Master of Science in Mechanical Engineering, Cleveland State University, 2021, Washkewicz College of Engineering

Advancements in control systems and optimization can potentially be used to enhance the performance of exoskeletons and prostheses in various aspects, such as to improve balance control and gait adaptation. These are the two aims of this thesis. Aim 1 is to improve the balance of an underactuated exoskeleton with full-state feedback. The exoskeleton was modeled as a three-link inverted pendulum with passive stiffness at the ankle and controlled actuations at its other two joints. Though the system has no controlled actuation at its pivot, the system could be stabilized at its equilibrium point by a linear quadratic regulator (LQR) at the other two actuated joints to maintain the upright position against small perturbations. The feedback control parameters were then optimized to further improve the stability of the system. Aim 2 is to improve the gait adaptation in exoskeletal walking. A control strategy based on human-in-the-loop optimization is presented in this thesis. This controller allows the exoskeleton to adapt to the changes in gait pattern and walking speed by optimization of the cost function based on muscle activation and ground reaction force. Simulation and real-time test experimental results of this adaptive controller are shown in this thesis.

Committee: Antonie van den Bogert (Committee Chair); Eric Schearer (Committee Member); Ryan Farris (Committee Member) Subjects: Engineering; Mechanical Engineering; Robotics

Doctor of Philosophy (Ph.D.), University of Dayton, 2016, Engineering

Variable Air Volume (VAV) systems are the most popular HVAC systems in commercial buildings. VAV systems are designed to deliver airflows at design conditions which only occur for a few hours in a year. Minimizing energy use in VAV systems requires reducing the amount of airflow delivered through the system at part load conditions. Air Handling Unit (AHU) fans are the major drivers of airflow in VAV systems and installing a Variable Frequency Drive (VFD) is the most common method of regulating airflow in VAV systems. A VFD drive does not necessarily save energy without use of an appropriate control strategy. Static pressure reset (SPR) is considered to be the most energy efficient control strategy for AHU fans with VFDs installed. The implementation of SPR however has many challenges; for example, rogue zones—zones which have faulty sensors or failed controls and actuators, system dynamics like hunting and system diversity. By investigating the parameters associated with the implementation of SPR in VAV systems, a new, improved, more stable SPR algorithm was developed and validated. This approach was further improved using Fault Detection and Diagnostics (FDD) to eliminate rogue zones. Additionally, a CO2-Demand Control Ventilation (DCV) based minimum airflow control was used to further reduce ventilation airflow and save more energy from SPR. Energy savings ranging from 25% to 51% were recorded in actual buildings with the new SPR algorithm. Finally, a methodology that utilizes historical VAV data was developed to estimate the potential savings that could be realized using SPR. The approach employed first determines an effective system loss coefficient as a function of mean damper position using the historical duct static pressure, VAV damper positions and airflows. Additionally, the historical data is used to identify the maximum mean duct damper position realizable as a result of insuring a sufficient number of VAVs are fully open at any time. Savings ar (open full item for complete abstract)

Committee: Kevin Hallinan (Committee Chair); Kelly Kissock (Committee Co-Chair); Andrew Chiasson (Committee Member); Zhenhua Jiang (Committee Member) Subjects: Energy; Engineering; Mechanical Engineering

Master of Science, The Ohio State University, 1971, Graduate School

Committee: Not Provided (Other) Subjects:

MS, University of Cincinnati, 2024, Engineering and Applied Science: Civil Engineering

