三峡库区大石板滑坡区排水系统效果评估

结合三峡库区大石板滑坡工程实例 ,以连续 36天的降雨过程为条件 ,利用已有的地下水位观测资料 ,采用人工神经网络方法预测滑坡内地下水位在排水工程实施前后的变化 ,以此作为非饱和饱和非衡定地下渗流计算的特定水头边界。根据计算的地下水位进行滑坡稳定性分析 ,结合稳定分析成果对排水系统工程的效果进行评价。结果表明 ,地下排水工程的实施可较大幅度地提高滑坡的稳定性。     

Critical Slope and Plasticity

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框架预应力锚杆边坡支护结构稳定性分析

以极限平衡理论及框架预应力锚杆边坡支护结构的滑动面破坏模式为基础,采用毕肖普法,并考虑竖向条间剪力对滑移面抗剪强度的影响,建立了边坡最危险滑移面的搜索模型,并推导了稳定系数的求解公式。运用遗传算法对支护结构最危险滑移面进行动态搜索和确定,计算其稳定性系数。该方法避免了在优化设计中陷入局部最小值的缺点,更具有有效性和准确性。     

An improved search strategy for the critical slip surface using finite element stress fields

The finite element method can be used to advantage in slope stability problems. This paper proposes a technique to search for the critical slip surface as well as to define and calculate the factor of safety for the slope, when the finite element method is used to model its formation. First, stresses are estimated at each Gaussian point from the finite element analysis. Then, the global stress smoothing method is applied to get a continuous stress field. Based on this stress field, the factor of safety is calculated for a specified slip surface by a stress integration scheme. An improved search strategy is proposed for a noncircular critical surface which starts with a search method for a circular critical surface. During the search process, points defining a trial slip surface can freely move in the finite element mesh subject to some kinematical constraints. This method can be applied to both the limit equilibrium method and the finite element method. Effects of the slope stress history and soil parameters on the resulting critical surface are investigated.     

地下水管理模型求解方法综述

地下水管理模型求解方法的研究是目前地下水管理领域的热点问题。本文从地下水管理模型传统优化算法和现代智能优化算法等方面进行了评述,着重讨论了目前应用较广泛的求解非线性地下水系统的优化算法,如遗传算法、模拟退火算法、人工神经网络算法等;阐述了地下水监测网优化设计研究以及多目标地下水管理模型的求解方法。最后指出应加强地下水动态规划管理模型和地下水系统随机管理模型的求解技术的研究。     

边坡稳定分析条块力-位移法及其应用

在现行条分法的基础上,建立了一种全新的边坡条块力-位移分析方法。现行条分法中条块底边的力学参数采用极限平衡状态力学参数,即每个条块底边均处于极限平衡状态,这种极限平衡状态对于残余应力是较为适宜的。采用理想弹塑性模型和一种全新的本构模型描述土条块底边力学特性,并以不平衡推力法为例,提出了临界状态条块的确定方法,针对可能的破坏模式进行了分析,并提出了边坡整体破坏各条块的应力和位移的确定方法,计算出相应的稳定系数,如传统强度折减法、综合下滑力-抗滑力法、主推力法、综合位移法和富余位移法稳定系数。通过计算分析论证了理想弹塑性模型在不改变力学参数的情况下是难以描述边坡渐近破坏过程的,而一种全新的本构模型可以描述渐近破坏各条块的力学行为。提出的条块力-位移法可以确定边坡在不同荷载和位移条件下的稳定性,也可以获得边坡的推力变化和滑面移动特征,进而实施边坡的应力、位移和稳定性的初步预测预报。     

Finite volume–based modeling of flow‐induced shear failure along fracture manifolds

In this paper, a numerical model to predict flow‐induced shear failure along pre‐existing fractures is presented. The framework is based on a discrete fracture representation embedded in a continuum describing the damaged matrix. A finite volume method is used to compute both flow and mechanical equilibrium, whereas specifically tailored basis functions are used to account for the physics at discontinuities. The failure criterion is based on a maximum shear strength limit, which changes with varying compressive stress on the fracture manifold. The displacements along fracture manifolds are obtained such that force balance is achieved under conditions, where shear stress of the failing fracture segment is constrained to the maximum shear strength at the segment. Simultaneously, the fluid pressure is computed independently of the shear slip. A relaxation model approach is used to obtain the maximum shear limit on the fracture manifold, which leads to grid convergence.     

