IDEAS home Printed from https://ideas.repec.org/a/taf/tjrtxx/v10y2022i3p393-411.html
   My bibliography  Save this article

Numerical study of dry snow accretion characteristics on the bogie surfaces of a high-speed train based on the snow deposition model

Author

Listed:
  • Lu Cai
  • Zhen Lou
  • Tian Li
  • Jiye Zhang

Abstract

To investigate the distribution of dry snow particles deposited on the bogie surfaces of a high-speed train, a snow particle deposition model based on the critical capture velocity and the critical wind friction speed was established. The suspension motion behaviour of snow particles in the air was simulated by the unsteady Reynolds-averaged Navier–Stokes (uRANS) simulations, based on the Realizable k–ε turbulence model and the Discrete Phase Model (DPM). The results show that the crossbeam of the bogie frame, the anti-snake movement dampers, the middle brake shoes of the rear brake rigging, the traction rods and the anti-rolling torsion bars are prone to accumulating snow. Furthermore, the critical capture velocity has a significant effect on the distribution of snow accretion. When the critical capture velocity is changed from 1.0 m/s to 3.0 m/s, the total snow accumulation on the bogie will increases by 20%.

Suggested Citation

  • Lu Cai & Zhen Lou & Tian Li & Jiye Zhang, 2022. "Numerical study of dry snow accretion characteristics on the bogie surfaces of a high-speed train based on the snow deposition model," International Journal of Rail Transportation, Taylor & Francis Journals, vol. 10(3), pages 393-411, May.
  • Handle: RePEc:taf:tjrtxx:v:10:y:2022:i:3:p:393-411
    DOI: 10.1080/23248378.2021.1918589
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23248378.2021.1918589
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/23248378.2021.1918589?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.

    More about this item

    Statistics

    Access and download statistics

    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:taf:tjrtxx:v:10:y:2022:i:3:p:393-411. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tjrt20 .

    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.