Philosophy, The Ohio State University, 2017, Electrical and Computer Engineering

Increasing demand for supporting more wireless services with higher performance and reliability within the frequency bands that are most conducive to operating cost-effective cellular and mobile broadband is aggravating current electromagnetic spectrum congestion. This situation motivates technology and management innovation to increase the efficiency of spectral use. If primary-secondary spectrum sharing can be shown possible without compromising (or while even improving) performance in an existing application, opportunities for efficiency may be realizable by making the freed spectrum available for commercial use. While both active and passive sensing systems are vitally important for many public good applications, opportunities for increasing the efficiency of spectrum use can be shown to exist for both systems. This dissertation explores methods and technologies for remote sensing systems that enhance spectral efficiency and enable dynamic spectrum access both within and outside traditionally allocated bands.

Committee: Joel Johnson (Advisor); Emre Ertin (Committee Member); Graeme Smith (Committee Member) Subjects: Electrical Engineering; Electromagnetics

MS, Kent State University, 2015, College of Arts and Sciences / Department of Computer Science

Air transportation is an important part of the modern world. The demand for air travel is increasing every day. Despite the rapid growth of technology, air travel systems failed to grow at the same rate. The current system for air traffic control (ATC) is similar to the system used decades ago. With the current growth in demand for air traveling, ATC will not be able to handle this increase. Therefore, a better system needs to be implemented for ATC. One of the possible approaches is an automated ATC using associative processing. In this thesis we gathered information about how the current ATC system works, following the Federal Aviation Administration (FAA) rules. We also provide multiple resources (e.g., FAA documents) that provide a deeper understanding of ATC that will be useful in further studies of this topic. Also addressed are some issues of the current system such as cost, delays, and errors that may result due to an air traffic controller's actions and the limited capacity of air traffic controllers. We implemented a model to represent some of the aspects of the current ATC using associative processing instead of air traffic controllers. Automation of the handoff operation, collision detection, collision avoidance, and course correction are implemented. Our results indicate that the current bottlenecks involving air traffic control can be avoided by implementing this type of system in the future. The same system can be used for other applications such as controlling the flight of unmanned aerial vehicles for an automated package delivery system.

Committee: Johnnie Baker (Advisor); Paul Farrell (Committee Member); Arden Ruttan (Committee Member) Subjects: Aerospace Engineering; Aerospace Materials; Computer Science

PhD, University of Cincinnati, 2000, Engineering : Aerospace Engineering

Two problems relating to the departure problem in air traffic control automation are examined. The first problem that is addressed is the scheduling of aircraft for departure. The departure operations at a major US hub airport are analyzed, and a discrete event simulation of the departure operations is constructed. Specifically, the case where there is a single departure runway is considered. The runway is fed by two queues of aircraft. Each queue, in turn, is fed by a single taxiway. Two salient areas regarding scheduling are addressed. The first is the construction of optimal departure sequences for the aircraft that are queued. Several greedy search algorithms are designed to minimize the total time to depart a set of queued aircraft. Each algorithm has a different set of heuristic rules to resolve situations within the search space whenever two branches of the search tree with equal edge costs are encountered. These algorithms are then compared and contrasted with a genetic search algorithm in order to assess the performance of the heuristics. This is done in the context of a static departure problem where the length of the departure queue is fixed. A greedy algorithm which deepens the search whenever two branches of the search tree with non-unique costs are encountered is shown to outperform the other heuristic algorithms. This search strategy is then implemented in the discrete event simulation. A baseline performance level is established, and a sensitivity analysis is performed by implementing changes in traffic mix, routing, and miles-in-trail restrictions for comparison. It is concluded that to minimize the average time spent in the queue for different traffic conditions, a queue assignment algorithm is needed to maintain an even balance of aircraft in the queues. A necessary consideration is to base queue assignment upon traffic management restrictions such as miles-in-trail constraints. The second problem addresses the technical challenges associated with (open full item for complete abstract)

