Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item Assessing the Thermal Safety and Thermochemistry of Lithium Metal All-Solid-State Batteries Through Differential Scanning Calorimetry and Modeling(2023) Johnson, Nathan Brenner; Albertus, Paul; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Solid-state batteries are often considered to have superior safety compared to their liquid electrolyte counterparts, but further analysis is needed, especially because the desired higher specific energy of a solid-state lithium metal battery results in a higher potential temperature rise from the electrical energy in the cell. Safety is a multi-faceted issue that should be carefully assessed. We build "all-inclusive microcell" Differential Scanning Calorimetry samples that include all cell stack layers for a Li0.43CoO2 | Li7La3Zr2O12 | Li cell in commercially relevant material ratios (e.g. capacity matched electrodes) and gather heat flow data. From this data, we use thermodynamically calculated enthalpies of reactions for this cell chemistry to predict key points in cell thermal runaway (e.g., onset temperature, maximum temperature) and assess battery safety at the materials stage of cell development. We construct a model of the temperature rise during a thermal ramp test and short circuit in a large-format solid-state Li0.43CoO2 | Li7La3Zr2O12 | Li battery based on microcell heat flow measurements. Our model shows self-heating onset temperatures at ∼200-250°C, due to O2 released from the metal oxide cathode. Cascading exothermic reactions may drive the cell temperature during thermal runaway to ∼1000 °C in our model, comparable to temperature rise from high-energy Li-ion cells, but subject to key assumptions such as O2 reacting with Li. Higher energy density cathode materials such as LiNi0.8Co0.15Al0.05O2 in our model show peak temperatures >1300°C. Transport of O2 or Li through the solid-state separator (e.g., through cracks), and the passivation of Li metal by solid products such as Li2O, are key determinants of the peak temperature. Our work demonstrates the critical importance of the management of molten Li and O2 gas within the cell, and the importance of future modeling and experimental work to quantify the rate of the 2Li+1/2O2→Li2O reaction, and others, within a large format Li metal solid-state battery.Item Assured Autonomy in Multiagent Systems with Safe Learning(2022) Fiaz, Usman Amin; Baras, John S; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Autonomous multiagent systems is an area that is currently receiving increasing attention in the communities of robotics, control systems, and machine learning (ML) and artificial intelligence (AI). It is evident today, how autonomous robots and vehicles can help us shape our future. Teams of robots are being used to help identify and rescue survivors in case of a natural disaster for instance. There we understand that we are talking minutes and seconds that can decide whether you can save a person's life or not. This example portrays not only the value of safety but also the significance of time, in planning complex missions with autonomous agents. This thesis aims to develop a generic, composable framework for a multiagent system (of robots or vehicles), which can safely carry out time-critical missions in a distributed and autonomous fashion. The goal is to provide formal guarantees on both safety and finite-time mission completion in real time, thus, to answer the question: “how trustworthy is the autonomy of a multi-robot system in a complex mission?” We refer to this notion of autonomy in multiagent systems as assured or trusted autonomy, which is currently a very sought-after area of research, thanks to its enormous applications in autonomous driving for instance. There are two interconnected components of this thesis. In the first part, using tools from control theory (optimal control), formal methods (temporal logic and hybrid automata), and optimization (mixed-integer programming), we propose multiple variants of (almost) realtime planning algorithms, which provide formal guarantees on safety and finite-time mission completion for a multiagent system in a complex mission. Our proposed framework is hybrid, distributed, and inherently composable, as it uses a divide-and-conquer approach for planning a complex mission, by breaking it down into several sub-tasks. This approach enables us to implement the resulting algorithms on robots with limited computational power, while still achieving close to realtime performance. We validate the efficacy of our methods on multiple use cases such as autonomous search and rescue with a team of unmanned aerial vehicles (UAVs) and ground robots, autonomous aerial grasping and navigation, UAV-based surveillance, and UAV-based inspection tasks in industrial environments. In the second part, our goal is to translate and adapt these developed algorithms to safely learn actions and policies for robots in dynamic environments, so that they can accomplish their mission even in the presence of uncertainty. To accomplish this goal, we introduce the ideas of self-monitoring and self-correction for agents using hybrid automata theory and model predictive control (MPC). Self-monitoring and self-correction refer to the problems in autonomy where the autonomous agents monitor their performance, detect deviations from normal or expected behavior, and learn to adjust both the description of their mission/task and their performance online, to maintain the expected behavior and performance. In this setting, we propose a formal and composable notion of safety and adaptation for autonomous multiagent systems, which we refer to as safe learning. We