Historical data analysis shows that escalation accidents, a so-called domino effect, may have an important role in disastrous accidents in the chemical and process industries. In this study, an agent-based modeling and simulation approach is proposed to study the propagation of domino effects in the chemical and process industries. Different to the analytical or Monte Carlo simulation approaches, which normally study the domino effect phenomenon at probabilistic network levels, the agent-based modeling technique explains the domino effects from a bottom-up perspective. In this approach, the installations involved in a domino effect are modeled as agents while the interactions among the installations (e.g., by means of heat radiation) are modeled via the basic rules of the agents. Application of the developed model to several case studies demonstrates the ability of the model not only in modeling higher-level domino effects and synergistic effects but also in accounting for temporal dependencies. The model can easily be applied to large-scale complicated cases.@en

The growing trend of interconnecting two or more chemical process or storage facilities represents a critical safety issue, since an accident can easily escalate from an industrial establishment to the nearby plants resulting in a domino effect. However, common safety analyses often ignore cascading events in chemical tank farms, their complex and transient evolution, and mitigation effects of add-on safety measures. The aim of the present work is to develop a structured approach for the assessment of complex domino events accounting for the influence of safety barriers. The approach is based on the adoption of Agent-based Model and Simulation for the assessment of Domino effect in presence of add-on Protections (DAMS-P). For the first time, the assessment of mitigated cascading events in chemical tank farms is carried out accounting for the transient evolution of multiple scenarios and related synergistic effects, and the effect of safety barriers and their possible time-dependent degradation. A verification of DAMS-P is firstly performed through the comparison against analytic probability evaluation based on event tree analysis and tested through the application of industrial cases. The results obtained constitute a useful support for decision-making and for the identification of critical barriers and their performance evaluation.@en

The propagation of accidents among process units may cause amplification of accident magnitude, resulting in a domino effect chain. Several catastrophic accidents occurred in the process and chemical industry presented these features. Hence, research efforts have been given to the analysis of the domino effects in order to enhance prevention and mitigation strategies. In this work, challenges of analysing domino effects in the chemical industries are discussed, highlighting that quantitative analytic approaches suffer from the complexity on assessing domino effects, especially when dealing with simultaneous accidents propagating among multiple units. Therefore, a bottom-up modelling approach, namely, the agent based modelling and simulation (ABM&S) approach, is introduced for analysing domino effects. Moreover, a prototype model for assessing domino effects in the chemical industries by using agent based modelling and simulation (DAMS) is given and further extensions of the prototype model is also discussed, highlighting the potential benefits.@en