Ricerc@Sapienza

In the wide framework of nuclear power plants, the dynamic probabilistic risk assessment could answer the time dependence deficiency of the event tree and fault tree analysis. The basic event tree approach relies on expert's pre-constructed accident sequences, without exploring the real nature of an accident scenario in which the time dependence on the occurrence of a selected number of events could strongly affect the accident sequence. Conversely, effects of events' timing can be studied adopting a Dynamic Event Tree approach.
The development of a Dynamic Event Tree methodology requires the integration between a system code capable of replicating an accident scenario, and a logic-driver code able to generate the event tree sequence, triggering plant safety systems and managing other relevant events throughout the simulation.
The project aims to develop a tool for the integration and communication between a system code (MELCOR) and a logic-driver code (RAVEN) to perform a dynamic probabilistic risk assessment of nuclear and other industrial plants. The tool will be developed using Python as programming language because of its versatility in transferring and handling huge amounts of data.
RAVEN (Risk Analysis Virtual Environment) is an open-source software tool developed at the Idaho National Laboratory (INL) to act as a control logic driver and post-processing tool for different applications. MELCOR is a fully integrated severe accident code that simulates thermal-hydraulic transients and self-consistently accounting for aerosol transport in industrial facilities and reactor cooling systems.
The developed tool will be used to perform dynamic event tree studies during accident transients in fission and fusion reactors. The new coupling between these two codes will provide a wide range of nuclear power plant risk assessment analyses and could establish a best practice.