IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i3p2568-d1052947.html
   My bibliography  Save this article

Research on the Construction of Safety Information Ontology Knowledge Base and Accident Reasoning for Complex Hazardous Production Systems-Taking Methanol Production Process as an Example

Author

Listed:
  • Meng Liu

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

  • Rui Huang

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

  • Fangting Xu

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

Abstract

Taking methanol production as an example, the concept of “ontology” is introduced to construct a safety knowledge ontology, and a safety information knowledge base is created with the help of the Protégé software. These can be used to efficiently handle the massive safety information data of dangerous chemical enterprises, associate all kinds of miscellaneous information, and improve the level of safety management. An accident tree reasoning model is designed to determine the cause of the accident using accident tree reasoning, and to mine the vast knowledge of safety information, according to safety information knowledge and accident tree analysis theory. Using these methods, the storage, processing, and reuse of safety information are realized, the efficiency of safety management can be improved, and the defects caused by incomplete personnel knowledge structure can be avoided.

Suggested Citation

  • Meng Liu & Rui Huang & Fangting Xu, 2023. "Research on the Construction of Safety Information Ontology Knowledge Base and Accident Reasoning for Complex Hazardous Production Systems-Taking Methanol Production Process as an Example," Sustainability, MDPI, vol. 15(3), pages 1-18, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2568-:d:1052947
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/3/2568/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/3/2568/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lv Chang & Qiongqiong Liu & Jin Yan & Peng Liu & Sida Zhu & Xiaoming Hu & Jun Ni & Tong Zhang & Hongtai Yang, 2022. "Risk Field Model Construction and Risk Classification of Hazardous Chemical Transportation," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-13, August.
    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. Huanhuan Wang & Yong Zhang & Runqiu Li & Yan Cui & Andan He & Weiqing Jiang, 2023. "Analyzing the Risk Factors of Hazardous Chemical Road Transportation Accidents Based on Grounded Theory and a Bayesian Network," Sustainability, MDPI, vol. 15(24), pages 1-21, December.

    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:jsusta:v:15:y:2023:i:3:p:2568-:d:1052947. 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.