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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Author: search.filters.author.West, MadisonSubject: search.filters.subject.Quantitative risk assessment

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    DEVELOPMENT OF A RELIABILITY DATA COLLECTION FRAMEWORK FOR HYDROGEN FUELING STATION QRA
    (2021) West, Madison; Groth, Katrina M; Reliability Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The wider adoption of hydrogen in multiple sectors of the economy requires that safety and risk issues be rigorously investigated. Quantitative Risk Assessment (QRA) is an important tool for enabling safe deployment of hydrogen fueling stations and is increasingly embedded in the permitting process. However, QRA needs reliability data, and currently the available hydrogen safety databases are not in a format conducive for use in QRA. A review of the International Journal of Hydrogen Energy articles on hydrogen fueling station QRA found that lack of hydrogen reliability data is the most common knowledge gap in this field. This study explores what QRA and reliability data currently look like in the context of hydrogen systems. It then presents a new reliability data collection framework for hydrogen systems that overcomes gaps in existing hydrogen safety databases. Current hydrogen safety data collection tools, H2Tools, HIAD, NREL CDPs, and CHS are analyzed and compared for applicability to QRA. Lessons learned from these data collection tools are extracted and combined with best practices from reliability engineering to create an improved database framework for hydrogen reliability data. This framework aims to standardize the hydrogen fueling stations component hierarchy, failure mode taxonomy, and outline high level elements necessary for adequate reliability data collection suitable for use in QRA. This research establishes the groundwork for a collaborative hydrogen reliability database and the future development of data driven hydrogen safety tools.