Modeling and analysis of vapour cloud explosions knock-on events by using a Petri-net approach

Jianfeng Zhou*, Genserik Reniers

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

10 Citations (Scopus)

Abstract

If flammable gas is mixed with air, and the mixture is ignited, it is possible to form a vapor cloud explosion (VCE) which may be very destructive, and easy to trigger a domino effect of accidents because of its large extent of impact. A VCE accident may induce secondary VCE accidents, then tertiary VCE accidents, and so on. This is called the cascading effect of VCE accidents, which requires an understanding of probabilities and propagation patterns to prevent and mitigate the potential damages. In this work, a methodology based on Petri-net is proposed to model the cascading effect of VCE accidents and perform probability analysis, taking the mutual influence between the accidents into account. The deficiency in probability analysis of VCE accidents is discussed. According to the limits of states and their changes which reflect characteristics of VCE propagation, a Petri-net approach is provided for modeling and analysis of VCE cascading effect, and the modeling approach and analysis process of VCE cascading effect are presented. The application and efficacy of the methodology are demonstrated via an example of VCE accidents occurring in a gasoline tank storage area. The results show that the developed methodology can effectively reveal the propagation patterns of VCEs cascading and calculate the respective probabilities of VCE accidents.

Original languageEnglish
Pages (from-to)188-195
Number of pages8
JournalSafety Science
Volume108
DOIs
Publication statusPublished - 2018

Keywords

  • Cascading effect
  • Petri-net
  • Probability analysis
  • Propagation patterns
  • Vapor cloud explosion

Fingerprint

Dive into the research topics of 'Modeling and analysis of vapour cloud explosions knock-on events by using a Petri-net approach'. Together they form a unique fingerprint.

Cite this