A dynamic event tree informed approach to probabilistic accident sequence modeling: Dynamics and variabilities in medium LOCA. (October 2015)

• Record Type: Journal Article
• Authors: Karanki, Durga Rao; Kim, Tae-Wan; Dang, Vinh N.
• Is Part Of: Reliability engineering & system safety. Volume 142(2015:Oct.)
• Page Start: 78
• Page End: 91
• Publication Date: 2015-10
• Subjects: Dynamic event tree analysis -- Success criteria -- Accident dynamic simulator -- MLOCA; 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.2015.04.011
• Languages: English
• ISSNs: 0951-8320

Abstract

Abstract: In Probability Safety Assessments, accident scenario dynamics are addressed in the accident sequence analysis task. In an analyst-driven, iterative process, assumptions are made about equipment responses and operator actions and simulations of the scenario evolution are performed. To calculate how scenario dynamics and stochastic variabilities may affect the results of this process in terms of estimated risk, this work applies Dynamic Event Trees (DETs) to more comprehensively examine the accident scenario space. Alternative event tree models are developed and the core damage frequency is quantified to reveal the effects of different delineations of the sequences and of the bounding assumptions underlying success criteria. The results from a case study on Medium-break Loss of Coolant Accident scenarios in a Pressurized Water Reactor are presented, considering the break size, available injection trains, and the timing of rapid cooldown and the switchover to recirculation. The results show not only that estimated risk can be very sensitive to the numerous assumptions made in current accident sequence analysis but also that bounding assumptions do not always result in conservative risk estimates, thereby confirming the benefits that DETs provide in terms of characterizing scenario dynamics. Highlights: The overall most challenging MLOCA break is at neither extreme of the size range. Selecting the limiting break size influenced estimated risk strongly (6″ vs 7″). Success criteria can be defined more realistically by splitting the MLOCA range. A more demanding success criterion for one top event can reduce overall risk. Non-limiting success branches may lead to more demanding subsequent success criteria.