基于模型修正的空间变异边坡可靠度分析方法

MODEL CORRECTION FACTOR METHOD BASED APPROACH FOR RELIABILITY ANALYSIS OF SPATIALLY VARIABLE SLOPES

空间变异边坡可靠度计算需要进行多次重复性边坡稳定性分析,常用的边坡稳定性分析极限平衡方法(LEM)计算效率较高而有限元方法(FEM)可捕捉真实的边坡失效机制,边坡可靠度评价中如能充分利用这两者的优势将具有重要的工程价值。该文在发展考虑参数空间变异性边坡可靠度分析的一阶可靠度方法(FORM)基础上,提出基于模型修正的空间变异边坡可靠度分析方法,引入一修正系数将基于LEM的简化极限状态面逐渐修正为基于FEM的准确极限状态面,最后基于修正系数和LEM安全系数计算公式采用线抽样法计算边坡失效概率。通过一个考虑参数空间变异性的摩擦/粘性土坡算例验证提出方法的有效性,并探讨土体参数空间变异性和黏聚力与内摩擦角之间互相关性对边坡可靠度的影响。结果表明:提出方法的边坡可靠度计算精度与基于FEM子集模拟方法一致,但是计算效率远远大于后者,尤其对于低概率水平边坡可靠度问题,从而为解决考虑土体参数空间变异性的低概率水平边坡可靠度问题提供一条新的途径。

Reliability analysis of spatially variable slopes involves repeatedly evaluating the slope stability using a deterministic analysis method such as the limit equilibrium method(LEM)or the finite element method(FEM).The LEM is conceptually simple and computationally efficient,while the FEM tends to give a more realistic prediction of slope failure mechanism,particularly when considering the spatial variability of soil properties.Thus,it is of great interest to adopt advantages of both LEM and FEM in estimating the reliability of slope stability.This paper aims to propose a model correction factor method(MCFM)based approach for reliability analysis of spatially variable slopes.In this approach,first-order reliability method is adopted for slope reliability analysis considering spatial variation.A model correction factor is introduced to modify the idealized LEM-based limit-state surface to the more accurate FEM-based limit-state surface.Finally,a line sampling is adopted to estimate the probability of slope failure based on the corrected LEM model with the model correction factor.The reliability assessment of a cohesive-frictional slope example is studied to investigate the performance of the proposed approach considering the spatial variability of the soil strength parameters.The results indicate the proposed approach not only provides an accurate estimation of probability of failure consistent with that obtained from the FEM-based subset simulation,but also significantly reduces the number of finite element analyses of slope stability.Thus,it provides an effective and versatile tool for slope reliability analysis at low-probability levels considering the spatial variability of the soil strength parameters.