The network of Himalayan roadways and highways connects some remote regions of valleys or hill slopes,which is vital for India’s socio-economic growth.Due to natural and artificial factors,frequency of slope instabil...The network of Himalayan roadways and highways connects some remote regions of valleys or hill slopes,which is vital for India’s socio-economic growth.Due to natural and artificial factors,frequency of slope instabilities along the networks has been increasing over last few decades.Assessment of stability of natural and artificial slopes due to construction of these connecting road networks is significant in safely executing these roads throughout the year.Several rock mass classification methods are generally used to assess the strength and deformability of rock mass.This study assesses slope stability along the NH-1A of Ramban district of North Western Himalayas.Various structurally and non-structurally controlled rock mass classification systems have been applied to assess the stability conditions of 14 slopes.For evaluating the stability of these slopes,kinematic analysis was performed along with geological strength index(GSI),rock mass rating(RMR),continuous slope mass rating(CoSMR),slope mass rating(SMR),and Q-slope in the present study.The SMR gives three slopes as completely unstable while CoSMR suggests four slopes as completely unstable.The stability of all slopes was also analyzed using a design chart under dynamic and static conditions by slope stability rating(SSR)for the factor of safety(FoS)of 1.2 and 1 respectively.Q-slope with probability of failure(PoF)1%gives two slopes as stable slopes.Stable slope angle has been determined based on the Q-slope safe angle equation and SSR design chart based on the FoS.The value ranges given by different empirical classifications were RMR(37-74),GSI(27.3-58.5),SMR(11-59),and CoSMR(3.39-74.56).Good relationship was found among RMR&SSR and RMR&GSI with correlation coefficient(R 2)value of 0.815 and 0.6866,respectively.Lastly,a comparative stability of all these slopes based on the above classification has been performed to identify the most critical slope along this road.展开更多
A common reclamation practice for closed coal surface mines is filling them with water to form pit lakes.The creation and sustainability of these lakes are significantly affected by the stability of the corresponding ...A common reclamation practice for closed coal surface mines is filling them with water to form pit lakes.The creation and sustainability of these lakes are significantly affected by the stability of the corresponding slopes.The present study provides a general framework for analyzing the water filling’s effect on slope stability based on a new water filling index,which can indirectly consider the factors affecting the process and efficiently quantify the filling speed’s influence.The assumptions of the proposed approach are thoroughly discussed,and the range of the water filling index is identified.Furthermore,the safety factor is calculated using the finite element method with the shear strength reduction technique during the filling process for various conditions(soil properties,slope geometry,hydraulic conditions,and water filling speed).Results are presented as normalized stability charts for practical use.During the water filling,the stability gradually decreases until the reservoir reaches a critical level of 10%e40%of the total height;it then increases to even more stable conditions than the initial one.Overall,the present analysis allows for the preliminary stability evaluation of a coal mine during the formation of a pit lake and the appropriate quantification of the water filling’s effect.展开更多
Slope stability prediction research is a complex non-linear system problem.In carrying out slope stability prediction work,it often encounters low accuracy of prediction models and blind data preprocessing.Based on 77...Slope stability prediction research is a complex non-linear system problem.In carrying out slope stability prediction work,it often encounters low accuracy of prediction models and blind data preprocessing.Based on 77 field cases,5 quantitative indicators are selected to improve the accuracy of prediction models for slope stability.These indicators include slope angle,slope height,internal friction angle,cohesion and unit weight of rock and soil.Potential data aggregation in the prediction of slope stability is analyzed and visualized based on Six-dimension reduction methods,namely principal components analysis(PCA),Kernel PCA,factor analysis(FA),independent component analysis(ICA),non-negative matrix factorization(NMF)and t-SNE(stochastic neighbor embedding).Combined with classic machine learning methods,7 prediction models for slope stability are established and their reliabilities are examined by random cross validation.Besides,the significance of each indicator in the prediction of slope stability is discussed using the coefficient of variation method.The research results show that dimension reduction is unnecessary for the data processing of prediction models established in this paper of slope stability.Random forest(RF),support vector machine(SVM)and k-nearest neighbour(KNN)achieve the best prediction accuracy,which is higher than 90%.The decision tree(DT)has better accuracy which is 86%.The most important factor influencing slope stability is slope height,while unit weight of rock and soil is the least significant.RF and SVM models have the best accuracy and superiority in slope stability prediction.The results provide a new approach toward slope stability prediction in geotechnical engineering.展开更多
The numerical simulation and slope stability prediction are the focus of slope disaster research.Recently,machine learning models are commonly used in the slope stability prediction.However,these machine learning mode...The numerical simulation and slope stability prediction are the focus of slope disaster research.Recently,machine learning models are commonly used in the slope stability prediction.However,these machine learning models have some problems,such as poor nonlinear performance,local optimum and incomplete factors feature extraction.These issues can affect the accuracy of slope stability prediction.Therefore,a deep learning algorithm called Long short-term memory(LSTM)has been innovatively proposed to predict slope stability.Taking the Ganzhou City in China as the study area,the landslide inventory and their characteristics of geotechnical parameters,slope height and slope angle are analyzed.Based on these characteristics,typical soil slopes are constructed using the Geo-Studio software.Five control factors affecting slope stability,including slope height,slope angle,internal friction angle,cohesion and volumetric weight,are selected to form different slope and construct model input variables.Then,the limit equilibrium method is used to calculate the stability coefficients of these typical soil slopes under different control factors.Each slope stability coefficient and its corresponding control factors is a slope sample.As a result,a total of 2160 training samples and 450 testing samples are constructed.These sample sets are imported into LSTM for modelling and compared with the support vector machine(SVM),random forest(RF)and convo-lutional neural network(CNN).The results show that the LSTM overcomes the problem that the commonly used machine learning models have difficulty extracting global features.Furthermore,LSTM has a better prediction performance for slope stability compared to SVM,RF and CNN models.展开更多
