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A novel dynamic risk assessment method for the petrochemical industry using bow-tie analysis and Bayesian network analysis method based on the methodological framework of ARAMIS project

Author

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  • Wu, Xingguang
  • Huang, Huirong
  • Xie, Jianyu
  • Lu, Meixing
  • Wang, Shaobo
  • Li, Wang
  • Huang, Yixuan
  • Yu, Weichao
  • Sun, Xiaobo

Abstract

In order to obtain the actual risk level and assess the performance of the safety barriers, bow-tie (BT) approach proposed by ARAMIS project is applied to accident scenarios identification and risk analysis, but this approach has limitations in dynamic risk assessment due to its static nature. This study takes the floating roof tank as the research object, and further proposes a dynamic risk assessment method based on the methodology proposed by the ARAMIS project. The BT model of the major leak of external floating roof tank was established by comprehensive consideration of the barrier functions and the logical relationship between causes and events. Furthermore, The BT to Bayesian network (BN) mapping algorithm was proposed to characterize system dynamics and uncertainty. The analysis results show that not only the dynamic assessment of the risk level for safety barriers in different states can be implemented, but also whether the current overall safety protection capability of the system is sufficient can be judged. The proposed method and findings can help managers identify safety barriers that play a key role in various accident risks, and provide effective support for risk management decision-making and implementation of preventive strategies.

Suggested Citation

  • Wu, Xingguang & Huang, Huirong & Xie, Jianyu & Lu, Meixing & Wang, Shaobo & Li, Wang & Huang, Yixuan & Yu, Weichao & Sun, Xiaobo, 2023. "A novel dynamic risk assessment method for the petrochemical industry using bow-tie analysis and Bayesian network analysis method based on the methodological framework of ARAMIS project," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    • Handle: RePEc:eee:reensy:v:237:y:2023:i:c:s0951832023003113
    DOI: 10.1016/j.ress.2023.109397
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    1. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2011. "Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 925-932.
    2. 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).
    3. Bucci, Paolo & Kirschenbaum, Jason & Mangan, L. Anthony & Aldemir, Tunc & Smith, Curtis & Wood, Ted, 2008. "Construction of event-tree/fault-tree models from a Markov approach to dynamic system reliability," Reliability Engineering and System Safety, Elsevier, vol. 93(11), pages 1616-1627.
    4. Xie, Shuyi & Dong, Shaohua & Chen, Yinuo & Peng, Yujie & Li, Xincai, 2021. "A novel risk evaluation method for fire and explosion accidents in oil depots using bow-tie analysis and risk matrix analysis method based on cloud model theory," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    5. Ding, Rui & Liu, Zehua & Xu, Jintao & Meng, Fanpeng & Sui, Yang & Men, Xinhong, 2021. "A novel approach for reliability assessment of residual heat removal system for HPR1000 based on failure mode and effect analysis, fault tree analysis, and fuzzy Bayesian network methods," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    6. Sýkora, Miroslav & Marková, Jana & Diamantidis, Dimitris, 2018. "Bayesian network application for the risk assessment of existing energy production units," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 312-320.
    7. Langdalen, Henrik & Abrahamsen, Eirik Bjorheim & Selvik, Jon Tømmerås, 2020. "On the importance of systems thinking when using the ALARP principle for risk management," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    8. Zhang, Y. & Weng, W.G., 2020. "Bayesian network model for buried gas pipeline failure analysis caused by corrosion and external interference," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    9. Ding, Feng & Wang, Yihua & Ma, Guoliang & Zhang, Xinrui, 2021. "Correlation reliability assessment of artillery chassis transmission system based on CBN model," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    10. 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).
    11. Yin, Yuanbo & Yang, Hao & Duan, Pengfei & Li, Luling & Zio, Enrico & Liu, Cuiwei & Li, Yuxing, 2022. "Improved quantitative risk assessment of a natural gas pipeline considering high-consequence areas," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    12. Liu, Aihua & Chen, Ke & Huang, Xiaofei & Li, Didi & Zhang, Xiaochun, 2021. "Dynamic risk assessment model of buried gas pipelines based on system dynamics," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    13. Arismendi, Renny & Barros, Anne & Grall, Antoine, 2021. "Piecewise deterministic Markov process for condition-based maintenance models — Application to critical infrastructures with discrete-state deterioration," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    14. Yang, Yongsheng & Khan, Faisal & Thodi, Premkumar & Abbassi, Rouzbeh, 2017. "Corrosion induced failure analysis of subsea pipelines," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 214-222.
    15. Kwag, Shinyoung & Gupta, Abhinav & Dinh, Nam, 2018. "Probabilistic risk assessment based model validation method using Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 380-393.
    16. Song, Guozheng & Khan, Faisal & Wang, Hangzhou & Leighton, Shelly & Yuan, Zhi & Liu, Hanwen, 2016. "Dynamic occupational risk model for offshore operations in harsh environments," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 58-64.
    17. Casson Moreno, Valeria & Marroni, Giulia & Landucci, Gabriele, 2022. "Probabilistic assessment aimed at the evaluation of escalating scenarios in process facilities combining safety and security barriers," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    18. Hou, Lei & Wu, Xingguang & Wu, Zhuang & Wu, Shouzhi, 2020. "Pattern identification and risk prediction of domino effect based on data mining methods for accidents occurred in the tank farm," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    19. van Staalduinen, Mark Adrian & Khan, Faisal & Gadag, Veeresh & Reniers, Genserik, 2017. "Functional quantitative security risk analysis (QSRA) to assist in protecting critical process infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 23-34.
    20. 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).
    21. Xing, Jinduo & Zeng, Zhiguo & Zio, Enrico, 2019. "A framework for dynamic risk assessment with condition monitoring data and inspection data," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    22. Yeter, B. & Garbatov, Y. & Guedes Soares, C., 2020. "Risk-based maintenance planning of offshore wind turbine farms," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    23. Li, Yuntao & Wang, Yumeng & Lai, Yuying & Shuai, Jian & Zhang, Laibin, 2023. "Monte Carlo-based quantitative risk assessment of parking areas for vehicles carrying hazardous chemicals," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    24. Zio, E., 2018. "The future of risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 176-190.
    25. 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).
    26. Caratozzolo, Vincenzo & Misuri, Alessio & Cozzani, Valerio, 2022. "A generalized equipment vulnerability model for the quantitative risk assessment of horizontal vessels involved in Natech scenarios triggered by floods," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    27. Carpitella, Silvia & Mzougui, Ilyas & Benítez, Julio & Carpitella, Fortunato & Certa, Antonella & Izquierdo, Joaquín & La Cascia, Marco, 2021. "A risk evaluation framework for the best maintenance strategy: The case of a marine salt manufacture firm," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    28. Xiang, W. & Zhou, W., 2021. "Bayesian network model for predicting probability of third-party damage to underground pipelines and learning model parameters from incomplete datasets," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    29. 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).
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