Quantitative risk assessment using hybrid causal logic model

Abstract

This paper presents a hybrid causal logic model, which integrates the traditional Quantitative Risk Assessment (QRA) models with Bayesian Network (BN) incorporating human and organizational factors. The multi-phase model allows different risk assessment methods to be applied to different parts. In the first phase, Event Tree (ET) defines the base scenarios for the source of risk issues. In the second phase, Fault Tree (FT) is used to model the factors how to contributing to the final failures. BN comprise the third phase, which extends the causal chain of basic events to potential human and organizational roots and provide a more precise quantitative links between the event nodes. The new model integrates the power of typical QRA for modeling deterministic causal paths with the flexibility of BN for modeling non-deterministic cause-effect relationships. The integration algorithm is demonstrated on an offshore fire case study. It clearly shows the new model is more flexible and useful than traditional QRA models.