A Resilience-Based Approach for the Prevention and Mitigation of Domino Effects

Chao Chen (), Genserik Reniers () and Ming Yang ()
Additional contact information
Chao Chen: Delft University of Technology
Genserik Reniers: Delft University of Technology
Ming Yang: Delft University of Technology

Chapter Chapter 7 in Integrating Safety and Security Management to Protect Chemical Industrial Areas from Domino Effects, 2022, pp 155-176 from Springer

Abstract: Abstract 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.

Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ssrchp:978-3-030-88911-1_7

Ordering information: This item can be ordered from
http://www.springer.com/9783030889111

DOI: 10.1007/978-3-030-88911-1_7

Access Statistics for this chapter

More chapters in Springer Series in Reliability Engineering from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().