共查询到18条相似文献，搜索用时 187 毫秒
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约束随机场下的边坡可靠度随机有限元分析方法 总被引：2，自引：1，他引：1
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。 相似文献
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溶蚀岩体随机结构模型建立及其在岩体渗漏评价中的应用 总被引：5，自引：1，他引：4
针对中小规模裂隙和溶蚀洞穴造成的溶蚀岩体渗漏 ,本文提出了溶蚀岩体渗漏评价的一种新思路 :首先对现场开挖所揭露的有限的裂隙和溶蚀洞穴观测资料进行统计分析 ,利用统计分析结果建立溶蚀岩体随机结构模型 ;然后根据随机结构模型所反映出的裂隙和溶蚀洞穴有关参数计算渗透参数 ;最后结合区域水力学条件计算岩体渗漏量。多次模拟后可以得到渗漏量的分布规律。其中 ,建立合理的随机结构模型是关系本方法成败的关键 ,文中给出了建立溶蚀岩体随机结构模型的步骤 ,提供了随机模拟的编程思路和程序框图 ,并结合具体的工程实例对该方法的应用前景进行了讨论 相似文献
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天然岩体内部含有微裂纹,其裂纹的发展贯通机制一直是岩石力学研究的热点问题。此外,岩体物理力学参数的空间变异性,也会影响其强度及破坏演化过程。本文采用了一种新的随机近场动力学方法(RPD),并对含缺陷岩体单轴压缩下的裂纹发展进行模拟,该方法结合了近场动力学方法在模拟裂纹发展及随机场方法在表征材料参数空间变异性方面的优势,使所建模型更接近真实岩体状态。利用MATLAB编程并依托含单一倾斜预制裂缝模型进行了计算程序的准确性验证。结果表明,所采用的随机近场动力学方法可以很好地模拟裂纹发展过程,预制裂缝倾角对后续裂纹发展有较大影响。此外,不考虑岩体物理力学材料参数空间变异性的存在时,会大大低估裂纹发展速度。 相似文献
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随机连续模型分析裂隙岩体耦合行为 总被引：2，自引：1，他引：1
利用能够反映岩体水力性质空间变异特性的随机连续模型对隧洞开挖过程中的裂隙岩体渗流-应力耦合过程进行了数值分析。随机渗透系数场通过顺序指示模拟方法生成。顺序指示法是一种非参数地质统计学技术,他允许输入任何形式的渗透系数概率分布而不需要对分布做任何假设。由随机模拟生成的渗透系数场被投影到有限元计算网格中进行耦合分析。力学响应使用基于连续介质的节理本构模型来反映岩体中软弱面的影响。结果表明,随机连续模型能够较好地预测裂隙岩体的稳定入渗率,水力性质的空间变异性对裂隙介质的耦合过程起着重要作用。在不排水条件下,隧洞每次开挖开始时,由于岩石应力重分布,孔隙水受到扰动,短时间内不能流动平衡,因此孔压会迅速上升,这对于围岩稳定是不利的。 相似文献
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针对具有随机分布特征的裂隙和中小规模溶蚀洞穴造成的溶蚀岩体渗漏问题,本文在建立溶蚀岩体随机结构模型的基础上,提出等效渗透系数的概念,并推导出等效渗透系数的计算公式.结合具体的工程实例,根据随机结构模型所反映出的裂隙和溶蚀洞穴的有关参数计算等效渗透系数,多次模拟后得到其分布规律.最后对该方法的应用前景进行了讨论. 相似文献
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波浪荷载作用下的海床响应是岩土工程领域的研究热点,波致海床液化是导致海床及结构物失稳的主要原因。针对海床响应分析中涉及的诸多不确定性因素,如沉积物参数的空间变异性以及荷载的随机性,建立了基于随机有限元方法的概率分析框架,将在MATLAB中实现的空间异质土体的模拟与在COMSOL中实现的孔隙弹性有限元分析通过LiveLink程序进行耦合。提出了一种分解的Karhunen-Loève（简称K-L）展开方法,该方法占用较少的计算时间和内存空间,使得高分辨率、大尺寸的三维随机场的模拟更加高效。应用上述概率框架分别对规则波浪荷载作用下的二维倾斜海床以及随机波浪荷载下的三维海床响应进行了研究,揭示了海床土体渗透系数K与剪切模量G的空间变异性以及波浪荷载随机性对孔隙水压力分布和海床液化深度的影响规律,表明了传统确定性分析方法将导致不安全的工程设计。 相似文献
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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。 相似文献
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Uncertainties in parameters of landslide susceptibility models often hinder them from providing accurate spatial and temporal predictions of landslide occurrences. Substantial contribution to the uncertainties in landslide assessment originates from spatially variable geotechnical and hydrological parameters. These input parameters may often vary significantly through space, even within the same geological deposit, and there is a need to quantify the effects of the uncertainties in these parameters. This study addresses this issue with a new three-dimensional probabilistic landslide susceptibility model. The spatial variability of the model parameters is modeled with the random field approach and coupled with the Monte Carlo method to propagate uncertainties from the model parameters to landslide predictions (i.e., factor of safety). The resulting uncertainties in landslide predictions allow the effects of spatial variability in the input parameters to be quantified. The performance of the proposed model in capturing the effect of spatial variability and predicting landslide occurrence has been compared with a conventional physical-based landslide susceptibility model that does not account for three-dimensional effects on slope stability. The results indicate that the proposed model has better performance in landslide prediction with higher accuracy and precision than the conventional model. The novelty of this study is illustrating the effects of the soil heterogeneity on the susceptibility of shallow landslides, which was made possible by the development of a three-dimensional slope stability model that was coupled with random field model and the Monte Carlo method.
