IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v157y2017icp87-100.html
   My bibliography  Save this article

Advances in multi-unit nuclear power plant probabilistic risk assessment

Author

Listed:
  • Modarres, Mohammad
  • Zhou, Taotao
  • Massoud, Mahmoud

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.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reensy:v:157:y:2017:i:c:p:87-100
    DOI: 10.1016/j.ress.2016.08.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832016303611
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2016.08.005?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Schroer, Suzanne & Modarres, Mohammad, 2013. "An event classification schema for evaluating site risk in a multi-unit nuclear power plant probabilistic risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 117(C), pages 40-51.
    2. Trucco, P. & Cagno, E. & Ruggeri, F. & Grande, O., 2008. "A Bayesian Belief Network modelling of organisational factors in risk analysis: A case study in maritime transportation," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 845-856.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fumin Deng & Yanjie Li & Huirong Lin & Jinrui Miao & Xuedong Liang, 2020. "A BWM-TOPSIS Hazardous Waste Inventory Safety Risk Evaluation," IJERPH, MDPI, vol. 17(16), pages 1-18, August.
    2. Justin Pence & Zahra Mohaghegh, 2020. "A Discourse on the Incorporation of Organizational Factors into Probabilistic Risk Assessment: Key Questions and Categorical Review," Risk Analysis, John Wiley & Sons, vol. 40(6), pages 1183-1211, June.
    3. Wu, Bing & Yip, Tsz Leung & Yan, Xinping & Guedes Soares, C., 2022. "Review of techniques and challenges of human and organizational factors analysis in maritime transportation," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    4. Yang, Zhisen & Yang, Zaili & Yin, Jingbo, 2018. "Realising advanced risk-based port state control inspection using data-driven Bayesian networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 38-56.
    5. Morais, Caroline & Estrada-Lugo, Hector Diego & Tolo, Silvia & Jacques, Tiago & Moura, Raphael & Beer, Michael & Patelli, Edoardo, 2022. "Robust data-driven human reliability analysis using credal networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    6. Sajid, Zaman & Khan, Faisal & Zhang, Yan, 2017. "Integration of interpretive structural modelling with Bayesian network for biodiesel performance analysis," Renewable Energy, Elsevier, vol. 107(C), pages 194-203.
    7. Yan-Feng Li & Jinhua Mi & Yu Liu & Yuan-Jian Yang & Hong-Zhong Huang, 2015. "Dynamic fault tree analysis based on continuous-time Bayesian networks under fuzzy numbers," Journal of Risk and Reliability, , vol. 229(6), pages 530-541, December.
    8. Carine Dominguez-Péry & Lakshmi Narasimha Raju Vuddaraju & Isabelle Corbett-Etchevers & Rana Tassabehji, 2021. "Reducing maritime accidents in ships by tackling human error: a bibliometric review and research agenda," Journal of Shipping and Trade, Springer, vol. 6(1), pages 1-32, December.
    9. Martins, Marcelo Ramos & Maturana, Marcos Coelho, 2013. "Application of Bayesian Belief networks to the human reliability analysis of an oil tanker operation focusing on collision accidents," Reliability Engineering and System Safety, Elsevier, vol. 110(C), pages 89-109.
    10. HÃ¥vold, Jon Ivar, 2010. "Safety culture and safety management aboard tankers," Reliability Engineering and System Safety, Elsevier, vol. 95(5), pages 511-519.
    11. Afshin Ghahramani & John McLean Bennett & Aram Ali & Kathryn Reardon-Smith & Glenn Dale & Stirling D. Roberton & Steven Raine, 2021. "A Risk-Based Approach to Mine-Site Rehabilitation: Use of Bayesian Belief Network Modelling to Manage Dispersive Soil and Spoil," Sustainability, MDPI, vol. 13(20), pages 1-23, October.
    12. Qiao, Wanguan, 2021. "Analysis and measurement of multifactor risk in underground coal mine accidents based on coupling theory," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    13. Sotiralis, P. & Ventikos, N.P. & Hamann, R. & Golyshev, P. & Teixeira, A.P., 2016. "Incorporation of human factors into ship collision risk models focusing on human centred design aspects," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 210-227.
    14. Elon Manurung & Effrida Effrida & Andreas James Gondowonto, 2019. "Effect of Financial Performance, Good Corporate Governance and Corporate Size on Corporate Value in Food and Beverages," International Journal of Economics and Financial Issues, Econjournals, vol. 9(6), pages 100-105.
    15. Wang, Shuaian & Yan, Ran & Qu, Xiaobo, 2019. "Development of a non-parametric classifier: Effective identification, algorithm, and applications in port state control for maritime transportation," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 129-157.
    16. Li, Huanhuan & Ren, Xujie & Yang, Zaili, 2023. "Data-driven Bayesian network for risk analysis of global maritime accidents," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    17. Wang, Likun & Yang, Zaili, 2018. "Bayesian network modelling and analysis of accident severity in waterborne transportation: A case study in China," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 277-289.
    18. Yoon, Jae Young & Kim, Dong-San, 2022. "Estimating the adverse effects of inter-unit radioactive release on operator actions at a multi-unit site," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    19. Bing Wu & Huibin Tian & Xinping Yan & C. Guedes Soares, 2020. "A probabilistic consequence estimation model for collision accidents in the downstream of Yangtze River using Bayesian Networks," Journal of Risk and Reliability, , vol. 234(2), pages 422-436, April.
    20. Kujala, P. & Hänninen, M. & Arola, T. & Ylitalo, J., 2009. "Analysis of the marine traffic safety in the Gulf of Finland," Reliability Engineering and System Safety, Elsevier, vol. 94(8), pages 1349-1357.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:157:y:2017:i:c:p:87-100. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.