Slope stability prediction plays a significant role in landslide disaster prevention and mitigation.This paper’s reduced error pruning(REP)tree and random tree(RT)models are developed for slope stability evaluation a...Slope stability prediction plays a significant role in landslide disaster prevention and mitigation.This paper’s reduced error pruning(REP)tree and random tree(RT)models are developed for slope stability evaluation and meeting the high precision and rapidity requirements in slope engineering.The data set of this study includes five parameters,namely slope height,slope angle,cohesion,internal friction angle,and peak ground acceleration.The available data is split into two categories:training(75%)and test(25%)sets.The output of the RT and REP tree models is evaluated using performance measures including accuracy(Acc),Matthews correlation coefficient(Mcc),precision(Prec),recall(Rec),and F-score.The applications of the aforementionedmethods for predicting slope stability are compared to one another and recently established soft computing models in the literature.The analysis of the Acc together with Mcc,and F-score for the slope stability in the test set demonstrates that the RT achieved a better prediction performance with(Acc=97.1429%,Mcc=0.935,F-score for stable class=0.979 and for unstable case F-score=0.935)succeeded by the REP tree model with(Acc=95.4286%,Mcc=0.896,F-score stable class=0.967 and for unstable class F-score=0.923)for the slope stability dataset The analysis of performance measures for the slope stability dataset reveals that the RT model attains comparatively better and reliable results and thus should be encouraged in further research.展开更多
This article systematically delves into a comprehensive analysis of the latest and most advanced techniques for the assessment of slope stability. It particularly focuses on strategies aimed at enhancing slope stabili...This article systematically delves into a comprehensive analysis of the latest and most advanced techniques for the assessment of slope stability. It particularly focuses on strategies aimed at enhancing slope stability in road construction. In addition to this analysis, the article presents an illustrative case study centered on the Toffo-Lalo Road Project. The core objective of this paper is to scrutinize the stability of large embankments in road construction, with a specific emphasis on the development and asphalt overlay of the Toffo-Lalo road. This scrutiny is conducted through the utilization of stability calculation software, GEOSTUDIO2018, specifically its SLOPE/W module. Within this framework, a detailed model of the cutbank located at KP1+750-2+250 was meticulously developed. This model takes into account the physical-mechanical characteristics of the soil at the site, as well as the topographic layout. Its attributes include a cohesion value of 11.3 Kpa, a density of 16.57 KN/m<sup>3</sup>, and a friction angle of 27˚. The modeling results, employing the Morgenstern-Price method—an approach renowned for its adherence to equilibrium conditions and provision of precise results—conclude that the safety coefficient (Fs = 1.429) prior to any reinforcement signifies a critical state of slope stability. To address this, the article explores the implementation of reinforcement techniques, particularly focusing on rigid inclusions like nailing and piles. The modeling exercises reveal a noteworthy enhancement in the safety coefficient (Fs) post-reinforcement. Furthermore, the article undertakes a parametric study to optimize the reinforcement strategies. This analysis highlights that anchoring at 0˚ downward relative to the horizontal plane and employing a pile angle of 90˚ represent the most favorable approaches. These measures yield safety coefficients of 3.60 and 2.34, respectively, indicating substantially improved slope stability.展开更多
This comprehensive review paper explores various aspects of geotechnical engineering, with a focus on the management of unstable terrains, numerical methods for solving complex soil and consolidation problems, rheolog...This comprehensive review paper explores various aspects of geotechnical engineering, with a focus on the management of unstable terrains, numerical methods for solving complex soil and consolidation problems, rheological analysis of suspensions and muddy soils, and stability analysis of slopes. It begins by examining the unique physicochemical properties of cohesive sediments, including cohesion and specific surface area. The temporal evolution of deposit concentration and average bed concentration in unstable terrains is discussed, along with settling behavior of isolated particles and hindered settling using empirical equations. Key sedimentation theories, such as Kynch’s theory, and geotechnical consolidation theories, including Terzaghi’s consolidation equation and Gibson’s theory, are presented. The investigation interrelates these theories and principles to offer a holistic view of managing unstable terrains. It also addresses the challenges associated with experimental determination of constitutive relationships and presents alternative simplification methods proposed by researchers. Additionally, it delves into numerical methods for solving nonlinear partial differential equations governing soil behavior, emphasizing the need for numerical frameworks and discussing various techniques and associated challenges. The rheological analysis section covers material flow behavior, rheological behavior models, and the rheological properties of water and cohesive sediment mixtures. Fundamental geotechnical calculations, constitutive laws, and failure criteria are explained, highlighting their relevance in geotechnical engineering applications. This paper provides a multidimensional perspective on geotechnical engineering, offering valuable insights into soil properties, consolidation processes, numerical methods, rheological analysis, and slope stability assessment for professionals in the field.展开更多
Little research can be found in relation to the stability of anisotropic and heterogenous soils in three dimensions.In this paper,we propose a study on the three-dimensional(3D)undrained slopes in anisotropic and hete...Little research can be found in relation to the stability of anisotropic and heterogenous soils in three dimensions.In this paper,we propose a study on the three-dimensional(3D)undrained slopes in anisotropic and heterogenous clay using advanced upper and lower bounds finite element limit analysis(FELA).The obtained stability solutions are normalized,and presented by a stability number that is a function of three geometrical ratios and two material ratios,i.e.depth ratio,length ratio,slope angle,shear strength gradient ratio and anisotropic strength ratio.Numerical results are compared with experimental data in the literature,and charts are presented to cover a wide range of design parameters.Using the multivariate adaptive regression splines(MARS)analysis,the respective influence and sensitivity of each design parameter on the stability number and the failure mechanism are investigated.An empirical equation is also developed to effectively estimate the stability number.展开更多
The importance of slope stability in civil engineering cannot be underestimated, as failure of these structures can result in significant damage to downstream infrastructure and property. In this study, we used the Bi...The importance of slope stability in civil engineering cannot be underestimated, as failure of these structures can result in significant damage to downstream infrastructure and property. In this study, we used the Bishop slice method, combining both an analytical approach and a numerical approach using the SLOPE/W module of the Geostudio 2018 R2 software. The results obtained from these two methods showed that increasing soil cohesion helps to improve slope stability. The safety coefficients obtained by the analytical method vary between 0.621 and 1.422, while those obtained by the numerical method vary between 0.622 and 1.447, for cohesion values ranging from 4 kPa to 20 kPa. The results obtained by these two methods show a linear relationship between the safety coefficients and soil cohesion. The equation of the analytical method is y = 0.0496x + 0.4407, while that of the numerical method is y = 0.0512x + 0.4357. The results of the analytical approach indicate that a safety coefficient of 1.5 is reached when the cohesion reaches a value of 22 kPa, while the numerical approach shows a safety coefficient of 1.5 reached at a cohesion of 21 kPa. The difference between these two cohesion values can be explained by the number of slices used, which is smaller in the analytical method. However, the equation derived from the analytical method can be used as a general guide to assess the evolution of the safety coefficient of an overloaded slope in long-term behaviour with an increase in cohesion. However, it is important to stress the importance of verification using specialised software based on the finite element method.展开更多