Buildings are the largest energy consumers, contributing to more than 40% of global carbon dioxide (CO2) emissions [1]. A significant portion of this energy consumption is attributed to building mechanical systems, particularly air handling units. Air handling units are a crucial component responsible for distributing conditioned air throughout the building. The supply and return fans within these units play a key role in air circulation and are responsible for substantial energy usage. This paper investigates strategies to decrease the energy burden on these fans. An evaluation of existing economizer damper control measures highlighted a dire need for a novel approach to modulate outdoor, exhaust, and return air dampers. The “split-signal damper control” suggested by Nassif and Moujaes [2] showed promising results, even though it required improvements for effective implementation in building mechanical systems. Further investigations introduced a method known as “duct static pressure set point reset”, which involves dynamically adjusting duct static pressure according to space airflow requirements rather than maintaining a constant pressure set point [3]. This research aims to improve the economizer damper control sequence for implementation in variable air volume (VAV) systems, develop a statistical model to simulate energy savings and refine the split-signal damper control sequence by integrating demand control ventilation (DCV). Additionally, cumulate energy savings and cost reductions due to duct static pressure set point adjustments, and improved economizer damper control sequence to attract building owners and operation managers. Experimental tests conducted on chilled water VAV system yielded an energy savings of 0.2% to 5% on improved split-signal damper control compared to the traditional three-coupled damper control method. Additionally, the control sequence could prevent reverse airflow through the exhaust damper. The statistic (open full item for complete abstract)

Committee: Nabil Nassif Ph.D. (Committee Chair); Tianren Wu Ph.D. (Committee Member); Arpan Guha Ph.D. (Committee Member) Subjects: Civil Engineering

Master of Science in Cyber Security (M.S.C.S.), Wright State University, 2023, Computer Science

Deploying Mandatory Access Controls (MAC) is a popular way to provide host protection against malware. Unfortunately, current implementations lack the flexibility to adapt to emergent malware threats and are known for being difficult to configure. A core tenet of MAC security systems is that the policies they are deployed with are immutable from the host while they are active. This work looks at deploying a MAC system that leverages using encrypted security tokens to allow for redeploying policy configurations in real-time without the need to stop a running process. This is instrumental in developing an adaptive framework for security systems with a Zero Trust based approach to process authentication. This work also develops Path-Safe, a MAC security system that focuses on protecting filesystem access from unauthorized processes and malware. We show that our security system can mitigate real-world malware threats with low overhead and high accuracy.

Committee: Junjie Zhang Ph.D. (Committee Chair); Lingwei Chen Ph.D. (Committee Member); Krishnaprasad Thirunarayan Ph.D. (Committee Member) Subjects: Computer Engineering; Computer Science; Information Systems; Information Technology

Doctor of Philosophy, The Ohio State University, 2023, Agricultural, Environmental and Developmental Economics

From a farmer to a policymaker, various stakeholders influence and are affected by the agricultural environment. This dissertation includes three essays that delve into the decision-making within the agricultural environment, exploring the incentives and outcomes for the stakeholders involved. With a focus on countries significant for global agriculture and food supply, these essays have important implications domestically and for the United States. My first essay evaluates herding as a potential source of bias in the USDA's international baseline projections. As USDA's annual Agricultural Baseline Projections contribute significantly to agricultural policy in the United States, their accuracy is vital. Although the bias in the baselines has been documented in the literature, its sources have not been evaluated yet. I propose herding, a behavioral phenomenon, as a potential bias-inducing choice in the preparation of the projections. My results provide strong evidence for the herding of projection trends toward the United States and suggest that herding is rational and error-reducing only for corn yield and wheat import projections but not for other crops and variables, thereby impacting not only the agricultural policy in the US but also global agricultural markets. The second essay evaluates the impact of an environmental policy that restricts land use for farmers in the context of the Brazilian Amazon, an area of crucial importance for global food supply. By analyzing the effects on both landowning farmers and landless peasants, this study examines the incentives generated and their subsequent influence on illegal occupations and land conflicts. The findings suggest that the policy leads to an increase in illegal occupations while decreasing land conflicts. Furthermore, by exploring heterogeneity in the impact relative to land values, I find that landowning farmers and squatters both make strategic choices about whether to engage in conflict depending on the (open full item for complete abstract)

Committee: Ani Katchova (Advisor); Brian Roe (Committee Member); Leah Bevis (Advisor) Subjects: Agriculture; Economics; Environmental Economics

