A computer program for evaluating the alpha factor model parameters using the Bayesian operation

Abstract

The assessment of common cause failure (CCF) is necessary for reducing the uncertainty during the process of probabilistic safety assessment. A basic unavailability assessment method is an approach for the quantitative analysis of CCF modeling using Bayesian probability, in which the estimation of parameters is more accurate by combining the failure information from system, component and cause level. This study describes the CCF evaluation program which has been developed for assessing the α-factor common cause failure parameters. Examples are presented to demonstrate the calculation process and necessary databases are presented. As a result, the posterior distributions for α-factors model parameter are obtained using the conjugate family distributions as well as general distributions for conducting a numerical estimation. Due to the fact that CCF is one of the significant factors to affect both core damage frequency and large early release frequency, the appropriate evaluation for the relevant parameters is essential, though there are rare the CCF data. In the previous study, the Multiple Greek Letter model (MGL) had been used for modeling the common cause failures in the OPR 1000 reactors. In the future modeling for the reactors, the α-factors approach might be employed for simulating the common cause failures as well as it will be quantified using the computer program developed by the C# language. The main operation to quantify the α-factors parameters is Bayesian which combines the prior distribution and the likelihood function to produce the posterior distribution. It is expected that this program might contribute to enhancing the quality of probabilistic safety assessment and to reducing common cause failure uncertainty.