Domino Effect Analysis, Assessment and Prevention in Process Industries

Wu Jun (), Yang Hui () and Cheng Yuan ()
Additional contact information
Wu Jun: School of Economics and Management, Beijing University of Chemical Technology, Beijing100029, China
Yang Hui: School of Economics and Management, Beijing University of Chemical Technology, Beijing100029, China
Cheng Yuan: Department of Automation, Tsinghua University, Beijing100084, China

Journal of Systems Science and Information, 2015, vol. 3, issue 6, 481-498

Abstract: Domino effect is a fairly common phenomenon in process industry accidents, which makes many process industry accidents serious and the consequent losses enhanced. Domino effect of the major accidents in chemical cluster is emphasized. Many researchers have studied domino effect in chemical clusters from different perspectives. In the review, we summarize the research from three aspects: The statistical analysis of domino accidents in chemical process industry, the evaluation of domino accidents and the prevention of domino accidents in chemical clusters by game theory. From the analysis, we can find the characteristic of domino accidents such as the time and the location, the origin and causes of domino accidents. The methods of assessing domino effects such as quantitative risk assessment (QRA), Bayesian networks (BN) and Monte Carlo simulation (MCS) are analyzed. The prevention of domino accidents in chemical clusters using game theory is seldom, and there is still much space for improvement in enterprises’ efforts to prevent risk of domino accidents.

Keywords: domino effect; quantitative assessment; game theory; chemical cluster (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/JSSI-2015-0481 (text/html)

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:bpj:jossai:v:3:y:2015:i:6:p:481-498:n:1

DOI: 10.1515/JSSI-2015-0481

Access Statistics for this article

Journal of Systems Science and Information is currently edited by Shouyang Wang

More articles in Journal of Systems Science and Information from De Gruyter
Bibliographic data for series maintained by Peter Golla ().