考虑参数空间变异性的失稳边坡参数概率反分析

发布时间：2018-02-28 04:48

本文关键词： 边坡空间变异性贝叶斯更新概率反分析响应面子集模拟　出处：《岩土工程学报》2017年03期 　论文类型：期刊论文

【摘要】：概率反分析能够有效地考虑岩土体参数不确定性并融合现场监测数据和观测信息等更新岩土体参数统计特征,进而使得边坡稳定性评价更为符合客观工程实际,然而目前参数概率反分析几乎没有考虑参数固有空间变异性的影响。结合多重响应面和子集模拟提出了考虑岩土体参数空间变异性的边坡参数概率反分析方法,并以芝加哥国会街切坡为例,融合边坡失稳和滑动面入滑点与出滑点的大致位置这两个现场观测信息,概率反分析得到边坡不排水抗剪强度参数的后验统计特征。结果表明:本文提出方法可以有效地解决考虑参数空间变异性的低概率水平边坡参数概率反分析问题,具有较高的计算效率。子集模拟中每层随机样本数目对计算结果具有重要的影响,常用的500组样本点难以获得满意的计算结果。此外,土体参数空间变异性对概率反分析计算结果具有重要的影响,考虑参数空间变异性边坡参数由平稳随机场更新为非平稳随机场,与工程实际相符,然而忽略参数空间变异性更新后的参数仍服从平稳分布。
[Abstract]:The probability back analysis can effectively consider the uncertainty of rock and soil parameters and fuse the statistical characteristics of rock and soil parameters such as field monitoring data and observation information, thus making the slope stability evaluation more in line with the objective engineering practice. However, at present, the influence of parameter inherent spatial variability is hardly taken into account in the parameter probability back analysis. A probability back analysis method for slope parameters considering the spatial variability of rock and soil parameters is proposed in combination with multi-response surface and subset simulation. Taking the cut slope of Chicago Capitol Street as an example, the two field observation information of slope instability and the general position of the entry and exit slip points of the sliding surface are fused. The posteriori statistical characteristics of slope undrained shear strength parameters are obtained by probabilistic back-analysis. The results show that the method presented in this paper can effectively solve the problem of probability back-analysis of low-probability horizontal slope parameters considering the spatial variability of parameters. In subset simulation, the number of random samples per layer has an important effect on the calculation results, and the commonly used 500 groups of sample points are difficult to obtain satisfactory results. The spatial variability of soil parameters has an important influence on the calculation results of probability back-analysis. Considering the change of slope parameters from stationary random field to non-stationary random field, it is consistent with engineering practice. However, after ignoring the parameter spatial variability update, the parameters are still obeyed from the stationary distribution.
【作者单位】：南昌大学建筑工程学院;
【基金】：国家自然科学基金项目(51509125,51409139) 江西省教育厅科学技术研究项目(GJJ150033) 长江科学院开发研究基金项目(CKWV2015222/KY)
【分类号】：TU43

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