revisit one of the earlier use cases to demonstrate the capabilities of our approach for a team of autonomous UAVs in a surveillance and search and rescue mission scenario. Despite portraying results mainly for UAVs in this thesis, we argue that the proposed planning framework is transferable to any team of autonomous agents, under some realistic assumptions. We hope that this research will serve several modern applications of public interest, such as autopilots and flight controllers, autonomous driving systems (ADS), autonomous UAV missions such as aerial grasping and package delivery with drones etc., by improving upon the existing safety of their autonomous operation.Item TARGETING MAGNETIC NANOCARRIERS IN THE HEAD FOR DRUG DELIVERY AND BIOSENSING APPLICATIONS(2016) Ramaswamy, Bharath; Shapiro, Benjamin; Bioengineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Magnetic nanocarriers have proven to be effective vehicles for transporting therapeutic and diagnostic agents in the body. Their main advantage is their ability to be manipulated by external magnets to direct them to specific targets in the body. In this dissertation, I study the transport, safety and efficacy of moving drug coated magnetic nanocarriers in different types of tissue. Movement of magnetic nanocarriers of sizes ranging from 100 nm to 1µm with different biocompatible coatings (Starch, PEG, Lipid and Chitosan) was quantified in different tissue types using an automated cryostat system. The safety of moving magnetic nanocarriers in live rodent brain tissue was assessed using electrophysiology, calcium imaging and immunohistochemistry. Moving magnetic nanocarriers in brain tissue did not significantly affect the firing ability of single neurons, synaptic connectivity and the overall functioning of the neuron network. As part of efficacy studies, steroid-eluting magnetic nanoparticles were targeted using external magnets to the inner ear of mice to counter hearing loss caused by cisplatin chemotherapeutics. This targeted steroid delivery to the cochlea significantly reduced the change in hearing threshold at 32 KHz caused by cisplatin injections and protected the hair cells from significant damage. Finally, I explore the potential of spin-transfer torque nano-oscillators, which are multi-layered ferromagnetic nanocarriers, as high-resolution in vivo wireless biosensors. These nanocarriers have been shown to detect action potentials from crayfish lateral giant neurons and that the microwave magnetic signals from these devices can be detected wirelessly by near field induction.Item Development of Planning And Evaluation Models For Superstreets(2016) Xu, Liu; Chang, Gang-Len; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Despite the extensive implementation of Superstreets on congested arterials, reliable methodologies for such designs remain unavailable. The purpose of this research is to fill the information gap by offering reliable tools to assist traffic professionals in the design of Superstreets with and without signal control. The entire tool developed in this thesis consists of three models. The first model is used to determine the minimum U-turn offset length for an Un-signalized Superstreet, given the arterial headway distribution of the traffic flows and the distribution of critical gaps among drivers. The second model is designed to estimate the queue size and its variation on each critical link in a signalized Superstreet, based on the given signal plan and the range of observed volumes. Recognizing that the operational performance of a Superstreet cannot be achieved without an effective signal plan, the third model is developed to produce a signal optimization method that can generate progression offsets for heavy arterial flows moving into and out of such an intersection design.Item Computational Foundations for Safe and Efficient Human-Robot Collaboration in Assembly Cells(2016) Morato, Carlos W; Gupta, Satyandra K; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Human and robots have complementary strengths in performing assembly operations. Humans are very good at perception tasks in unstructured environments. They are able to recognize and locate a part from a box of miscellaneous parts. They are also very good at complex manipulation in tight spaces. The sensory characteristics of the humans, motor abilities, knowledge and skills give the humans the ability to react to unexpected situations and resolve problems quickly. In contrast, robots are very good at pick and place operations and highly repeatable in placement tasks. Robots can perform tasks at high speeds and still maintain precision in their operations. Robots can also operate for long periods of times. Robots are also very good at applying high forces and torques. Typically, robots are used in mass production. Small batch and custom production operations predominantly use manual labor. The high labor cost is making it difficult for small and medium manufacturers to remain cost competitive in high wage markets. These manufactures are mainly involved in small batch and custom production. They need to find a way to reduce the labor cost in assembly operations. Purely robotic cells will not be able to provide them the necessary flexibility. Creating hybrid cells where humans and robots can collaborate in close physical proximities is a potential solution. The underlying idea behind such cells is to decompose assembly operations into tasks such that humans and robots can collaborate by performing sub-tasks that are suitable for them. Realizing hybrid cells that enable effective human and robot collaboration is challenging. This dissertation addresses the following