Abstract
Abstract
Uncertainties arising from different sources have to be considered for the quantification of common cause failures (CCFs). At GRS a CCF model (coupling model) has been developed for the estimation of CCF probabilities. An essential feature of the coupling model is the consideration of these uncertainties by using Bayesian estimation methods. Experiences from applying the coupling model to CCF event data over several years and analyzing the results in detail has led to improvements in the application of the model. In this paper the improved methodology of the coupling model is presented. Special emphasis is given to the description of the sources of uncertainties which are considered in the coupling model and the mathematical methodology, how these uncertainties are represented and propagated through the model. In closing topics of future improvements of the coupling models are discussed.