Systematic approach and mathematical development for conditional core damage probabilities under station blackout of a nuclear power plant. (January 2022)

• Record Type: Journal Article
• Authors: Kim, Man Cheol
• Is Part Of: Reliability engineering & system safety. Volume 217(2022)
• Publication Date: 2022-01
• Subjects: Probabilistic safety assessment -- Station blackout -- Loss of offsite power -- Emergency diesel generator -- Mathematical development -- Monte Carlo simulation; 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.2021.107969
• Languages: English
• ISSNs: 0951-8320

Abstract

Highlights: Station blackout (SBO) risk of a nuclear power plant is more accurately calculated. A systematic approach for identifying SBO sequences is presented. Mathematical formulas for conditional core damage probabilities are derived. Mathematical formulas are verified with Monte Carlo simulation. A significant term for SBO risk that has not been considered previously is included. Abstract: Station blackout (SBO), a total loss of alternating current (AC) power, is considered to contribute significantly to nuclear power plant risk. The analysis of SBO risk is complicated due to time-dependent interactions among events. Simplifying assumptions that are currently used extensively in probabilistic safety assessment may lead to an overly conservative estimation of SBO risk, which may distort the overall plant risk profile and the associated accident management strategy. To calculate more accurate SBO risk, this study first identified SBO sequences and the associated time-dependent interactions by differentiating fail-to-start and fail-to-run failures of alternative AC power source and turbine-driven pumps. Mathematical formulas were developed to calculate the conditional core damage probabilities corresponding to the identified SBO sequences. These mathematical formulas were verified via a Monte Carlo simulation. This study is expected to contribute to the development of an integrated framework for SBO risk analysis that includes all possible SBO sequences, related events, and their time-dependent interactions.