Multi-unit Level 2 probabilistic safety assessment: Approaches and their application to a six-unit nuclear power plant site

Cho, Jaehyun; Han, Sang Hoon; Kim, Dong-San; Lim, Ho-Gon

doi:10.1016/j.net.2018.04.005

Cited by 28 publications

(1 citation statement)

References 13 publications

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“…The initial MUPSA studies [2,3] were performed due to the gradually increasing concern regarding multi-unit nuclear accidents. After the Fukushima accident in 2011, many studies and reports on MUPSA [4][5][6][7][8][9][10][11][12][13][14][15][16] were published. In 2019, the International Atomic Energy Agency (IAEA) published a technical report [17] as part of a safety report series that provides comprehensive guidance for performing MUPSA.…”

Section: Introduction 1multi-unit Probabilistic Safety Assessmentsmentioning

confidence: 99%

A Method to Avoid Underestimated Risks in Seismic SUPSA and MUPSA for Nuclear Power Plants Caused by Partitioning Events

Jung

2021

Energies

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Seismic probabilistic safety assessment (PSA) models for nuclear power plants (NPPs) have many non-rare events whose failure probabilities are proportional to the seismic ground acceleration. It has been widely accepted that minimal cut sets (MCSs) that are calculated from the seismic PSA fault tree should be converted into exact solutions, such as binary decision diagrams (BDDs), and that the accurate seismic core damage frequency (CDF) should be calculated from the exact solutions. If the seismic CDF is calculated directly from seismic MCSs, it is drastically overestimated. Seismic single-unit PSA (SUPSA) models have random failures of alternating operation systems that are combined with seismic failures of components and structures. Similarly, seismic multi-unit PSA (MUPSA) models have failures of NPPs that undergo alternating operations between full power and low power and shutdown (LPSD). Their failures for alternating operations are modeled using fraction or partitioning events in seismic SUPSA and MUPSA fault trees. Since partitioning events for one system are mutually exclusive, their combinations should be excluded in exact solutions. However, it is difficult to eliminate the combinations of mutually exclusive events without modifying PSA tools for generating MCSs from a fault tree and converting MCSs into exact solutions. If the combinations of mutually exclusive events are not deleted, seismic CDF is underestimated. To avoid CDF underestimation in seismic SUPSAs and MUPSAs, this paper introduces a process of converting partitioning events into conditional events, and conditional events are then inserted explicitly inside a fault tree. With this conversion, accurate CDF can be calculated without modifying PSA tools. That is, this process does not require any other special operations or tools. It is strongly recommended that the method in this paper be employed for avoiding CDF underestimation in seismic SUPSAs and MUPSAs.

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Section: Introduction 1multi-unit Probabilistic Safety Assessmentsmentioning

confidence: 99%

A Method to Avoid Underestimated Risks in Seismic SUPSA and MUPSA for Nuclear Power Plants Caused by Partitioning Events

Jung

2021

Energies

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Evaluating Risks of Multi-unit Nuclear Sites: Insights and Considerations

Alrammah

2023

Arab J Sci Eng

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Seismic stability reliability assessment of nuclear power plant’s bank revetment considering unreinforced and reinforced situations

Zhou

Pang

2020

Annals of Nuclear Energy

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Multi-unit Level 2 probabilistic safety assessment: Approaches and their application to a six-unit nuclear power plant site

Cited by 28 publications

References 13 publications

A Method to Avoid Underestimated Risks in Seismic SUPSA and MUPSA for Nuclear Power Plants Caused by Partitioning Events

A Method to Avoid Underestimated Risks in Seismic SUPSA and MUPSA for Nuclear Power Plants Caused by Partitioning Events

Evaluating Risks of Multi-unit Nuclear Sites: Insights and Considerations

Seismic stability reliability assessment of nuclear power plant’s bank revetment considering unreinforced and reinforced situations

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