Spatial risk analysis of Li-shan landslide in Taiwan

By coupling limit equilibrium analysis and Monte Carlo analysis with a geography information system (GIS), this study implements a method that can evaluate the risk (corresponding to probability of failure in this study) of landslide with consideration of spatial uncertainties. The GIS can adopt the three-dimensional information including surface topography, underground geomaterial distribution and groundwater level to determine slope profiles for analysis. Then the safety of defined slope can be evaluated by limit equilibrium analysis. In this study, the mechanical properties of geomaterial were considered as random variables instead of single values. The slope and groundwater profiles are also randomly adopted. Through a Monte Carlo sampling process, a distribution of safety factor and probability of failure can be determined. This probabilistic risk analysis approach was applied to Li-shan landslide in Central Taiwan.

Due to heavy rains, the sites near the highway 7A (mileage 73 k + 150) and the highway 8 (mileage 82 k) in the Li-shan Township began to subside in mid April 1990. Topography, geology, and groundwater condition of this area were first reviewed. Based on this review, together with field investigations and a series of limit equilibrium back analyses, a general hypothetic model was established to illustrate the failure mechanism of this landslide area. Then the developed probabilistic risk analysis model is applied to spatially evaluate the risk of this landslide area as well as the performance of the remediation treatment.     

基于有限元极限平衡法的尾矿坝坝体稳定分析

在平面应变条件下,采用基于弹塑性应力应变分析的有限元极限平衡法对尾矿坝坝体的稳定性进行研究。该方法可较好地结合极限平衡分析方法和有限元应力分析方法的特点。通过弹塑性有限元分析,合理准确地考虑结构整体应力场的影响,进而结合Hooke-Jeeves法优化搜索最危险滑动面的位置及其对应的最小安全系数。以某尾矿坝实际工程为例,比较分析了考虑正常、洪水以及特殊工况运行下有限元极限平衡法与极限平衡条分法和有限元强度折减法在安全系数大小及滑动面形状和位置的差异,重点运用有限元极限平衡法对尾矿坝坝体的稳定性进行验算并作出安全评价,为尾矿坝的安全设计施工提供可靠依据和技术支撑。     

基于极限分析上限方法的海底斜坡地震稳定性

极限分析上限方法在海底斜坡稳定性评价中受到了广泛关注,但已有成果未考虑地震荷载以及多土层海底斜坡可能出现的局部破坏机制。基于上限定理,推导了拟静力水平地震条件下多土层海底斜坡外力功率与内能耗散率平衡方程;结合强度折减技术和最优化方法,求解了海底斜坡整体和局部地震稳定性安全系数,并实现了多土层海底斜坡的局部滑动面搜索;通过典型算例分析,验证了本文方法的有效性。在此基础上,探讨了不同水平地震条件下两种组合土层海底斜坡的整体和局部稳定性,通过与数值解对比,其结果可以较准确地评价海底斜坡稳定性并有效预测滑移面位置。最后,将极限分析上限方法应用于一海底斜坡工程实例。     

禁忌搜索在边坡稳定分析中的应用

在禁忌搜索和极限平衡分析的基础上,提出了全局确定边坡最小安全系数的禁忌搜索方法,并建立了响应的模型;该方法是一种启发式的全局搜索方法,可以搜索出全局最小安全系数,同时还能确定出与之对应的最危险滑动面。将该方法应用于不同几何形状和土层信息的边坡稳定分析中,结果表明,提出的方法能够避免局部最小解,并能搜索到全局最小安全系数。     

