Bio-cementation for tidal erosion resistance improvement of foreshore slopes based on microbially induced magnesium and calcium precipitation

In most coastal and estuarine areas,tides easily cause surface erosion and even slope failure,resulting in severe land losses,deterioration of coastal infrastructure,and increased floods.The bio-cementation technique has been previously demonstrated to effectively improve the erosion resistance of slopes.Seawater contains magnesium ions(Mg^(2+))with a higher concentration than calcium ions(Ca^(2+));therefore,Mg^(2+)and Ca^(2+)were used together for bio-cementation in this study at various Mg^(2+)/Ca^(2+)ratios as the microbially induced magnesium and calcium precipitation(MIMCP)treatment.Slope angles,surface strengths,precipitation contents,major phases,and microscopic characteristics of precipitation were used to evaluate the treatment effects.Results showed that the MIMCP treatment markedly enhanced the erosion resistance of slopes.Decreased Mg^(2+)/Ca^(2+)ratios resulted in a smaller change in angles and fewer soil losses,especially the Mg^(2+)concentration below 0.2 M.The decreased Mg^(2+)/Ca^(2+)ratio achieved increased precipitation contents,which contributed to better erosion resistance and higher surface strengths.Additionally,the production of aragonite would benefit from elevated Mg^(2+)concentrations and a higher Ca^(2+)concentration led to more nesquehonite in magnesium precipitation crystals.The slopes with an initial angle of 53°had worse erosion resistance than the slopes with an initial angle of 35°,but the Mg^(2+)/Ca^(2+)ratios of 0.2:0.8,0.1:0.9,and 0:1.0 were effective for both slope stabilization and erosion mitigation to a great extent.The results are of great significance for the application of MIMCP to improve erosion resistance of foreshore slopes and the MIMCP technique has promising application potential in marine engineering.

Evaluation of slope stability through rock mass classification and kinematic analysis of some major slopes along NH-1A from Ramban to Banihal, North Western Himalayas

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.

A Calculation Method of Double Strength Reduction for Layered Slope Based on the Reduction of Water Content Intensity

The calculation of the factor of safety(FOS)is an important means of slope evaluation.This paper proposed an improved double strength reductionmethod(DRM)to analyze the safety of layered slopes.The physical properties of different soil layers of the slopes are different,so the single coefficient strength reduction method(SRM)is not enough to reflect the actual critical state of the slopes.Considering that the water content of the soil in the natural state is the main factor for the strength of the soil,the attenuation law of shear strength of clayey soil changing with water content is fitted.This paper also establishes the functional relationship between different reduction coefficients.Then,a USDFLD subroutine is programmed using the secondary development function of finite element software.Controlling the relationship between field variables and calculation time realizes double strength reduction applicable to the layered slope.Finally,by comparing the calculation results of different examples,it is proved that the stress and displacement distribution of the critical slope state obtained by the improved method is more realistic,and the calculated safety factor is more reliable.The newly proposedmethod considers the difference of intensity attenuation between different soil layers under natural conditions and avoids the disadvantage of the strength reduction method with uniform parameters,which provides a new idea and method for stability analysis of layered and complex slopes.

Stability analysis of loose accumulation slopes under rainfall:case study of a high‑speed railway in Southwest China

The high and steep slopes along a high-speed railway in the mountainous area of Southwest China are mostly composed of loose accumulations of debris with large internal pores and poor stability,which can easily induce adverse geological disasters under rainfall conditions.To ensure the smooth construction of the high-speed railway and the subsequent safe operation,it is necessary to master the stability evolution process of the loose accumulation slope under rainfall.This article simulates rainfall using the finite element analysis software’s hydromechanical coupling module.The slope stability under various rainfall situations is calculated and analysed based on the strength reduction method.To validate the simulation results,a field monitoring system is established to study the deformation characteristics of the slope under rainfall.The results show that rainfall duration is the key factor affecting slope stability.Given a constant amount of rainfall,the stability of the slope decreases with increasing duration of rainfall.Moreover,when the amount and duration of rainfall are constant,continuous rainfall has a greater impact on slope stability than intermittent rainfall.The setting of the field retaining structures has a significant role in improving slope stability.The field monitoring data show that the slope is in the initial deformation stage and has good stability,which verifies the rationality of the numerical simulation method.The research results can provide some references for understanding the influence of rainfall on the stability of loose accumulation slopes along high-speed railways and establishing a monitoring system.

