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
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Item APPLICATION OF A BAYESIAN NETWORK BASED FAILURE DETECTION AND DIAGNOSIS FRAMEWORK ON MARITIME DIESEL ENGINES(2022) Reynolds, Steven; Groth, Katrina; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Diesel engine propulsion has been the largest driver of maritime trade and transportation since its development in the early 20th century and the technology surrounding the operation and maintenance of these systems has grown in complexity leading to rapid advancement in amount and variety of data being collected. This increase in reliability data provides a fantastic opportunity to improve upon the existing tools troubleshooting and decision support tool used within the maritime engine community to enable a more robust understanding of engine reliability. This work leverages this opportunity and applies it to the Coast Guard and its acquisition of the Fast Response Cutter (FRC) fleet powered by two MTU20V4000M93 engines integrated with top of line monitoring and control equipment.The purpose of this research is to create procedures for creating a Failure Detection and Diagnosis (FDD) model of a maritime diesel engine that updates existing Probabilistic Risk Analysis (PRA) data with input from the engine monitoring and control system using Bayesian inference. A literature review of existing work within the PRA and Prognostics and Health Management (PHM) fields was conducted with specific focus on the advancement and gaps in the field specific to their use in maritime engine applications. Following this, a hierarchal ruleset was created that outlines procedures for integrating existing PRA data and PHM metrics into a Bayesian Network structure. This methodology was then used to build a Bayesian Network based FDD model of the FRC engine. This model was then validated by Coast Guard Engineers and run through a diagnostic use case scenario demonstrating the model’s suitability in the diagnostic space.Item Investigation into the Influence of Build Parameters on Failure of 3D Printed Parts(2016) Fornasini, Giacomo; Schmidt, Linda C; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Additive manufacturing, including fused deposition modeling (FDM), is transforming the built world and engineering education. Deep understanding of parts created through FDM technology has lagged behind its adoption in home, work, and academic environments. Properties of parts created from bulk materials through traditional manufacturing are understood well enough to accurately predict their behavior through analytical models. Unfortunately, Additive Manufacturing (AM) process parameters create anisotropy on a scale that fundamentally affects the part properties. Understanding AM process parameters (implemented by program algorithms called slicers) is necessary to predict part behavior. Investigating algorithms controlling print parameters (slicers) revealed stark differences between the generation of part layers. In this work, tensile testing experiments, including a full factorial design, determined that three key factors, width, thickness, infill density, and their interactions, significantly affect the tensile properties of 3D printed test samples.Item An Analysis of Thermally Induced Arcing Failure of Electrical Cable(2013) Fisher, Ryan Patrick; Stoliarov, Stanislav I; Fire Protection Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Arc failure of Southwire Romex Simpull non-metallic sheathed 14/2 American wire gauge (AWG) with ground cable due to external heat was examined. This type of cable was selected due to its widespread use in residential building wiring. This research is motivated by the fact that currently there are no widely accepted methods or models used to predict electric arc failure in cables exposed to thermal conditions or to determine whether an arc failure event was the cause or result of a fire. A variety of tests were performed at various temperatures to learn more about the arc failure of these cables. The cables were exposed to precise temperatures with a steady heating rate in a convection oven in order to best attempt to eliminate heat transfer through the cable. In order to explore the effect current may have on the time to arc failure of the cable, experiments at different temperatures were performed in both loaded and unloaded scenarios. During many of these tests, voltage and current measurements were collected during an arcing event. As part of the process of exploring the events leading up to arc failure, electrical resistance tests of the cable's insulation components were examined. A model was developed to predict time to arc failure at a variety of temperatures based on thermal degradation of the PVC insulation. The purpose of the developed model is to be able to predict cable failure based on known thermal conditions. The proposed values of the model developed are in examining a prior thermally induced electrical arcing incident or