Rock bridge slice element method in slope stability analysis based on multi-scale geological structure mapping

The searching method of failure surface which consists of complex geological structures in high and steep rock slopes was studied. Based on computer simulation technology and Monte-Carlo method, three dimensional multi-scale geological structures such as engineering scale and statistical scale structures of the slope were simulated. The searching method of failure route which consists of joints and rock bridges was determined via simulation annealing method by considering the shear strength of joints or rock bridges in one supposed route. When shear strengths of all the supposed routes were computed, the least shear strength route was considered failure route. Then, the inclined slice of joint slices and rock bridge slices were separated according to the position of joints and rock bridges. For the rock bridge slices, by distinguishing the failure model, the force direction to the next slice was defined. Finally, the limit equilibrium equations for every slice were established, and the slope stability factor was obtained. One practical example indicates that the discussed method is more closely to the real condition.

Slope stability hazard management systems

Weather-related geo-hazards are a major concern for both natural slopes and man-made slopes and embankments. Government agencies and private companies are increasingly required to ensure that there is adequate protection of sloping sur- faces in order that interaction with the climate does not produce instability. Superior theoretical formulations and computer tools are now available to address engineering design issues related to the near ground surface soil-atmospheric interactions. An ex- ample is given in this paper that illustrates the consequences of not paying adequate attention to the hazards of slope stability prior to the construction of a highway in South America. On the other hand, examples are given from Hong Kong and China's Mainland where significant benefits are derived from putting in place a hazard slope stability management system. Some results from a hazard management slope stability study related to the railway system in Canada are also reported. The study took advantage of recent research on unsaturated soil behaviour and applied this information to real-time modelling of climatic conditions. The quantification of the water balance at the ground surface, and subsequent infiltration, is used as the primary tool for hazard level assessment. The suggested hazard model can be applied at either specific high risk locations or in a more general, broad-based manner over large areas. A more thorough understanding of unsaturated soil behaviour as it applies to near ground surface soils, along with the numerical computational power of the computer has made it possible for new approaches to be used in slope hazard management engineering.

Stochastic seismic slope stability assessment using polynomial chaos expansions combined with relevance vector machine

This paper presents probabilistic assessment of seismically-induced slope displacements considering uncertainties of seismic ground motions and soil properties.A stochastic ground motion model representing both the temporal and spectral non-stationarity of earthquake shakings and a three-dimensional rotational failure mechanism are integrated to assess Newmark-type slope displacements.A new probabilistic approach that incorporates machine learning in metamodeling technique is proposed,by combining relevance vector machine with polynomial chaos expansions(RVM-PCE).Compared with other PCE methods,the proposed RVM-PCE is shown to be more effective in estimating failure probabilities.The sensitivity and relative influence of each random input parameter to the slope displacements are discussed.Finally,the fragility curves for slope displacements are established for sitespecific soil conditions and earthquake hazard levels.The results indicate that the slope displacement is more sensitive to the intensities and strong shaking durations of seismic ground motions than the frequency contents,and a critical Arias intensity that leads to the maximum annual failure probabilities can be identified by the proposed approach.

Three Practical Methods for Analyzing Slope Stability

Since the environmental capacity and the arable as well as the inhabitant lands have actually reached a full balance, the slopes are becoming the more and more important options for various engineering constructions. Because of the geological complexity of the slope, the design and the decision-making of a slope-based engineering is still not practical to rely solely on the theoretical analysis and numerical calculation, but mainly on the experience of the experts. Therefore, it has important practical significance to turn some successful experience into mathematic equations. Based upon the abundant typical slope engineering construction cases in Yunnan, Southwestern China, 3 methods for analyzing the slope stability have been developed in this paper. First of all, the corresponded analogous mathematic equation for analyzing slope stability has been established through case studies. Then, artificial neural network and multivariate regression analysis have also been set up when 7 main influencing factors are adopted.

