IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v353y2024ipbs0306261923015118.html
   My bibliography  Save this article

A novel in-depth intelligent evaluation approach for the gas drainage effect from point monitoring to surface to volume

Author

Listed:
  • Tongqiang, Xia
  • Diao, Li
  • Xiaolin, Li
  • Xin, Yan
  • J.G., Wang

Abstract

Developing a comprehensive and intelligent evaluation approach for dynamic gas extraction parameters is especially important for the operation and management of gas drainage in coal mines. However, existing approaches lack an in-depth intelligent evaluation approach for acquiring surface parameters of gas flow and volume characteristic parameters of the entire drainage area from the finite monitoring data. To fill this gap, a novel Field-Zone-Network model as a unique approach were presented to overcome the above-mentioned challenges, with innovative multi-parameter solution and inversion models. It utilized advanced mathematical algorithms for parameter estimation of gas drainage, by integrating the finite monitoring points data of pipe network and physical characteristic parameters of pipe network and coal seam. The model's accuracy and reliability were validated through rigorous comparisons with field data collected from coal mines and numerical simulations conducted in simulated scenarios. It realized the sufficient mining of finite monitoring data from points (monitoring points) to surface (network) to volume (coal seam). Further, the newly comprehensive software was developed to enable real-time monitoring, analysis, and evaluation of gas drainage effect, providing valuable insights for optimizing extraction operations in coal mines. This research contributes to the advancement of gas drainage in coal mines by presenting a novel Field-Zone-Network model and comprehensive software, empowering efficient and intelligent gas extraction operations with enhanced monitoring and evaluation capabilities.

Suggested Citation

  • Tongqiang, Xia & Diao, Li & Xiaolin, Li & Xin, Yan & J.G., Wang, 2024. "A novel in-depth intelligent evaluation approach for the gas drainage effect from point monitoring to surface to volume," Applied Energy, Elsevier, vol. 353(PB).
  • Handle: RePEc:eee:appene:v:353:y:2024:i:pb:s0306261923015118
    DOI: 10.1016/j.apenergy.2023.122147
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923015118
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2023.122147?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.

    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:appene:v:353:y:2024:i:pb:s0306261923015118. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.