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 COST-EFFECTIVE PROGNOSTICS AND HEALTH MONITORING OF LOCALLY DAMAGED PIPELINES WITH HIGH CONFIDENCE LEVEL(2020) Aria, Amin; Modarres, Mohammad; Azarm, Shapour; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Localized pipeline damages, caused by degradation processes such as corrosion, are prominent, can result in pipeline failure and are expensive to monitor. To prevent pipeline failure, many Prognostics and Health Monitoring (PHM) approaches have been developed in which sensor network for online, and human inspection for offline data gathering are separately used. In this dissertation, a two-level (segment- and integrated-level) PHM approach for locally damaged pipelines is proposed where both of these degradation data gathering schemes (i.e., detection methods) are considered simultaneously. The segment-level approach, in which the damage behavior is considered to be uniform, consists of a static and a dynamic phase. In the static phase, a new optimization problem for the health monitoring layout design of locally damaged pipelines is formulated. The solution to this problem is an optimal configuration (or layout) of degradation detection methods with a minimized health monitoring cost and a maximized likelihood of damage detection. In the dynamic phase, considering the optimal layout, an online fusion of high-frequency sensors data and low-frequency inspection information is conducted to estimate and then update the pipeline’s Remaining Useful Life (RUL) estimate. Subsequently, the segment-level optimization formulation is modified to improve its scalability and facilitate updating layouts considering the online RUL estimates. Finally, at the integrated-level, the modified segment-level approach is used along with Stochastic Dynamic Programming (SDP) to produce an optimal set of layouts for a long pipeline consisting of multiple segments with different damage behavior. Experimental data and several notional examples are used to demonstrate the performance of the proposed approaches. Synthetically generated damage data are used in two examples to demonstrate that the proposed segment-level layout optimization approach results in a more robust solution compared to single detection approaches and deterministic methods. For the dynamic segment-level phase, acoustic emission sensor signals and microscopic images from a set of fatigue crack experiments are considered to show that combining sensor- and image-based damage size estimates leads to accuracy improvements in RUL estimation. Lastly, using synthetically generated damage data for three hypothetical pipeline segments, it is shown that the constructed integrated-level approach provides an optimal set of layouts for several pipeline segments.Item USING THE Q-WEIBULL DISTRIBUTION FOR RELIABILITY ENGINEERING MODELING AND APPLICATIONS(2019) Xu, Meng; Herrmann, Jeffrey W.; Droguett, Enrique López; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Modeling and improving system reliability require selecting appropriate probability distributions for describing the uncertainty in failure times. The q-Weibull distribution, which is based on the Tsallis non-extensive entropy, is a generalization of the Weibull distribution in the context of non-extensive statistical mechanics. The q-Weibull distribution can be used to describe complex systems with long-range interactions and long-term memory, can model various behaviors of the hazard rate, including unimodal, bathtub-shaped, monotonic, and constant, and can reproduce both short and long-tailed distributions. Despite its flexibility, the q-Weibull has not been widely used in reliability applications partly because parameter estimation is challenging. This research develops and tests an adaptive hybrid artificial bee colony approach for estimating the parameters of a q-Weibull distribution. This research demonstrates that the q-Weibull distribution has a superior performance over Weibull distribution in the characterization of lifetime data with a non-monotonic hazard rate. Moreover, in terms of system reliability, the q-Weibull distribution can model dependent series systems and can be modified to model dependent parallel systems. This research proposes using the q-Weibull distribution to directly model failure time of a series system composed of dependent components that are described by Clayton copula and discusses the connection between the q-Weibull distribution and the Clayton copula and shows the equivalence in their parameters. This dissertation proposes a Nonhomogeneous Poisson Process (NHPP) with a q-Weibull as underlying time to first failure (TTFF) distribution to model the minimal repair process of a series system composed of multiple dependent components. The proposed NHPP q-Weibull model has the advantage of fewer parameters with smaller uncertainty when used as an approximation to the Clayton copula approach, which in turn needs more information on the assumption for the underlying distributions of components and the exact component cause of system failure. This dissertation also proposes a q-Fréchet distribution, dual distribution to q-Weibull distribution, to model a parallel system with dependent component failure times that are modeled as a Clayton copula. The q-Weibull and q-Fréchet distributions are successfully applied to predict series and parallel system failures, respectively, using data that is characterized by non-monotonic hazard rates.Item DEVELOPMENT OF AN INTEGRATED RIDE-SHARED MOBILITY-ON-DEMAND (MOD) AND PUBLIC TRANSIT SYSTEM(2019) XU, LIU; Haghani, Ali; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The Mobility-on-Demand (MOD) services, like the ones offered by Uber and Lyft, are transforming urban transportation by providing more sustainable and convenient service that allows people to access anytime and anywhere. In most U.S. cities with sprawling suburban areas, the utilization of public transit for commuting is often low due to lack of accessibility. Thereby the MOD system can function as a first-and-last-mile