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An integrated probabilistic risk assessment methodology for maritime transportation of spent nuclear fuel based on event tree and hydrodynamic model

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  • Tao, Longlong
  • Chen, Liwei
  • Ge, Daochuan
  • Yao, Yuantao
  • Ruan, Fang
  • Wu, Jie
  • Yu, Jie

Abstract

Spent nuclear fuel maritime transportation (SNFMT) accident may cause radiation hazards to personnel, vessels, and the ocean environment. Current risk assessment methods of SNFMT lack full consideration and quantification of the risk indicators. In this work, an integrated probabilistic risk assessment (IPRA) methodology incorporating multiple risk factors-based accident probability model and public dose-based radiological consequence model quantitatively is proposed for SNFMT. First, from the sociotechnical-environmental risk perspective, the SMCETC (Ship, Management, Crew, Environment, Tank, Channel) comprehensive risk indicators are identified for ET-FT modeling. Second, considering the effects of continuous emissions, water depth, tidal cycle, and radioactive decay, a shallow water equations-based hydrodynamic model is established to simulate the radionuclide concentration in coastal water. Third, the ET-FT model-based accident frequency and the radionuclide concentration-based population radiation consequence are integrated, and subsequently the public radioactive risks are obtained. Finally, a case study is presented to demonstrate the feasibility and value of the proposed method. The time-related public radioactive risks were quantified and 28 highly safety importance risk factors were found and ranked. The proposed IPRA methodology integrates deterministic and probabilistic modeling perspectives, and provides a comprehensive risk assessment tool for SNFMT.

Suggested Citation

  • Tao, Longlong & Chen, Liwei & Ge, Daochuan & Yao, Yuantao & Ruan, Fang & Wu, Jie & Yu, Jie, 2022. "An integrated probabilistic risk assessment methodology for maritime transportation of spent nuclear fuel based on event tree and hydrodynamic model," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
  • Handle: RePEc:eee:reensy:v:227:y:2022:i:c:s0951832022003507
    DOI: 10.1016/j.ress.2022.108726
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    1. Zio, Enrico & Mustafayeva, Maryam & Montanaro, Andrea, 2022. "A Bayesian Belief Network Model for the Risk Assessment and Management of Premature Screen-Out during Hydraulic Fracturing," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    2. Hu, Yunwei & Parhizkar, Tarannom & Mosleh, Ali, 2022. "Guided simulation for dynamic probabilistic risk assessment of complex systems: Concept, method, and application," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    3. 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.
    4. Mohaghegh, Zahra & Kazemi, Reza & Mosleh, Ali, 2009. "Incorporating organizational factors into Probabilistic Risk Assessment (PRA) of complex socio-technical systems: A hybrid technique formalization," Reliability Engineering and System Safety, Elsevier, vol. 94(5), pages 1000-1018.
    5. Christian, Robby & Kang, Hyun Gook, 2017. "Probabilistic risk assessment on maritime spent nuclear fuel transportation—Part I: Transport cask damage probability," Reliability Engineering and System Safety, Elsevier, vol. 164(C), pages 124-135.
    6. Yildiz, Serdar & Uğurlu, Özkan & Wang, Jin & Loughney, Sean, 2021. "Application of the HFACS-PV approach for identification of human and organizational factors (HOFs) influencing marine accidents," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    7. Johnson, Caroline A. & Flage, Roger & Guikema, Seth D., 2021. "Feasibility study of PRA for critical infrastructure risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    8. Tao, Longlong & Wu, Jie & Ge, Daochuan & Chen, Liwei & Sun, Ming, 2022. "Risk-informed based comprehensive path-planning method for radioactive materials road transportation," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    9. Worrell, Clarence & Luangkesorn, Louis & Haight, Joel & Congedo, Thomas, 2019. "Machine learning of fire hazard model simulations for use in probabilistic safety assessments at nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 128-142.
    10. Ung, S.T., 2021. "Navigation Risk estimation using a modified Bayesian Network modeling-a case study in Taiwan," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    11. Christian, Robby & Kang, Hyun Gook, 2017. "Probabilistic risk assessment on maritime spent nuclear fuel transportation (Part II: Ship collision probability)," Reliability Engineering and System Safety, Elsevier, vol. 164(C), pages 136-149.
    12. Kayisoglu, Gizem & Gunes, Bunyamin & Besikci, Elif Bal, 2022. "SLIM based methodology for human error probability calculation of bunker spills in maritime operations," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    13. Khan, Bushra & Khan, Faisal & Veitch, Brian & Yang, Ming, 2018. "An operational risk analysis tool to analyze marine transportation in Arctic waters," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 485-502.
    14. Rocchetta, R. & Li, Y.F. & Zio, E., 2015. "Risk assessment and risk-cost optimization of distributed power generation systems considering extreme weather conditions," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 47-61.
    15. Zhang, D. & Yan, X.P. & Yang, Z.L. & Wall, A. & Wang, J., 2013. "Incorporation of formal safety assessment and Bayesian network in navigational risk estimation of the Yangtze River," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 93-105.
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