To study the safety and stability of large slopes, taking the right side slope of the Yuxi’an tunnel of the Yuchu Expressway Bridge in Yunnan Province as an example, limit equilibrium and finite element analysis were...To study the safety and stability of large slopes, taking the right side slope of the Yuxi’an tunnel of the Yuchu Expressway Bridge in Yunnan Province as an example, limit equilibrium and finite element analysis were applied to engineering examples to calculate the stability coefficient of the slope before and after excavation in the natural state. After comparative analysis, it was concluded that the former had a clear mechanical model and concept, which could quickly provide stability results;the latter could accurately determine the sliding surface of the slope and simulate the stress state changes of the rock and soil mass. The stability coefficients calculated by the two methods were within the stable range, but their values were different. On this basis, combined with the calculation principles, advantages and disadvantages of the two methods, a comprehensive analysis method of slope stability based on the limit equilibrium and finite element methods was proposed, and the rationality of the stability coefficient calculated by this method was judged for a slope case.展开更多
Knowledge of the state of stability of mining pits is both a basic condition, an essential axis and a safety benchmark for mining operations. This stability is largely based on the knowledge of the rock mass shelterin...Knowledge of the state of stability of mining pits is both a basic condition, an essential axis and a safety benchmark for mining operations. This stability is largely based on the knowledge of the rock mass sheltering the mining works and this requires a perfect characterization of all of its structural formations through mapping (manual or digital). The families of discontinuities, namely family 1 (bedding), family 2 (Joint 2) and family 3 (Joint 1) obtained through structural mapping in the Essakane open pit mine, made it possible to analyze the failure modes at the origin of rock instabilities. The respective dips of these different directional families are: 77˚ - 85˚/N 058˚ - 068˚, 66˚ - 74˚/N 133˚ - 143˚, 25˚ - 35˚/N115˚ - 130˚. An average safety factor of 4.3 was estimated for the area with a quality of the rock mass (RMR) estimated at 47. The results obtained reflect on the one hand the risks of instability associated with the quality of the rock mass studied and on the other hand highlights the state of stability of the study area.展开更多
Slope failures lead to catastrophic consequences in numerous countries and thus the stability assessment for slopes is of high interest in geotechnical and geological engineering researches.A hybrid stacking ensemble ...Slope failures lead to catastrophic consequences in numerous countries and thus the stability assessment for slopes is of high interest in geotechnical and geological engineering researches.A hybrid stacking ensemble approach is proposed in this study for enhancing the prediction of slope stability.In the hybrid stacking ensemble approach,we used an artificial bee colony(ABC)algorithm to find out the best combination of base classifiers(level 0)and determined a suitable meta-classifier(level 1)from a pool of 11 individual optimized machine learning(OML)algorithms.Finite element analysis(FEA)was conducted in order to form the synthetic database for the training stage(150 cases)of the proposed model while 107 real field slope cases were used for the testing stage.The results by the hybrid stacking ensemble approach were then compared with that obtained by the 11 individual OML methods using confusion matrix,F1-score,and area under the curve,i.e.AUC-score.The comparisons showed that a significant improvement in the prediction ability of slope stability has been achieved by the hybrid stacking ensemble(AUC?90.4%),which is 7%higher than the best of the 11 individual OML methods(AUC?82.9%).Then,a further comparison was undertaken between the hybrid stacking ensemble method and basic ensemble classifier on slope stability prediction.The results showed a prominent performance of the hybrid stacking ensemble method over the basic ensemble method.Finally,the importance of the variables for slope stability was studied using linear vector quantization(LVQ)method.展开更多
Slope failure due to improper excavation is one of common engineering disasters in China.To explore the failure mechanism of soil slope induced by toe excavation,especially to investigate the influence of excavation u...Slope failure due to improper excavation is one of common engineering disasters in China.To explore the failure mechanism of soil slope induced by toe excavation,especially to investigate the influence of excavation unloading path and rate on slope stability,a numerical slope model was built via particle flow code PFC2 D.The development of crack and strain during excavation were obtained and used to evaluate the deformation characteristics.Furthermore,excavation types representing different unloading paths and rates were compared in terms of crack number and strain level.Results indicate that crack number and strain level induced by horizontal column excavation are much greater than those of vertical column excavation and oblique excavation.The crack number and strain level increase with excavation unloading rate.Besides,the feasibility of taking the average strain of slope surface and the average value of maximum strain along monitoring lines to represent the global deformation characteristics were discussed.This study can provide a theoretical guidance for slope monitoring and preliminary optimal selection of excavation scheme in the design and construction of slope engineering.展开更多
Rock slope stability is of great concern along highway routes as stability problems on cut slopes may cause fatal events as well as loss of property.In rock slope engineering,stability evaluations are commonly perform...Rock slope stability is of great concern along highway routes as stability problems on cut slopes may cause fatal events as well as loss of property.In rock slope engineering,stability evaluations are commonly performed by means of analytical or numerical analyses,principally considering the factor of safety concept.As a matter of fact,the probabilistic assessment of slope stability is progressively getting popularity due to difficulties in assigning the most appropriate values to design parameters in analytical or numerical methods.Additionally,the effect of heterogeneities in rock masses and discontinuities on the analysis results is minimized through the probabilistic concept.In this study,slope stability of high and steep sedimentary rock cut slopes along a state highway in AdilcevazBitlis(Turkey) was evaluated on the basis of probabilistic approach using the Slope Stability Probability Classification(SSPC) system.The probabilistic assessment indicates major slope stability problems because of discontinuity controlled and discontinuity orientation independent mass movements.Almost all studied cut slopes suffer from orientation-independent stability problems with very low stability probabilities.Additionally,the probability of planar and toppling failures issignificantly high with respect to the SSPC system.The stability problems along the investigated rock slopes were also verified by field reconnaissance.Remedial measures such as slope re-design and reinforcement at the studied locations should be taken to prevent hazardous events along the highway.On the other hand,the probabilistic approach may be a useful tool during rock slope engineering to overcome numerous uncertainties when probabilistic and analytic results are compared.展开更多