solution to attract more riders to use public transit. Seamless integration of ride-shared MOD service with public transit presents enormous potential in reducing pollution, saving energy, and alleviating congestion. This research proposes a general mathematical framework for solving a multi-modal large-scale ride-sharing problem under real-time context. The framework consists of three core modules. The first module partitions the entire map into a set of more scalable zones to enhance computational efficiency. The second module encompasses a mixed-integer-programming model to concurrently find the optimal vehicle-to-request and request-to-request matches in a hybrid network. The third module forecasts the demand for each station in the near future and then generates an optimized vehicle allocation plan to best serve the incoming rider requests. To ensure its applicability, the proposed model accounts for transit frequency, MOD vehicle capacity, available fleet size, customer walk-away condition and travel time uncertainty. Extensive experimental results prove that the proposed system can bring significant vehicular emission reduction and deliver timely ride-sharing service for a large number of riders. The main contributions of this study are as follows: • Design of a general framework for planning a multi-modal ride-sharing system in cities with under-utilized public transit system; • Development of an efficient real-time algorithm that can produce solutions of desired quality and scalability and redistribute the available fleet corresponding to the future demand evolution; • Validation of the potential applicability of the proposed system and quantitatively reveal the trade-off between service quality and system efficiency.Item STRUCTURAL EVOLUTION DURING THERMAL TREATMENTS AND THE RESULTANT MECHANICAL BEHAVIOR OF HIGH STRENGTH LOW ALLOY STEELS(2018) Draper, Matthew Charles; Ankem, Sreeramamurthy; Material Science and Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)HY steels were designed as a solid solution strengthened grade for both high yield strength and high impact toughness in structural applications for Naval vessels. These alloys are susceptible to both hydrogen and temper embrittlement which necessitates high expense manufacturing processes to preclude these conditions. Successful implementation of lower cost and higher reliability treatments requires an improved understanding of the structural evolution and corresponding changes in mechanical behavior for the alloy. This research combines mechanical and microstructural characterization methods along with thermodynamic and kinetic models to build a comprehensive understanding of the effects of thermal treatments on the structure-property relationship of the alloy system. The embrittlement rate was studied between 315°C and 565°C at varied logarithmic time intervals up to 40,000 minutes. The embrittlement recovery rate was studied between 593°C and 704°C at logarithmic time intervals up to 10,000 minutes. Finally, hydrogen aging was studied between 315°C and 565°C at varied thermodynamically equivalent time intervals. A variety of test methods were employed for characterization including: traditional metallographic techniques, mechanical testing, computational modeling, and a novel image analysis technique for carbide analysis. Metallographic along with computational work supports a conclusion that temper embrittlement and subsequent recovery cannot be solely explained by the segregation of phosphorus and other embrittling elements to grain boundaries. Rather it is shown for the first time that alloy carbides play a key role in embrittlement for this system. The evolution of these carbides serves both to create initiation sites for cleavage fracture and deplete the matrix of Mo, which is a P scavenger. Recovery from embrittlement is thus proposed to be related to both the removal of P from the boundary and the dissolution of carbides. From these results a series of kinetic models have been developed for the nucleation, dissolution, and coarsening of alloy carbides. Models developed for the mitigation of monatomic hydrogen show a novel treatment for hydrogen aging via performing the aging within the embrittlement range with follow on treatments designed to recover from embrittlement. This new treatment has the potential to reduce hydrogen aging times by up to 90% in industrial manufacture.Item MODELING AND SIMULATION OF A SEMICONDUCTOR MANUFACTURING FAB FOR CYCLE TIME ANALYSIS(2018) Shinde, Aditya Ramaji; Fu, Michael; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The goal of the thesis is to conduct a study of the effects of scheduling policies and machine failures on the manufacturing cycle time of the Integrated Circuit (IC) manufacturing process for two processor chips, namely Skylake and Kabylake, manufactured by Intel. The fab simulation model was developed as First in First Out (FIFO), Shortest Processing Time (SPT), Priority based (PB), and Failure FIFO (machine failures) model, and the average cycle times and queue waiting times under the four scheduling policy models were compared for both the Skylake and Kabylake wafers. The study revealed that scheduling policies SPT and PB increased the average cycle time for Skylake wafers while decreasing the average cycle time for the Kabylake wafers, when compared to the base FIFO model. Machine failures increased the average cycle time for both types of wafers.Item The personnel system of the foreign service of the United States; an analysis and evaluation of the Foreign Service Officer Corps(1952) Moser, Martin William; Digital Repository at the University of Maryland; University of Maryland (College Park, Md)Item A comparative study of methods for the combination of predictors in public personnel selection(1952) Maslow, Albert P.; Digital Repository at the University of Maryland; University of Maryland (College Park, Md)Item MODEL BASED SYSTEMS ENGINEERING APPROACH FOR COLLABORATIVE REQUIREMENTS IN COOLING WATER SYSTEM