Coupling Model: A Common-Cause-Failure Model with Consideration of Interpretation Uncertainties

The quantification of common-cause failures (CCFs) is often connected with uncertainties in how to interpret observed CCF events and with how far they are applicable to the specific group of components in question. A method has been developed that allows consideration of these kinds of uncertainties on the basis of a modification of the Binomial-Failure-Rate model. The quantification of interpretation uncertainties by means of interpretation alternatives is discussed as well as their effects on the estimation of the coupling parameter of the underlying CCF model. The estimation of the coupling parameter under consideration of the aforementioned uncertainties is performed by a Bayesian approach. To facilitate the specification of interpretation uncertainties, a default proposal of the interpretation vector is automatically generated on the basis of component fault states gained by expert judgment. Modification of the default vector is possible depending on engineering judgment of technical or operational differences between the observed and the target group of components.