PSAM 16 Conference Paper Overview
Welcome to the PSAM 16 Conference paper and speaker overview page.
Lead Author: Michelle Bensi Co-author(s): • Katrina Groth (kgroth@umd.edu)
• Zeyun Wu (zwu@vcu.edu)
• Zhegang Ma (zhegang.ma@inl.gov)
• Ray Schneider(schneire@westinghouse.com)
• Somayeh Mohammadi (somayeh@terpmail.umd.edu)
• Tao Liu (liut8@vcu.edu)
• Ahmad Al-Douri (clevine1@umd.edu)
• Camille Levine (clevine1@umd.edu)
| Identifying and Prioritizing Sources of Uncertainty in External Hazard Probabilistic Risk Assessment: Project Activities and Progress |
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| There are inherently significant sources of uncertainty in external hazard probabilistic risk assessment (XHPRA) for nuclear power facilities. The state of knowledge and practice associated with these uncertainties varies across hazard groups (e.g., earthquakes, wind, and flooding). There is currently a research need to build upon the existing state of knowledge to develop a technically sound, risk-informed strategy for identifying and characterizing drivers of hazard uncertainty in XHPRA for multiple classes of hazards. This paper summarizes the ongoing progress of a multi-year research project that seeks to: (1) develop a structured process for identifying, evaluating, categorizing, and communicating the impact of uncertainties on XHPRAs, (2) investigate the spectrum of uncertainties associated with realistically parsing hazard information into the XHPRA, (3) understand how uncertainties in the physical hazard characteristics/timing interfaces with plant response strategies (e.g., plant physics and human reliability), and (4) assess the combined impact of these uncertainties (and uncertainty reduction efforts) on the development of the XHPRA. This research will ultimately help to facilitate the prioritization of uncertainty reduction activities based on their risk significance, risk reduction benefit, and value. |
Paper MB158 Preview
Author and Presentation Info
Lead Author Name: Michelle (Shelby) Bensi (mbensi@umd.edu)
Bio: Michelle (Shelby) Bensi, Ph.D. is an assistant professor in the Department of Civil and Environmental Engineering at the University of Maryland (UMD). Dr. Bensi’s research centers on the application of probabilistic risk assessment concepts and tools as well as statistical/machine learning techniques to problems involving engineered systems exposed to natural hazards. Dr. Bensi focuses primarily on topics related to the probabilistic assessment of natural hazards (e.g., seismic, coastal, inland flooding, precipitation), risk-informed applications, and disaster resilience. Prior to joining the UMD faculty, Dr. Bensi served as an engineer at the United States Nuclear Regulatory Commission where she was heavily involved in the agency's response to the Fukushima Dai-ichi reactor accidents. Dr. Bensi serves as a member of the American Nuclear Society and American Society of Mechanical Engineers (ANS/ASME) Joint Committee on Nuclear Risk Management (JCNRM).
Country: United States of America
Company: University of Maryland
Job Title: Assistant Professor
Bio: Michelle (Shelby) Bensi, Ph.D. is an assistant professor in the Department of Civil and Environmental Engineering at the University of Maryland (UMD). Dr. Bensi’s research centers on the application of probabilistic risk assessment concepts and tools as well as statistical/machine learning techniques to problems involving engineered systems exposed to natural hazards. Dr. Bensi focuses primarily on topics related to the probabilistic assessment of natural hazards (e.g., seismic, coastal, inland flooding, precipitation), risk-informed applications, and disaster resilience. Prior to joining the UMD faculty, Dr. Bensi served as an engineer at the United States Nuclear Regulatory Commission where she was heavily involved in the agency's response to the Fukushima Dai-ichi reactor accidents. Dr. Bensi serves as a member of the American Nuclear Society and American Society of Mechanical Engineers (ANS/ASME) Joint Committee on Nuclear Risk Management (JCNRM).
Country: United States of America
Company: University of Maryland
Job Title: Assistant Professor