An accident within a chemical plant may trigger escalation effects, leading to a catastrophic degradation of operating performance. Due to possible severe consequences of domino effects, safety and security measures are needed to prevent and mitigate domino effects in chemical industrial areas. However, safety and security measures may be insufficient for tackling unpredictable and unpreventable domino effects induced by multi-target attacks or natural disasters. Therefore, This chapter develops a resilient-based approach for domino effect management in the process and chemical industry (Chen et al. in Reliab Eng Syst Saf, 2021; Chen in A dynamic and integrated approach for modeling and managing domino-effects. Delft University of Technology, 2021). A dynamic stochastic methodology is developed to quantify the resilience of chemical plants. In this methodology, a “resilience evolution scenario” consists of four stages: disruption, escalation, adaptation, and restoration. A resilient chemical plant depends on resistant capability, mitigation capability, adaptation capability, and restoration capability. The uncertainties in the disruption and escalation stages are modeled by the dynamic Monte Carlo method. Possible resilience scenarios are obtained by sampling random data. Then, the resilience of a chemical plant can be determined based on the resilience scenarios.
|Title of host publication||Integrating Safety and Security Management to Protect Chemical Industrial Areas from Domino Effects|
|Number of pages||22|
|Publication status||Published - 2022|
|Name||Springer Series in Reliability Engineering|
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