Abstract
Slopes with fabric anisotropy widely exist in nature due to complex geological depositions and the inherent spatial variability of geomaterials. The soil with fabric anisotropy is herein characterized by a random field, and the factor of safety (FS) of an anisotropic soil slope is calculated by the finite element method. By virtue of Monte Carlo simulations, the statistical characteristics of FS of an undrained clay slope are estimated. The analysis results suggest that the soil fabric anisotropy has a significant effect on the landslide susceptibility. When the anisotropy with rotated angles inclines around 45° or 135°, the probability of slope failure is higher than that at other rotated angles, and the variability of FS reaches its upper limit when the anisotropy inclines parallel to the slope angle. Compared to a slope in uniform soils, an anisotropic soil slope generally has a lower FS, implying potential risks induced by the uniform soil assumption. The possibility of landslide occurrences becomes greater for a longer anisotropic length (i.e., a stronger correlation between neighboring soil properties in a dirction). The results shed lights on the role of appropriately characterizing the geotechnical anisotropy in probabilistic slope stability analyses, which can be further used for a regional landslide susceptibility assessment.
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Funding
This research is supported by the NSFC-NRF 3rd Joint Research Grant (Earth Science) (Grant No. 41861144022) and National Natural Science foundation of China (Grant No. 51879203).
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Appendix
Appendix
Four groups of Monte Carlo simulations with different anisotropic angles were carried out (600 realizations for one group). As shown in Fig.13, the results almost converge to a fixed value as the number of simulations reaches 600 times. The finding indicates that 600 simulations for each parametric study would be a reasonable compromise between computational efforts and accuracy.
Convergence investigation of the number of simulations on (a) mean and (b) coefficient of variation (COV) of the factor of safety based on Monte Carlo simulations
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Ding, YN., Li, DQ., Zarei, C. et al. Probabilistically quantifying the effect of geotechnical anisotropy on landslide susceptibility. Bull Eng Geol Environ 80, 6615–6627 (2021). https://doi.org/10.1007/s10064-021-02197-3
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DOI: https://doi.org/10.1007/s10064-021-02197-3