Seminar: Advanced Risk Assessment Methods for electrical generation and beyond

Electricité de France (EDF) is the largest company in the world to produce electricity from nuclear power. It operates 58 Pressurized Water Reactors that gives about 70% of its generation capacities. 

EDF also operates large hydraulic fleet. The safety requirement of its nuclear and hydraulic fleet, has allowed EDF to have long-standing experience in using and developing advanced risk analysis tools of complex systems.

In this presentation I will give an overview of the advanced, dynamic methods that are in use at EDF R&D for risk assessment.  I will mention discreet dynamic methods like Boolean Driven Markov Processes that were used to justify technical specifications for extended on-power maintenance time for some of the nuclear power plant components. I will present Distributed Hybrid Stochastic Automata tool PyCATSHOO (a python/C++ library that is distributed under freeware licence) that is used for safety studies of EDF hydraulic fleet and dynamic risk assessment for Sodium Fast Reactors. I will also present an ongoing project between EDF and OSU on coupling of Probabilistic Risk Assessment with the simulation tools using Idaho National Lab developed software RAVEN. We apply all these methods for electrical generation facilities, but they are very well applicable in other engineering domains where standard risk assessment methods like Event Trees and Fault Trees find its limits.