DAMS: A Model to Assess Domino Effects by Using Agent-Based Modeling and Simulation

Laobing Zhang, Gabriele Landucci, Genserik Reniers*, Nima Khakzad, Jianfeng Zhou

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

17 Citations (Scopus)

Abstract

Historical data analysis shows that escalation accidents, so-called domino effects, have an important role in disastrous accidents in the chemical and process industries. In this study, an agent-based modeling and simulation approach is proposed to study the propagation of domino effects in the chemical and process industries. Different from the analytical or Monte Carlo simulation approaches, which normally study the domino effect at probabilistic network levels, the agent-based modeling technique explains the domino effects from a bottom-up perspective. In this approach, the installations involved in a domino effect are modeled as agents whereas the interactions among the installations (e.g., by means of heat radiation) are modeled via the basic rules of the agents. Application of the developed model to several case studies demonstrates the ability of the model not only in modeling higher-level domino effects and synergistic effects but also in accounting for temporal dependencies. The model can readily be applied to large-scale complicated cases.

Original languageEnglish
Pages (from-to)1585-1600
Number of pages16
JournalRisk Analysis
Volume38
Issue number8
DOIs
Publication statusPublished - 2018

Keywords

  • Agent-based modeling
  • computational experiments
  • domino effect
  • major accident hazard

Fingerprint

Dive into the research topics of 'DAMS: A Model to Assess Domino Effects by Using Agent-Based Modeling and Simulation'. Together they form a unique fingerprint.

Cite this