IDEAS home Printed from https://ideas.repec.org/a/wsi/ijmpcx/v26y2015i03ns0129183115500345.html
   My bibliography  Save this article

Modality transition-based network from multivariate time series for characterizing horizontal oil–water flow patterns

Author

Listed:
  • Mei-Shuang Ding

    (School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, P. R. China)

  • Ning-De Jin

    (School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, P. R. China)

  • Zhong-Ke Gao

    (School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, P. R. China)

Abstract

The simultaneous flow of oil and water through a horizontal pipe is a common occurrence during petroleum industrial processes. Characterizing the flow behavior underlying horizontal oil–water flows is a challenging problem of significant importance. In order to solve this problem, we carry out experiment to measure multivariate signals from different flow patterns and then propose a novel modality transition-based network to analyze the multivariate signals. The results suggest that the local betweenness centrality and weighted shortest path of the constructed network can characterize the transitions of flow conditions and further allow quantitatively distinguishing and uncovering the dynamic flow behavior underlying different horizontal oil–water flow patterns.

Suggested Citation

  • Mei-Shuang Ding & Ning-De Jin & Zhong-Ke Gao, 2015. "Modality transition-based network from multivariate time series for characterizing horizontal oil–water flow patterns," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 26(03), pages 1-14.
    • Handle: RePEc:wsi:ijmpcx:v:26:y:2015:i:03:n:s0129183115500345
    DOI: 10.1142/S0129183115500345
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0129183115500345
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0129183115500345?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:wsi:ijmpcx:v:26:y:2015:i:03:n:s0129183115500345. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijmpc/ijmpc.shtml .

    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.