Intelligent prediction of slope stability based on visual exploratory data analysis of 77 in situ cases

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.

Slope stability prediction based on a long short-term memory neural network:comparisons with convolutional neural networks,support vector machines and random forest models

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.

Improved Prediction of Slope Stability under Static and Dynamic Conditions Using Tree-BasedModels

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.

Stability analysis of a slope containing water-sensitive mudstone considering different rainfall conditions at an open-pit mine

Mudstone, as a typical soft rock with wide distribution, has been endangering the slopes containing mudstone by its watersensitivity of swelling and weakening strength when encountering water. To comprehensively understand the water-sensitivity of mudstone and reveal its infuence on slope stability, we took the working slope containing water-sensitive mudstone of Shengli No.1 open-pit coal mine in Xilinhot, Inner Mongolia, China, as an example. Mudstone samples taken from the working slope were remodeled and saturated, and then triaxial tested to obtain the efective cohesion and efective internal friction angle. The flter paper method was used to obtain the soil–water characteristic curve of unsaturated mudstone. The pore structure of mudstone samples with diferent water contents were analyzed using the mercury intrusion porosimetry tests combined with the fractal dimension. The total pore content of the mudstone sample with lower water content is greater than that of the mudstone sample with higher water content. The mesopores are more in the mudstone sample with lower water content, while the small pores are more in the mudstone sample with higher water content. The variation of water content will change the complexity of mudstone pore structure. The higher the water content, the simpler the mudstone pore structure and the smoother the pore surface. Numerical calculations were conducted on the stability of the working slope under diferent rainfall conditions. The efective saturation on the mudstone layer surface changed and the plastic strain all occurred on the mudstone steps under diferent rainfall conditions. The key to preventing landslide of the slope containing water-sensitive mudstone in Shengli No.1 open-pit coal mine is to control the deformation and sliding of the mudstone layer.

UAV-mounted Ground Penetrating Radar: an example for the stability analysis of a mountain rock debris slope

This paper describes scientific research conducted to highlight the potential of an integrated GPR-UAV system in engineering-geological applications.The analysis focused on the stability of a natural scree slope in the Germanasca Valley,in the western Italian Alps.As a consequence of its steep shape and the related geological hazard,the study used different remote sensed methodologies such as UAV photogrammetry and geophysics survey by a GPR-drone integrated system.Furthermore,conventional in-situ surveys led to the collection of geological and geomorphological data.The use of the UAV-mounted GPR allowed us to investigate the bedrock depth under the detrital slope deposit,using a non-invasive technique able to conduct surveys on inaccessible areas prone to hazardous conditions for operators.The collected evidence and the results of the analysis highlighted the stability of the slope with Factors of Safety,verified in static conditions(i.e.,natural static condition and static condition with snow cover),slightly above the stability limit value of 1.On the contrary,the dynamic loading conditions(i.e.,seismic action applied)showed a Factor of Safety below the stability limit value.The UAV-mounted GPR represented an essential contribution to the surveys allowing the definition of the interface debris deposit-bedrock,which are useful to design the slope model and to evaluate the scree slope stability in different conditions.

Critical Assessment of Slope Stability: A Case Study on the Toffo-Lalo Road Project

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/m3, 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.

Strategies for Advancing Road Construction Slope Stability: Unveiling Innovative Techniques for Managing Unstable Terrain

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.