three computational issues involved in developing and utilizing hybrid assembly cells: - We should be able to automatically generate plans to operate hybrid assembly cells to ensure efficient cell operation. This requires generating feasible assembly sequences and instructions for robots and human operators, respectively. Automated planning poses the following two challenges. First, generating operation plans for complex assemblies is challenging. The complexity can come due to the combinatorial explosion caused by the size of the assembly or the complex paths needed to perform the assembly. Second, generating feasible plans requires accounting for robot and human motion constraints. The first objective of the dissertation is to develop the underlying computational foundations for automatically generating plans for the operation of hybrid cells. It addresses both assembly complexity and motion constraints issues. - The collaboration between humans and robots in the assembly cell will only be practical if human safety can be ensured during the assembly tasks that require collaboration between humans and robots. The second objective of the dissertation is to evaluate different options for real-time monitoring of the state of human operator with respect to the robot and develop strategies for taking appropriate measures to ensure human safety when the planned move by the robot may compromise the safety of the human operator. In order to be competitive in the market, the developed solution will have to include considerations about cost without significantly compromising quality. - In the envisioned hybrid cell, we will be relying on human operators to bring the part into the cell. If the human operator makes an error in selecting the part or fails to place it correctly, the robot will be unable to correctly perform the task assigned to it. If the error goes undetected, it can lead to a defective product and inefficiencies in the cell operation. The reason for human error can be either confusion due to poor quality instructions or human operator not paying adequate attention to the instructions. In order to ensure smooth and error-free operation of the cell, we will need to monitor the state of the assembly operations in the cell. The third objective of the dissertation is to identify and track parts in the cell and automatically generate instructions for taking corrective actions if a human operator deviates from the selected plan. Potential corrective actions may involve re-planning if it is possible to continue assembly from the current state. Corrective actions may also involve issuing warning and generating instructions to undo the current task.Item The Effect of a Safety Controller on User Performance Through a Prosthetic Interface(2014) Shuggi, Isabelle Marie; Herrmann, Jeffrey W.; Gentili, Rodolphe J.; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The objective of this thesis was to examine the interaction between user safety and cognitive-motor performance during reaching movements executed with a robotic arm through a human body machine interface (HBMI). Specifically, the effects of a safety controller on user cognitive workload and kinematics were assessed during learning the control of a simulated prosthetic arm through limited head movements. The results revealed that, compared to the group performing without the safety controller, the users assisted with the safety controller exhibited: i) a lower rate of information transfer, ii) a higher cognitive workload and iii) a reduced number of times the user brought the robotic arm close to the workspace boundaries when performing the adaptive reaching task. These results suggest that the autonomous safety controller increased user cognitive workload and reduced information transfer but provided a safer environment. This work contributes to the development of assistive technology such as HBMI and neuroprosthetics.Item VIOLENCE AND DISORDER, SCHOOL CLIMATE, AND PBIS: THE RELATIONSHIP AMONG SCHOOL CLIMATE, STUDENT OUTCOMES, AND THE USE OF POSITIVE BEHAVIORAL INTERVENTIONS AND SUPPORTS.(2013) Eacho, Thomas Christopher; Leone, Peter E; Special Education; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The primary purpose of this study was to examine the relationship between school climate and student outcome variables. The secondary purpose was to examine the relationship between the use of Positive Behavioral Interventions and Supports (PBIS) and the same student outcome variables. Variables depicting student perceptions of school climate, self-reported student academic achievement, student perceptions of physical safety in school, and school use of PBIS were drawn from the baseline data collection of the Maryland Safe and Supportive Schools (MDS3) Initiative. Descriptive statistics, bivariate correlations, and multilevel modeling were used to analyze the MDS3 data and to answer four research questions. Descriptive results showed that greater risk factors including feelings of being unsafe, involvement in violence, and poor academic achievement were associated with being male, nonwhite, and in the ninth grade. Bivariate correlations showed statistically significant relationships between student academic achievement and perceptions of school climate, race, gender, and grade level. Average academic achievement at the school level was statistically significantly associated with average school climate, school minority rate, high free and reduced meals (FARM) rate, and use of PBIS. Student perceived physical safety had statistically significant associations with perceptions of school climate, race, gender, and grade level. Average physical safety at the school level was