Assessing model of highway slope stability based on optimized SVM

Considering the geological hazards attributed to the highway slope,using a common simple model cannot accurately assess the stability of the slope.First,principal component analysis(PCA)was conducted to extract the principal components of six factors(namely,bulk density,cohesion,internal friction angle,slope angle,slope height,and pore water pressure ratio)affecting the slope stability.Second,four principal components were adopted as input variables of the support vector machine(SVM)model optimized by genetic algorithm(GA).The output variable was slope stability.Lastly,the assessing model of highway slope stability based on PCA-GA-SVM is established.The maximal absolute error of the model is 0.0921 and the maximal relative error is 9.21%by comparing the assessment value and the practical value of the test sample.The above studies are conducive to enrich the assessing model of highway slope stability and provide some reference for highway slope engineering treatment.

The Studies of Slope Stability Around Gilgel Gibe-ⅡHydroelectric Project,Southwest of Ethiopia

The hillside and road cuttings of most parts of the north,south and western regions of the Ethiopian Plateau have a record of instability.Landslide-generated problems claimed many lives and property damages in the country.On the road from town Fofa to Gilgel GibeⅡproject instability problem is common.Since the area is extremely rugged,the variation in the elevation is very large and

Primary Investigations on Yangtze River Bank Slope Stability in Wanzhou for the Three Gorges Reservoir Project

This paper investigates the main factors contributing to bank slope failures, such as the structure of rock and soil, water level change, bank slope gradient, vegetation, weathering and human activities. Based on these investigations, the bank slope failure models are analyzed. The stability of bank slopes in Wanzhou is investigated using geological surveying, 2D resistivity imaging surveying, excavated trenches and other methods. Finally, the disasters of bank slope failures in Wanzhou were investigated in detail. The results show that instability problems might occur in 60.38 km of bank slopes when the water level rises to 175 m. It is suggested that 37.8 km of unstable bank slopes should be stabilized, and 14.2 km of unstable banks should be moved or avoided after further geological surveying and reconnaissance. These results provide scientific basis and reliable data for the government to develop the third geodisaster prevention plan for the Three Gorges reservoir.

Short-term displacement prediction for newly established monitoring slopes based on transfer learning

This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,where lots of newly established monitoring slopes lack sufficient historical deformation data,making it difficult to extract deformation patterns and provide effective predictions which plays a crucial role in the early warning and forecasting of landslide hazards.A slope displacement prediction method based on transfer learning is therefore proposed.Initially,the method transfers the deformation patterns learned from slopes with relatively rich deformation data by a pre-trained model based on a multi-slope integrated dataset to newly established monitoring slopes with limited or even no useful data,thus enabling rapid and efficient predictions for these slopes.Subsequently,as time goes on and monitoring data accumulates,fine-tuning of the pre-trained model for individual slopes can further improve prediction accuracy,enabling continuous optimization of prediction results.A case study indicates that,after being trained on a multi-slope integrated dataset,the TCN-Transformer model can efficiently serve as a pretrained model for displacement prediction at newly established monitoring slopes.The three-day average RMSE is significantly reduced by 34.6%compared to models trained only on individual slope data,and it also successfully predicts the majority of deformation peaks.The fine-tuned model based on accumulated data on the target newly established monitoring slope further reduced the three-day RMSE by 37.2%,demonstrating a considerable predictive accuracy.In conclusion,taking advantage of transfer learning,the proposed slope displacement prediction method effectively utilizes the available data,which enables the rapid deployment and continual refinement of displacement predictions on newly established monitoring slopes.

Improved Statically Solvable Slice Method for Slope Stability Analysis

Although slice methods are simple and effective slope stability analysis approaches,they are statically indeterminate.Several modifications of the slice method,such as the Spencer,MorgensternPrice,and Chen-Morgenstern methods,are statically determinate and solvable as they assume the inter-slice force inclination angle;however,there is a small gap between the assumptions and actual landslide stability analysis.Through reasonable theoretical analysis,the Su slice method provides a reliable approach for determining the inter-slice force inclination angle that can be used in slice analysis to accurately analyse,calculate,and evaluate the stability of landslides.However,the Su slice method requires further research and analysis,especially in terms of the parameter values sinλbiandρ.In this study,we investigated more accurate methods for calculating the parameters sinλbiandρ.In addition,an adjustment coefficient(μ)was introduced to improve the solution method for the inter-slice force inclination angle.The inter-slice force inclination and safety factors of three landslides with arc-shaped slip surfaces and one landslide with a polyline-shaped slip surface were analysed and compared using the different slice methods.The improved inter-slice force inclination not only satisfies the calculation of static force equilibrium condition but also satisfies the calculation of both the force and moment equilibrium conditions.The improved method for calculating inter-slice force inclination presented the best correlation.The safety factors calculated using the improved Su slice method were close to those obtained using numerical simulations and the Morgenstern-Price method.Despite negligible differences among the safety factors calculated using the Su slice,improved Su slice,and M-P methods,the accuracy of the improved Su slice method was better than the M-P method in terms of inter-slice force inclination angles which can be useful to improve protection engineering design.

