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祁小辉, 李典庆, 周创兵, 方国光. 考虑土体空间变异性的边坡最危险滑动面随机分析方法[J]. 岩土工程学报, 2013, 35(4): 745-753.
引用本文: 祁小辉, 李典庆, 周创兵, 方国光. 考虑土体空间变异性的边坡最危险滑动面随机分析方法[J]. 岩土工程学报, 2013, 35(4): 745-753.
QI Xiao-hui, LI Dian-qing, ZHOU Chuang-bing, PHOON Kok-kwang. Stochastic analysis method of critical slip surfaces in soil slopes considering spatial variability[J]. Chinese Journal of Geotechnical Engineering, 2013, 35(4): 745-753.
Citation: QI Xiao-hui, LI Dian-qing, ZHOU Chuang-bing, PHOON Kok-kwang. Stochastic analysis method of critical slip surfaces in soil slopes considering spatial variability[J]. Chinese Journal of Geotechnical Engineering, 2013, 35(4): 745-753.

考虑土体空间变异性的边坡最危险滑动面随机分析方法

Stochastic analysis method of critical slip surfaces in soil slopes considering spatial variability

  • 摘要: 现有边坡可靠度研究均未考虑土体空间变异性对边坡最危险滑面的影响。为此,提出了考虑土体空间变异性的边坡最危险滑动面随机分析方法。首先,采用谱表现法建立了表征土体空间变异性的随机场模型。在此基础上,提出了基于SIGMA/W和SLOPE/W的自动定位搜索最危险滑动面方法。其次,采用非侵入式随机分析方法研究了抗剪强度参数空间变异性对边坡最危险滑动面空间分布的影响。最后,采用算例验证了所提方法的有效性。结果表明:提出的边坡最危险滑动面随机分析方法能够有效地确定边坡最危险滑动面空间分布特征。土体抗剪强度参数的空间变异性对边坡最危险滑动面的空间分布特征有重要的影响,它直接决定了边坡最危险滑动面的位置和滑体规模。土体抗剪强度参数波动范围越大,最危险滑动面的空间分布范围越大。随着土体抗剪强度参数水平向和竖直向波动范围比值的增大,边坡上部发生局部滑动的可能性增大。抗剪强度参数的变异系数越大,最危险滑动面的空间分布范围越大,边坡发生小规模局部滑动的可能性越大。

     

    Abstract: The effect of spatial variability in soil parameters on the critical slip surfaces has not been investigated substantially. Therefore, this paper aims to propose a stochastic method to determine the critical slip surfaces in soil slopes considering spatial variability of soil strength properties. First, the spectral representation method is adopted to simulate random field of spatially varying soils. Based on this random field model, the critical slip surface is determined by means of the auto-searching method with SIGMA/W and SLOPE/W. Second, the effect of spatial variability in soil parameters on the characteristics of the critical slip surfaces is investigated using a non-intrusive stochastic analysis method. Finally, an illustrative example is presented to demonstrate the validity of the proposed method. The results indicate that the proposed stochastic method can determine the characteristics of the critical slip surfaces effectively. The spatial variability has a significant influence on the position and scale of the critical slip surfaces. The longer the scale of fluctuation is, the wider the critical slip surface distribution is. The possibility of upper-located local sliding increases with the increasing ratio of horizontal fluctuation scale to vertical fluctuation scale. As the coefficients of variation of soil parameters increase, the range of critical slip surface will increase, and small-scale local sliding is more likely to happen.

     

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