Climate change and groundwater conditions in the Mekong Region–A review

Changes in the climatic system introduce uncertainties in the supply and management of water resources. The Intergovernmental Panel on Climate Change(IPCC) predicts an increase of 2 to 4 °C over the next 100 years. Temperature increases will impact the hydrologic cycle by directly increasing the evaporation of surface water sources. Consequently, changes in precipitation will indirectly impact the flux and storage of water in surface and subsurface reservoirs(i.e., lakes, soil moisture, groundwater, etc.). In addition, increases in temperature contribute to increases in the sea level, which may lead to sea water intrusions, water quality deterioration, potable water shortages, etc. Climate change has direct impacts on the surface water and the control of storage in rivers, lakes and reservoirs, which indirectly controls the groundwater recharge process. The main and direct impact of climate change on groundwater is changes in the volume and distribution of groundwater recharge. The impact of climate change on groundwater resources requires reliable forecasting of changes in the major climatic variables and accurate estimations of groundwater recharge. A number of Global Climate Models(GCMs) are available for understanding climate and projecting climate change.These GCMs can be downscaled to a basin scale, and when they are coupled with relevant hydrological models, the output of these coupled models can be used to quantify the groundwater recharge, which will facilitate the adoption of appropriate adaptation strategies under the impact of climate change.     

Some applications of a backpropagation neural network in geo-engineering

A MATLAB based backpropagation neural network (BPNN) model has been developed. Two major geo-engineering applications, namely, earth slope movement and ground movement around tunnels, are identified. Data obtained from case studies are used to train and test the developed model and the ground movement is predicted with the help of input variables that have direct physical significance. A new approach is adopted by introducing an infiltration coefficient in the network architecture apart from antecedent rainfall, slope profile, groundwater level and strength parameters to predict the slope movement. The input variables for settlement around underground excavations are taken from literature. The neural network models demonstrate a promising result predicting fairly successfully the ground behavior in both cases. If input variables influencing output goals are clearly identified and if a decent number of quality data are available, backpropagation neural network can be successfully applied as mapping and prediction tools in geotechnical investigations.     

Pattern recognition in lithology classification: modeling using neural networks,self-organizing maps and genetic algorithms

Effective characterization of lithology is vital for the conceptualization of complex aquifer systems, which is a prerequisite for the development of reliable groundwater-flow and contaminant-transport models. However, such information is often limited for most groundwater basins. This study explores the usefulness and potential of a hybrid soft-computing framework; a traditional artificial neural network with gradient descent-momentum training (ANN-GDM) and a traditional genetic algorithm (GA) based ANN (ANN-GA) approach were developed and compared with a novel hybrid self-organizing map (SOM) based ANN (SOM-ANN-GA) method for the prediction of lithology at a basin scale. This framework is demonstrated through a case study involving a complex multi-layered aquifer system in India, where well-log sites were clustered on the basis of sand-layer frequencies; within each cluster, subsurface layers were reclassified into four depth classes based on the maximum drilling depth. ANN models for each depth class were developed using each of the three approaches. Of the three, the hybrid SOM-ANN-GA models were able to recognize incomplete geologic pattern more reasonably, followed by ANN-GA and ANN-GDM models. It is concluded that the hybrid soft-computing framework can serve as a promising tool for characterizing lithology in groundwater basins with missing lithologic patterns.     

