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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Advanced methodologies for reliability-based design optimization and structural health prognostics
(2010) Wang, Pingfeng; Youn, Byeng Dong; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Failures of engineered systems can lead to significant economic and societal losses. To minimize the losses, reliability must be ensured throughout the system's lifecycle in the presence of manufacturing variability and uncertain operational conditions. Many reliability-based design optimization (RBDO) techniques have been developed to ensure high reliability of engineered system design under manufacturing variability. Schedule-based maintenance, although expensive, has been a popular method to maintain highly reliable engineered systems under uncertain operational conditions. However, so far there is no cost-effective and systematic approach to ensure high reliability of engineered systems throughout their lifecycles while accounting for both the manufacturing variability and uncertain operational conditions. Inspired by an intrinsic ability of systems in ecology, economics, and other fields that is able to proactively adjust their functioning to avoid potential system failures, this dissertation attempts to adaptively manage engineered system reliability during its lifecycle by advancing two essential and co-related research areas: system RBDO and prognostics and health management (PHM). System RBDO ensures high reliability of an engineered system in the early design stage, whereas capitalizing on PHM technology enables the system to proactively avoid failures in its operation stage. Extensive literature reviews in these areas have identified four key research issues: (1) how system failure modes and their interactions can be analyzed in a statistical sense; (2) how limited data for input manufacturing variability can be used for RBDO; (3) how sensor networks can be designed to effectively monitor system health degradation under highly uncertain operational conditions; and (4) how accurate and timely remaining useful lives of systems can be predicted under highly uncertain operational conditions. To properly address these key research issues, this dissertation lays out four research thrusts in the following chapters: Chapter 3 - Complementary Intersection Method for System Reliability Analysis, Chapter 4 - Bayesian Approach to RBDO, Chapter 5 - Sensing Function Design for Structural Health Prognostics, and Chapter 6 - A Generic Framework for Structural Health Prognostics. Multiple engineering case studies are presented to demonstrate the feasibility and effectiveness of the proposed RBDO and PHM techniques for ensuring and improving the reliability of engineered systems within their lifecycles.
A Simplified Model of Planetary Chemical Vapor Deposition Reactors
(2009) Shahshahan, Negin; Adomaitis, Raymond A.; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
A simplified model for planetary chemical vapor deposition reactors is proposed and used to compute deposition species mole fraction and deposition rate in the reactor depletion zone. First, the modeling and optimization work performed in the literature is reviewed and their representative deposition rate profiles are extracted. Afterwards, several simplifying assumptions are applied to derive the reactor modeling equation, and the eigenfunction expansion solution is subsequently computed using a previously developed MATLAB object-oriented computational framework. The simulation result for the deposition profile is improved by modifying the inlet boundary condition, and is then compared with the previously published profiles. The MATLAB optimization toolbox is used to find the optimal deposition profile giving the best match with the published, detailed simulator profiles. Finally, an evaluation of the model consistency with the published results is given.
INTEGER PROGRAM OPTIMIZATION OF COACH ASSIGNMENT WITHIN AN OVERLAPPED NETWORK
(2008) Kolarz, Steven; Haghani, Ali; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
In these days of increasing traffic congestion, increasing energy prices, and decreasing transportation funding it is imperative that efficient, alternate transportation be maintained. It is therefore the goal of this thesis to propose an Integer Program model for optimizing train consists (the number of cars assigned to a particular passenger train) to lower the operational costs while still meeting demand. Further benefits are the increased utilization of the existing car fleet of the service optimized and the reduction of the overall car fleet required. All of these goals are met by the model contained here-in, and validated through an optimization of Amtrak's Northeast Operations. The model shows distinct improvements in lowering operational costs, reducing the overall fleet required, and increasing car utilization for all cases optimized. These include cases to determine sensitivity analysis, where a minimum train length is imposed and where a maximum terminal capacity is imposed.