Master of Science, The Ohio State University, 2023, Mechanical Engineering

Global vehicle emission regulations along with a growing consumer demand is a driving force in shifting the automotive industry towards a cleaner future. This shift requires significant automotive advancements in energy efficiency. Powertrain electrification and connected and autonomous vehicle (CAV) technology are key innovations that can reduce energy consumption and emissions. This thesis aims to improve the energy efficiency of a vehicle under varying conditions and determine the effect of charging on energy consumption. The vehicle model is established and utilized in the formulation of an optimal control problem in order to minimize energy consumption. The developed method to solve the optimization problem is applied in a large-scale study, culminating in an analysis of the effects of varying charging behavior on the energy consumption of the vehicle. The vehicle model is developed and validated over 25 real-world cycles resulting in an average fuel consumption, battery energy consumption, and total energy consumption errors of 2.2%, 2.9%, and 2.8%, respectively. The velocity dynamics and powertrain of the modeled vehicle are co-optimized to improve a weighted cost between energy consumption and travel time. The optimization results in an average decrease of 10% in fuel consumption, 8% in battery energy consumption, and 19% in total energy consumption. Lastly, the large-scale study reveals a correlation between charging behavior and both the effect of charging event placement and the presence of look-ahead information on energy efficiency. The resulting trends in charging behavior give context for energy efficient trip planning.

Committee: Stephanie Stockar (Advisor); Marcello Canova (Committee Chair) Subjects: Mechanical Engineering

BA, Oberlin College, 2022, Economics

The United States lags far behind other developed countries in terms of preschool provision and access. Because subsidized preschool effectively serves as childcare for enrolled students, preschool policies have ramifications in the labor market; namely, whether or not parents return to work after having children. This paper investigates the only two state-wide universal pre-k programs in the country, those of Florida and Vermont. I use a synthetic controls approach in order to address the impact these programs have had on maternal labor force participation rates in each state. I find that while Vermont's pre-k policy may have produced a significant increase in maternal labor force participation, the results from Florida's policy are insignificant. This outcome suggests that differences in how the policies have been implemented drive whether or not the policy has meaningful impacts on mothers' decisions to rejoin the labor force. Vermont offers more full-day options than Florida, although both programs are only free for half-day provision; additionally, Florida offers programming for children ages 4 and up, while Vermont offers programming for children 3 and up. Finally, I suggest other routes to explore which may aid pre-k policies in making it more accessible for mothers to return to work: these include more targeted programs, more full-day options, and subsidized (rather than free) provisions.

Committee: Christopher Andrew James Cotter (Committee Chair); Paul A. Brehm (Advisor) Subjects: Early Childhood Education; Economic Theory; Economics; Education; Preschool Education

Master of Science (M.S.), University of Dayton, 2021, Aerospace Engineering

A large body of work in the field of fluid dynamics has sought to understand the physics of wings moving in rapid motions (or high reduced frequencies) and at high angles of attack. These types of motions are prevalent in small air vehicles but also apply to larger fixed wing aircraft that are encountering gusts. Controlling vehicles through these large gusts is a major goal in the fluid dynamics community. Much work has been done to model these dynamics in a way that controllers can be implemented to mitigate unwanted force and transient effects from these movements and encounters. Currently, researchers develop closed loop controllers using simulation of the unsteady aerodynamics around a wing or an airfoil with computational fluid dynamics techniques. The angle of attack history of these simulations is then used to inform open loop experiments for validation. A large need in this work is the ability to implement these controllers in a laboratory environment where the feedback from the system can be implemented directly to the wing to validate the entire system experimentally. In addition, it is unclear if the models being used to simulate the unsteady aerodynamics for high amplitude lift encounters are accurate or even needed for controlling a wing through these encounters. Many of the unsteady aerodynamic models only work at low amplitudes and low reduced frequencies. An experimental controller that works for these high amplitude and high reduced frequency cases could be used to study the angle of attack history needed to achieve mitigation of the gust effects. This could help improve the existing unsteady models in a way that they could accurately represent the physics in these higher regimes. The current work focuses on a methodology for implementing closed loop feedback and control systems to achieve coefficient of lift control of a AR 4 flat plate undergoing pure pitch in the University of Dayton Water Tunnel (UD-WaT) using two different (open full item for complete abstract)

