考虑各向异性空间变异性的边坡可靠度分析

在边坡可靠度分析中，通常采用横观各向异性或各向同性随机场来刻画土体参数的空间变异特性，而忽略了土体参数的各向异性空间变异性，从而可能会得出错误的可靠度评价结果。为此，建立考虑各向异性空间变异性的边坡可靠度随机有限差分方法（RFDM）计算框架，并以一般各向异性空间变异性边坡为参考边坡，从波动范围方向结构、互相关系数、变异系数和波动范围等方面系统地探讨各向异性空间变异性对边坡可靠度的影响。结果表明：基于坐标转换的各向异性随机场模拟方法可以有效地刻画土体参数各向异性空间变异性；应变聚类边坡临界滑面搜索算法适用于复杂临界滑面的精确搜索；相比一般各向异性空间变异性，旋转各向异性空间变异性会高估边坡失效概率，横观各向异性空间变异性会严重低估边坡失效概率，而各向同性空间变异性会在较大和较小的波动范围内分别高估和低估边坡失效概率。

Analysis on slope reliability considering anisotropic spatial variability of soil parameters

In current slope reliability analysis, the failure probability might be wrongly calculated because of the inadequate consideration of anisotropic spatial variability of soil parameters. Therefore, a random finite difference method (RFDM) framework considering anisotropic spatial variability is established. Taking the general anisotropic spatial variability slope as a reference slope, the influence of anisotropic spatial variability on slope reliability is systematically studied from the aspects of fluctuation range direction structure, cross-correlation coefficient, variation coefficient and fluctuation range. The results show that the coordinate-transformation-based anisotropic random field simulation method can effectively characterize anisotropic spatial variability of soil parameters. Strain-clustering-based slope critical slip surface searching algorithm can accurately determine the complex critical sliding surface of slope. Compared with the general anisotropic spatial variability, the slope failure probability is overestimated and greatly underestimated when considering rotational anisotropy and transverse anisotropy, respectively. In addition, considering isotropic random fields can overestimate and underestimate the slope failure probability in case of greater and smaller scale of fluctuation, respectively.