Analysis and Experimental Demonstration of Conformal Adaptive Phase-Locked Fiber Array for Laser Communications and Beam Projection Applications
(2008-10-07) Liu, Ling; Vorontsov, Mikhail A.; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
The primary goal of this research is the analysis, development, and experimental demonstration of an adaptive phase-locked fiber array system for free-space optical communications and laser beam projection applications. To our knowledge, the developed adaptive phase-locked system composed of three fiber collimators (subapertures) with tip-tilt wavefront phase control at each subaperture represents the first reported fiber array system that implements both phase-locking control and adaptive wavefront tip-tilt control capabilities. This research has also resulted in the following innovations: (a) The first experimental demonstration of a phase-locked fiber array with tip-tilt wavefront aberration compensation at each fiber collimator; (b) Development and demonstration of the fastest currently reported stochastic parallel gradient descent (SPGD) system capable of operation at 180,000 iterations per second; (c) The first experimental demonstration of a laser communication link based on a phase-locked fiber array; (d) The first successful experimental demonstration of turbulence and jitter-induced phase distortion compensation in a phase-locked fiber array optical system; (e) The first demonstration of laser beam projection onto an extended target with a randomly rough surface using a conformal adaptive fiber array system. Fiber array optical systems, the subject of this study, can overcome some of the drawbacks of conventional monolithic large-aperture transmitter/receiver optical systems that are usually heavy, bulky, and expensive. The primary experimental challenges in the development of the adaptive phased-locked fiber-array included precise (<5>microrad) alignment of the fiber collimators and development of fast (100kHz-class) phase-locking and wavefront tip-tilt control systems. The precise alignment of the fiber collimator array is achieved through a specially developed initial coarse alignment tool based on high precision piezoelectric picomotors and a dynamic fine alignment mechanism implemented with specially designed and manufactured piezoelectric fiber positioners. Phase-locking of the fiber collimators is performed by controlling the phases of the output beams (beamlets) using integrated polarization-maintaining (PM) fiber-coupled lithium niobate phase shifters. The developed phase-locking controllers are based on either the SPGD algorithm or the multi-dithering technique. Subaperture wavefront phase tip-tilt control is realized using piezoelectric fiber positioners that are controlled using a computer-based SPGD controller. Both coherent (phase-locked) and incoherent beam combining in the fiber array system are analyzed theoretically and experimentally. Two special fiber-based beam-combining testbeds have been built to demonstrate the technical feasibility of phase-locking compensation prior to free-space operation. In addition, the reciprocity of counter-propagating beams in a phase-locked fiber array system has been investigated. Coherent beam combining in a phase-locking system with wavefront phase tip-tilt compensation at each subaperture is successfully demonstrated when laboratory-simulated turbulence and wavefront jitters are present in the propagation path of the beamlets. In addition, coherent beam combining with a non-cooperative extended target in the control loop is successfully demonstrated.
Integrated Energy and Environmental Analysis of Utility-Scale Wind Power Production
(2008-08-11) Riposo, David Matthew; Kangas, Patrick; Marine-Estuarine-Environmental Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Climate change associated with industrial activity threatens environmental and economic systems worldwide. Wind power was presented as one of several technologies that collectively could mitigate many of the adverse effects of global climate change if deployed at sufficient scale. The objective of this study was to explore the sustainability implications of deploying wind at that scale. The Maple Ridge Wind Energy Facility was identified as the target for analysis. Emergy analysis was performed to explore the total environmental and economic impact of the facility in common units; Energy Return on Energy Investment (EROI) was quantified to explore the net energy yield of the facility. EROI and emergy analyses suggested that Maple Ridge is a sustainable enterprise with moderate environmental impact relative to other electricity generation facilities. Implications of these results on the energy landscape of the future were discussed. Policy options to facilitate wind energy industrial growth were explored.
