4.7 Article

Estimation of probability distribution of shear strength of slip zone soils in Middle Jurassic red beds in Wanzhou of China

Journal

LANDSLIDES
Volume 14, Issue 6, Pages 2165-2174

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s10346-017-0890-z

Keywords

Landslides; Probability density function; The Middle Jurassic red beds; Slip zone soil; Shear strength

Funding

  1. National Natural Science Foundation of China [41572289, 41572292]

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Due to the heterogeneity of geological materials, the shear strength of slip zone soils varies randomly. In general, the probability distribution of shear strength is determined empirically or tested by the few numbers of collected soil samples. However, the calculated failure probability of landslide could not be reliable due to oversimplified estimation of the shear strength. Thereby, it is necessary to analyze the random distribution types of shear strength systematically. This paper aims to analyze random properties of shear strength of slip zone soils in Middle Jurassic red beds which are the typical Slip Prone Strata. The shear strength of Jurassic red beds varies spatially due to the complexity of bedding history and tectonics. Two thousand eight hundred five results of shear tests are collected from 44 landslides in the Middle Jurassic red beds in Wanzhou of China. The goodness-of-fit test was applied to determine probability distribution of soils. The minimum acceptant level values of natural friction angle peak, natural residual friction angle, saturated friction angle peak, and saturated residual friction angle in three distribution types are 0.739, 0.75, 0.319, and 0.858. And natural cohesion peak, natural residual cohesion, saturated residual cohesion, and saturated cohesion peak are 0.819, 0.67, 0.888, and 0.225. Results indicate that friction angle fits normal distribution perfectly, and cohesion matches log-normal distribution very well except that saturated cohesion peak agrees beta distribution best. The findings obtained from this study are very useful in the probabilistic analysis of slope in similar areas with the same backgrounds.

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