Committee: Sidaard Gunasekaran Ph.D. (Advisor); Alberto Medina Ph.D. (Committee Member); Raul Ordonez Ph.D. (Committee Member) Subjects: Aerospace Engineering; Electrical Engineering

Doctor of Philosophy, The Ohio State University, 2021, Mechanical Engineering

Global CO2 emissions regulations, in conjunction with increasing customer demands are requiring significant improvements in vehicle energy (or fuel) efficiency. In this drive to reduce fuel consumption, improvements in the powertrain (or propulsion system) continue to be a major area of focus, particularly shifting to higher levels of electrification. A next step in the evolution of improving fuel efficiency is to have the propulsion system controller make use of vehicle-level information. In this context, Connected and Automated Vehicle (CAV) technologies offer the potential for enhancing the vehicle fuel efficiency as well as improving vehicle safety and comfort by leveraging information from advanced mapping and location, and Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication. The focus of this thesis is to develop Dynamic Programming (DP) and Approximate Dynamic Programming (ADP) based approaches that combine the energy-saving potentials of powertrain electrification and CAV technologies, and further compound them. In this work, an ADP-based scheme is used to jointly optimize the vehicle velocity and energy management strategy of an electrified CAV over real-world driving routes. This predictive controls framework uses preview information from the route and environment to achieve significant fuel efficiency improvements even in the presence of variabilities (such as driver aggressiveness and varying traffic signal information). The controller was then implemented and tested in a demonstration vehicle at a proving ground facility over reconstructed route scenarios. Further, this thesis explores approaches to reducing the computational complexity of optimization methods based on Dynamic Programming, which can restrict its use in many real-time applications. To this end, two sub-optimal methodologies are proposed. One of them, the integrated DP-ECMS (Dynamic Programming-Equivalent Consumption Minimization Strategy) method embeds a heur (open full item for complete abstract)

Committee: Marcello Canova PhD (Advisor); Abhishek Gupta PhD (Committee Member); Chris Atkinson PhD (Committee Member); Giorgio Rizzoni PhD (Committee Member) Subjects: Automotive Engineering; Mechanical Engineering

Master of Science, The Ohio State University, 2020, Mechanical Engineering

The air we breathe is getting dangerously polluted with passenger vehicles and heavy-duty vehicles being one of the major sources of this pollution, producing significant amounts of nitrogen oxides, carbon monoxide, and other harmful gases. The U.S. Environmental Protection Agency (EPA) has laid stringent rules and aggressive policies to curb this pollution. Hybrid Electric Vehicles (HEV) and Electric Vehicles (EV) are a promising option considering their efficient operation and reduced emissions. These technologies are being developed at a rapid pace and can occupy a significant place in the automotive market. Companies are investing heavily to enhance the skills of future generation of engineers to develop these technologies through student competitions and workshops. EcoCAR Mobility Challenge (ECMC), a four-year Advanced Vehicle Technology Competition (AVTC) is one-way companies are pursuing this challenge. ECMC challenges teams to apply advanced propulsion systems, as well as connected and automated vehicle technology to improve the energy efficiency, safety, and consumer appeal of a 2019 Chevrolet Blazer – specifically for the carsharing market. The work described in this thesis focuses on the Model Based design approach adopted for the vehicle plant model and controls development during years one and two of the competition. The process includes the vehicle architecture selection process, component and soft ECU model development and finally describes the framework developed for testing of the control algorithm using an example of a fault scenario.

