An approach to address probabilistic assumptions on the availability of safety systems for deterministic safety analysis

[EN] There is an attempt nowadays to provide a more comprehensive and realistic safety assessment of design and operation of Nuclear Power Plants. In this context, innovative approaches are being proposed for safety assessment of nuclear power plants design including both design basis conditions and design extension conditions. An area of research aims at developing methods for combining insights from probabilistic and deterministic safety analyses in Option 4, also called realistic approach, from the International Atomic Energy Agency specific safety guide. The development of Option 4 or realistic approach involves the adoption of best estimate computer codes, best estimate assumptions on systems availability and best estimate of initial and boundary conditions for the safety analysis. This paper focusses on providing the fundamentals and practical implementation of an approach to integrate PSA-based probabilistic models and data, which incorporate best estimate assumptions on the availability of safety systems, into Option 4. It is presented a practical approach to identify relevant, i.e. most probable, configurations of safety systems and to assess the associated occurrence probability of each configuration using PSA models and data of a NPP, which is based on the use of a Pure Monte Carlo method. An example of application is provided to demonstrate how this approach performs. The case study focusses on an accident scenario corresponding to the initiating event Loss Of Feed Water (LOFW) for a typical three-loops Pressurized Water Reactor (PWR) NPP. Authors are grateful to the Spanish CSN (Consejo de Seguridad Nuclear) for the financial support of this research (Research Project SIN/4078/2013/640; MASA Project). Martorell Alsina, SS.; Martorell-Aygues, P.; Martón Lluch, I.; Sánchez Galdón, AI.; Carlos Alberola, S. (2017). An approach to address probabilistic assumptions on the availability of safety systems for deterministic safety analysis. Reliability Engineering & System Safety. 160:136-150. https://doi.org/10.1016/j.ress.2016.12.009