DESIGN(2014) Abeye, Binyam; Bara, John; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Evaluation of the manufacturing process industry confirms that there is still manual exchange of product data between design and procurement engineers and equipment suppliers. Manual data exchange incurs human error, increases the cost, and takes more time. Also manual data exchange prevents designers from automatically evaluating a larger pool of suppliers and verifying supplier requirements. Even current PLM software faces difficulties with flow of requirements information from different suppliers. This thesis proposes to develop a collaborative requirements framework using a Model Based System Engineering approach to representing, communicating, and verifying requirements. Collaborative requirements entail that equipment data and process system requirements are shared in a common way to encourage automated of equipment tradeoff and requirement traceability. The collaborative requirement framework includes SysML to represent the multiple views of requirements and their relation to the system structure and behavior, Multilevel Flow Model functional diagrams to depict the high level qualitative functionality with relation to requirements, and lastly an optimization tool to verify requirements. Overall, this thesis shows the benefits of using the collaborative requirements framework automating data exchange between design engineers and equipment suppliers.Item DYNAMIC BEHAVIOR OF OPERATING CREW IN COMPLEX SYSTEMS: AN OBJECT-BASED MODELING & SIMULATION APPROACH(2013) Azarkhil, Mandana; Mosleh, Ali; Reliability Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)High-risk environments such as the control room of Nuclear Power Plants are extremely stressful for the front line operators; during accidents and under high task load situations, the operators are solely responsible for the ultimate decision-making and control of such complex systems. Individuals working as a team constantly interact with each other and therefore introduce team related issues such as coordination, supervision and conflict resolution. The aggregate impact of multiple human errors inside communication and coordination loops in a team context can give rise to complex human failure modes and failure mechanisms. This research offers a model of operating crew as an interactive social unit and investigates the dynamic behavior of the team under upset situations through a simulation method. The domain of interest in this work is the class of operating crew environments that are subject to structured and regulated guidelines with formal procedures providing the core of their response to accident conditions. In developing the cognitive models for the operators and teams of operators, their behavior and relations, this research integrates findings from multiple disciplines such as cognitive psychology, human factors, organizational factors, and human reliability. An object-based modeling methodology is applied to represent system elements and different roles and behaviors of the members of the operating team. The proposed team model is an extended version of an existing cognitive model of individual operator behavior known as IDAC (Information, Decision, and Action in Crew context). Scenario generation follows DPRA (Dynamic Probabilistic Risk Assessment) methodologies. The method capabilities are demonstrated through building and simulating a simplified model of a steam/power generating plant. Different configurations of team characteristics and influencing factors have been simulated and compared. The effects of team factors and crew dynamics on system risk with main focus on team errors, associated causes and error management processes and their impact on team performance have been studied through a large number of simulation runs. The results are also compared with several theoretical models and empirical studies.Item STRATEGIC PRODUCT DESIGN DECISIONS FOR UNCERTAIN, CONVERGING AND SERVICE ORIENTED MARKETS(2012) Wang, Zhichao; Azarm, Shapour; Kannan, P.K.; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Market driven product design decisions are receiving increasing attention in the engineering design research literature. Econometric models and marketing research techniques are being integrated into engineering design in order to assist with profit maximizing product design decisions. This stream of research is referred to as "Design for Market Systems" (DMS). The existing DMS approaches fall short when the market environment is complex. The complexity can be incurred by the uncertain action-reactions of market players which impose unexpected market responses to a new design. The complexity can originate from the emergence of a niche product which creates a new product market by integrating the features of two or more existing products categories. The complexity can also arise when the designer is challenged to handle the couplings of outsourced subsystems from suppliers and explore the integration of the product with service providers. The objective of the thesis is to overcome such limitations and facilitate design decisions by modeling and interpreting the complex market environment. The research objective is achieved by three research thrusts. Thrust 1 examines the impact of action-reactions of market players on the long and short term design decisions for single category products using an agent based simulation approach. Thrust 2 concerns the design decisions for "convergence products". A convergence product physically integrates two or more existing product categories into a common product form. Convergence products make the consumer choice behavior and profit implications of design alternatives differ significantly from the situation where only a single product market is involved. Thrust 3 explores product design decisions while considering the connection to the upstream suppliers and downstream service providers. The connection is achieved by a quantitative understanding of interoperability of physical product modules as well as between a physical product and a service provider.