Real-time risk analysis of safety systems

Abstract

Methods for plant-specific, real-time, risk assessment are presented using Bayesian analysis with copulas. These are used to develop: (i) a forecasting analyzer that predicts the frequencies of occurrence of abnormal events, (ii) a reliability analyzer that predicts the failure probabilities of safety systems involving equipment and human actions, and (iii) an accident closeness analyzer that predicts the fuzzy memberships to various critical zones, indicating the proximity of a current plant state to a failure or disaster, through the use of accident precursor data. These methods, which involve repetitive risk analysis after abnormal events occur, are especially beneficial for operations involving complex nonlinearities and multi-component interactions, helping to achieve inherently safer operations. Furthermore, these methods demonstrate the importance of using plant-specific estimates of failure probabilities rather than generic values in the risk assessment of chemical plants. In this analysis, the propagations of abnormal events through the safety systems are modeled in real-time using SIMULINK and ASPEN DYNAMICS. The analysis methods are illustrated for a continuous ethyl benzene process.