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Precursors and startling lessons: Statistical analysis of 1250 events with safety significance from the civil nuclear sector

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  • Ayoub, Ali
  • Stankovski, Andrej
  • Kröger, Wolfgang
  • Sornette, Didier

Abstract

We analyze the ETH Zurich open curated database of 1250 worldwide nuclear events focused on safety significance with potentials for precursors, presented in the companion paper. We find that major accidents always trigger a wave of “reactive†reporting as well as changes in regulatory or corporate management that last 5 to 6 years, mostly due to increased alertness, improved transparency, uncovering latent design errors, and heightened public pressure. The leading causes for multi-unit events are found to be external triggers and design issues, confirming the need to adapt PSAs to cover multi-unit events accordingly. Common-cause failures (CCF) are found to occur fairly frequently, at different levels, and can significantly erode the safety of the plant. From the lessons learned from this analysis, we suggest that frequent review of components design and operating procedures, employing different teams for testing and maintenance activities on redundant trains, and sharing operational experience between plants of similar designs, are some of the steps that should be taken in order to limit future occurrences of CCFs and beyond that further improve plant safety. We identify some quantitative signs of aging for plants after the age of 25. Our findings stress the need for larger recording, reliance, and sharing of operational data to support learning from experience and avoid reoccurrence of accidents and events.

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  • Ayoub, Ali & Stankovski, Andrej & Kröger, Wolfgang & Sornette, Didier, 2021. "Precursors and startling lessons: Statistical analysis of 1250 events with safety significance from the civil nuclear sector," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
  • Handle: RePEc:eee:reensy:v:214:y:2021:i:c:s0951832021003410
    DOI: 10.1016/j.ress.2021.107820
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    References listed on IDEAS

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    1. Zhang, Xiaoge & Mahadevan, Sankaran, 2021. "Bayesian network modeling of accident investigation reports for aviation safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    2. Ayoub, Ali & Stankovski, Andrej & Kröger, Wolfgang & Sornette, Didier, 2021. "The ETH Zurich curated nuclear events database: Layout, event classification, and analysis of contributing factors," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    3. Modarres, Mohammad & Zhou, Taotao & Massoud, Mahmoud, 2017. "Advances in multi-unit nuclear power plant probabilistic risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 87-100.
    4. Spencer Wheatley & Benjamin Sovacool & Didier Sornette, 2017. "Of Disasters and Dragon Kings: A Statistical Analysis of Nuclear Power Incidents and Accidents," Risk Analysis, John Wiley & Sons, vol. 37(1), pages 99-115, January.
    5. Khakzad, Nima & Khan, Faisal & Paltrinieri, Nicola, 2014. "On the application of near accident data to risk analysis of major accidents," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 116-125.
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    Cited by:

    1. Li, Xin & Chen, Chao & Hong, Yi-du & Yang, Fu-qiang, 2023. "Exploring hazardous chemical explosion accidents with association rules and Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    2. Bauranov, Aleksandar & Rakas, Jasenka, 2024. "Bayesian network model of aviation safety: Impact of new communication technologies on mid-air collisions," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    3. Ayoub, Ali & Stankovski, Andrej & Kröger, Wolfgang & Sornette, Didier, 2021. "The ETH Zurich curated nuclear events database: Layout, event classification, and analysis of contributing factors," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    4. Al-Douri, Ahmad & Levine, Camille S. & Groth, Katrina M., 2023. "Identifying human failure events (HFEs) for external hazard probabilistic risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    5. Liu, Jiaxin & Yu, Deping & Yang, Taibo & Liu, Caixue & Wang, Guangjin & Liu, Xiaoming, 2023. "Discovering the causes for the change of the vibration characteristics of the core support barrel in PWR nuclear power plants: A combined investigation based on ex-core neutron noise analysis and nume," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    6. Martínez-Galán Fernández, Pablo & Guillén López, Antonio J. & Márquez, Adolfo Crespo & Gomez Fernández, Juan Fco. & Marcos, Jose Antonio, 2022. "Dynamic Risk Assessment for CBM-based adaptation of maintenance planning," Reliability Engineering and System Safety, Elsevier, vol. 223(C).

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