Slope stability prediction plays a significant role in landslide disaster prevention and mitigation.This study develops an ensemble learning-based method to predict the slope stability by introducing the random forest...Slope stability prediction plays a significant role in landslide disaster prevention and mitigation.This study develops an ensemble learning-based method to predict the slope stability by introducing the random forest(RF)and extreme gradient boosting(XGBoost).As an illustration,the proposed approach is applied to the stability prediction of 786 landslide cases in Yunyang County,Chongqing,China.For comparison,the predictive performance of RF,XGBoost,support vector machine(SVM),and logistic regression(LR)is systematically investigated based on the well-established confusion matrix,which contains the known indices of recall rate,precision,and accuracy.Furthermore,the feature importance of the 12 influencing variables is also explored.Results show that the accuracy of the XGBoost and RF for both the training and testing data is superior to that of SVM and LR,revealing the superiority of the ensemble learning models(i.e.XGBoost and RF)in the slope stability prediction of Yunyang County.Among the 12 influencing factors,the profile shape is the most important one.The proposed ensemble learning-based method offers a promising way to rationally capture the slope status.It can be extended to the prediction of slope stability of other landslide-prone areas of interest.展开更多
Slope failures are an inevitable aspect of economic pit slope designs in the mining industry.Large open pit guidelines and industry standards accept up to 30%of benches in open pits to collapse provided that they are ...Slope failures are an inevitable aspect of economic pit slope designs in the mining industry.Large open pit guidelines and industry standards accept up to 30%of benches in open pits to collapse provided that they are controlled and that no personnel are at risk.Rigorous ground control measures including real time monitoring systems at TARP(trigger-action-response-plan)protocols are widely utilized to prevent personnel from being exposed to slope failure risks.Technology and computing capability are rapidly evolving.Aerial photogrammetry techniques using UAV(unmanned aerial vehicle)enable geotechnical engineers and engineering geologists to work faster and more safely by removing themselves from potential line-of-fire near unstable slopes.Slope stability modelling software using limit equilibrium(LE)and finite element(FE)methods in three dimensions(3D)is also becoming more accessible,user-friendly and faster to operate.These key components enable geotechnical engineers to undertake site investigations,develop geotechnical models and assess slope stability faster and in more detail with less exposure to fall of ground hazards in the field.This paper describes the rapid and robust process utilized at BHP Limited for appraising a slope failure at an iron ore mine site in the Pilbara region of Western Australia using a combination of UAV photogrammetry and 3D slope stability models in less than a shift(i.e.less than 12 h).展开更多
The anisotropy effect is one of the most prominent phenomena in soil mechanics. Although many experimental programs have investigated anisotropy in sand, a computational procedure for determining anisotropy is lacking...The anisotropy effect is one of the most prominent phenomena in soil mechanics. Although many experimental programs have investigated anisotropy in sand, a computational procedure for determining anisotropy is lacking. Thus, this work aims to develop a procedure for connecting the sand friction angle and the loading orientation. All principal stress rotation tests in the literatures were processed via an artificial neural network. Then, with sensitivity analysis, the effect of intrinsic soil properties,consolidation history, and test sample characteristics on enhancing anisotropy was examined. The results imply that decreasing the grain size of the soil increases the effect of anisotropy on soil shear strength. In addition, increasing the angularity of grains increases the anisotropy effect in the sample. The stability of a sandy slope was also examined by considering the anisotropy in shear strength parameters. If the anisotropy effect is neglected, slope safety is overestimated by 5%-25%. This deviation is more apparent in flatter slopes than in steeper ones. However, the critical slip surface in the most slopes is the same in isotropic and anisotropic conditions.展开更多
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 te...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.展开更多
Seismic pile–slope stability analysis and the formation mechanism of soil arching have not been well studied. This study used a threedimensional(3D) finite difference to determine soil and pile parameter changes in t...Seismic pile–slope stability analysis and the formation mechanism of soil arching have not been well studied. This study used a threedimensional(3D) finite difference to determine soil and pile parameter changes in the static and seismic stability of the pile–slope caused by the interaction between stabilizing piles. Pile–slope stability analysis was performed to determine the optimal design of piles along a slope and the corresponding failure mode involving the formation of soil arching around two adjacent piles. The Factor of Safety(FS) of the slope was evaluated using the shear strength reduction method for static and seismic analyses. The results of the analysis show that suitable pile spacing(S) and a suitable pile diameter(D) in the middle of a slope result in the maximum FS for the pile–slope system and the formation of soil arching around two adjacent piles. FS of the pile–slope increased negligibly in the seismic analysis of piles located at the slope crest and toe. An optimized pile diameter and installation location afforded the maximum FS for the slope that corresponded to a specified slope failure mode for different pile locations. A pile spacing S ≤ 2.5D for piles installed in the middle of the slope is suggested for increasing the static and seismic pile–slope stability.展开更多
Natural soils contain a certain amount of salt in the form of dissolved ions or electrically charged atoms,originated from the long-term erosion by acidic rainwater.The dissolved salt poses an extra osmotic water pote...Natural soils contain a certain amount of salt in the form of dissolved ions or electrically charged atoms,originated from the long-term erosion by acidic rainwater.The dissolved salt poses an extra osmotic water potential being normally neglected in laboratory measurements and numerical analyses.However,ignorance of salinity may result in overestimation of stability,and the design may not be as conservative as thought.Therefore,this research aims to first experimentally examine the influence of pore water salinity on water retention curve and saturated permeability of natural dispersive loess under saline and desalinated conditions.Second,the measured parameters are used for stability analyses of a railway embankment in an area subjected to regional rainfall incident.Eventually,a numerical parametric study is carried out to explore the significance of different rainfall schemes,construction patterns,and anisotropic permeability on the factor of safety.Results reveal that desalinization suppresses the water retention capability,which in turn results in a tremendous declination of unsaturated hydraulic conductivity.Despite the natural saline embankment,rainfall can hardly infiltrate into the desalinated embankment due to the lower conductivity.Therefore,the factor of safety for natural saline conditions drops notably,while only marginal changes occur in the case of the desalinated embankment.展开更多
