路堤边坡稳定可靠度计算中的模型不确定性分析

基于均质路堤边坡Monte Carlo法的稳定可靠度计算,分析了临界滑面搜索策略和稳定分析方法两类模型不确定性对边坡可靠度的影响特性,讨论了边坡失效概率随土工参数变异性的变化规律。研究表明,选用不同的临界滑面搜索策略所得可靠度结果差异不大,参数滑面法（overall slope）的失效概率略大于均值滑面法（global minimum）,但差别对边坡稳定性分析没有实质性影响;土性参数变异水平是影响边坡可靠度的最重要因素,边坡在相同设计参数安全系数下的可靠度指标随参数变异性增大而急剧降低;不同稳定性分析方法对应的安全系数概率密度函数曲线形态基本一致,但失效概率差异明显,因此目标可靠度指标取值应与稳定性分析方法相适应。提出的考虑土工参数变异水平的安全系数取值修正原则,对改进确定性设计的边坡稳定分析技术有积极意义。     

考虑参数空间变异结构的结构化交叉约束随机场模拟方法研究

斜坡岩土体抗剪强度参数的空间变异性具有一定的结构性。为研究岩土体参数空间变异结构对边坡失效概率的影响,依据变异函数的内涵推导出变程与相关距离的数学变换关系,并在此基础上提出了结构化交叉约束随机场模拟方法,用以模拟具有互相关性的参数随机场。建立了结构化交叉约束随机场计算模型,研究不同空间变异结构的抗剪强度参数对边坡失效概率的影响。研究结果表明:结构化交叉约束随机场可用于生成模拟具有复杂各向异性空间变异结构的参数随机场,由于考虑了随机偏差、条件数据和空间变异结构,能较为真实地反映地层实际参数,数据波动较条件参数插值场小。可靠性分析结果表明:不考虑抗剪强度参数空间结构分析易高估边坡的失效概率;考虑c′和φ′互相关性时,失效概率随着相关系数的增加而增加,当参数间呈负相关性时更容易高估边坡的失效概率。     

不排水抗剪强度非平稳随机场模拟及边坡可靠度分析

边坡可靠度分析中通常假定采用平稳或准平稳随机场表征土体参数的空间变异性,然而大量现场试验数据表明,土体参数如不排水抗剪强度沿土体埋深常呈现明显的非平稳分布特征,即其均值和标准差均随埋深发生变化,因此亟需发展土体参数非平稳随机场模型及其模拟方法。针对目前不能有效单独模拟土体参数趋势分量和随机波动分量的不确定性,提出了一种有效的不排水抗剪强度参数非平稳随机场模型,并给出了土体参数二维非平稳随机场模拟方法计算流程,同时将新提出的模型与现有非平稳随机场模型及平稳随机场模型进行了系统比较。最后通过不排水饱和黏土边坡算例验证了提出模型的有效性,并揭示了不排水抗剪强度非平稳分布特征对边坡可靠度的影响规律。结果表明：提出模型能够有效地单独模拟土体参数趋势分量和随机波动分量的不确定性,考虑土体参数均值和标准差随埋深增加而增大的特性,可为表征土体参数非平稳分布特征提供了一条有效的途径。此外,与采用非平稳随机场模拟土体参数空间变异性相比,采用常用的平稳随机场模型会低估边坡失效概率,从而造成偏危险的边坡工程设计方案。     

考虑参数空间变异性的非饱和土坡可靠度分析

在考虑多个土体参数空间变异性的基础上,提出了基于拉丁超立方抽样的非饱和土坡稳定可靠度分析的非侵入式随机有限元法。利用Hermite随机多项式展开拟合边坡安全系数与输入参数间的隐式函数关系,采用拉丁超立方抽样技术产生输入参数样本点,通过Karhunen-Loève展开方法离散土体渗透系数、有效黏聚力和内摩擦角随机场,并编写了计算程序NISFEM-KL-LHS。研究了该方法在稳定渗流条件下非饱和土坡可靠度分析中的应用。结果表明：非侵入式随机有限元法为考虑多个土体参数空间变异性的非饱和土坡可靠度问题提供了一种有效的分析工具。土体渗透系数空间变异性和坡面降雨强度对边坡地下水位和最危险滑动面位置均有明显的影响。当降雨强度与饱和渗透系数的比值大于0.01时,边坡失效概率急剧增加。当土体参数变异性或者参数间负相关性较大时,忽略土体参数空间变异性会明显高估边坡失效概率。     

