A practical methodology for modeling and estimation of common cause failure parameters in multi-unit nuclear PSA model

When assessing the risk related to Nuclear Power Plants in terms of impacts on the population health and on the environment, multi-unit issues should be taken into account. The specific aim of a Probabilistic Safety Assessment at site level is to deal with the dependencies existing between the units on that site. One of important dependency factors is the potential existence of the inter-unit common cause failures (CCF) that could affect identical systems (with or without interconnections) present in each unit. As they are identical this makes them potentially sensitive to inter-unit CCF, in addition to intra-unit CCF that are usually modeled for redundant systems. In this paper, we propose a practical methodology for modelling and estimation of CCF in a multi-unit PSA context. Two methods of modelling multi-unit CCF are firstly presented. A methodology for collecting and analyzing multi-unit CCF data is then proposed. This method is developed by extending the original impact vectors approach to the multi-unit context. Finally, in order to estimate the multi-unit CCF parameters in the case of incomplete data, we propose a CCF simulation method. The application of this method is considered in three different cases and compared with Bayesian and mapping up methods. (C) 2017 Elsevier Ltd. All rights reserved.