TY - CHAP
T1 - A Resilience-Based Approach for the Prevention and Mitigation of Domino Effects
AU - Chen, Chao
AU - Reniers, Genserik
AU - Yang, Ming
N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85118454374&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-88911-1_7
DO - 10.1007/978-3-030-88911-1_7
M3 - Chapter
AN - SCOPUS:85118454374
T3 - Springer Series in Reliability Engineering
SP - 155
EP - 176
BT - Integrating Safety and Security Management to Protect Chemical Industrial Areas from Domino Effects
PB - Springer
ER -