文摘The network of Himalayan roadways and highways connects some remote regions of valleys or hill slopes,which is vital for India’s socio-economic growth.Due to natural and artificial factors,frequency of slope instabilities along the networks has been increasing over last few decades.Assessment of stability of natural and artificial slopes due to construction of these connecting road networks is significant in safely executing these roads throughout the year.Several rock mass classification methods are generally used to assess the strength and deformability of rock mass.This study assesses slope stability along the NH-1A of Ramban district of North Western Himalayas.Various structurally and non-structurally controlled rock mass classification systems have been applied to assess the stability conditions of 14 slopes.For evaluating the stability of these slopes,kinematic analysis was performed along with geological strength index(GSI),rock mass rating(RMR),continuous slope mass rating(CoSMR),slope mass rating(SMR),and Q-slope in the present study.The SMR gives three slopes as completely unstable while CoSMR suggests four slopes as completely unstable.The stability of all slopes was also analyzed using a design chart under dynamic and static conditions by slope stability rating(SSR)for the factor of safety(FoS)of 1.2 and 1 respectively.Q-slope with probability of failure(PoF)1%gives two slopes as stable slopes.Stable slope angle has been determined based on the Q-slope safe angle equation and SSR design chart based on the FoS.The value ranges given by different empirical classifications were RMR(37-74),GSI(27.3-58.5),SMR(11-59),and CoSMR(3.39-74.56).Good relationship was found among RMR&SSR and RMR&GSI with correlation coefficient(R 2)value of 0.815 and 0.6866,respectively.Lastly,a comparative stability of all these slopes based on the above classification has been performed to identify the most critical slope along this road.
基金This work has received funding from the European Union’s Research Fund for Coal and Steel under the projects RAFF grant agreement No.847299 and POMHAZ grant agreement No.101057326.Financial assistance by the European Commission is much appreciated.
文摘A common reclamation practice for closed coal surface mines is filling them with water to form pit lakes.The creation and sustainability of these lakes are significantly affected by the stability of the corresponding slopes.The present study provides a general framework for analyzing the water filling’s effect on slope stability based on a new water filling index,which can indirectly consider the factors affecting the process and efficiently quantify the filling speed’s influence.The assumptions of the proposed approach are thoroughly discussed,and the range of the water filling index is identified.Furthermore,the safety factor is calculated using the finite element method with the shear strength reduction technique during the filling process for various conditions(soil properties,slope geometry,hydraulic conditions,and water filling speed).Results are presented as normalized stability charts for practical use.During the water filling,the stability gradually decreases until the reservoir reaches a critical level of 10%e40%of the total height;it then increases to even more stable conditions than the initial one.Overall,the present analysis allows for the preliminary stability evaluation of a coal mine during the formation of a pit lake and the appropriate quantification of the water filling’s effect.
基金by the National Natural Science Foundation of China(No.52174114)the State Key Laboratory of Hydroscience and Engineering of Tsinghua University(No.61010101218).
文摘Slope stability prediction research is a complex non-linear system problem.In carrying out slope stability prediction work,it often encounters low accuracy of prediction models and blind data preprocessing.Based on 77 field cases,5 quantitative indicators are selected to improve the accuracy of prediction models for slope stability.These indicators include slope angle,slope height,internal friction angle,cohesion and unit weight of rock and soil.Potential data aggregation in the prediction of slope stability is analyzed and visualized based on Six-dimension reduction methods,namely principal components analysis(PCA),Kernel PCA,factor analysis(FA),independent component analysis(ICA),non-negative matrix factorization(NMF)and t-SNE(stochastic neighbor embedding).Combined with classic machine learning methods,7 prediction models for slope stability are established and their reliabilities are examined by random cross validation.Besides,the significance of each indicator in the prediction of slope stability is discussed using the coefficient of variation method.The research results show that dimension reduction is unnecessary for the data processing of prediction models established in this paper of slope stability.Random forest(RF),support vector machine(SVM)and k-nearest neighbour(KNN)achieve the best prediction accuracy,which is higher than 90%.The decision tree(DT)has better accuracy which is 86%.The most important factor influencing slope stability is slope height,while unit weight of rock and soil is the least significant.RF and SVM models have the best accuracy and superiority in slope stability prediction.The results provide a new approach toward slope stability prediction in geotechnical engineering.
基金funded by the National Natural Science Foundation of China (41807285)。
文摘The numerical simulation and slope stability prediction are the focus of slope disaster research.Recently,machine learning models are commonly used in the slope stability prediction.However,these machine learning models have some problems,such as poor nonlinear performance,local optimum and incomplete factors feature extraction.These issues can affect the accuracy of slope stability prediction.Therefore,a deep learning algorithm called Long short-term memory(LSTM)has been innovatively proposed to predict slope stability.Taking the Ganzhou City in China as the study area,the landslide inventory and their characteristics of geotechnical parameters,slope height and slope angle are analyzed.Based on these characteristics,typical soil slopes are constructed using the Geo-Studio software.Five control factors affecting slope stability,including slope height,slope angle,internal friction angle,cohesion and volumetric weight,are selected to form different slope and construct model input variables.Then,the limit equilibrium method is used to calculate the stability coefficients of these typical soil slopes under different control factors.Each slope stability coefficient and its corresponding control factors is a slope sample.As a result,a total of 2160 training samples and 450 testing samples are constructed.These sample sets are imported into LSTM for modelling and compared with the support vector machine(SVM),random forest(RF)and convo-lutional neural network(CNN).The results show that the LSTM overcomes the problem that the commonly used machine learning models have difficulty extracting global features.Furthermore,LSTM has a better prediction performance for slope stability compared to SVM,RF and CNN models.
