Severe accident scenario uncertainty analysis using the dynamic event tree method

Zheng, X. ; Tamaki, Hitoshi ; Ishikawa, Jun ; Sugiyama, Tomoyuki ; Maruyama, Yu 

Several types of uncertainties exist during the simulation of a severe accident. These may result from incomplete knowledge about the plant systems, accident progression and oversimplified numerical models. Among them, parameter uncertainty can be treated via Monte-Carlo-sampling-based methods. To tackle the severe accident scenario uncertainty, we must resort to advanced dynamic probabilistic risk assessment (PRA) methods. In this paper, authors reviewed the previous dynamic PRA methods and tools, and then performed a preliminary scenario uncertainty analysis, by using an integrated SA code (THALES2) and a scenario generator (RAPID, risk assessment with plant interactive dynamics), both being developed at JAEA. THALES2 is a fast-running severe accident code for the simulation of severe accident progression and source term in light water reactors. Typical scenarios of station-blackout (SBO)-initiated accidents in boiling water reactors are generated and simulated. The dynamic event tree (DET) method is applied to consider the stochastic uncertainties during the scenario progression. Major groups of SBO sequences with the similar accident characteristics can be found. To provide a reference value for risk, a conditional core damage frequency is calculated accordingly. This is a preliminary analysis for severe accident scenario uncertainty quantification at JAEA, and further DPRA researches are in progress.