Resilience-based optimal firefighting to prevent domino effects in process plants

Salvatore Cincotta, N. Khakzad, Valerio Cozzani, Genserik Reniers

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)
1 Downloads (Pure)

Abstract

Domino effects triggered by fire can cause extremely severe damages to the chemical and process plants. In the need of a more effective prevention of fire domino effects, the present study focuses on firefighting which has received less attention compared to passive and active fire protection systems. Considering both the vulnerability and recoverability phases during fire domino effects, we have introduced a methodology for optimal identification of firefighting strategies so as to increase the resiliency of process plants in dealing with fire escalation scenarios. The area above the resilience curve (AARC), which is equal to the accumulation of loss of resilience over time, was considered as the metric to identify the optimal firefighting strategies. In other words, the strategy leading to the lowest AARC can be selected as the optimal strategy from a resiliency perspective
Original languageEnglish
Pages (from-to)82-89
Number of pages8
JournalJournal of Loss Prevention in the Process Industries
Volume58
DOIs
Publication statusPublished - 2019

Keywords

  • Bayesian network
  • Domino effect
  • Firefighting
  • Optimization
  • Resilience

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