Committee: Gary Slater (Advisor) Subjects: Engineering, Aerospace

MS, University of Cincinnati, 2005, Engineering : Aerospace Engineering

Due to the runway threshold and airport capacity constraints, aircraft are often required to delay their arrival time when they are approaching the TRACON (Terminal Radar Approach Control) area to meet separation requirements and to ensure safety. This is particularly true in the US in the northeast corridor, where sectors are small, with shorter controllable time, and involving very complex and heavy traffic flows. In this situation, downstream schedule constraints may be passed upstream, most likely across multiple ARTCCs (Air Route Traffic Control Centers) and multiple sectors. More sectors may be needed to absorb the required delay. The technical issue for delaying aircraft over extended region is that uncertainties in flight time, and the rather close tolerance on final spacing, make delay predictions far into the future rather suspect. This paper provides a delay strategy that the problem of distributing delay across multiple sectors is addressed as a discrete optimal control problem. Game theory, coupled with dynamic programming (DP) is used in this research to give an optimal solution for the delay controls in each sector. In this application the sector delay is chosen to minimize a performance index and the uncertainty is viewed as an adversary trying to maximize the performance index. This DP approach is capable of creating a favorable delay distribution solution and the solution is fuel efficient. It is easy for controller to implement because the algorithm is computationally efficient, the method can quickly reallocate the delay by adjusting the model parameters to provide a robust solution. As currently formulated the DP algorithm ensures only separation at the terminal fix. However, at several intermediate points, the traffic may merge into a single stream from several directions. An algorithm is developed to integrate the DP algorithm so as to solve the intermediate merging conflict as well as ensuring terminal separation. The validity of this mechani (open full item for complete abstract)

Committee: Dr. Gary Slater (Advisor) Subjects:

MS, University of Cincinnati, 2003, Engineering : Aerospace Engineering

One key element in improving air traffic capacity and efficiency is the ability of the air traffic management system to predict accurately the future position of a vehicle along a standard route. Perhaps the most challenging problem in the current practice is to predict accurately the altitude profile of an aircraft during the ascent phase of flight. During the ascent, the vehicle performance is extremely sensitive to uncertainties in the vehicle weight, thrust and piloting procedures, none of which are currently known to air traffic controller whose job is to merge this departure aircraft into an en route stream of traffic. This thesis work investigates the use of adaptive control techniques to improve climb performance prediction. The aim is to accurately predict time to ‘top of climb' in the ascending phase of aircraft trajectory. The study is conducted in support of the CTAS air traffic control software, which is in development at NASA Ames Research Center in California. This investigation consists of a comparison between actual departure trajectories for MD80 type of aircraft and the results of MATLAB-based numerical simulation attempting to duplicate the measured energy rate and hence the trajectory during the climb phase. The technical approach taken in this thesis is to start with initial a priori models of aerodynamics and engine thrust. The thrust dependency is adapted based on the observed and calculated energy rates of the vehicle. The results indicate that this adaptive model can greatly improve climb performance prediction.

Committee: Dr. Gary Slater (Advisor) Subjects: Engineering, Aerospace

PHD, Kent State University, 2012, College of Arts and Sciences / Department of Computer Science

This dissertation has two complementary focuses. First, it provides a solution to large scale real-time system air traffic Control (ATC) using an enhanced SIMD machine model called an associative processor (AP). The second is the comparison of this implementation with a multiprocessor implementation and the implications of these comparisons. This paper demonstrates how one application, ATC, can more easily, more simply, and more efficiently be implemented on an AP than is generally possible on other types of traditional hardware. The AP implementation of ATC will take advantage of its deterministic hardware to use static scheduling. Our solution differs from previous ATC systems that are designed for MIMD computers and have a great deal of difficulty meeting the predictability requirements for ATC, which are critical for meeting the strict certification standards required for safety critical software components. The proposed AP solution supports accurate predictions of worst case execution times and guarantees all deadlines are met. Furthermore, the software developed based on the AP model is much simpler and smaller in size than the current corresponding ATC software. As the associative processor is built from SIMD hardware, it is considerably cheaper and simpler than the MIMD hardware currently used to support ATC. While APs were used for ATC-type applications earlier, these are no longer available. We use a ClearSpeed CSX600 accelerator to emulate the AP solutions of ATC on an ATC prototype consisting of eight data-intensive ATC real-time tasks. Its performance is evaluated in terms of execution time and predictability and is compared with an 8-core multiprocessor (MP) using OpenMP. Our extensive experiments show that the AP implementation meets all deadlines while the MP will regularly miss a large number of deadlines. It is shown that the proposed AP solution will support accurate predictions of worst case execution times and will guarantee that all deadlines a (open full item for complete abstract)

Committee: Johnnie Baker (Advisor) Subjects: Computer Science