Quantitative resilience assessment of chemical process systems using functional resonance analysis method and Dynamic Bayesian network

The emergent hazards of chemical process systems cannot be wholly identified and are highly uncertain due to the complicated technical-human-organizational interactions. Under unpredictable circumstances, resilience becomes an essential property a system that helps it better adapt disruptions restore from surprising damages. assessment needs enhanced identify accident's root causes on level interactions, development specific attributes withstand or recover disruptions. outcomes valuable potential design operational improvements ensure complex functionality safety. current study integrates Functional Resonance Analysis Method dynamic Bayesian Network for quantitative assessment. method is demonstrated through two-phase separator acid gas sweetening unit. Aspen Hysys simulator applied estimate failure probabilities needed in model. provides useful tool rigorous analysis