Critical Asset and Portfolio Risk Analysis for Homeland Security
(2008-07-21) McGill, William L; Ayyub, Bilal M; Reliability Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Providing a defensible basis for allocating resources for critical infrastructure and key resource protection is an important and challenging problem. Investments can be made in countermeasures that improve the security and hardness of a potential target exposed to a security hazard, deterrence measures to decrease the likeliness of a security event, and capabilities to mitigate human, economic, and other types of losses following an incident. Multiple threat types must be considered, spanning everything from natural hazards, industrial accidents, and human-caused security threats. In addition, investment decisions can be made at multiple levels of abstraction and leadership, from tactical decisions for real-time protection of assets to operational and strategic decisions affecting individual assets and assets comprising a regions or sector. The objective of this research is to develop a probabilistic risk analysis methodology for critical asset protection, called Critical Asset and Portfolio Risk Analysis, or CAPRA, that supports operational and strategic resource allocation decisions at any level of leadership or system abstraction. The CAPRA methodology consists of six analysis phases: scenario identification, consequence and severity assessment, overall vulnerability assessment, threat probability assessment, actionable risk assessment, and benefit-cost analysis. The results from the first four phases of CAPRA combine in the fifth phase to produce actionable risk information that informs decision makers on where to focus attention for cost-effective risk reduction. If the risk is determined to be unacceptable and potentially mitigable, the sixth phase offers methods for conducting a probabilistic benefit-cost analysis of alternative risk mitigation strategies. Several case studies are provided to demonstrate the methodology, including an asset-level analysis that leverages systems reliability analysis techniques and a regional-level portfolio analysis that leverages techniques from approximate reasoning. The main achievements of this research are three-fold. First, this research develops methods for security risk analysis that specifically accommodates the dynamic behavior of intelligent adversaries, to include their tendency to shift attention toward attractive targets and to seek opportunities to exploit defender ignorance of plausible targets and attack modes to achieve surprise. Second, this research develops and employs an expanded definition of vulnerability that takes into account all system weaknesses from initiating event to consequence. That is, this research formally extends the meaning of vulnerability beyond security weaknesses to include target fragility, the intrinsic resistance to loss of the systems comprising the asset, and weaknesses in response and recovery capabilities. Third, this research demonstrates that useful actionable risk information can be produced even with limited information supporting precise estimates of model parameters.
An XML Application-Based Interface to Developing Modular System Simulations
(2008-01-25) Weisflog, Jens; Adomaitis, Ray; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
We introduce a framework for the development of modular lumped and distributed parameter system models, the latter described by boundary value problems. The simulation of such systems requires careful analysis and a rigorous approach to development to provide both accuracy and computational efficiency. We explain the current implementation, which solves such systems in a MATLAB environment using object-oriented programming principles as part of the Modular Distributed Parameter System Analysis and Simulation (MDPSAS) package. We propose a mechanism for creating user-defined simulation elements using a web-based collaborative interface. The creation of a novel semantic vocabulary built into an XML application language called ModSimML is presented as a tool for data structuring and exchange. The development of a schema for the XML application formalizes of our data model. The utility of this interface is described via an application to research in Biological Micro-Electro-Mechanical Systems (BioMEMS), whose simulations require assembly from modular components.
Automatic Generation of Generalized Event Sequence Diagrams for Guiding Simulation Based Dynamic Probabilistic Risk Assessment of Complex Systems
(2007-11-27) Nejad-Hosseinian, Seyed Hamed; Mosleh, Ali; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Dynamic probabilistic risk assessment (DPRA) is a systematic and comprehensive methodology that has been used and refined over the past two decades to evaluate the risks associated with complex systems such as nuclear power plants, space missions, chemical plants, and military systems. A critical step in DPRA is generating risk scenarios which are used to enumerate and assess the probability of different outcomes. The classical approach to generating risk scenarios is not, however, sufficient to deal with the complexity of the above-mentioned systems. The primary contribution of this dissertation is in offering a new method for capturing different types of engineering knowledge and using them to automatically generate risk scenarios, presented in the form of generalized event sequence diagrams, for dynamic systems. This new method, as well as several important applications, is described in detail. The most important application is within a new framework for DPRA in which the risk simulation environment is guided to explore more interesting scenarios such as low-probability/high-consequence scenarios. Another application considered is the use of the method to enhance the process of risk-based design.