Determination of the critical rainfall of runoff-initiated debris flows by the perspective of physical mechanics and Shields stress

The critical rainfall of runoff-initiated debris flows is utmost importance for local early hazard forecasting.This paper presents research on the critical rainfall of runoff-initiated debris flows through comparisons between slope gradients and three key factors,including topographic contributing area,dimensionless discharge,and Shields stress.The rainfall amount was estimated by utilizing in-situ rainfall records and a slope-dependent Shields stress model was created.The created model can predict critical Shields stress more accurately than the other two models.Furthermore,a new dimensionless discharge equation was proposed based on the corresponding discharge-gradient datasets.The new equation,along with factors such as contributing area above bed failure sites,channel width,and mean diameter of debris flow deposits,predicts a smaller rainfall amount than the in-situ measured records.Although the slope-dependent Shields stress model performs well and the estimated rainfall amount is lower than the in-situ records,the sediment initiation in the experiments falls within sheet flow regime due to a large Shields stress.Therefore,further sediment initiation experiments at a steeper slope range are expected in the future to ensure that the sediment transport belongs to mass failure regime characterized by a low level of Shields stress.Finally,a more accurate hazard forecast on the runoff-initiated debris flow holds promise when the corresponding critical slope-dependent dimensionless discharge of no motion,fluvial sediment transport,mass flow regime,and sheet flow regime are considered.

Numerical three-dimensional modeling of earthen dam piping failure

A physically-based numerical three-dimensional earthen dam piping failure model is developed for homogeneous and zoned soil dams.This model is an erosion model,coupled with force/moment equilibrium analyses.Orifice flow and two-dimensional(2D)shallow water equations(SWE)are solved to simulate dam break flows at different breaching stages.Erosion rates of different soils with different construction compaction efforts are calculated using corresponding erosion formulae.The dam's real shape,soil properties,and surrounding area are programmed.Large outer 2D-SWE grids are used to control upstream and downstream hydraulic conditions and control the boundary conditions of orifice flow,and inner 2D-SWE flow is used to scour soil and perform force/moment equilibrium analyses.This model is validated using the European Commission IMPACT(Investigation of Extreme Flood Processes and Uncertainty)Test#5 in Norway,Teton Dam failure in Idaho,USA,and Quail Creek Dike failure in Utah,USA.All calculated peak outflows are within 10%errors of observed values.Simulation results show that,for a V-shaped dam like Teton Dam,a piping breach location at the abutment tends to result in a smaller peak breach outflow than the piping breach location at the dam's center;and if Teton Dam had broken from its center for internal erosion,a peak outflow of 117851 m'/s,which is 81%larger than the peak outflow of 65120 m3/s released from its right abutment,would have been released from Teton Dam.A lower piping inlet elevation tends to cause a faster/earlier piping breach than a higher piping inlet elevation.

An Improved Particle Swarm Optimization Algorithm with Harmony Strategy for the Location of Critical Slip Surface of Slopes

The determination of optimal values for three parameters required in the original particle swarm optimization algorithm is very difficult. It is proposed that two new parameters simulating the harmony search strategy can be adopted instead of the three parameters which are required in the original particle swarm optimization algorithm to update the positions of all the particles. The improved particle swarm optimization is used in the location of the critical slip surface of soil slope, and it is found that the improved particle swarm optimization algorithm is insensitive to the two parameters while the original particle swarm optimization algorithm can be sensitive to its three parameters.

Improved prediction of slope stability using a hybrid stacking ensemble method based on finite element analysis and field data

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.

Finite element analyses of slope stability problems using non-associated plasticity

In recent years, finite element analyses have increasingly been utilized for slope stability problems. In comparison to limit equilibrium methods, numerical analyses do not require any definition of the failure mechanism a priori and enable the determination of the safety level more accurately. The paper compares the performances of strength reduction finite element analysis(SRFEA) with finite element limit analysis(FELA), whereby the focus is related to non-associated plasticity. Displacement-based finite element analyses using a strength reduction technique suffer from numerical instabilities when using non-associated plasticity, especially when dealing with high friction angles but moderate dilatancy angles. The FELA on the other hand provides rigorous upper and lower bounds of the factor of safety(FoS) but is restricted to associated flow rules. Suggestions to overcome this problem, proposed by Davis(1968), lead to conservative FoSs; therefore, an enhanced procedure has been investigated. When using the modified approach, both the SRFEA and the FELA provide very similar results. Further studies highlight the advantages of using an adaptive mesh refinement to determine FoSs. Additionally, it is shown that the initial stress field does not affect the FoS when using a Mohr-Coulomb failure criterion.

