HE Shu-jun, ZHANG Chun-shan, WU Shu-ren. 2008: Reliability analysis of the multi-layer landslide in loess based on the Monte-Carlo simulating method. Geological Bulletin of China, 27(11): 1822-1831.
    Citation: HE Shu-jun, ZHANG Chun-shan, WU Shu-ren. 2008: Reliability analysis of the multi-layer landslide in loess based on the Monte-Carlo simulating method. Geological Bulletin of China, 27(11): 1822-1831.

    Reliability analysis of the multi-layer landslide in loess based on the Monte-Carlo simulating method

    • The slope stability analysis is the limit equilibrium method generally adopted in engineering designs. In order to calculate the stability factor of landslides, rock and soil and the calculating model will be usually simplified, some subordinate factors influencing landslide stability are neglected and all kids of primary influence factors of landslides will be commonly regarded as confirming parameters in calculation. Because of non-homogeneity of rocks and soils themselves of landslides and randomness and variability of confirming parameters, the real security degree of the entire landslide cannot be objectively reflected with the only stability factor. Take the Xiayahe landslide for example, it is confirmed by detailed field survey, geotechnical exploration and indoor geotechnical experiments that the landslide with four layers is difficult to calculate by a single slide layer. So stability factors of the four-layer landslide are firstly calculated with the overplus-pushing method. Then the probability and reliability of the four-layer landslide are obtained with the Monte-Carlo simulating method. Thus the security degree of the four-layer Xiayahe landslide is expressed quantitatively. Comparative analysis of the stability factors and instability probability of the four-layer Xiayahe landslide and comprehensive evaluation of the stability and risk probability of the four-layer landslide provide a basis for the engineering control and prediction and early-warning of the landslide and hazard danger evaluation.
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