IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v233y2023ics0951832023000145.html
   My bibliography  Save this article

Exploring hazardous chemical explosion accidents with association rules and Bayesian networks

Author

Listed:
  • Li, Xin
  • Chen, Chao
  • Hong, Yi-du
  • Yang, Fu-qiang

Abstract

Hazardous chemical accidents pose a severe threat to human and economic activities. To explore the causes and paths of hazardous chemical explosion accidents (HCEAs) in China, a qualitative and quantitative model was proposed in this study. Firstly, 129 accident cases were collected from the official website of the Ministry of Emergency Management of the People's Republic of China, and the accident factors were screened based on association rule (AR). Then, the fault tree (FT) structure of HCEA was developed by the AR, and the qualitative model was transformed into a quantitative Bayesian network (BN) model. Finally, the accident path, the importance size of the basic events, and the sensitivity of the direct cause of the accident were uncovered based on the BN model. The results show that improper temperature control due to operating procedures is the most likely route to accidents. Among the basic events, process management and operating procedures issues ranked the first in importance, with the most significant impact on HCEA. The sensitivity of improper temperature control far exceeds other direct causes and is most likely to induce accidents directly. According to the study results, some feasible measures are put forward to improve the safety management of hazardous chemical production.

Suggested Citation

  • Li, Xin & Chen, Chao & Hong, Yi-du & Yang, Fu-qiang, 2023. "Exploring hazardous chemical explosion accidents with association rules and Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    • Handle: RePEc:eee:reensy:v:233:y:2023:i:c:s0951832023000145
    DOI: 10.1016/j.ress.2023.109099
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832023000145
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2023.109099?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Çakır, Erkan & Fışkın, Remzi & Sevgili, Coşkan, 2021. "Investigation of tugboat accidents severity: An application of association rule mining algorithms," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    2. 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).
    3. Mkrtchyan, L. & Podofillini, L. & Dang, V.N., 2015. "Bayesian belief networks for human reliability analysis: A review of applications and gaps," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 1-16.
    4. Lan, He & Ma, Xiaoxue & Ma, Laihao & Qiao, Weiliang, 2023. "Pattern investigation of total loss maritime accidents based on association rule mining," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    5. Catelani, Marcantonio & Ciani, Lorenzo & Guidi, Giulia & Patrizi, Gabriele, 2021. "An enhanced SHERPA (E-SHERPA) method for human reliability analysis in railway engineering," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    6. Abreu, Danilo T.M.P. & Maturana, Marcos C. & Droguett, Enrique Lopez & Martins, Marcelo R., 2022. "Human reliability analysis of conventional maritime pilotage operations supported by a prospective model," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    7. Men, Jinkun & Chen, Guohua & Yang, Yunfeng & Reniers, Genserik, 2022. "An event-driven probabilistic methodology for modeling the spatial-temporal evolution of natural hazard-induced domino chain in chemical industrial parks," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    8. Zhi Yuan & Nima Khakzad & Faisal Khan & Paul Amyotte, 2015. "Risk Analysis of Dust Explosion Scenarios Using Bayesian Networks," Risk Analysis, John Wiley & Sons, vol. 35(2), pages 278-291, February.
    9. Fu, Lipeng & Wang, Xueqing & Zhao, Heng & Li, Mengnan, 2022. "Interactions among safety risks in metro deep foundation pit projects: An association rule mining-based modeling framework," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    10. 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).
    11. Baraldi, Piero & Podofillini, Luca & Mkrtchyan, Lusine & Zio, Enrico & Dang, Vinh N., 2015. "Comparing the treatment of uncertainty in Bayesian networks and fuzzy expert systems used for a human reliability analysis application," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 176-193.
    12. Zinetullina, Altyngul & Yang, Ming & Khakzad, Nima & Golman, Boris & Li, Xinhong, 2021. "Quantitative resilience assessment of chemical process systems using functional resonance analysis method and Dynamic Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    13. Lan, He & Ma, Xiaoxue & Qiao, Weiliang & Deng, Wanyi, 2023. "Determining the critical risk factors for predicting the severity of ship collision accidents using a data-driven approach," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    14. B. Zhao, 2016. "Facts and lessons related to the explosion accident in Tianjin Port, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 707-713, October.
    15. Ayoub, Ali & Stankovski, Andrej & Kröger, Wolfgang & Sornette, Didier, 2021. "Precursors and startling lessons: Statistical analysis of 1250 events with safety significance from the civil nuclear sector," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    16. Wu, Chao & Huang, Lang, 2019. "A new accident causation model based on information flow and its application in Tianjin Port fire and explosion accident," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 73-85.
    17. 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).
