Advances in multi-unit nuclear power plant probabilistic risk assessment. (January 2017)

• Record Type: Journal Article
• Authors: Modarres, Mohammad; Zhou, Taotao; Massoud, Mahmoud
• Is Part Of: Reliability engineering & system safety. Volume 157(2017)
• Page Start: 87
• Page End: 100
• Publication Date: 2017-01
• Subjects: Multi-Unit PRA -- Multi-Module PRA -- PRA -- Dependent Failures -- Multi-Unit Incident Data; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2016.08.005
• Languages: English
• ISSNs: 0951-8320

Abstract

Abstract: The Fukushima Dai-ichi accident highlighted the importance of risks from multiple nuclear reactor unit accidents at a site. As a result, there has been considerable interest in Multi-Unit Probabilistic Risk Assessment (MUPRA) in the past few years. For considerations in nuclear safety, the MUPRA estimates measures of risk and identifies contributors to risk representing the entire site rather than the individual units in the site. In doing so, possible unit-to-unit interactions and dependencies should be modeled and accounted for in the MUPRA. In order to effectively account for these risks, six main commonality classifications—initiating events, shared connections, identical components, proximity dependencies, human dependencies, and organizational dependencies—may be used. This paper examines advances in MUPRA, offers formal definitions of multi-unit site risk measures and proposes quantitative approaches and data to account for unit-to-unit dependencies. Finally, a parametric approach for the multi-unit dependencies has been discussed and a simple example illustrates application of the proposed methodology. Highlights: This paper will discuss the technical aspects of an integrated MUPRA, including consideration of dependencies and assessment of the multi-unit dependency data and models for quantifying such dependencies. The paper also provides discussions on formal definitions and metrics for multi-unit site risks. The parametric methods are used to address multi-unit dependency situations. A conceptual two-unit logic example is used to demonstrate the application of proposed methodology.