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Application of Graph Theory to Cost‐Effective Fire Protection of Chemical Plants During Domino Effects

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  • Nima Khakzad
  • Gabriele Landucci
  • Genserik Reniers

Abstract

In the present study, we have introduced a methodology based on graph theory and multicriteria decision analysis for cost‐effective fire protection of chemical plants subject to fire‐induced domino effects. By modeling domino effects in chemical plants as a directed graph, the graph centrality measures such as out‐closeness and betweenness scores can be used to identify the installations playing a key role in initiating and propagating potential domino effects. It is demonstrated that active fire protection of installations with the highest out‐closeness score and passive fire protection of installations with the highest betweenness score are the most effective strategies for reducing the vulnerability of chemical plants to fire‐induced domino effects. We have employed a dynamic graph analysis to investigate the impact of both the availability and the degradation of fire protection measures over time on the vulnerability of chemical plants. The results obtained from the graph analysis can further be prioritized using multicriteria decision analysis techniques such as the method of reference point to find the most cost‐effective fire protection strategy.

Suggested Citation

  • Nima Khakzad & Gabriele Landucci & Genserik Reniers, 2017. "Application of Graph Theory to Cost‐Effective Fire Protection of Chemical Plants During Domino Effects," Risk Analysis, John Wiley & Sons, vol. 37(9), pages 1652-1667, September.
    • Handle: RePEc:wly:riskan:v:37:y:2017:i:9:p:1652-1667
    DOI: 10.1111/risa.12712
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    References listed on IDEAS

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    8. Khakzad, Nima, 2015. "Application of dynamic Bayesian network to risk analysis of domino effects in chemical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 263-272.
    9. Janssens, Jochen & Talarico, Luca & Reniers, Genserik & Sörensen, Kenneth, 2015. "A decision model to allocate protective safety barriers and mitigate domino effects," Reliability Engineering and System Safety, Elsevier, vol. 143(C), pages 44-52.
    10. Nima Khakzad & Faisal Khan & Paul Amyotte & Valerio Cozzani, 2014. "Risk Management of Domino Effects Considering Dynamic Consequence Analysis," Risk Analysis, John Wiley & Sons, vol. 34(6), pages 1128-1138, June.
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    Cited by:

    1. Khakzad, Nima & Reniers, Genserik, 2019. "Low-capacity utilization of process plants: A cost-robust approach to tackle man-made domino effects," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    2. Lan, Meng & Gardoni, Paolo & Qin, Rongshui & Zhang, Xiao & Zhu, Jiping & Lo, Siuming, 2022. "Modeling NaTech-related domino effects in process clusters: A network-based approach," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    3. Guo, Xiaoxue & Ding, Long & Ji, Jie & Cozzani, Valerio, 2022. "A cost-effective optimization model of safety investment allocation for risk reduction of domino effects," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    4. Chen, Chao & Yang, Ming & Reniers, Genserik, 2021. "A dynamic stochastic methodology for quantifying HAZMAT storage resilience," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    5. Misuri, Alessio & Landucci, Gabriele & Cozzani, Valerio, 2021. "Assessment of risk modification due to safety barrier performance degradation in Natech events," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    6. Gholamizadeh, Kamran & Zarei, Esmaeil & Yazdi, Mohammad & Ramezanifar, Ehsan & Aliabadi, Mostafa Mirzaei, 2024. "A hybrid model for dynamic analysis of domino effects in chemical process industries," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    7. Chen, Chao & Reniers, Genserik & Khakzad, Nima, 2021. "A dynamic multi-agent approach for modeling the evolution of multi-hazard accident scenarios in chemical plants," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    8. Matteini, Anita & Argenti, Francesca & Salzano, Ernesto & Cozzani, Valerio, 2019. "A comparative analysis of security risk assessment methodologies for the chemical industry," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    9. Wu, Jiansong & Bai, Yiping & Fang, Weipeng & Zhou, Rui & Reniers, Genserik & Khakzad, Nima, 2021. "An Integrated Quantitative Risk Assessment Method for Urban Underground Utility Tunnels," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    10. Pieter van Gelder & Pim Klaassen & Behnam Taebi & Bart Walhout & Ruud van Ommen & Ibo van de Poel & Zoe Robaey & Lotte Asveld & Ruud Balkenende & Frank Hollmann & Erik Jan van Kampen & Nima Khakzad & , 2021. "Safe-by-Design in Engineering: An Overview and Comparative Analysis of Engineering Disciplines," IJERPH, MDPI, vol. 18(12), pages 1-28, June.
    11. Lin Xie & Mary Ann Lundteigen & Yiliu Liu, 2020. "Reliability and barrier assessment of series–parallel systems subject to cascading failures," Journal of Risk and Reliability, , vol. 234(3), pages 455-469, June.
    12. Ding, Long & Khan, Faisal & Ji, Jie, 2022. "A novel vulnerability model considering synergistic effect of fire and overpressure in chemical processing facilities," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    13. Khakzad, Nima, 2021. "Optimal firefighting to prevent domino effects: Methodologies based on dynamic influence diagram and mathematical programming," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    14. Weiliang Qiao & Enze Huang & Hongtongyang Guo & Yang Liu & Xiaoxue Ma, 2022. "Barriers Involved in the Safety Management Systems: A Systematic Review of Literature," IJERPH, MDPI, vol. 19(15), pages 1-35, August.
    15. Ding, Long & Khan, Faisal & Ji, Jie, 2020. "A novel approach for domino effects modeling and risk analysis based on synergistic effect and accident evidence," Reliability Engineering and System Safety, Elsevier, vol. 203(C).

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