An integrated probabilistic risk assessment methodology for maritime transportation of spent nuclear fuel based on event tree and hydrodynamic model. (November 2022) - Tao, Longlong; Chen, Liwei; Ge, Daochuan; Yao, Yuantao; Ruan, Fang; Wu, Jie; Yu, Jie
Highlights: A novel IPRA methodology for spent fuel maritime transportation risk is proposed. Multiple risk factors-based accident frequency analysis method is presented. Shallow water equations-based consequence evaluation model is established. Public radioactive risks are quantified and critical risk factors are found. 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.