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The propagation of fire in chemical plants â\u80\u93 also known as fire domino effects - largely depends on the performance of add-on passive and active protection systems such as sprinkler systems, water deluge systems, emergency shut down and emergency blow down systems, fireproofing, and emergency response. Although such safety barriers are widely employed to prevent or delay the initiation or escalation of fire domino effects, their inclusion in the modeling and risk assessment of fire domino effects has hardly been taken into account. In the present study, the dynamic evolution of fire protection systems has been investigated qualitatively using event tree analysis. To quantify the temporal changes and their impact on the escalation of fire domino effects, a dynamic Bayesian network methodology has been developed. The application of the methodology has been demonstrated using an illustrative case study, considering a variety of fire scenarios, target installations, and firefighting systems

In the present study, we have introduced a methodology based on graph theory and multicriteria decision analysis for cost‐effective fire protection of chemical plants subject to fire‐induced domino effects. By modeling domino effects in chemical plants as a directed graph, the graph centrality measures such as out‐closeness and betweenness scores can be used to identify the installations playing a key role in initiating and propagating potential domino effects. It is demonstrated that active fire protection of installations with the highest out‐closeness score and passive fire protection of installations with the highest betweenness score are the most effective strategies for reducing the vulnerability of chemical plants to fire‐induced domino effects. We have employed a dynamic graph analysis to investigate the impact of both the availability and the degradation of fire protection measures over time on the vulnerability of chemical plants. The results obtained from the graph analysis can further be prioritized using multicriteria decision analysis techniques such as the method of reference point to find the most cost‐effective fire protection strategy.

This chapter describes a security risk assessment and protection methodology that was developed

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