基于点估计法的黄土边坡可靠度研究

在不同的黄土地区选取4个工点的典型路堑高边坡,基于点估计理论和有限元强度折减法计算边坡可靠指标。结果表明:工点2的稳定系数虽达到1.46,却有19.2%的失效概率; 工点1和4的坡型、地层岩性及层厚等工况较接近,失效概率差值达29.8%,参数变异性是造成其差异的主要原因。用点估计法计算边坡可靠度,并采用可靠度理论分析黄土边坡稳定性,能较好的解决土性参数离散性对边坡稳定性评价的影响。     

约束随机场下的边坡可靠度随机有限元分析方法

目前边坡可靠度中常用的简化分析方法,不考虑边坡土体的空间变异性,每次计算整个边坡都取用相同的强度参数,由离散点试样试验得到的土体参数统计特性只能反映点特性,而边坡的稳定性受滑面上平均抗剪强度特性控制,因此,需要考虑空间范围内的平均特性。描述空间变异性的随机场理论对变异性较高的土体,实际上高估了其空间变异性。把随机场理论和地质统计中的区域化变量理论结合起来,建立约束随机场,并在此基础上进行Monte-Carlo随机有限元分析。计算实例表明,在高变异性条件下约束随机场能有效降低完全随机场的模拟方差,得到更低的破坏概率。对比了随机有限元和简化法的计算结果表明,简化法在土体强度变异性很高时其结果并非偏于保守。另外也指出了可靠度分析中存在的边坡尺度效应和简化法的适用条件。     

考虑参数旋转各向异性空间变异性的边坡大变形概率分析

为揭示土体参数旋转各向异性空间变异性对边坡大变形特征的影响规律,将土体不排水抗剪强度参数模拟为旋转各向异性随机场,提出采用多重响应面法对随机场样本进行边坡稳定性安全系数高效求解和升序排列,进而使用随机物质点法按序模拟随机场样本的边坡大变形过程.以一饱和不排水粘土边坡为例,研究了旋转各向异性随机场的旋转角度β和弱主方向自相关长度θ₂对边坡大变形特征和破坏模式的影响.结果表明：提出的基于多重响应面的随机物质点方法可以高效开展边坡大变形概率分析;β和θ₂对边坡大变形特征和破坏模式均有显著影响;边坡大变形破坏的影响距离、滑动距离和滑动体积的平均值与标准差均随θ₂的增加而增加;边坡大变形过程中可能产生4种破坏模式,其中深层滑动和渐进式滑动为该边坡模型的主要概率失稳模式.因此,提出的方法为边坡大变形概率分析提供了一条有效途径,考虑参数旋转各向异性空间变异性的边坡大变形概率分析对准确评估边坡失稳风险具有一定的理论参考意义.     

基于多重响应面法的空间变异土坡系统可靠度分析

空间变异土坡可靠度问题应该视为系统可靠度问题,多重响应面法为高效、准确地对其进行求解提供了一条有效途径。针对单一滑面确定了合理的空间变异土坡安全系数的响应面形式,并探讨了可靠度分析精度和随机场离散精度间的近似线性关系。建立基于大量潜在滑面的多重响应面,计算系统失效概率,并识别其中的代表性滑面。通过两个土坡算例验证所提方法的有效性。结果表明:随着空间变异性的增强,土坡可靠度的系统性增强,单一滑面的失效概率将显著低估土坡整体失效概率;通过控制随机场离散精度,可以事先保证一定的可靠度分析精度,从而有效地避免离散出过多并不重要的随机变量;合理地选择多重响应面形式有利于进一步提高计算效率和计算精度;多重响应面法可以同时分析所有潜在滑面的失效概率以及系统失效概率,并识别出代表性滑面,为边坡防治提供参考。     

岩土参数相关性的地基承载力模糊可靠性分析

地基的失效可视为模糊事件。影响地基承载力因素表现出空间变异性。根据随机场理论描述土性参数的空间变异性,考虑土性参数的自相关性及其互相关性,得出参数间的相关性在可靠性分析中不可忽视的结论。     

基于有限元强度折减法的边坡动力稳定性可靠性分析

传统有限元强度折减法在边坡稳定性数值分析中取得了一定的成功,但由于未考虑岩土体材料参数的变异性等不确定性因素,尚不能直接应用于边坡稳定性特别是动力稳定性可靠性分析问题。为此提出了基于有限元强度折减法的地震边坡动力稳定性可靠性分析方法。将有限元极限分析法、动力分析法和可靠性分析法三者耦合,分析求解边坡在地震作用下的动力稳定性可靠性问题,并将这一过程在数值计算程序中得以实现。在计算分析过程中,克服了原方法需不断人工试算才能得到边坡安全系数而无法量化处理问题,并对边坡动力失效准则进行了适用于程序化的改进,使其计算过程完全实现自主运行。结合典型算例分析结果表明,该方法显著的特点是能较全面地反映岩土体的动力特性和边坡岩土体材料强度参数的变异性及相关性,所得结果相对更加合理且更符合工程实际。该方法既是对有限元强度折减法的应用范围的有益推广,也为边坡动力稳定性可靠性问题研究提供了一条新的有效途径。     