    18. Li, Huanhuan & Ren, Xujie & Yang, Zaili, 2023. "Data-driven Bayesian network for risk analysis of global maritime accidents," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    19. Wang, Zengkai & Zeng, Shengkui & Guo, Jianbin & Che, Haiyang, 2021. "A Bayesian network for reliability assessment of man-machine phased-mission system considering the phase dependencies of human cognitive error," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Jinpei & Bai, Xuejie & Liu, Yankui, 2023. "Globalized robust bilevel optimization model for hazmat transport network design considering reliability," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    2. Hunte, Joshua L. & Neil, Martin & Fenton, Norman E., 2024. "A hybrid Bayesian network for medical device risk assessment and management," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    3. Li, Guoqi & Pu, Gang & Yang, Jiaxin & Jiang, Xinguo, 2024. "A multidimensional quantitative risk assessment framework for dense areas of stay points for urban HazMat vehicles," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    4. Fan, Shiqi & Yang, Zaili, 2024. "Accident data-driven human fatigue analysis in maritime transport using machine learning," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    5. Zhang, Hengqi & Geng, Hua & Zeng, Huarong & Jiang, Li, 2023. "Dynamic risk evaluation and control of electrical personal accidents," Reliability Engineering and System Safety, Elsevier, vol. 237(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lan, He & Ma, Xiaoxue & Qiao, Weiliang & Deng, Wanyi, 2023. "Determining the critical risk factors for predicting the severity of ship collision accidents using a data-driven approach," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    2. Lan, He & Ma, Xiaoxue & Qiao, Weiliang & Ma, Laihao, 2022. "On the causation of seafarers’ unsafe acts using grounded theory and association rule," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    3. Shi, Wen & Zhou, Qing & Zhou, Yanju, 2023. "An efficient elementary effect-based method for sensitivity analysis in identifying main and two-factor interaction effects," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    4. Abreu, Danilo T.M.P. & Maturana, Marcos C. & Droguett, Enrique Lopez & Martins, Marcelo R., 2022. "Human reliability analysis of conventional maritime pilotage operations supported by a prospective model," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    5. Patriarca, Riccardo & Ramos, Marilia & Paltrinieri, Nicola & Massaiu, Salvatore & Costantino, Francesco & Di Gravio, Giulio & Boring, Ronald Laurids, 2020. "Human reliability analysis: Exploring the intellectual structure of a research field," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    6. 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).
    7. Arman Nedjati & Mohammad Yazdi & Rouzbeh Abbassi, 2022. "A sustainable perspective of optimal site selection of giant air-purifiers in large metropolitan areas," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 8747-8778, June.
    8. 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).
    9. Podofillini, Luca & Reer, Bernhard & Dang, Vinh N., 2023. "A traceable process to develop Bayesian networks from scarce data and expert judgment: A human reliability analysis application," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    10. Liu, Cuiwei & Wang, Yazhen & Li, Xinhong & Li, Yuxing & Khan, Faisal & Cai, Baoping, 2021. "Quantitative assessment of leakage orifices within gas pipelines using a Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    11. Lan, He & Ma, Xiaoxue & Ma, Laihao & Qiao, Weiliang, 2023. "Pattern investigation of total loss maritime accidents based on association rule mining," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    12. Zwirglmaier, Kilian & Straub, Daniel & Groth, Katrina M., 2017. "Capturing cognitive causal paths in human reliability analysis with Bayesian network models," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 117-129.
    13. 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).
    14. Wang, Wei & Di Maio, Francesco & Zio, Enrico, 2020. "Considering the human operator cognitive process for the interpretation of diagnostic outcomes related to component failures and cyber security attacks," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    15. Wu, Bing & Yip, Tsz Leung & Yan, Xinping & Guedes Soares, C., 2022. "Review of techniques and challenges of human and organizational factors analysis in maritime transportation," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    16. Morais, Caroline & Estrada-Lugo, Hector Diego & Tolo, Silvia & Jacques, Tiago & Moura, Raphael & Beer, Michael & Patelli, Edoardo, 2022. "Robust data-driven human reliability analysis using credal networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    17. 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).
    18. Zheng Tang & Yijia Li & Xiaofeng Hu & Huanggang Wu, 2019. "Risk Analysis of Urban Dirty Bomb Attacking Based on Bayesian Network," Sustainability, MDPI, vol. 11(2), pages 1-12, January.
    19. 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).
    20. Wang, Rongxi & Li, Yufan & Xu, Jinjin & Wang, Zhen & Gao, Jianmin, 2022. "F2G: A hybrid fault-function graphical model for reliability analysis of complex equipment with coupled faults," Reliability Engineering and System Safety, Elsevier, vol. 226(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:233:y:2023:i:c:s0951832023000145. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.