围岩力学参数反演的GSA-BP神经网络模型及应用

针对遗传算法（GA）存在早熟现象和局部寻优能力较差等缺陷,引入具有很强局部搜索能力的模拟退火算法（SA）,组成改进的遗传模拟退火算法（GSA）提高优化问题的能力和求解质量。针对BP神经网络容易陷入局部最小和收敛速度慢等方面的不足,应用改进的遗传模拟退火算法搜索BP神经网络的最优权值和阀值,提高BP神经网络的预测精度,建立了围岩力学参数反分析的GSA-BP神经网络模型。将该模型应用于乌东德水电站右岸地下厂房围岩力学参数的反演分析中,根据监测围岩变形数据反演围岩力学参数,反演所得参数应用到正计算分析中,得出的计算位移与实测值吻合较好,说明该方法的有效性和应用于该工程的可行性。     

A comparative study of various commercially available programs in slope stability analysis

The objective of this paper is to study the effect of different slip surface search techniques on the factors of safety obtained using the limit equilibrium (LE) slope stability methods. This objective is accomplished by comparing results from the finite element method, the linear grid method, the rectangular grid method, and the Monte-Carlo searching techniques using different commercially available programs. The results showed that the LE methods are very efficient methods when coupled with a robust searching technique namely the Monte-Carlo method. In addition, the selected slip surface search technique highly influenced the location of the critical slip surfaces as well as the value of the calculated factors of safety.     

填筑和开挖边坡的稳定性分析

在有限元应力应变分析的基础上,采用以剪应力定义的安全系数和模式搜索的方法确定边坡的安全系数及最危险滑动面。在平面应变条件下,对土层均质的填筑和开挖边坡的稳定性进行了较为全面的研究,并同天然边坡的安全系数和破坏面进行比较,计算结果表明,这3类边坡滑动面的形状基本一致,天然边坡安全系数要高于填筑和开挖边坡;同时比较了采用有限元稳定评价方法和采用极限平衡方法计算结果的差别;最后分析研究了计算参数变化对填筑和开挖边坡稳定性的影响。     

基于最小势能法的三维临界滑裂面搜索方法

为了得到三维边坡的临界滑裂面,提出了6个参数控制的三维滑裂面构造方法,基于边坡三维最小势能稳定性分析方法建立目标函数,采用遗传算法实现了临界滑裂面的搜索,并开发了相应的搜索程序。为检验文中搜索方法的合理性,将其与其他方法得到的临界滑裂面以及最小安全系数进行比较,并且将室内模型试验得到的临界滑面与理论搜索的结果进行对比。研究表明：搜索方法可实现稳步收敛;针对算例进行多变量同时变化的搜索验算,得到了与极限平衡法较为接近的结果,表明提出的搜索方法是合理的;理论计算结果与室内模型试验坡面加载得到的边坡临界滑面较为接近,再次验证三维边坡临界滑面搜索方法是可行的。     

物质点强度折减法及其在边坡中的应用

物质点法适用于模拟连续介质大变形,如边坡失稳全过程。在物质点法中应用强度折减法,用于边坡稳定性评价。与极限平衡法相比,二者安全系数计算值、滑动面位置结果基本一致;与有限元强度折减法相比,物质点法失稳评价标准的物理意义明确。利用物质点法大变形计算优势,评价边坡失稳后的破坏后果,通过算例说明其评价不同安全系数下的滑坡堆积形态及滑移距离的能力,尤其是评价滑坡对临近建筑物的影响程度的能力。物质点强度折减法可用于边坡稳定性评价及边坡破坏后果评价。     

禁忌搜索在确定土坡危险滑动面中的应用

在土坡稳定的计算过程中常采用经典的极限平衡法。对每一条可能的圆弧滑动面通过条分法计算其安全系数,最小的安全系数就代表了土坡的实际安全系数。在此过程中,滑动面的圆心坐标和半径可以视为安全系数的函数,滑动面的圆心坐标和半径是自变量,安全系数就是函数值。这样,土坡安全系数的计算过程实际上是对安全系数这个函数求极值的过程。通过将土坡的安全系数视为圆心坐标和滑弧半径的函数,应用连续变量的禁忌搜索技术计算土坡稳定安全系数,提高土坡稳定计算的可靠性。