基于FELA的随机场方法在考虑降雨入渗的边坡开挖稳定性分析中的应用

黑山共和国南北高速公路项目部分路段处于复理石地区,降雨集中、空间变异性显著且分层分布的岩土体给道路边坡施工带来了挑战。条分法、常规有限元法等确定性分析方法不能考虑岩土材料的不确定性,给出的具有唯一性、确定性的结果不能反映边坡稳定的不确定性。以该工程某边坡为例,采用有限元极限分析方法（FELA）,考虑岩土材料强度的空间变异性,利用上下限解法得出安全系数的分布区间。由勘察资料得到材料均值、标准差和空间相关长度并重建描述抗剪强度指标的二维随机场,同时考虑开挖岩层的节理分布,分析边坡在分级开挖过程中,各施工步骤的稳定性和破坏模式。与有限元分析结果相比,随机场条件下,部分情况开挖阶段安全系数低于限值,并出现局部破坏和整体破坏两种形式。结合不饱和土理论,模拟暴雨情况下雨水的入渗深度并在饱和区采用降低后的强度参数重新计算。通过蒙特卡洛模拟,得到各工况下安全系数、滑动体体积、挡墙弯矩和锚杆内力的概率密度分布函数。挡墙结构约束土体的变形,使得破坏模式趋向于整体破坏,安全系数分布区间变小。锚杆能带动更多土体进入工作状态,同样约束安全系数分布区间。旱季施工与雨季施工边坡破坏区域不同,同等支护条件下,雨季边坡安全系数分布区间更大,且均值明显降低。      

Probabilistic modelling of auto-correlation characteristics of heterogeneous slopes

Spatial variability of soil materials has long been recognised as an important factor influencing the reliability of geo-structures. This study stochastically investigates the influence of spatial variability of shear strength on the stability of heterogeneous slopes, focusing on the auto-correlation function, auto-correlation distance and cross-correlation between soil parameters. The finite element method is merged with the random field theory to probabilistically evaluate factor of safety and probability of failure via Monte-Carlo simulations. The simulation procedure is explained in detail with suggestions on improving efficiency of the Monte-Carlo process. A simple procedure to create cross-correlation between random variables, which allows direct comparison of the influence of each strength variable, is discussed. The results show that the auto-correlation distance and cross-correlation can significantly influence slope stability, while the choice of auto-correlation function only has a minor effect. An equation relating the probability of failure with the auto-correlation distance is suggested in light of the analyses performed in this work and other results from the literature.     

Conditional random field reliability analysis of a cohesion-frictional slope

Discarding known data from cored samples in the reliability analysis of a slope in spatially variable soils is a waste of site investigation effort. The traditional unconditional random field simulation, which neglects these known data, may overestimate the simulation variance of the underlying random fields of the soil properties. This paper attempts to evaluate the reliability of a slope in spatially variable soils while considering the known data at particular locations. Conditional random fields are simulated based on the Kriging method and the Cholesky decomposition technique to match the known data at measured locations. Subset simulation (SS) is then performed to calculate the probability of slope failure. A hypothetical homogeneous cohesion-frictional slope is taken as an example to investigate its reliability conditioned on several virtual samples. Various parametric studies are performed to explore the effect of different layouts of the virtual samples on the factor of safety (FS), the spatial variation of the critical slip surface and the probability of slope failure. The results suggest that whether the conditional random fields can be accurately simulated depends highly on the ratio of the sample distance and the autocorrelation distance. Better simulation results are obtained with smaller ratios. Additionally, compared with unconditional random field simulations, conditional random field simulations can significantly reduce the simulation variance, which leads to a narrower variation range of the FS and its location and a much lower probability of failure. The results also highlight the great significance of the conditional random field simulation at relatively large autocorrelation distances.     

Modeling uncertainty in stability analysis for design of embankment dams on difficult foundations

A probabilistic 3-D slope stability analysis model (PTDSSAM) is developed to evaluate the stability of embankment dams and their foundations under conditions of staged construction taking into consideration uncertainty, spatial variabilities and correlations of shear strength parameters, as well as the uncertainties in pore water pressure. The model has the following capabilities: (1) conducting undrained shear strength analysis (USA) and effective stress analysis (ESA) slope stability analysis of staged construction, (2) incorporation of field monitored data of pore water pressure, and (3) incorporation of increase of undrained shear strength with depth, effective stress, and pore water pressure dissipation. The PTDSSAM model is incorporated in a computer program that can analyze slopes located in multilayered deposits, considering the total slope width.

