Using graph theory to analyze the vulnerability of process plants in the context of cascading effects

被引:105
作者
Khakzad, Nima [1 ]
Reniers, Genserik [2 ,3 ,4 ]
机构
[1] Mem Univ Newfoundland, SREG, St John, NF A1B 3X5, Canada
[2] Delft Univ Technol, Fac Technol Policy & Management, Safety & Secur Sci Grp S3 G, NL-2628 BX Delft, Netherlands
[3] Univ Antwerp, Fac Appl Econ, Antwerp Res Grp Safety & Secur ARGoSS, B-2000 Antwerp, Belgium
[4] KULeuven, Res Grp CEDON, B-1000 Brussels, Belgium
关键词
Cascading effect; Process plant; Vulnerability analysis; Graph metrics; Bayesian network; DOMINO EFFECT ANALYSIS; SAFETY ANALYSIS; PROCESS SYSTEMS; PREVENTION; STRATEGIES; RESILIENCE;
D O I
10.1016/j.ress.2015.04.015
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Dealing with large quantities of flammable and explosive materials, usually at high-pressure high-temperature conditions, makes process plants very vulnerable to cascading effects compared with other infrastructures. The combination of the extremely low frequency of cascading effects and the high complexity and interdependencies of process plants makes risk assessment and vulnerability analysis of process plants very challenging in the context of such events. In the present study, cascading effects were represented as a directed graph; accordingly, the efficacy of a set of graph metrics and measurements was examined in both unit and plant-wide vulnerability analysis of process plants. We demonstrated that vertex-level closeness and betweenness can be used in the unit vulnerability analysis of process plants for the identification of critical units within a process plant. Furthermore, the graph-level closeness metric can be used in the plant-wide vulnerability analysis for the identification of the most vulnerable plant layout with respect to the escalation of cascading effects. Furthermore, the results from the application of the graph metrics have been verified using a Bayesian network methodology. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:63 / 73
页数:11
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