Theses and Dissertations from UMD

Permanent URI for this communityhttp://hdl.handle.net/1903/2

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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2013 - 20142

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    Managing Risk Assessment Stakeholder Engagement Processes: A Case Study
    (2014) Leveridge, M. Dianne; Baecher, Greg; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Risk engineers conduct comprehensive risk assessments for many types of large projects, often singularly focused on the technical assessment and its value to the technical engineering team. Limiting or excluding community stakeholder involvement from the assessment process increases stakeholder skepticism, apprehension, and mistrust regarding safety, health and welfare of those stakeholders living or working nearby. Social experts have repeatedly documented connections between perception framing, communication processes, and risks. This research considers the connections between stakeholder perceptions and communication plans associated with risks listed in the risk register, and communication plans designed based upon including social expert suggestions for six projects: three bio-safety laboratories; two levee system assessment projects; and one Superfund site. The project risk assessment value is researched through the lens of risk perception and communication planning via the risk register. The concept of a Risk Perception Management (RPM) Plan developed in collaboration with social science experts and integrated with the risk register is presented. This research shows how the RPM concept iteratively captures stakeholder perceptions to build associated communication plans, thus increasing risk assessment value for stakeholders and decision-makers.
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    RESILIENCE OF TRANSPORTATION INFRASTRUCTURE SYSTEMS: QUANTIFICATION AND OPTIMIZATION
    (2013) Faturechi, Reza; Miller-Hooks, Elise; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Transportation systems are critical lifelines for society, but are at risk from natural or human-caused hazards. To prevent significant loss from disaster events caused by such hazards, the transportation system must be resilient, and thus able to cope with disaster impact. It is impractical to reinforce or harden these systems to all types of events. However, options that support quick recovery of these systems and increase the system's resilience to such events may be helpful. To address these challenges, this dissertation provides a general mathematical framework to protect transportation infrastructure systems in the presence of uncertain events with the potential to reduce system capacity/performance. A single, general decision-support optimization model is formulated as a multi-stage stochastic program. The program seeks an optimal sequence of decisions over time based upon the realization of random events in each time stage. This dissertation addresses three problems to demonstrate the application of the proposed mathematical model in different transportation environments with emphasis on system-level resilience: Airport Resilience Problem (ARP), Building Evacuation Design Problem (BEDP), and Travel Time Resilience in Roadways (TTR). These problems aim to measure system performance given the system's topological and operational characteristics and support operational decision-making, mitigation and preparedness planning, and post-event immediate response. Mathematical optimization techniques including, bi-level programming, nonlinear programming, stochastic programming and robust optimization, are employed in the formulation of each problem. Exact (or approximate) solution methodologies based on concepts of primal and dual decomposition (integer L-shaped decomposition, Generalized Benders decomposition, and progressive hedging), disjunctive optimization, scenario simulation, and piecewise linearization methods are presented. Numerical experiments were conducted on network representations of a United States rail-based intermodal container network, the LaGuardia Airport taxiway and runway pavement network, a single-story office building, and a small roadway network.