The main outputs of the program are the geometric parameters of the most critical sliding surface (i.e., center of rotation/radius of rotation and critical width of failure), mean 2-D safety factor, mean 3-D safety factor, squared coefficient of variation of resisting moment, and the probability of slope failure. The program is applied to a case study, Karameh dam in Jordan. Monitored data of induced pore water pressure in the dam embankment and soft foundation were gathered during dam construction.

The stability of Karameh dam embankment and foundation was evaluated during staged construction using deterministic and probabilistic analysis. Foundation stability was evaluated based on the monitored data of pore water pressure.

The study showed that the mean values of the corrective factors which account for the discrepancies between the in situ and laboratory-measured values of soil properties and for the modeling errors have significant influence on the 2-D safety factor, 3-D safety factor, slope probability of failure, and on the expected failure width.

The degree of spatial correlation associated with shear strength parameters within a soil deposit also influences the probability of slope failure and the expected failure width. This correlation is quantified by scale of fluctuation. It is found that a larger scale of fluctuation gives an increase in the probability of slope failure and a reduction in the critical failure width.     

Probabilistic failure analysis of infinite slopes under random rainfall processes and spatially variable soil

Rainfall-induced landslides occur during or immediately after rainfall events in which the pore water pressure builds up, leading to shallow slope failure. Thereby, low permeability layers result in high gradients in pore water pressure. The spatial variability of the soil permeability influences the probability such low permeability layers, and hence the probability of slope failure. In this paper, we investigate the influence of the vertical variability of soil permeability on the slope reliability, accounting for the randomness of rainfall processes. We model the saturated hydraulic conductivity of the soil with a one-dimensional random field. The random rainfall events are characterised by their duration and intensity and are modelled through self-similar random processes. The transient infiltration process is represented by Richards equation, which is evaluated numerically. The reliability analysis of the infinite slope is based on the factor of safety concept for evaluating slope stability. To cope with the large number of random variables arising from the discretization of the random field and the rainfall process, we evaluate the slope reliability through Subset Simulation, which is an adaptive Monte Carlo method known to be especially efficient for reliability analysis of such high-dimensional problems. Numerical investigations show higher probability of slope failure with increased spatial variability of the saturated hydraulic conductivity and with more uniform rainfall patterns.     

基于场变量的边坡稳定分析有限元强度折减法?

有限元强度折减法在实施过程中往往要根据不同的折减系数手工修改输入文件,并不断进行试算,过程较繁琐。为了简化计算过程,提高计算效率,在有限元强度折减法的基础上,结合ABAQUS提供的场变量,提出一种适用于有限元强度折减计算的新方法--基于场变量的有限元强度折减法。通过在ABAQUS中设置岩土体黏聚力与内摩擦角为场变量的函数,场变量为增量步时间t的函数,从而通过控制增量步时间t实现黏聚力与内摩擦角的折减,通过一次计算即可求得边坡的安全系数,无需手工修改折减系数反复试算。结合有关文献对该方法用于边坡稳定分析的可行性进行了验证,并与二分法确定安全系数的计算效率进行了比较。结果表明：该方法求得的安全系数是有效可靠的,用于边坡稳定性的计算是可行的,简化了有限元强度折减法的计算过程,提高了计算效率。     

基于饱和渗透系数空间变异结构的斜坡渗流及失稳特征

以往研究一般采用单随机变量方法（SRV）或基于水平或垂直方向波动范围生成的空间变异随机场来模拟岩土参数的空间变异性,对具有倾斜定向特征的空间变异随机场未有涉及.基于条件模拟相关理论和非侵入式随机有限元的理论框架,提出了利用序贯高斯模拟方法进行斜坡参数条件随机场模拟并运用有限元方法进行斜坡渗流和稳定性分析的方法.针对理想边坡,对各向同性和几何各向异性的共7种空间变异结构的饱和渗透系数（K_s）各进行了200次条件随机场模拟,基于条件随机场模拟结果进行了有限元渗流和稳定性计算,对每种空间变异结构多次计算结果进行了统计分析.结果表明:本文所提出的方法不仅再现了研究区域参数的空间二阶统计特性,通过设定变异函数参数进行不同空间变异类型、变异程度、变异定向性的随机场模拟,同时利用现场观测数据对随机场模拟结果进行条件限制,从而提高了随机场的赋值精度;K_s的空间变异结构对孔隙水压力的分布规律、地下水位线变化范围、稳定性系数和最危险滑动面分布特征均有一定程度的影响.本研究为库岸斜坡稳定性评价提供方法支撑.