Using higher-level failure data in fault tree quantification

Abstract This paper presents a Bayesian method which can simultaneously combine basic event and statistically independent higher event-level failure data in fault tree quantification. Such higher-level data could correspond to train, subsystem or system failure events. In fact, because highest-level data are usually available for existing facilities, the method presented here allows such data to be propagated to lower levels. The method has two stages: (1) a top-down propagation scheme which allocates the higher event-level information to the basic events, at a cost of making them dependent; and (2) a scheme for sampling the probabilities of the dependent basic events. A simple example illustrates the performance of the method.