Committee: Shawn Midlam-Mohler Dr. (Advisor); Giorgio Rizzoni Dr. (Committee Member) Subjects: Mechanical Engineering

Master of Science in Engineering (MSEgr), Wright State University, 2019, Electrical Engineering

As control systems become more sophisticated, more accurate system models are needed for control law design and simulation. In this research, a nonlinear dynamic model of a quadcopter UAV is presented and model parameters are estimated off-line using in-flight experimental data. In addition, a model-based classical control law for the quadcopter UAV is designed, simulated, and then deployed in UAV flight tests. The intent of this research is to identify a model which may be simple enough to easily use for control law design, and accurate enough for simulation. In addition, a model-based classical control law is designed to for flight control. The parameters of the nonlinear dynamic model are estimated with the Linear Least Squares Error method. In-flight disturbances are introduced in flight tests to ensure frequency rich data. The performances of different models are compared using validation flight test data to select an accurate model. This model is used as the simulation model and the design model. Model-based control law design techniques are used to create a flight control law which provides good performance both in the simulator, as well as when deployed to the quadcopter. To perform these tests, the Real-Time - Marseille Grenoble Project software is used for the creation of ground station programs and flight control algorithms in Simulink. This test environment integrates a VICON camera systems, QuaRC Real Time system, a 3DR APM 2.6 micro-controller unit, and a Gumstix Overo AirSTORM micro-controller unit to create a low-cost quadcopter research platform.

Committee: Xiadong Zhang Ph.D. (Advisor); Jonathan Muse Ph.D. (Committee Member); Kuldip Rattan Ph.D. (Committee Member) Subjects: Electrical Engineering

Master of Science in Mechanical Engineering (MSME), Wright State University, 2019, Mechanical Engineering

Usually power take off (PTO) with a two-spool turbofan engine has been accomplished via the high pressure (HP) shaft and bleed air from the high-pressure compressor (HPC). The PTO is used to run various aircraft components such as generators and hydraulic pumps, which also produce waste heat. To better understand the coupled transient nature of balancing engine thrust, power take off and thermal management, a transient variable cycle three stream turbofan engine model has been developed to investigate the integrated behavior. The model incorporates many dynamic features including a third-stream heat exchanger as a heat sink for thermal management and HP/LP shaft PTO. This paper describes a method of controlling HPC surge margin and maintaining the desired thrust while extracting power using both the HP and LP spools. The transient interactions as both PTO and 3rd stream heat rejection are simultaneously applied to the transient variable cycle engine model utilizing different control effectors were investigated. The rate of transient heat rejection was found to impact surge margin. Rapidly applied heat loads caused larger surge margin transients than heat loads applied more gradually despite the same maximum heat rejection. Optimal PTO profiles between the LP and HP shaft to minimize the amount of fuel used for a given PTO amount and flight envelope were also investigated. Finally, a notional mission was simulated with varying flight parameters and dynamic PTO based on optimal PTO profiles along with heat generation and afterburner. The controls were found to be sufficient to successfully run the mission however such simplified controls could induce numerical instabilities in certain mission profiles. This shows that while these simple controls are sufficient for these notional test runs more sophisticated controls will be necessary for a proper generic engine model.

Committee: Rory Roberts Ph.D. (Committee Chair); George Huang Ph.D. (Committee Member); Mitch Wolff Ph.D. (Committee Member) Subjects: Aerospace Engineering; Engineering; Mechanical Engineering; Systems Design

MS, University of Cincinnati, 2018, Engineering and Applied Science: Aerospace Engineering

With aims of providing a service for people travelling by foot in crime-stricken neighborhoods, a UAV must be developed capable of following a person through said environments. In cities especially, GPS-denial and obstructions may cause GPS-based and vision-based navigation to fail while following a person, or walker, for the extended period of flight time required for this mission. In order to address this issue, a velocity controller interfaced with PX4 flight controller firmware was designed which uses the walker's measured velocity, likely obtained in a finalized design through a smartphone's accelerometer and gyroscope, to maintain the last recorded distance to the target. This is accomplished by taking in the walker's velocity and converting it into commands which mimic the motion of the walker. Additionally, a controller was designed which uses the angle between the unmanned aerial vehicle (UAV) and the walker, with respect to the east-axis, as well as UAV distance to walker to create velocity commands that reduce said distance to a desired value. Both controllers were tested in simulation and hardware experiments. The results of these tests indicate that a UAV would be able to maintain its distance to the target for short periods of time, and that the method described is an adequate replacement to hovering after loss of visual. Further, the UAV, using relative angle and distance, was able to successfully fly within the desired distance zone and maintain that approximate distance for the rest of the experiment.

