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Risk Assessment of Slope Failure Using Assumption of Maximum Area of Sliding Mass and Factor of Safety Equal to Unit

Autor(en):


Medium: Fachartikel
Sprache(n): en 
Veröffentlicht in: Advances in Civil Engineering, , v. 2019
Seite(n): 1-11
DOI: 10.1155/2019/6268079
Abstrakt:

This paper aims to develop an effective tool for quantifying the risk of slope failure and identifying the sources of failure risk by combining the limit equilibrium method and the assumption of maximum area of sliding mass with factor of safety = 1. The assumption adopted in this study is firstly validated through the results from the homogeneous slope model, the laboratory experiment, and the smoothed particle hydrodynamics (SPH) program, respectively. Secondly, the proposed method is implemented through the quantification of slope failure risk and the identification of failure sources for a homogeneous slope and a cohesive slope. The conventional method which quantifies the failure risk based on the slip surface with minimum factor of safety (FS) is also performed to enable the comparison with the proposed method. The comparative study has demonstrated that the conventional method tends to underestimate the failure risk due to the negligence of the whole failure process as compared with the proposed method. The failure risk has a tendency to increase as vertical spatial variability of friction angle and Su grow less significant for both proposed method and conventional method. However, the failure sources identified by the conventional method are more likely to decrease as the vertical spatial variability of Su becomes less significant for cohesive slope, whereas the proposed method is able to find a nearly constant number of failure sources by considering the whole process of slope failure. As a result, it is worthwhile to point out that attention is highly recommended to be focused on the failure sources when the spatial variability is less significant, even if it is not considered during the risk mitigation and reinforcing works.

Copyright: © 2019 Xuesong Chu et al.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

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  • Reference-ID
    10311736
  • Veröffentlicht am:
    17.04.2019
  • Geändert am:
    11.07.2019