基金supported by the National Key Research and Development Plan of China under Grant No.2021YFB2600703.
文摘Slope stability prediction plays a significant role in landslide disaster prevention and mitigation.This paper’s reduced error pruning(REP)tree and random tree(RT)models are developed for slope stability evaluation and meeting the high precision and rapidity requirements in slope engineering.The data set of this study includes five parameters,namely slope height,slope angle,cohesion,internal friction angle,and peak ground acceleration.The available data is split into two categories:training(75%)and test(25%)sets.The output of the RT and REP tree models is evaluated using performance measures including accuracy(Acc),Matthews correlation coefficient(Mcc),precision(Prec),recall(Rec),and F-score.The applications of the aforementionedmethods for predicting slope stability are compared to one another and recently established soft computing models in the literature.The analysis of the Acc together with Mcc,and F-score for the slope stability in the test set demonstrates that the RT achieved a better prediction performance with(Acc=97.1429%,Mcc=0.935,F-score for stable class=0.979 and for unstable case F-score=0.935)succeeded by the REP tree model with(Acc=95.4286%,Mcc=0.896,F-score stable class=0.967 and for unstable class F-score=0.923)for the slope stability dataset The analysis of performance measures for the slope stability dataset reveals that the RT model attains comparatively better and reliable results and thus should be encouraged in further research.
文摘This article systematically delves into a comprehensive analysis of the latest and most advanced techniques for the assessment of slope stability. It particularly focuses on strategies aimed at enhancing slope stability in road construction. In addition to this analysis, the article presents an illustrative case study centered on the Toffo-Lalo Road Project. The core objective of this paper is to scrutinize the stability of large embankments in road construction, with a specific emphasis on the development and asphalt overlay of the Toffo-Lalo road. This scrutiny is conducted through the utilization of stability calculation software, GEOSTUDIO2018, specifically its SLOPE/W module. Within this framework, a detailed model of the cutbank located at KP1+750-2+250 was meticulously developed. This model takes into account the physical-mechanical characteristics of the soil at the site, as well as the topographic layout. Its attributes include a cohesion value of 11.3 Kpa, a density of 16.57 KN/m<sup>3</sup>, and a friction angle of 27˚. The modeling results, employing the Morgenstern-Price method—an approach renowned for its adherence to equilibrium conditions and provision of precise results—conclude that the safety coefficient (Fs = 1.429) prior to any reinforcement signifies a critical state of slope stability. To address this, the article explores the implementation of reinforcement techniques, particularly focusing on rigid inclusions like nailing and piles. The modeling exercises reveal a noteworthy enhancement in the safety coefficient (Fs) post-reinforcement. Furthermore, the article undertakes a parametric study to optimize the reinforcement strategies. This analysis highlights that anchoring at 0˚ downward relative to the horizontal plane and employing a pile angle of 90˚ represent the most favorable approaches. These measures yield safety coefficients of 3.60 and 2.34, respectively, indicating substantially improved slope stability.
文摘This comprehensive review paper explores various aspects of geotechnical engineering, with a focus on the management of unstable terrains, numerical methods for solving complex soil and consolidation problems, rheological analysis of suspensions and muddy soils, and stability analysis of slopes. It begins by examining the unique physicochemical properties of cohesive sediments, including cohesion and specific surface area. The temporal evolution of deposit concentration and average bed concentration in unstable terrains is discussed, along with settling behavior of isolated particles and hindered settling using empirical equations. Key sedimentation theories, such as Kynch’s theory, and geotechnical consolidation theories, including Terzaghi’s consolidation equation and Gibson’s theory, are presented. The investigation interrelates these theories and principles to offer a holistic view of managing unstable terrains. It also addresses the challenges associated with experimental determination of constitutive relationships and presents alternative simplification methods proposed by researchers. Additionally, it delves into numerical methods for solving nonlinear partial differential equations governing soil behavior, emphasizing the need for numerical frameworks and discussing various techniques and associated challenges. The rheological analysis section covers material flow behavior, rheological behavior models, and the rheological properties of water and cohesive sediment mixtures. Fundamental geotechnical calculations, constitutive laws, and failure criteria are explained, highlighting their relevance in geotechnical engineering applications. This paper provides a multidimensional perspective on geotechnical engineering, offering valuable insights into soil properties, consolidation processes, numerical methods, rheological analysis, and slope stability assessment for professionals in the field.
文摘Little research can be found in relation to the stability of anisotropic and heterogenous soils in three dimensions.In this paper,we propose a study on the three-dimensional(3D)undrained slopes in anisotropic and heterogenous clay using advanced upper and lower bounds finite element limit analysis(FELA).The obtained stability solutions are normalized,and presented by a stability number that is a function of three geometrical ratios and two material ratios,i.e.depth ratio,length ratio,slope angle,shear strength gradient ratio and anisotropic strength ratio.Numerical results are compared with experimental data in the literature,and charts are presented to cover a wide range of design parameters.Using the multivariate adaptive regression splines(MARS)analysis,the respective influence and sensitivity of each design parameter on the stability number and the failure mechanism are investigated.An empirical equation is also developed to effectively estimate the stability number.
