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Low-capacity utilization of process plants: A cost-robust approach to tackle man-made domino effects

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  • Khakzad, Nima
  • Reniers, Genserik

Abstract

Process plants can be potential targets to terrorist attacks with the aim of triggering domino effects. Compared to accidental domino effects where the possibility of having multiple primary events is very remote, man-made domino effects are likelier to be initiated from multiple units within the plant in order to increase the knock-on likelihood and thus causing maximum damage. In this regard, identification of critical units that - under attack - may lead to likelier and severer domino effects is crucial both to assess the vulnerability of process plants and subsequently to increase their robustness to such attacks. In the present work, we have applied graph theory and dynamic Bayesian network to identify critical units. Further, low-capacity utilization of process plants (e.g., by keeping some of the storage tanks empty) has been demonstrated as an effective strategy in the case of imminent terrorist attacks. As such, the robustness of the plant against intentional attacks can temporarily be increased while considering the cost incurred because of such a low-capacity utilization.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:reensy:v:191:y:2019:i:c:s0951832017309158
    DOI: 10.1016/j.ress.2018.03.030
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    References listed on IDEAS

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    1. Nima Khakzad & Faisal Khan & Paul Amyotte & Valerio Cozzani, 2013. "Domino Effect Analysis Using Bayesian Networks," Risk Analysis, John Wiley & Sons, vol. 33(2), pages 292-306, February.
    2. Landucci, Gabriele & Argenti, Francesca & Tugnoli, Alessandro & Cozzani, Valerio, 2015. "Quantitative assessment of safety barrier performance in the prevention of domino scenarios triggered by fire," Reliability Engineering and System Safety, Elsevier, vol. 143(C), pages 30-43.
    3. Landucci, Gabriele & Reniers, Genserik & Cozzani, Valerio & Salzano, Ernesto, 2015. "Vulnerability of industrial facilities to attacks with improvised explosive devices aimed at triggering domino scenarios," Reliability Engineering and System Safety, Elsevier, vol. 143(C), pages 53-62.
    4. Sumitra Sri Bhashyam & Gilberto Montibeller, 2016. "In the Opponent's Shoes: Increasing the Behavioral Validity of Attackers’ Judgments in Counterterrorism Models," Risk Analysis, John Wiley & Sons, vol. 36(4), pages 666-680, April.
    5. Gilboa,Itzhak, 2009. "Theory of Decision under Uncertainty," Cambridge Books, Cambridge University Press, number 9780521517324, September.
    6. Khakzad, Nima & Reniers, Genserik, 2015. "Using graph theory to analyze the vulnerability of process plants in the context of cascading effects," Reliability Engineering and System Safety, Elsevier, vol. 143(C), pages 63-73.
    7. 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.
    8. 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.
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    Cited by:

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    3. Iaiani, Matteo & Sorichetti, Riccardo & Tugnoli, Alessandro & Cozzani, Valerio, 2024. "Modelling standoff distances to prevent escalation in shooting attacks to tanks storing hazardous materials," Reliability Engineering and System Safety, Elsevier, vol. 241(C).

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