IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i15p5622-d879336.html
   My bibliography  Save this article

Analysis on Causative Factors and Evolution Paths of Blast Furnace Gas Leak Accident

Author

Listed:
  • Ying Lu

    (School of Resource and Environmental Engineering, Wuhan University of Science and Technology, Wuhan 430081, China
    Hubei Industrial Safety Engineering Technology Research Center, Wuhan 430081, China)

  • Yueming Lu

    (School of Resource and Environmental Engineering, Wuhan University of Science and Technology, Wuhan 430081, China)

  • Jingwen Wang

    (School of Resource and Environmental Engineering, Wuhan University of Science and Technology, Wuhan 430081, China)

  • Xibei Zhang

    (School of Resource and Environmental Engineering, Wuhan University of Science and Technology, Wuhan 430081, China)

  • Wangsheng Chen

    (School of Resource and Environmental Engineering, Wuhan University of Science and Technology, Wuhan 430081, China
    Hubei Industrial Safety Engineering Technology Research Center, Wuhan 430081, China)

Abstract

Although the interest in metallurgical accident investigation of blast furnace gas (BFG) leakage has increased to explore the engineering failures, more effort is needed to address the individual and organizational causative factors to clear and determine the weak links for improving safety management and accident prevention to achieve green metallurgical manufacturing. This study aims to examine the causative factors and evolution paths of BFG leakage by introducing a combined method, the 24 model and Bayesian network (BN), based on 50 cases of fire, explosion and suffocation accidents caused by BFG leakage. A BN model of BFG leakage was established based on the identification of 25 causative factors by the 24 model. Results showed that eight nodes, including A1 (unsafe operation), A2 (unsafe behavior), A4 (unsafe condition), B1 (valve failure), B2 (improper gas safety operation), X4 (use of BFG violates regulations), X5 (water gas is not cut off before shutdown reduction) and X6 (incomplete steam purging), were more sensitive than others, and the posterior probability of nodes A1, A2, A3 (unsafe command), A4, B1, B2, B4 (improper emergency behavior), B5 (unsafe behaviors on BFG site) increased compared to prior probability. Three main accident causal chains were obtained which indicate that control the unsafe operations (A1) related to gas (B2) and valve (B1) are suggested to be improved. Another important factor is A4 (unsafe condition), which is related to intrinsic safety conditions. Considering the results, the key points of 3E strategy about BFG leakage prevention are suggested. This study provides useful insights to understand the organizational and individual factors and their relative influence in BFG leakage accidents, which will support BFG leakage prevention and safety management.

Suggested Citation

  • Ying Lu & Yueming Lu & Jingwen Wang & Xibei Zhang & Wangsheng Chen, 2022. "Analysis on Causative Factors and Evolution Paths of Blast Furnace Gas Leak Accident," Energies, MDPI, vol. 15(15), pages 1-20, August.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:15:p:5622-:d:879336
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/15/5622/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/15/5622/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liu, Zengkai & Ma, Qiang & Cai, Baoping & Shi, Xuewei & Zheng, Chao & Liu, Yonghong, 2022. "Risk coupling analysis of subsea blowout accidents based on dynamic Bayesian network and NK model," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    2. Yingying Xing & Shengdi Chen & Shengxue Zhu & Jian Lu, 2020. "Analysis Factors That Influence Escalator-Related Injuries in Metro Stations Based on Bayesian Networks: A Case Study in China," IJERPH, MDPI, vol. 17(2), pages 1-21, January.
    Full references (including those not matched with items on IDEAS)

    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. He, Rui & Zhu, Jingyu & Chen, Guoming & Tian, Zhigang, 2022. "A real-time probabilistic risk assessment method for the petrochemical industry based on data monitoring," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    2. Wang, Jian & Gao, Shibin & Yu, Long & Ma, Chaoqun & Zhang, Dongkai & Kou, Lei, 2023. "A data-driven integrated framework for predictive probabilistic risk analytics of overhead contact lines based on dynamic Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    3. Guo, Jian & Luo, Cheng & Ma, Kaijiang, 2023. "Risk coupling analysis of road transportation accidents of hazardous materials in complicated maritime environment," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    4. Cao, Bohan & Yin, Qishuai & Guo, Yingying & Yang, Jin & Zhang, Laibin & Wang, Zhenquan & Tyagi, Mayank & Sun, Ting & Zhou, Xu, 2023. "Field data analysis and risk assessment of shallow gas hazards based on neural networks during industrial deep-water drilling," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    5. Qiu, Na & Liu, Xiuquan & Li, Yanwei & Hu, Pengji & Chang, Yuanjiang & Chen, Guoming & Meng, Huixing, 2024. "Dynamic catastrophe analysis of deepwater mooring platform/riser/wellhead coupled system under ISW," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    6. Guo, Jian & Ma, Kaijiang, 2024. "Risk analysis for hazardous chemical vehicle-bridge transportation system: A dynamic Bayesian network model incorporating vehicle dynamics," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    7. Liu, Xuan & Meng, Huixing & An, Xu & Xing, Jinduo, 2024. "Integration of functional resonance analysis method and reinforcement learning for updating and optimizing emergency procedures in variable environments," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    8. Wang, Chenyushu & Cai, Baoping & Shao, Xiaoyan & Zhao, Liqian & Sui, Zhongfei & Liu, Keyang & Khan, Javed Akbar & Gao, Lei, 2023. "Dynamic risk assessment methodology of operation process for deepwater oil and gas equipment," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    9. Hongwei Li & Yuxi Wang & Yingying Xing & Xiaochen Zhao & Ke Wang, 2021. "Contributing Factors Affecting the Severity of Metro Escalator Injuries in the Guangzhou Metro, China," IJERPH, MDPI, vol. 18(2), pages 1-15, January.
    10. Xue, Gang & Liu, Shifeng & Ren, Long & Gong, Daqing, 2024. "Risk assessment of utility tunnels through risk interaction-based deep learning," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    11. 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).
    12. Zhang, Hengqi & Geng, Hua, 2023. "A methodology to identify and assess high-risk causes for electrical personal accidents based on directed weighted CN," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    13. Hai, Nan & Gong, Daqing & Liu, Shifeng & Dai, Zixuan, 2022. "Dynamic coupling risk assessment model of utility tunnels based on multimethod fusion," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    14. 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).
    15. Jie Liu & Liting Wan & Wanqing Wang & Guanding Yang & Qian Ma & Haowen Zhou & Huyun Zhao & Feng Lu, 2023. "Integrated Fuzzy DEMATEL-ISM-NK for Metro Operation Safety Risk Factor Analysis and Multi-Factor Risk Coupling Study," Sustainability, MDPI, vol. 15(7), pages 1-26, March.
    16. Fan, Cunlong & Montewka, Jakub & Bolbot, Victor & Zhang, Yang & Qiu, Yuhui & Hu, Shenping, 2024. "Towards an analysis framework for operational risk coupling mode: A case from MASS navigating in restricted waters," Reliability Engineering and System Safety, Elsevier, vol. 248(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:gam:jeners:v:15:y:2022:i:15:p:5622-:d:879336. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.