Quantification of Dynamic Event Trees – A comparison with event trees for MLOCA scenario

Dynamic event trees (DETs) provide the means to simulate physical system evolutions, the evolution of system states due to stochastic events, and the dynamic interactions between these evolutions. For risk assessment, the framework avoids the need to specify a priori the sequence of stochastic events prior to the plant response simulation and to iterate between the definition of the sequences and simulation of the responses. For nuclear power plants, DETs have been applied to treat scenarios up to core damage as well as post-core damage accident scenarios. The quantification of the frequencies of the sequences leading to the undesired system outcomes, while conceptually straightforward, faces several implementation issues. These include, for instance, the treatment of support system dependencies and of events characterized by a continuous aleatory variable. Some solutions to these issues are proposed and applied in a case study dealing with Medium Break Loss of Coolant Accident (MLOCA) scenarios. Additionally, the results obtained from DET quantification are compared with those estimated with a "classical" event tree model for these scenarios. This comparison provides some case-specific results on the impact of the improved modeling of dynamics on risk estimates. - Highlights: • MLOCA scenarios with multiple types of variabilities were simulated in a DET model. • For quantification, an alternative to coupling fault trees to a DET is presented. • The generated DET sequences are represented one‐to‐one with event and fault trees. • DET quantification is compared to estimates based on bounding success criteria. • Both the estimated MLOCA risk and dominant contributors were impacted.