Hybrid Causal Logic Methodology for Risk Assessment
(2007-11-27) Wang, Chengdong; Mosleh, Ali; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Probabilistic Risk Assessment is being increasingly used in a number of industries such as nuclear, aerospace, chemical process, to name a few. Probabilistic Risk Assessment (PRA) characterizes risk in terms of three questions: (1) What can go wrong? (2) How likely is it? (3) What are the consequences? Probabilistic Risk Assessment studies answer these questions by systematically postulating and quantifying undesired scenarios in a highly integrated, top down fashion. The PRA process for technological systems typically includes the following steps: objective and scope definition, system familiarization, identification of initiating events, scenario modeling, quantification, uncertainty analysis, sensitivity analysis, importance ranking, and data analysis. Fault trees and event trees are widely used tools for risk scenario analysis in PRAs of technological systems. This methodology is most suitable for systems made of hardware components. A more comprehensive treatment of risks of technical systems needs to consider the entire environment within which such systems are designed and operated. This environment includes the physical environment, the socio-economic environment, and in some cases the regulatory and oversight environment. The technical system, supported by an organization of people in charge of its operation, is at the cross-section of these environments. In order to develop a more comprehensive risk model for these systems, an important step is to extend the modeling capabilities of the conventional Probabilistic Risk Assessment methodology to also include risks associated with human activities and organizational factors in addition to hardware and software failures and adverse conditions of the physical environment. The causal modeling should also extend to the influence of regulatory and oversight functions. This research offers such a methodology. It proposes a multi-layered modeling approach so that most the appropriate techniques are applied to different individual domains of the system. The approach is called the Hybrid Causal Logic (HCL) methodology. The main layers include: (a) A model to define safety/risk context. This is done using a technique known as event sequence diagram (ESD) method that helps define the kinds of accidents and incidents that can occur in relation to the system being considered; (b) A model that captures the behaviors of the physical system (hardware, software, and environmental factors) as possible causes or contributing factors to accidents and incidents delineated by the event sequence diagrams. This is done by common system modeling techniques such as fault tress (FT); and (c) A model to extend the causal chain of events to their potential human and organizational roots. This is done using Bayesian belief networks (BBN). Bayesian belief networks are particularly useful as they do not require complete knowledge of the relation between causes and effects. The integrated model is therefore a hybrid causal model with the corresponding sets of taxonomies and analytical and computational procedures. In this research, a methodology to combine fault trees, event trees or event sequence diagrams, and Bayesian belief networks has been introduced. Since such hybrid models involve significant interdependencies, the nature of such dependencies are first determined to pave the way for developing proper algorithmic solutions of the logic model. Major achievements of this work are: (1) development of the Hybrid Causal Logic model concept and quantification algorithms; (2) development and testing of computer implementation of algorithms (collaborative work); (3) development and implementation of algorithms for HCL-based importance measures, an uncertainty propagation method the BBN models, and algorithms for qualitative-quantitative Bayesian belief networks; and (4) development and testing of the Integrated Risk Information System (IRIS) software based on HCL methodology.
ARCOLOGY OPTIMIZATION AND SIMULATION FRAMEWORK
(2007-11-06) Andruscavage, Rowin Warin; Austin, Mark; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Arcology design combines urban planning and architecture with the mechanics of ecology. The physical design of an arcology would encompass the creation of a "hyperstructure" that delivers utility and transportation infrastructure in a highly integrated compact package. This thesis defines and describes a prototype simulation framework that would execute and evaluate intelligent demand-responsive multimodal mass transit schemes. Given a set of connected nodes serviced by different fleets of vehicles, a global optimizer attempts to generate a coordinated fleet schedule that meets various demand patterns. Factorial design of experiments and parametric analysis on the resulting simulated performance data of several simplified 1D and 2D scenarios help identify significant system design variables, including the number and size of the vehicle fleet, station configuration, transit network topology, and initial distribution of travel demand between station nodes. This tool explores the effectiveness of transit-oriented design paradigms supporting arcologies and other urban forms.

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