in determining the suitability of a cable in an abnormal thermal environment. The results of this research will be useful in continuing the research and education of the arc failure of electrical cables.Item Detection of Interconnect Failure Precursors using RF Impedance Analysis(2010) Kwon, Daeil; Pecht, Michael G; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Many failures in electronics result from the loss of electrical continuity of common board-level interconnects such as solder joints. Measurement methods based on DC resistance such as event detectors and data-loggers have long been used by the electronics industry to monitor the reliability of interconnects during reliability testing. DC resistance is well-suited for characterizing electrical continuity, such as identifying an open circuit, but it is not useful for detecting a partially degraded interconnect. Degradation of interconnects, such as cracking of solder joints due to fatigue or shock loading, usually initiates at an exterior surface and propagates towards the interior. A partially degraded interconnect can cause the RF impedance to increase due to the skin effect, a phenomenon wherein signal propagation at frequencies above several hundred MHz is concentrated at the surface of a conductor. Therefore, RF impedance exhibits greater sensitivity compared to DC resistance in detecting early stages of interconnect degradation and provides a means to prevent and predict an important cause of electronics failures. This research identifies the applicability of RF impedance as a means of a failure precursor that allows for prognostics on interconnect degradation based on electrical measurement. It also compares the ability of RF impedance with that of DC resistance to detect early stages of interconnect degradation, and to predict the remaining life of an interconnect. To this end, RF impedance and DC resistance of a test circuit were simultaneously monitored during interconnect stress testing. The test vehicle included an impedance-controlled circuit board on which a surface mount component was soldered using two solder joints at the end terminations. During stress testing, the RF impedance exhibited a gradual non-linear increase in response to the early stages of solder joint cracking while the DC resistance remained constant. The gradual increase in RF impedance was trended using prognostic algorithms in order to predict the time to failure of solder joints. This prognostic approach successfully predicted solder joint remaining life with a prediction error of less than 3%. Furthermore, it was demonstrated both theoretically and experimentally that the RF impedance analysis was able to distinguish between two competing interconnect failure mechanisms: solder joint cracking and pad cratering. These results indicate that RF impedance provides reliable interconnect failure precursors that can be used to predict interconnect failures. Since the performance of high speed devices is adversely affected by early stages of interconnect degradation, RF impedance analysis has the potential to provide improved reliability assessment for these devices, as well as accurate failure prediction for current and future electronics.Item ENTREPRENEURIAL SELF-EFFICACY AND THE SUCCESS OF SUBSEQUENT VENTURE STARTUP AFTER FAILURE(2010) Boss, Alan Dennis; Baum, J. Robert; Sims, Henry P; Business and Management: Management & Organization; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Everyone experiences failure at some point in their lifetime. Entrepreneurs, especially, have a high incidence of failure, with estimates that over sixty percent fail within six years. Yet, a high percentage of failed entrepreneurs recover and persevere to start another business. Sometimes, they even become "serial entrepreneurs" who start many businesses. How do entrepreneurs recover from failure and have success? This research focuses on the failed entrepreneur, and I investigate aspects of how and why some failed entrepreneurs recover and start a new business. My research focuses on characteristics of the failed entrepreneurs themselves, and how certain attributes might differentiate between failed entrepreneurs who recover successfully versus those who do not. Based upon fundamental theories of human behavior and recent inquiries that have influenced the entrepreneurship literature, I draw upon research about entrepreneurs' personal competencies that stand out as predictors of venture persistence and success, specifically, (1) domain-specific self-efficacy (2) emotion regulation, (3) practical intelligence, and (4) self-leadership, to propose a path to recovery when failure occurs. I suggest that these areas of research may enhance our knowledge of how and why failed entrepreneurs recover from failure. In addition, I investigate how characteristics of the immediate context or environment support or discourage subsequent startup. I interview and survey failed entrepreneurs, beginning with a list of firms from a Bay Area