Engineering geological conditions and features of geologic hazards in Wudongde reservoir of Jinshajiang River valley

There is a great difference between the distribution and evolvement characteristics of slope geological hazard in the same geographical location and climatic conditions,taking the similar structural-genetic connection in Wudongde reservoir area of Jinshajiang River valley for example. In all engineering geological conditions,the chronologic age and attitude of strata,and the lithologic association factors control the distributions and evolvement characteristics of slope geological hazard in the studied area. The study shows that the slopes in geological evolution are in different stages. The conclusion helps to understand the types and the intensity of geological disasters.

土与强风化岩双元边坡圆弧-平面破坏模式与支护设计方法

为了探究土与强风化岩边坡中强风化岩不破坏的临界坡率及稳定性判断方法,基于济南地层,得出适用于数值模拟的土层参数,并利用强度折减法求出边坡的临界坡率,为施工提供参考。针对强风化岩不破坏的边坡,运用改进的瑞典条分法求出边坡安全系数解析解,并利用滑移线场法求出滑移线,为安全系数解析解的应用提供依据。结果表明,岩层厚度超过边坡高度1/2或坡率大于1:0.5时,强风化岩一定破坏;解析解得出的安全系数偏小,有利于工程安全;针对土与强风化岩边坡,文中结果可确定边坡破坏区域,设计支护方案。

NPR锚索对白云岩矿失稳边坡控制效应研究

节理裂隙是露天矿开采中边坡失稳的主要影响因素,因此,研究节理裂隙有利于解决矿区边坡开采的安全性问题。以北京黄峪口白云岩矿失稳边坡为工程地质背景,采用现场调查(测线法和赤平极射投影法)、NPR锚索数值模拟和现场监测方法,以NPR锚索主动支护思想为核心对其进行了试验研究。研究表明:①黄峪口白云岩矿边坡岩层基本呈水平状或与边坡走向方向一致,边坡体结构破碎,节理裂隙发育,存在软弱夹层和多条滑带,边坡有严重失稳的趋势。②NPR锚索入射角为20°时达到边坡最佳支护效果,边坡位移约2.55 cm,说明NPR锚索对破碎边坡起到较大的抗滑作用。③根据现场监测得出NPR锚索的锚索轴力可达300 kN左右,支护后的边坡较稳定。研究反映出,NPR锚索对节理裂隙发育的边坡控制效果较好,可为类似露天矿边坡治理提供参考。

Predicting the friction angle of clays using a multi-layer perceptron neural network enhanced by yeo-johnson transformation and coral reefs optimization

The accurate prediction of the friction angle of clays is crucial for assessing slope stability in engineering applications.This study addresses the importance of estimating the friction angle and presents the development of four soft computing models:YJ-FPA-MLPnet,YJ-CRO-MLPnet,YJ-ACOC-MLPnet,and YJCSA-MLPnet.First of all,the Yeo-Johnson(YJ)transformation technique was used to stabilize the variance of data and make it more suitable for parametric statistical models that assume normality and equal variances.This technique is expected to improve the accuracy of friction angle prediction models.The friction angle prediction models then utilized multi-layer perceptron neural networks(MLPnet)and metaheuristic optimization algorithms to further enhance performance,including flower pollination algorithm(FPA),coral reefs optimization(CRO),ant colony optimization continuous(ACOC),and cuckoo search algorithm(CSA).The prediction models without the YJ technique,i.e.FPA-MLPnet,CRO-MLPnet,ACOC-MLPnet,and CSA-MLPnet,were then compared to those with the YJ technique,i.e.YJ-FPA-MLPnet,YJ-CRO-MLPnet,YJ-ACOC-MLPnet,and YJ-CSA-MLPnet.Among these,the YJ-CRO-MLPnet model demonstrated superior reliability,achieving an accuracy of up to 83%in predicting the friction angle of clay in practical engineering scenarios.This improvement is significant,as it represents an increase from 1.3%to approximately 20%compared to the models that did not utilize the YJ transformation technique.

