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A novel vulnerability model considering synergistic effect of fire and overpressure in chemical processing facilities

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  • Ding, Long
  • Khan, Faisal
  • Ji, Jie

Abstract

Processing facilities are faced with spatial-temporal dependent multiple-hazards. These hazards could cause catastrophic consequences. A novel vulnerability model called the “fire and explosion synergistic effect model†(FESEM) is proposed in the present study to model equipment vulnerability under the spatial-temporal synergistic of heat radiation and overpressure. On the basis of the fire synergistic effect model, the FESEM firstly model the temperature elevation and the yield strength reduction of the storage tank wall under fire heat radiation. Then, based on the von Mises yield criterion, the FESEM models the equivalent stress under overpressure. Combining the lowered yield strength induced by fire heat radiation and equivalent stress induced by overpressure under the synergistic effect, the logistic function is used to estimate time to failure and escalation probability. The application of the model is demonstrated in the case study, which confirms that the synergistic effect is significant and closer to reality. The parameters that have considerable effects on time to failure and escalation probability are discussed. The proposed method will serve as a rapid quantitative risk assessment tool of multi-hazard coupling, including the domino effect. The model will serve as an essential guide for preventing and controlling domino effects.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:reensy:v:217:y:2022:i:c:s0951832021005792
    DOI: 10.1016/j.ress.2021.108081
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    References listed on IDEAS

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    4. 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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    7. 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).
    8. Chen, Chao & Reniers, Genserik & Khakzad, Nima, 2019. "Integrating safety and security resources to protect chemical industrial parks from man-made domino effects: A dynamic graph approach," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    9. 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).
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    12. Celano, Francesca & Dolšek, Matjaž, 2021. "Fatality risk estimation for industrialized urban areas considering multi-hazard domino effects triggered by earthquakes," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    13. Ovidi, Federica & Zhang, Laobing & Landucci, Gabriele & Reniers, Genserik, 2021. "Agent-based model and simulation of mitigated domino scenarios in chemical tank farms," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    14. Argenti, Francesca & Landucci, Gabriele & Reniers, Genserik & Cozzani, Valerio, 2018. "Vulnerability assessment of chemical facilities to intentional attacks based on Bayesian Network," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 515-530.
    15. 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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    6. Amin, Md. Tanjin & Scarponi, Giordano Emrys & Cozzani, Valerio & Khan, Faisal, 2024. "Improved pool fire-initiated domino effect assessment in atmospheric tank farms using structural response," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    7. Li, Qilin & Wang, Yang & Chen, Wensu & Li, Ling & Hao, Hong, 2024. "Machine learning prediction of BLEVE loading with graph neural networks," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    8. Marroni, Giulia & Casini, Leonardo & Bartolucci, Andrea & Kuipers, Sanneke & Casson Moreno, Valeria & Landucci, Gabriele, 2024. "Development of fragility models for process equipment affected by physical security attacks," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    9. Li, Xiaofeng & Chen, Guohua & Amyotte, Paul & Khan, Faisal & Alauddin, Mohammad, 2023. "Vulnerability assessment of storage tanks exposed to simultaneous fire and explosion hazards," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
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