Dynamic risk analysis using bow-tie approach

Accident probability estimation is a common and central step to all quantitative risk assessment methods. Among many techniques available, bow-tie model (BT) is very popular because it represent the accident scenario altogether including causes and consequences. However, it suffers a static structure limiting its application in real-time monitoring and probability updating which are key factors in dynamic risk analysis. The present work is focused on using BT approach in a dynamic environment in which the occurrence probability of accident consequences changes. In this method, on one hand, failure probability of primary events of BT, leading to the top event, are developed using physical reliability models, and constantly revised as physical parameters (e.g., pressure, velocity, dimension, etc) change. And, on the other hand, the failure probability of safety barriers of the BT are periodically updated using Bayes’ theorem as new information becomes available over time. Finally, the resulting, updated BT is used to estimate the posterior probability of the consequences which in turn results in an updated risk profile.

► A methodology is proposed to make bow-tie method adapted for dynamic risk analysis.
► Physical reliability models are used to revise the top event.
► Bayes’ theorem is used to update the probability of safety barriers.
► The number of accidents in sequential time intervals is used to form likelihood function.
► The risk profile is updated for varying physical parameters and for different times.