statistically significantly associated with average school climate, school minority rate, high FARM rate, and use of PBIS. Multilevel models of academic achievement showed disparities based on race, gender, grade level, perceptions of school climate, and enrollment in schools with high FARM rate. Multilevel models of physical safety showed disparities based on gender, grade level, perceptions of school climate, enrollment in schools with high FARM rate, and average school level perceptions of school climate. The use of PBIS in schools had little impact on either multilevel model. Recommendations include examining school climate carefully and implementing practices that aim to improve school climate, particularly for those students with the most risk factors.Item Sum Frequency Generation in Laser Safety and Quantum Telecommunications Applications(2011) Houston, Jemellie; Clark, Charles W; Chemical Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This thesis describes the implications of sum-frequency generation in both laser safety and quantum telecommunications applications. Green laser pointer technology uses frequency doubling of invisible 1064 nm infrared radiation to visible 532 nm green radiation. An inexpensive green laser pointer was found to emit infrared leakage primarily due to the lack of an infrared-blocking filter. An experimental setup using common household materials was presented to detect unwanted infrared radiation from such devices. Also reported, is the design and characterization of a high-speed versatile 780 nm pump source up to 1.25 GHz through second harmonic generation from a wavelength of 1560 nm. The 780 nm source is currently being used for the production of correlated photon pairs, one of which is at 656 nm, the hydrogen Balmer alpha line. The final goal will be to generate a high-speed entanglement source after some adjustments in the correlated pair source assembly. This will improve an operational quantum key distribution system.Item Fire Safety of Today's and Tomorrow's Vehicles(2008-05-02) Levy, Kevin Martin; Sunderland, Peter B; Milke, James A; Fire Protection Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This thesis considers fire hazards in the existing vehicle fleet and uses failure modes and effects analyses of three generic designs to identify and rank potential fire hazards in the Emerging Fuel Vehicle (EFV) fleet. A statistics based predictive quantitative risk assessment framework and estimated uncertainty analysis is presented to predict risk of EFV fleets. The analysis also determines that the frequency of fire occurrence is the greatest factor that contributes to risk of death in fire. These preliminary results predict 420±14 fire related deaths per year for a fleet composed entirely of gasoline-electric hybrid vehicles, 910±340 for compressed natural gas vehicles, and 1300±570 for hydrogen fuel-cell vehicles relative to the statistical record of 350 for traditional fuel vehicles. The results are intended to provide vital fire safety information to the traveling public as well as to emergency response personnel to increase safety when responding to EFV fire hazards.Item Leadership and Safety Climate in High-Risk Military Organizations(2007-04-25) Adamshick, Mark Henry; Gansler, Jacques S; Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Preventable accidents and mishaps continue to degrade the readiness of U.S. military forces. In 2006, the National Safety Council reported an annual rate of over 30 accidental fatalities per 100,000 Department of Defense members and estimated that preventable injuries and illnesses cost the department approximately $21 billion per year. Reducing these occurrences was the policy mandate of the Secretary of Defense in 2003. He challenged the military service secretaries to reduce their mishap rates by 50 percent over a two-year period ending September 30, 2005. While each of the military services formulated its own compliance strategy, none of them met the reduction goal. In some cases, the mishap rate actually increased. The purpose of this dissertation is to evaluate the Department of the Navy's (DON) policy compliance strategy and to assess its shortcomings and areas for future improvements. The Navy focused their efforts on leadership-intervention best practices designed to elevate the safety climate in their high-risk units, primarily their aviation components. These units contribute almost 90 percent of the annual mishap cost due to preventable accidents. DON policy-makers theorized that certain leadership interventions would improve safety climate thereby reducing the likelihood that unit members would engage in unsafe behavior both on and off the job. This dissertation evaluates the validity of that general theory, and the appropriateness of the specific leadership interventions chosen, in two distinct data collection and analysis phases. In the first phase, statistical analysis is conducted on a safety-climate survey database maintained by the Naval Post-Graduate School containing 20,000 Navy and Marine Corps military survey respondents assigned to F/A-18 aircraft squadrons completed over the past 5 years. In Phase 2, Commander, Naval Air Forces Atlantic Fleet authorized climate research in four Navy F/A-18 squadrons located at Oceana Naval Air Station. Upon analysis, the intervention methods implemented in the Navy's mishap reduction strategy showed little correlation with safety climate improvement. Phase 2 analysis identified several organizational programs and specific leadership qualities that correlate with elevated safety climate and revealed a preliminary causal relationship between safety climate and safety performance.