Exploring mechanism of hidden,steep obliquely inclined bedding landslides using a 3DEC model:A case study of the Shanyang landslide in Shaanxi Province,China

Catastrophic geological disasters frequently occur on slopes with obliquely inclined bedding structures(also referred to as obliquely inclined bedding slopes),where the apparent dip sliding is not readily visible.This phenomenon has become a focal point in landslide research.Yet,there is a lack of studies on the failure modes and mechanisms of hidden,steep obliquely inclined bedding slopes.This study investigated the Shanyang landslide in Shaanxi Province,China.Using field investigations,laboratory tests of geotechnical parameters,and the 3DEC software,this study developed a numerical model of the landslide to analyze the failure process of such slopes.The findings indicate that the Shanyang landslide primarily crept along a weak interlayer under the action of gravity.The landslide,initially following a dip angle with the support of a stable inclined rock mass,shifted direction under the influence of argillization in the weak interlayer,moving towards the apparent dip angle.The slide resistance effect of the karstic dissolution zone was increasingly significant during this process,with lateral friction being the primary resistance force.A reduction in the lateral friction due to karstic dissolution made the apparent dip sliding characteristics of the Shanyang landslide more pronounced.Notably,deformations such as bending and uplift at the slope’s foot suggest that the main slide resistance shifts from lateral friction within the karstic dissolution zone to the slope foot’s resistance force,leading to the eventual buckling failure of the landslide.This study unveils a novel failure mode of apparent dip creep-buckling in the Shanyang landslide,highlighting the critical role of lateral friction from the karstic dissolution zone in its failure mechanism.These insights offer a valuable reference for mitigating risks and preventing disasters related to obliquely inclined bedding landslides.

Extensive identification of landslide boundaries using remote sensing images and deep learning method

The frequent occurrence of extreme weather events has rendered numerous landslides to a global natural disaster issue.It is crucial to rapidly and accurately determine the boundaries of landslides for geohazards evaluation and emergency response.Therefore,the Skip Connection DeepLab neural network(SCDnn),a deep learning model based on 770 optical remote sensing images of landslide,is proposed to improve the accuracy of landslide boundary detection.The SCDnn model is optimized for the over-segmentation issue which occurs in conventional deep learning models when there is a significant degree of similarity between topographical geomorphic features.SCDnn exhibits notable improvements in landslide feature extraction and semantic segmentation by combining an enhanced Atrous Spatial Pyramid Convolutional Block(ASPC)with a coding structure that reduces model complexity.The experimental results demonstrate that SCDnn can identify landslide boundaries in 119 images with MIoU values between 0.8and 0.9;while 52 images with MIoU values exceeding 0.9,which exceeds the identification accuracy of existing techniques.This work can offer a novel technique for the automatic extensive identification of landslide boundaries in remote sensing images in addition to establishing the groundwork for future inve stigations and applications in related domains.

基于地质环境分析的复杂山区道路防护工程设计

以复杂山区道路防护工程设计为研究对象,通过对地质环境的深入分析,结合工程地质学和地质工程力学理论,对山区道路在地质灾害作用下的稳定性和安全性进行了系统的评估。以地质勘测数据和现场调查结果为依据,提出了地质灾害预警系统、坡面防护结构设计、路基稳定性改善方案等针对性防护措施。通过数值模拟和实地测试验证,为复杂山区道路安全运行提供了科学和可行的技术保障,确保了工程设计的可靠性和实用性。

