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A methodology based on Dijkstra's algorithm and mathematical programming for optimal evacuation in process plants in the event of major tank fires

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  • Khakzad, Nima

Abstract

Effective evacuation plans are essential to protecting workers in the event of major fires in process plants. However, despite some general guidelines, there is no specific methodology available for identification of such plans. In the present study, we have developed a methodology for identifying optimal evacuation strategies in the event of single and multiple tank fires. In this study, considering heat flux as the main cause of casualties in outdoor fires, the conventional relationship for calculating thermal dose was first modified to estimate the values of thermal dose more accurately. The Dijkstra's algorithm was then employed to identify the evacuation paths to safe spots. Due to the limited capacity of safe spots, mathematical programming was used to determine how many people should be allocated to each safe spot and via which evacuation path so as to minimize the risk of casualties. The developed methodology was demonstrated to outperform the ad hoc evacuation plans in minimizing the casualties while allowing the analyst to update the evacuation plans in accordance with the evolution of fire scenarios.

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  • Khakzad, Nima, 2023. "A methodology based on Dijkstra's algorithm and mathematical programming for optimal evacuation in process plants in the event of major tank fires," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    • Handle: RePEc:eee:reensy:v:236:y:2023:i:c:s0951832023002065
    DOI: 10.1016/j.ress.2023.109291
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    References listed on IDEAS

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    1. Tugnoli, Alessandro & Scarponi, Giordano Emrys & Antonioni, Giacomo & Cozzani, Valerio, 2022. "Quantitative assessment of domino effect and escalation scenarios caused by fragment projection," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
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    4. 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.
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    8. 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).
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    13. 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.
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    15. Khakzad, Nima & Landucci, Gabriele & Reniers, Genserik, 2017. "Application of dynamic Bayesian network to performance assessment of fire protection systems during domino effects," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 232-247.
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    Cited by:

    1. Yang, Jianfeng & Zhang, Bo & Chen, Liangchao & Diao, Xu & Hu, Yuanhao & Suo, Guanyu & Li, Ru & Wang, Qianlin & Li, Jinghai & Zhang, Jianwen & Dou, Zhan, 2023. "Improved solid radiation model for thermal response in large crude oil tanks," Energy, Elsevier, vol. 284(C).
    2. 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).

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