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Which Fire to Extinguish First? A Risk‐Informed Approach to Emergency Response in Oil Terminals

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  • Nima Khakzad

Abstract

The performance of fire protection measures plays a key role in the prevention and mitigation of fire escalation (fire domino effect) in process plants. In addition to passive and active safety measures, the intervention of firefighting teams can have a great impact on fire propagation. In the present study, we have demonstrated an application of dynamic Bayesian network to modeling and safety assessment of fire domino effect in oil terminals while considering the effect of safety measures in place. The results of the developed dynamic Bayesian network—prior and posterior probabilities—have been combined with information theory, in the form of mutual information, to identify optimal firefighting strategies, especially when the number of fire trucks is not sufficient to handle all the vessels in danger.

Suggested Citation

  • Nima Khakzad, 2018. "Which Fire to Extinguish First? A Risk‐Informed Approach to Emergency Response in Oil Terminals," Risk Analysis, John Wiley & Sons, vol. 38(7), pages 1444-1454, July.
  • Handle: RePEc:wly:riskan:v:38:y:2018:i:7:p:1444-1454
    DOI: 10.1111/risa.12946
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    References listed on IDEAS

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    1. Necci, Amos & Argenti, Francesca & Landucci, Gabriele & Cozzani, Valerio, 2014. "Accident scenarios triggered by lightning strike on atmospheric storage tanks," Reliability Engineering and System Safety, Elsevier, vol. 127(C), pages 30-46.
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    4. 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.
    5. Khakzad, Nima & Landucci, Gabriele & Cozzani, Valerio & Reniers, Genserik & Pasman, Hans, 2018. "Cost-effective fire protection of chemical plants against domino effects," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 412-421.
    6. Zhou, Jianfeng & Reniers, Genserik & Khakzad, Nima, 2016. "Application of event sequence diagram to evaluate emergency response actions during fire-induced domino effects," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 202-209.
    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.
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    Cited by:

    1. Yang Liu & Xiaoxue Ma & Weiliang Qiao & Huiwen Luo & Peilong He, 2021. "Human Factor Risk Modeling for Shipyard Operation by Mapping Fuzzy Fault Tree into Bayesian Network," IJERPH, MDPI, vol. 19(1), pages 1-31, December.
    2. Gregory Levitin & Liudong Xing & Yuanshun Dai, 2020. "Mission Abort Policy for Systems with Observable States of Standby Components," Risk Analysis, John Wiley & Sons, vol. 40(10), pages 1900-1912, October.
    3. Dimaio, F. & Scapinello, O. & Zio, E. & Ciarapica, C. & Cincotta, S. & Crivellari, A. & Decarli, L. & Larosa, L., 2021. "Accounting for Safety Barriers Degradation in the Risk Assessment of Oil and Gas Systems by Multistate Bayesian Networks," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    4. 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).
    5. Khakzad, Nima, 2023. "A goal programming approach to multi-objective optimization of firefighting strategies in the event of domino effects," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    6. Nima Khakzad, 2018. "A Graph Theoretic Approach to Optimal Firefighting in Oil Terminals," Energies, MDPI, vol. 11(11), pages 1-14, November.

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