This paper presents a new computational procedure for the quantification of fault trees containing dependent basic events. The quantification procedure expands the modeling power of fault trees, by allowing such enhancements as the quantification of multiple basic events in a fault tree by connecting them to different variables in a single Bayesian Belief Network (BBN) structure. The procedure was developed to support the analysis of Hybrid Causal Logic models, which are comprised of Event Sequence Diagrams (ESD), Fault Trees, and BBNs, and which are investigated as a way of modeling of causal factors with widespread influences in risk models.

The...