Committee: Rajnikant Sharma Ph.D. (Committee Chair); Kelly Cohen Ph.D. (Committee Member); George T. Black M.S. (Committee Member) Subjects: Aerospace Materials

Master of Science, The Ohio State University, 2018, Mechanical Engineering

This thesis discusses the implementation of a Dynamic Programming algorithm that solves for the velocity and powertrain control optimization of a 48V mild-HEV over multiple custom driving scenarios. The results are compared to a baseline vehicle forward-looking model, by both observing the effects of both optimal velocity and optimal energy management. The biggest differences in the energy management occur during regeneration events, where the majority of energy regeneration happens at stopping events if the road ahead is known, whereas the more conservative online controller uses the engine to regenerate the battery throughout the route. The computation time resulting from the Dynamic Programming optimization is found to be tenfold that of the actual travel time, hence it could not be implemented as a real-time controller as is. A method to reduce the number of control inputs on the system to a single control input is implemented. It introduces the torque split inside of the Dynamic Programming by use of an Equivalent Consumption Minimization Strategy. The results are found to be slightly sub-optimal and some change in the velocity optimization is observed. With this new method, the computation time is halved.

Committee: Marcello Canova Dr. (Advisor); Giorgio Rizzoni Dr. (Committee Member); Levent Guvenc Dr. (Committee Member) Subjects: Mechanical Engineering

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

Dynamic eco-driving is an umbrella term describing speed control schemes that utilize connected and automated vehicle technology for the purpose of saving fuel. If dynamic eco-driving is to be widely prescribed as an integral part of widespread fuel-saving endeavors, its expected performance as part of the overall traffic system must be analyzed. Specifically, it must be determined to what extent this type of control remains effective in the presence of dense traffic. We present first a series of multi-vehicle traffic simulations which begin to answer important questions surrounding the effects of dynamic eco-driving on traffic and its potential for fuel savings in a mixed traffic environment. Three representative methods of dynamic eco-driving are tested in traffic scenarios and the estimated fuel economy, trip time, and average speed results are compared. Independent variables include technology penetration rate and amount of traffic, quantified by the delay level of service of the road network's traffic light facility. It is shown that, for the given test cases, average mpg increases linearly with technology penetration rate and dynamic eco-driving causes an increase in average mpg regardless of traffic amount. Overall, results are promising for the usefulness of this clever class of fuel-saving technologies, in high traffic as well as low. Naturally occurring flocks and swarms have long commanded human attention, with much engineering inspiration being drawn from their beauty, order, and cooperation. Recent simulation and modeling of swarms has given rise to interesting mathematical problems as well as useful control strategies for machine applications. To our knowledge, no microscopic, decentralized model of vehicle interactions based on swarming philosophy exists. Here we develop a new model of vehicle interactions on a two-lane highway, made up of ordinary differential equations and smooth functions. The new model's purpose is not primarily traffic simula (open full item for complete abstract)

Committee: Umit Ozguner PhD (Advisor); Keith Redmill PhD (Committee Member); Andrea Serrani PhD (Committee Member) Subjects: Electrical Engineering