文摘The importance of slope stability in civil engineering cannot be underestimated, as failure of these structures can result in significant damage to downstream infrastructure and property. In this study, we used the Bishop slice method, combining both an analytical approach and a numerical approach using the SLOPE/W module of the Geostudio 2018 R2 software. The results obtained from these two methods showed that increasing soil cohesion helps to improve slope stability. The safety coefficients obtained by the analytical method vary between 0.621 and 1.422, while those obtained by the numerical method vary between 0.622 and 1.447, for cohesion values ranging from 4 kPa to 20 kPa. The results obtained by these two methods show a linear relationship between the safety coefficients and soil cohesion. The equation of the analytical method is y = 0.0496x + 0.4407, while that of the numerical method is y = 0.0512x + 0.4357. The results of the analytical approach indicate that a safety coefficient of 1.5 is reached when the cohesion reaches a value of 22 kPa, while the numerical approach shows a safety coefficient of 1.5 reached at a cohesion of 21 kPa. The difference between these two cohesion values can be explained by the number of slices used, which is smaller in the analytical method. However, the equation derived from the analytical method can be used as a general guide to assess the evolution of the safety coefficient of an overloaded slope in long-term behaviour with an increase in cohesion. However, it is important to stress the importance of verification using specialised software based on the finite element method.
文摘To study the safety and stability of large slopes, taking the right side slope of the Yuxi’an tunnel of the Yuchu Expressway Bridge in Yunnan Province as an example, limit equilibrium and finite element analysis were applied to engineering examples to calculate the stability coefficient of the slope before and after excavation in the natural state. After comparative analysis, it was concluded that the former had a clear mechanical model and concept, which could quickly provide stability results;the latter could accurately determine the sliding surface of the slope and simulate the stress state changes of the rock and soil mass. The stability coefficients calculated by the two methods were within the stable range, but their values were different. On this basis, combined with the calculation principles, advantages and disadvantages of the two methods, a comprehensive analysis method of slope stability based on the limit equilibrium and finite element methods was proposed, and the rationality of the stability coefficient calculated by this method was judged for a slope case.
文摘Knowledge of the state of stability of mining pits is both a basic condition, an essential axis and a safety benchmark for mining operations. This stability is largely based on the knowledge of the rock mass sheltering the mining works and this requires a perfect characterization of all of its structural formations through mapping (manual or digital). The families of discontinuities, namely family 1 (bedding), family 2 (Joint 2) and family 3 (Joint 1) obtained through structural mapping in the Essakane open pit mine, made it possible to analyze the failure modes at the origin of rock instabilities. The respective dips of these different directional families are: 77˚ - 85˚/N 058˚ - 068˚, 66˚ - 74˚/N 133˚ - 143˚, 25˚ - 35˚/N115˚ - 130˚. An average safety factor of 4.3 was estimated for the area with a quality of the rock mass (RMR) estimated at 47. The results obtained reflect on the one hand the risks of instability associated with the quality of the rock mass studied and on the other hand highlights the state of stability of the study area.
基金We acknowledge the funding support from Australia Research Council(Grant Nos.DP200100549 and IH180100010).
文摘Slope failures lead to catastrophic consequences in numerous countries and thus the stability assessment for slopes is of high interest in geotechnical and geological engineering researches.A hybrid stacking ensemble approach is proposed in this study for enhancing the prediction of slope stability.In the hybrid stacking ensemble approach,we used an artificial bee colony(ABC)algorithm to find out the best combination of base classifiers(level 0)and determined a suitable meta-classifier(level 1)from a pool of 11 individual optimized machine learning(OML)algorithms.Finite element analysis(FEA)was conducted in order to form the synthetic database for the training stage(150 cases)of the proposed model while 107 real field slope cases were used for the testing stage.The results by the hybrid stacking ensemble approach were then compared with that obtained by the 11 individual OML methods using confusion matrix,F1-score,and area under the curve,i.e.AUC-score.The comparisons showed that a significant improvement in the prediction ability of slope stability has been achieved by the hybrid stacking ensemble(AUC?90.4%),which is 7%higher than the best of the 11 individual OML methods(AUC?82.9%).Then,a further comparison was undertaken between the hybrid stacking ensemble method and basic ensemble classifier on slope stability prediction.The results showed a prominent performance of the hybrid stacking ensemble method over the basic ensemble method.Finally,the importance of the variables for slope stability was studied using linear vector quantization(LVQ)method.
基金supported by the General Financial Grant from the Natural Science Foundation of Chongqing,China(cstc2018jcyjAX0632)the Chongqing Postdoctoral Science Foundation(cstc2019jcyj-bshX0032)the Chongqing Engineering Research Center of Disaster Prevention&Control for Banks and Structures in Three Gorges Reservoir Area(Nos.SXAPGC18ZD01 and SXAPGC18YB03)。
文摘Slope failure due to improper excavation is one of common engineering disasters in China.To explore the failure mechanism of soil slope induced by toe excavation,especially to investigate the influence of excavation unloading path and rate on slope stability,a numerical slope model was built via particle flow code PFC2 D.The development of crack and strain during excavation were obtained and used to evaluate the deformation characteristics.Furthermore,excavation types representing different unloading paths and rates were compared in terms of crack number and strain level.Results indicate that crack number and strain level induced by horizontal column excavation are much greater than those of vertical column excavation and oblique excavation.The crack number and strain level increase with excavation unloading rate.Besides,the feasibility of taking the average strain of slope surface and the average value of maximum strain along monitoring lines to represent the global deformation characteristics were discussed.This study can provide a theoretical guidance for slope monitoring and preliminary optimal selection of excavation scheme in the design and construction of slope engineering.
基金financially supported by the Scientific Research Projects Office of YüzüncüYil University(YYU-BAP,Project Number 2012-FBEYL48)
文摘Rock slope stability is of great concern along highway routes as stability problems on cut slopes may cause fatal events as well as loss of property.In rock slope engineering,stability evaluations are commonly performed by means of analytical or numerical analyses,principally considering the factor of safety concept.As a matter of fact,the probabilistic assessment of slope stability is progressively getting popularity due to difficulties in assigning the most appropriate values to design parameters in analytical or numerical methods.Additionally,the effect of heterogeneities in rock masses and discontinuities on the analysis results is minimized through the probabilistic concept.In this study,slope stability of high and steep sedimentary rock cut slopes along a state highway in AdilcevazBitlis(Turkey) was evaluated on the basis of probabilistic approach using the Slope Stability Probability Classification(SSPC) system.The probabilistic assessment indicates major slope stability problems because of discontinuity controlled and discontinuity orientation independent mass movements.Almost all studied cut slopes suffer from orientation-independent stability problems with very low stability probabilities.Additionally,the probability of planar and toppling failures issignificantly high with respect to the SSPC system.The stability problems along the investigated rock slopes were also verified by field reconnaissance.Remedial measures such as slope re-design and reinforcement at the studied locations should be taken to prevent hazardous events along the highway.On the other hand,the probabilistic approach may be a useful tool during rock slope engineering to overcome numerous uncertainties when probabilistic and analytic results are compared.
