IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v101y2020i1d10.1007_s11069-020-03863-7.html
   My bibliography  Save this article

Stochastic assessment of slope failure run-out triggered by earthquake ground motion

Author

Listed:
  • Yu Huang

    (Tongji University
    Tongji University)

  • Geye Li

    (Tongji University)

  • Min Xiong

    (Tongji University)

Abstract

Analysis of the run-out of landslides is essential and vital for disaster mitigation. However, accurate run-out analysis is difficult because of the uncertainty of earthquake ground motion and variability of soil properties. To solve this problem, a new run-out assessment framework that combines the methods of probability density evolution and smoothed particle hydrodynamics is proposed. This novel framework can consider multiple stochastic factors and different slope failure models of changing sliding surfaces. We used a homogeneous 2D slope as an example and generated stochastic seismic loading samples with an intensity-frequency non-stationary ground motion model. Soil property parameters (cohesion and internal friction angle) were assumed to obey logarithmic normal distribution, and run-out parameters were evolved. Moreover, based on an equivalent extreme event, the distributions of final run-out parameters were obtained. In an example with slope height of 100 m and angle of 45°, the probability that the run-out distance is

Suggested Citation

  • Yu Huang & Geye Li & Min Xiong, 2020. "Stochastic assessment of slope failure run-out triggered by earthquake ground motion," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 101(1), pages 87-102, March.
    • Handle: RePEc:spr:nathaz:v:101:y:2020:i:1:d:10.1007_s11069-020-03863-7
    DOI: 10.1007/s11069-020-03863-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-020-03863-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-020-03863-7?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ma, Guotao & Rezania, Mohammad & Mousavi Nezhad, Mohaddeseh & Phoon, Kok-Kwang, 2024. "Multivariate copula-based framework for stochastic analysis of landslide runout distance," Reliability Engineering and System Safety, Elsevier, vol. 250(C).

    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:spr:nathaz:v:101:y:2020:i:1:d:10.1007_s11069-020-03863-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.