Doctor of Philosophy, The Ohio State University, 1965, Graduate School

Committee: Not Provided (Other) Subjects: Engineering

Master of Science, The Ohio State University, 2016, Mechanical Engineering

Increasingly stringent regulations on emissions require automobile manufacturers to find new ways to reduce the emissions produced by their vehicles. If current trends provide an indication of where the automotive industry is headed, hybrid electric vehicles (HEVs) and electric vehicles (EVs) will become prevalent in the market in coming years. These technologies are all relatively new and still need much development before they can hold a significant place in the automotive market. It is for this reason that companies are investing heavily in training the next generation of engineers to work on this problem. EcoCAR 3, a four year long Advanced Vehicle Technology Competition (AVTC), is one way companies are pursuing the training of future engineers. EcoCAR 3 challenges the engineering students to modify a stock Chevrolet Camaro, donated by GM, to reduce the vehicle's energy consumption and tailpipe emissions, while maintaining standard vehicle performance. Currently, the competition just ended its second year and is beginning year 3. During year 1, the team focused on selecting the powertrain architecture for the Chevrolet Camaro and procuring components from different suppliers. The vehicle architecture that met the goals of both the competition and the team is a Post-transmission Plug-in Hybrid Electric Vehicle (PHEV) configuration. During Year 2, the team's major goals were to mechanically and electrically design the different subsystems, have the entire vehicle integrated and have the vehicle run on its electric propulsion system. Having the vehicle to run by the end of the year 2 required the team to develop controls in parallel to the mechanical and electrical integration of the vehicle. In order to successfully accomplish all the goals in a timely manner the team followed a Model-Based Design (MBD) approach. The work described in this project focuses on the development process that was followed during the development of a full-vehicle model: EcoSIM 3 in th (open full item for complete abstract)

Committee: Shawn Midlam-Mohler Dr. (Advisor); Giorgio Rizzoni Dr. (Committee Member) Subjects: Mechanical Engineering

Master of Science, The Ohio State University, 2016, Electrical and Computer Engineering

An open rapid-prototyping engine control system is developed based on a commercial platform and implemented on a 2L four-stroke diesel engine at the Ohio State University Center for Automotive Research. The procedure for setting up basic diesel engine controls on an unknown engine is summarized, and a generalized software architecture for portable controls modeling is outlined. An outline is provided of the documentation generated in the course of the project.

Committee: Giorgio Rizzoni Ph.D (Advisor); Marcello Canova Ph.D (Committee Member); Steven Bibyk Ph.D (Committee Member) Subjects: Engineering

PhD, University of Cincinnati, 2016, Engineering and Applied Science: Aerospace Engineering

The National Air Space (NAS) can be easily described as a complex aviation system-of-systems that seamlessly works in harmony to provide safe transit for all aircraft within its domain. The number of aircraft within the NAS is growing and according the FAA, ``[o]n any given day, more than 85,000 flights are in the skies in the United States...This translates into roughly 5,000 planes in the skies above the United States at any given moment. More than 15,000 federal air traffic controllers in airport traffic control towers, terminal radar approach control facilities and air route traffic control centers guide pilots through the system''. The FAA is currently rolling out the Next Generation Air Transportation System (NextGen) to handle projected growth while leveraging satellite-based navigation for improved tracking. A key component to instantiating NextGen lies in the equipage of Automatic Dependent Surveillance-Broadcast (ADS-B), a performance based surveillance technology that uses GPS navigation for more precise positioning than radars providing increased situational awareness to air traffic controllers. Furthermore, the FAA is integrating UAS into the NAS, further congesting the airways and information load on air traffic controllers. The expected increase in aircraft density due to NextGen implementation and UAS integration will require innovative algorithms to cope with the increase data flow and to support air traffic controllers in their decision-making. This research presents a few innovative algorithms to support increased aircraft density and UAS integration into the NAS. First, it is imperative that individual tracks are correlated prior to fusing to ensure a proper picture of the environment is correct. However, current approaches do not scale well as the number of targets and sensors are increased. This work presents a fuzzy clustering design to hierarchically break the problem down into smaller subspaces prior to correlation. This approach provide (open full item for complete abstract)

Committee: Kelly Cohen Ph.D. (Committee Chair); Sundararaman Anand Ph.D. (Committee Member); Manish Kumar Ph.D. (Committee Member); Bruce Walker Sc.D. (Committee Member) Subjects: Aerospace Materials