基金supports from National Natural Science Foundation of China(Grant No.52008058)National Key R&D Program of China(Grant No.2019YFC1509605)High-end Foreign Expert Introduction program(Grant No.G20200022005).
文摘Slope stability prediction plays a significant role in landslide disaster prevention and mitigation.This study develops an ensemble learning-based method to predict the slope stability by introducing the random forest(RF)and extreme gradient boosting(XGBoost).As an illustration,the proposed approach is applied to the stability prediction of 786 landslide cases in Yunyang County,Chongqing,China.For comparison,the predictive performance of RF,XGBoost,support vector machine(SVM),and logistic regression(LR)is systematically investigated based on the well-established confusion matrix,which contains the known indices of recall rate,precision,and accuracy.Furthermore,the feature importance of the 12 influencing variables is also explored.Results show that the accuracy of the XGBoost and RF for both the training and testing data is superior to that of SVM and LR,revealing the superiority of the ensemble learning models(i.e.XGBoost and RF)in the slope stability prediction of Yunyang County.Among the 12 influencing factors,the profile shape is the most important one.The proposed ensemble learning-based method offers a promising way to rationally capture the slope status.It can be extended to the prediction of slope stability of other landslide-prone areas of interest.
文摘Slope failures are an inevitable aspect of economic pit slope designs in the mining industry.Large open pit guidelines and industry standards accept up to 30%of benches in open pits to collapse provided that they are controlled and that no personnel are at risk.Rigorous ground control measures including real time monitoring systems at TARP(trigger-action-response-plan)protocols are widely utilized to prevent personnel from being exposed to slope failure risks.Technology and computing capability are rapidly evolving.Aerial photogrammetry techniques using UAV(unmanned aerial vehicle)enable geotechnical engineers and engineering geologists to work faster and more safely by removing themselves from potential line-of-fire near unstable slopes.Slope stability modelling software using limit equilibrium(LE)and finite element(FE)methods in three dimensions(3D)is also becoming more accessible,user-friendly and faster to operate.These key components enable geotechnical engineers to undertake site investigations,develop geotechnical models and assess slope stability faster and in more detail with less exposure to fall of ground hazards in the field.This paper describes the rapid and robust process utilized at BHP Limited for appraising a slope failure at an iron ore mine site in the Pilbara region of Western Australia using a combination of UAV photogrammetry and 3D slope stability models in less than a shift(i.e.less than 12 h).
文摘The anisotropy effect is one of the most prominent phenomena in soil mechanics. Although many experimental programs have investigated anisotropy in sand, a computational procedure for determining anisotropy is lacking. Thus, this work aims to develop a procedure for connecting the sand friction angle and the loading orientation. All principal stress rotation tests in the literatures were processed via an artificial neural network. Then, with sensitivity analysis, the effect of intrinsic soil properties,consolidation history, and test sample characteristics on enhancing anisotropy was examined. The results imply that decreasing the grain size of the soil increases the effect of anisotropy on soil shear strength. In addition, increasing the angularity of grains increases the anisotropy effect in the sample. The stability of a sandy slope was also examined by considering the anisotropy in shear strength parameters. If the anisotropy effect is neglected, slope safety is overestimated by 5%-25%. This deviation is more apparent in flatter slopes than in steeper ones. However, the critical slip surface in the most slopes is the same in isotropic and anisotropic conditions.
基金financially supported by the Research Grants Council of the Hong Kong Special Administrative Region(Project No.15212418)。
文摘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.
文摘Seismic pile–slope stability analysis and the formation mechanism of soil arching have not been well studied. This study used a threedimensional(3D) finite difference to determine soil and pile parameter changes in the static and seismic stability of the pile–slope caused by the interaction between stabilizing piles. Pile–slope stability analysis was performed to determine the optimal design of piles along a slope and the corresponding failure mode involving the formation of soil arching around two adjacent piles. The Factor of Safety(FS) of the slope was evaluated using the shear strength reduction method for static and seismic analyses. The results of the analysis show that suitable pile spacing(S) and a suitable pile diameter(D) in the middle of a slope result in the maximum FS for the pile–slope system and the formation of soil arching around two adjacent piles. FS of the pile–slope increased negligibly in the seismic analysis of piles located at the slope crest and toe. An optimized pile diameter and installation location afforded the maximum FS for the slope that corresponded to a specified slope failure mode for different pile locations. A pile spacing S ≤ 2.5D for piles installed in the middle of the slope is suggested for increasing the static and seismic pile–slope stability.
基金the Iran’s National Elites Foundation and the Research Grant Office at Sharif University Technology for supporting this research by way of “Dr Kazemi-Ashtiani Award” and grant “G970902”,respectively。
文摘Natural soils contain a certain amount of salt in the form of dissolved ions or electrically charged atoms,originated from the long-term erosion by acidic rainwater.The dissolved salt poses an extra osmotic water potential being normally neglected in laboratory measurements and numerical analyses.However,ignorance of salinity may result in overestimation of stability,and the design may not be as conservative as thought.Therefore,this research aims to first experimentally examine the influence of pore water salinity on water retention curve and saturated permeability of natural dispersive loess under saline and desalinated conditions.Second,the measured parameters are used for stability analyses of a railway embankment in an area subjected to regional rainfall incident.Eventually,a numerical parametric study is carried out to explore the significance of different rainfall schemes,construction patterns,and anisotropic permeability on the factor of safety.Results reveal that desalinization suppresses the water retention capability,which in turn results in a tremendous declination of unsaturated hydraulic conductivity.Despite the natural saline embankment,rainfall can hardly infiltrate into the desalinated embankment due to the lower conductivity.Therefore,the factor of safety for natural saline conditions drops notably,while only marginal changes occur in the case of the desalinated embankment.