business consulting firm that helps failed companies "work out" of their business. Other contact sources include small business development centers, personal contacts, university entrepreneurship centers, and two populations of healthcare workers in the southern United States. Results of this study include entrepreneurial self-efficacy fully mediating the effects of both practical intelligence and emotion regulation on subsequent venture success, as well as partial mediation of support from social contacts on success. Theoretical and practical implications are discussed. Although research has been conducted on future success of successful entrepreneurs, as far as I can determine, no other academic researcher has attempted to understand and empirically demonstrate the future success of failed entrepreneurs.Item Failure Mechanisms in Wideband Semiconductor Power Devices(2006-06-05) Zhang, Xiaohu; Bernstein, Joseph; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Silicon carbide (SiC), as one of the wide bandgap semiconductors, is a promising material for next-generation power devices due to its high critical electric field, high thermal conductivity, and high saturated electron drift velocity properties. Extensive studies have been focused their electrical characterizations. Failure mechanisms of SiC devices, however, have not been fully explored. In this work the failure mechanisms of SiC power devices, including Schottky diodes, power MOSFETs and IGBTs, are investigated. The characteristics of SiC Schottky diodes have been investigated and simulated based on the drift-diffusion model. Interface state degradation has been identified as the mechanism responsible for the non-catastrophic failure happened in Schottky diode. Experimental and simulation results are provided to support this conclusion. Single-event burnout (SEB) and single-event gate rupture (SEGR) failure mechanisms have been investigated for SiC power MOSFETS in details in this work since power MOSFETs have been used in very critical applications. The features of SiC power MOSFET SEB and SEGR failures have been simulated successfully and compared to those of Si power MOSFETs. The much better robustness of SiC power MOSFES against SEB failures has been demonstrated by the simulation results. At last the latch-up failure mechanism has been investigated for SiC IGBTs. Compared to Si IGBTs, the results show that SiC IGBTs have a stronger capability against the latch-up failure. The design and application guideline for SiC power devices can be made base on the results obtained in this work.Item DEEP SUBMICRON CMOS VLSI CIRCUIT RELIABILITY MODELING, SIMULATION AND DESIGN(2005-11-29) Li, Xiaojun; Bernstein, Joseph B; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)CMOS VLSI circuit reliability modeling and simulation have attracted intense research interest in the last two decades, and as a result almost all IC Design For Reliability (DFR) tools now try to incrementally simulate device wearout mechanisms in iterative ways. These DFR tools are capable of accurately characterizing the device wearout process and predicting its impact on circuit performance. Nevertheless, excessive simulation time and tedious parameter testing process often limit popularity of these tools in product design and fabrication. This work develops a new SPICE reliability simulation method that shifts the focus of reliability analysis from device wearout to circuit functionality. A set of accelerated lifetime models and failure equivalent circuit models are proposed for the most common MOSFET intrinsic wearout mechanisms, including Hot Carrier Injection (HCI), Time Dependent Dielectric Breakdown (TDDB), and Negative Bias Temperature Instability (NBTI). The accelerated lifetime models help to identify the most degraded transistors in a circuit in terms of the device's terminal voltage and current waveforms. Then corresponding failure equivalent circuit models are incorporated into the circuit to substitute these identified transistors. Finally, SPICE simulation is performed again to check circuit functionality and analyze the impact of device wearout on circuit operation. Device wearout effects are lumped into a very limited number of failure equivalent circuit model parameters, and circuit performance degradation and functionality are determined by the magnitude of these parameters. In this new method, it is unnecessary to perform a large number of small-step SPICE simulation iterations. Therefore, simulation time is obviously shortened in comparison to other tools. In addition, a reduced set of failure equivalent circuit model parameters, rather than a large number of device SPICE model parameters, need to be accurately characterized at each interim wearout process. Thus device testing and parameter extraction work are also significantly simplified. These advantages will allow circuit designers to perform quick and efficient circuit reliability analyses and to develop practical guidelines for reliable electronic designs.