相似文献13.
The reliability of heterogeneous slopes can be evaluated using a wide range of available probabilistic methods. One of these methods is the random finite element method (RFEM), which combines random field theory with the non‐linear elasto‐plastic finite element slope stability analysis method. The RFEM computes the probability of failure of a slope using the Monte Carlo simulation process. The major drawback of this approach is the intensive computational time required, mainly due to the finite element analysis and the Monte Carlo simulation process. Therefore, a simplified model or solution, which can bypass the computationally intensive and time‐consuming numerical analyses, is desirable. The present study investigates the feasibility of using artificial neural networks (ANNs) to develop such a simplified model. ANNs are well known for their strong capability in mapping the input and output relationship of complex non‐linear systems. The RFEM is used to generate possible solutions and to establish a large database that is used to develop and verify the ANN model. In this paper, multi‐layer perceptrons, which are trained with the back‐propagation algorithm, are used. The results of various performance measures indicate that the developed ANN model has a high degree of accuracy in predicting the reliability of heterogeneous slopes. The developed ANN model is then transformed into relatively simple formulae for direct application in practice. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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Ji Yuan Iason Papaioannou Daniel Straub 《Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards》2019,13(1):20-33
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. 相似文献
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针对确定性模型难以描述含水层非均质空间分布的问题,提出基于随机理论的地下水环境风险评价方法。以矩形场地地下水污染风险评价为例,采用蒙特卡罗法生成大量渗透系数随机场,模拟含水层参数各种可能的非均质空间分布,在此基础上建立场地地下水流模型与溶质运移模型,分别计算污染物在地下水中的迁移转化情况。统计大量随机模拟中污染事故发生的频率,当模拟次数足够多时,污染频率收敛于污染概率,污染风险即通过污染概率体现出来。该方法将模型参数设为满足一定分布特征的随机变量,避免了确定性方法得出的武断的评价结果,可为工厂的选址、水源地的选址等工作提供科学指导。 相似文献
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用MonteCarlo随机模拟方法模拟砂土颗粒在重力作用下,在圆柱与长方体容器中的自然堆积过程。首先用参考网格法生成一个砂土颗粒的松散结构,松散结构中粒子与粒子、粒子与边界间不存在任何接触;然后启动MonteCarlo随机模拟算法,即给处于松散结构中的每个粒子施加随机位移,得到新构形,如果新构形中粒子间或粒子与边界间发生重叠,则放弃这个构形;如果没有重叠存在,则判别粒子体系的势能变化,运用Metropolis准则来判别这个构形是否被接受,重复这个过程可以得到砂土的密集堆积结构。采用Schinner建议的接触发现算法判别粒子间是否存在重叠,同时详细介绍了粒子与边界间的接触发现算法。模拟结果表明,用MonteCarlo方法模拟砂土的自然堆积结构是非常有效的,可以为砂土的流动、压实等的数值模拟工作提供初始构形。 相似文献
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Dislocation modelling of an earthquake fault is of great importance due to the fact that ground surface response may be predicted by the model. However, geological features of a fault cannot be measured exactly, and therefore these features and data involve uncertainties. This paper presents a Monte Carlo based random model of faults with finite element method incorporating split node technique to impose the effects of discontinuities. Length and orientation of the fault are selected as random parameters in the domain model, and hence geometrical uncertainties are encountered. Mean and standard deviation values, as well as probability density function of ground surface responses due to the dislocation are computed. Based on analytical and numerical calculation of dislocation, two approaches of Monte Carlo simulations are proposed. Various comparisons are examined to illustrate the capability of both methods for random simulation of faults. 相似文献
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Passive earth pressure calculations in geotechnical analysis are usually performed with the aid of the Rankine or Coulomb theories of earth pressure based on uniform soil properties. These traditional earth pressure theories assume that the soil is uniform. The fact that soils are spatially variable leads to two potential problems in design: do sampled soil properties adequately reflect the effective properties of the entire soil mass and does spatial variability in soil properties lead to passive earth pressures that are significantly different from those predicted using traditional theories? This paper combines non-linear finite element analysis with random field simulation to investigate these two questions. The specific case investigated is a two-dimensional frictionless passive wall with a cohesionless drained soil mass. The wall is designed against sliding using Rankine's earth pressure theory. The unit weight is assumed to be constant throughout the soil mass and the design friction angle is obtained by sampling the simulated random soil field. For a single sample, the friction angle is used as an effective soil property in the Rankine model. For two samples, an average of the sampled friction angles is used. Failure is defined as occurring when the Rankine predicted passive resistance acting on the wall, modified by a factor of safety, is greater than that computed by the random finite element method. Using Monte Carlo simulation, the probability of failure of the traditional design approach is assessed as a function of the factor of safety using and the spatial variability of the soil. 相似文献