青藏高原构造混杂岩带的孕灾地质基因与重大工程地质问题研究

孕灾地质基因是指一定区域所具有的促进地质灾害孕生的内在关键因素。板块构造混杂岩带所处的特殊构造部位决定了其复杂的演化过程和特殊的地质基因。本文在梳理青藏高原构造混杂岩带地质特征的基础上,总结分析了其孕灾地质基因,包括活跃的地质构造、复杂的水热条件、混杂的岩性组合、特殊的蚀变软岩和构造岩溶导水通道等,是引发重大地质灾害和工程地质安全风险的根源。结合典型案例,剖析了构造混杂岩带大型滑坡的成因类型主要有三大类:构造控制型、泥质软岩控制型和蚀变蛇绿岩带控制型,其中蚀变蛇绿岩带是构造混杂岩带最具特色的易滑地质结构,具有典型的地质构造与特殊岩性联合控制特征。构造混杂岩带隧道工程变形破坏主要有塌方、水平收敛、环向收敛、底鼓和错断等五种模式,黏土化蚀变软岩的不良工程特性是制约构造混杂岩带隧道围岩稳定性的重要因素。针对传统的工程地质理论和灾害风险防控技术难以适应构造混杂岩带大规模工程建设面临的挑战,提出了有待深入研究的关键问题和防灾减灾策略。

基于路段单元的公路地质灾害风险气象预警系统

面向山区交通风险管控需求,以公路为承灾体对象的地质灾害风险气象预警研究具有重要意义。以浙江省磐安县方前镇为研究区,考虑道路等级、斜坡单元、边坡类型和边坡稳定性现状4个方面,研究确定公路地质灾害预警单元的划分方法;考虑历史地质灾害的发育规律,将公路边坡分为土质、岩质和土岩混合质边坡3种类型,分别建立不同类型边坡地质灾害易发性评价体系,并通过层次分析法计算各指标权重及分值;在确定各预警单元所辖边坡地质灾害易发性等级的基础上,结合研究区四级气象预警判据建立基于路段单元的公路地质灾害风险气象预警模型,采用Java语言开发预警系统。经与2021年“烟花”台风期新生公路地质灾害点验证发现,预警成功率为100%。研究结果提供了公路地质灾害风险气象预警单元的划分方法和系统研发思路,能够为山区公路地质灾害风险气象预警提供借鉴与参考。

GIS COMPONENT BASED 3D LANDSLIDE HAZARD ASSESSMENT SYSTEM: 3DSLOPEGIS

In this paper, based on a new Geographic Information System (GIS) grid-based three-dimensional (3D) deterministic model and taken the slope unit as the study object, the landslide hazard is mapped by the index of the 3D safety factor. Compared with the one-dimensional (1D) model of infinite slope, which is now widely used for deterministic model based landslide hazard assessment in GIS, the GIS grid-based 3D model is more acceptable and is more adaptable for three-dimensional landslide. Assuming the initial slip as the lower part of an ellipsoid, the 3D critical slip surface in the 3D slope stability analysis is obtained by means of a minimization of the 3D safety factor using the Monte Carlo random simulation. Using a hydraulic model tool for the watershed analysis in GIS, an automatic process has been developed for identifying the slope unit from digital elevation model (DEM) data. Compared with the grid-based landslide hazard mapping method, the slope unit possesses clear topographical meaning, so its results are more credible. All the calculations are implemented by a computational program, 3DSlopeGIS, in which a GIS component is used for fulfilling the GIS spatial analysis function, and all the data for the 3D slope safety factor calculation are in the form of GIS data (the vector and the grid layers). Because of all these merits of the GIS-based 3D landslide hazard mapping method, the complex algorithms and iteration procedures of the 3D problem can also be perfectly implemented.

山区切坡活动引发地质灾害风险评估及其防控措施

以秦岭北麓西安市临潼区仁宗街道为研究区,在野外调查、遥感解译的基础上,确定、分析了40处地质灾害隐患点的发育特征及其主要影响因素;基于DEM数据,构建了研究区663个斜坡单元地质灾害风险评估体系,通过地质灾害易发性、危险性和易损性分析,得到了考虑斜坡稳定性和承灾体危害性的仁宗街道斜坡单元地质灾害综合风险评估结果;通过野外实地验证,证实了评估结果的准确性和可靠性。据此划分了地质灾害防治区,从防灾减灾和工程建设两维度提出了仁宗街道的地质灾害风险防控措施建议,为研究区国土空间规划提供参考依据。