Uncertainties and their treatment in the quantitative risk assessment of domino effects: Classification and review

Yuanyuan Xu*, Genserik Reniers, Ming Yang, Shuaiqi Yuan, Chao Chen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

14 Citations (Scopus)
115 Downloads (Pure)

Abstract

Domino accidents are typical low-frequency and high-consequence events in chemical process industries. Applying quantitative risk assessment (QRA) in domino accident assessment is challenging due to the uncertainties in the escalation process. Meanwhile, the outcomes of QRA are subject to a certain degree of unreliability due to the inappropriate representation of uncertainty. This paper reviews the literature in the field of QRA of domino accidents that may happen in the chemical process industries. Firstly, the sources of uncertainty in risk assessment of domino effects are identified and categorized based on a fundamental structure of uncertainty and a QRA framework. Furthermore, the current methodologies and approaches applied for handling various uncertainties (input uncertainty, model parameter uncertainty, and model structure uncertainty) in the QRA related to domino effects are reviewed. Based on the literature review results, current challenges with respect to uncertainty handling in QRA of domino accidents are discussed, and recommendations for future research are given before the conclusions are presented. This study helps researchers to get insights into the interface between uncertainty fundamentals and the QRA framework and the current status of uncertainty handling in the QRA of domino effects. Furthermore, this study promotes the development of new approaches for handling uncertainty in domino accident analysis.
Original languageEnglish
Pages (from-to)971-985
Number of pages15
JournalProcess Safety and Environmental Protection
Volume172
DOIs
Publication statusPublished - 2023

Keywords

  • Chemical process industry
  • Domino effects
  • Quantitative risk assessment
  • Uncertainty fundamentals
  • Uncertainty handling

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