Slope stability analysis under seismic load by vector sum analysis method

The vibration characteristics and dynamic responses of rock and soil under seismic load can be estimated with dynamic finite element method （DFEM）. Combining with the DFEM, the vector sum analysis method （VSAM） is employed in seismic stability analysis of a slope in this paper. Different from other conventional methods, the VSAM is proposed based on the vector characteristic of force and current stress state of the slope. The dynamic stress state of the slope at any moment under seismic load can he obtained by the DFEM, thus the factor of safety of the slope at any moment during earthquake can be easily obtained with the VSAM in consideration of the DFEM. Then, the global stability of the slope can be estimated on the basis of time-history curve of factor of safety and reliability theory. The VSAM is applied to a homogeneous slope under seismic load. The factor of safety of the slope is 1.30 under gravity only and the dynamic factor of safety under seismic load is 1.21. The calculating results show that the dynamic characteristics and stability state of the slope with input ground motion can be actually analyzed. It is believed that the VSAM is a feasible and practical approach to estimate the dynamic stability of slopes under seismic load.

Physical model test study on shear strength characteristics of slope sliding surface in Nanfen open-pit mine

A physical model for the footwall slope of Nanfen open-pit mine, China was established using a selfdeveloped deep geological engineering disaster model test system. A thermosensitive similar material,paraffin, was selected to simulate a weak structural plane in the slope to reproduce the landslide process.From an experimental perspective, the variation trend of shear strength parameters of weak structural plane and the mechanical support characteristics of NPR(negative Poisson’s ratio) anchor cable under the condition of a large landslide deformation and failure were examined. The results of this model test showed that slope failure has four distinct stages:(1) soil compaction stage,(2) crack generation stage,(3) crack propagation stage, and(4) sliding plane transfixion stage. According to the test results, the rock mechanics parameters of weak surface in the footwall slope of Nanfen open-pit mine were calculated.The cohesion is approximately 1.35×10~5 Pa, and the internal friction angle is approximately 6.33°.During slope failure, the NPR anchor cable experiences a large deformation but no damage occurs, indicating that the NPR anchor cable can be continuously monitored and reinforced during the deformation and failure of landslide. The stress characteristics of NPR anchor cables during the test are consistent with the monitoring results of Newtonian force at the landslide site, proving that NPR anchor cables are effective and reasonable in landslide monitoring and early warning.

Advanced reliability analysis of slopes in spatially variable soils using multivariate adaptive regression splines

This study aims to extend the multivariate adaptive regression splines(MARS)-Monte Carlo simulation(MCS) method for reliability analysis of slopes in spatially variable soils. This approach is used to explore the influences of the multiscale spatial variability of soil properties on the probability of failure(P_f) of the slopes. In the proposed approach, the relationship between the factor of safety and the soil strength parameters characterized with spatial variability is approximated by the MARS, with the aid of Karhunen-Loeve expansion. MCS is subsequently performed on the established MARS model to evaluate Pf.Finally, a nominally homogeneous cohesive-frictional slope and a heterogeneous cohesive slope, which are both characterized with different spatial variabilities, are utilized to illustrate the proposed approach.Results showed that the proposed approach can estimate the P_f of the slopes efficiently in spatially variable soils with sufficient accuracy. Moreover, the approach is relatively robust to the influence of different statistics of soil properties, thereby making it an effective and practical tool for addressing slope reliability problems concerning time-consuming deterministic stability models with low levels of P_f.Furthermore, disregarding the multiscale spatial variability of soil properties can overestimate or underestimate the P_f. Although the difference is small in general, the multiscale spatial variability of the soil properties must still be considered in the reliability analysis of heterogeneous slopes, especially for those highly related to cost effective and accurate designs.

Influence of excavation schemes on slope stability: A DEM study

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.