›› 2015, Vol. 36 ›› Issue (S2): 665-672.doi: 10.16285/j.rsm.2015.S2.094

• Numerical Analysis • Previous Articles     Next Articles

Analysis of model uncertainty for stability reliability of embankment slope

WU Xing-zheng1, 2, JIANG Liang-wei1, 2, LUO Qiang1, 2, KONG De-hui1, 2, ZHANG Liang1, 2   

  1. 1. School of Civil Engineering, Southwest Jiaotong University, Chengdu, Sichuan 610031, China; 2. MOE Key Laboratory of High-speed Railway Engineering, Southwest Jiaotong University, Chengdu, Sichuan 610031,China)
  • Received:2014-06-15 Online:2015-08-31 Published:2018-06-14

Abstract: On the basis of reliability index of homogeneous embankment slope calculated with Monte Carlo method, the influences of critical slip surface searching strategy and stability analysis methods on slope reliability computation are analyzed; and the variation characteristic of slope failure probability with the variability of geotechnical parameters is discussed. The results show that: (1) Failure probability calculated by the critical slip surface searching approach of “overall slope” is slightly larger than by “global minimum”; but there is little substantial influence on analysis of slope stability. (2) The variability of geotechnical parameters is the main factor affecting the slope reliability; and the reliability index decreases sharply with increasing variability of parameters. (3) There is nearly same curve shape but various horizontal position of probability density function of safety factor approached with different stability analysis methods; and it result in significant difference of failure probability; so the target reliability index of design should correspond to the adopted stability analysis method. The principle that safety factor value should be modified by considering the geotechnical parameter variability is put forward; it may provide improvement conception to the traditional slope stability analysis which obtained with the mean value of geotechnical parameters.

Key words: embankment slope, stability analysis, Monte Carlo method, model uncertainty, variability of parameters

CLC Number: 

  • U 231.1+1
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