IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v233y2019i6p1106-1121.html
   My bibliography  Save this article

Dynamic reliability evaluation of vehicle–track coupled systems considering the randomness of suspension and wheel–rail parameters

Author

Listed:
  • Yahui Zhang
  • Wei Wang
  • Huajiang Ouyang

Abstract

The ride quality and running safety of high-speed trains are directly influenced by uncertainties of some key parameters, such as the damping and stiffness coefficients of suspension systems, wheel–rail coefficient of friction and wheel–rail profiles. Dynamic reliability problems of vehicle–track coupled systems under the influence of the above random parameters are studied in this article. An efficient numerical method is presented by combining a prediction-based iterative solution technique with subset simulation method. The solution efficiency of deterministic responses is improved by means of efficient prediction of wheel–rail forces, and the number of deterministic solutions required is reduced by expressing a small failure probability as a product of large conditional probabilities. The accuracy and the efficiency of the present method are verified by comparing with the direct Monte Carlo simulation. The failure probability distribution curves of the lateral ride index on straight track and the derailment coefficient during curve negotiation are obtained and the reliability sensitivity analyses are also carried out. The main conclusions are given as follows: the reliability of the system is higher when the randomness of the parameters with greater sensitivity is not considered; the increase of the damping of anti-yaw damper or the wheel–rail coefficient of friction will improve the ride quality on straight track, but will lower the running safety when negotiating a curved track.

Suggested Citation

  • Yahui Zhang & Wei Wang & Huajiang Ouyang, 2019. "Dynamic reliability evaluation of vehicle–track coupled systems considering the randomness of suspension and wheel–rail parameters," Journal of Risk and Reliability, , vol. 233(6), pages 1106-1121, December.
  • Handle: RePEc:sae:risrel:v:233:y:2019:i:6:p:1106-1121
    DOI: 10.1177/1748006X19863640
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X19863640
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1748006X19863640?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
    ---><---

    References listed on IDEAS

    as
    1. Tee, Kong Fah & Khan, Lutfor Rahman & Li, Hongshuang, 2014. "Application of subset simulation in reliability estimation of underground pipelines," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 125-131.
    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. Yu, Weichao & Huang, Weihe & Wen, Kai & Zhang, Jie & Liu, Hongfei & Wang, Kun & Gong, Jing & Qu, Chunxu, 2021. "Subset simulation-based reliability analysis of the corroding natural gas pipeline," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    2. Kong Fah Tee & Andrew Utomi Ebenuwa, 2019. "Combination of line sampling and important sampling for reliability assessment of buried pipelines," Journal of Risk and Reliability, , vol. 233(2), pages 139-150, April.
    3. Zhou, Xingyuan & van Gelder, P.H.A.J.M. & Liang, Yongtu & Zhang, Haoran, 2020. "An integrated methodology for the supply reliability analysis of multi-product pipeline systems under pumps failure," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    4. Liu, Fuchao & Wei, Pengfei & Tang, Chenghu & Wang, Pan & Yue, Zhufeng, 2019. "Global sensitivity analysis for multivariate outputs based on multiple response Gaussian process model," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 287-298.
    5. Chemweno, Peter & Pintelon, Liliane & Muchiri, Peter Nganga & Van Horenbeek, Adriaan, 2018. "Risk assessment methodologies in maintenance decision making: A review of dependability modelling approaches," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 64-77.
    6. Li, Yuyin & Zhang, Yahui & Kennedy, David, 2018. "Reliability analysis of subsea pipelines under spatially varying ground motions by using subset simulation," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 74-83.
    7. Kong Fah Tee & Lutfor Rahman Khan & Tahani Coolen-Maturi, 2015. "Application of receiver operating characteristic curve for pipeline reliability analysis," Journal of Risk and Reliability, , vol. 229(3), pages 181-192, June.

    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:sae:risrel:v:233:y:2019:i:6:p:1106-1121. 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: SAGE Publications (email available below). General contact details of provider: .

    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.