Optimizing slope safety factor prediction via stacking using sparrow search algorithm for multi-layer machine learning regression models

The safety factor is a crucial quantitative index for evaluating slope stability.However,the traditional calculation methods suffer from unreasonable assumptions,complex soil composition,and inadequate consideration of the influencing factors,leading to large errors in their calculations.Therefore,a stacking ensemble learning model(stacking-SSAOP)based on multi-layer regression algorithm fusion and optimized by the sparrow search algorithm is proposed for predicting the slope safety factor.In this method,the density,cohesion,friction angle,slope angle,slope height,and pore pressure ratio are selected as characteristic parameters from the 210 sets of established slope sample data.Random Forest,Extra Trees,AdaBoost,Bagging,and Support Vector regression are used as the base model(inner loop)to construct the first-level regression algorithm layer,and XGBoost is used as the meta-model(outer loop)to construct the second-level regression algorithm layer and complete the construction of the stacked learning model for improving the model prediction accuracy.The sparrow search algorithm is used to optimize the hyperparameters of the above six regression models and correct the over-and underfitting problems of the single regression model to further improve the prediction accuracy.The mean square error(MSE)of the predicted and true values and the fitting of the data are compared and analyzed.The MSE of the stacking-SSAOP model was found to be smaller than that of the single regression model(MSE=0.03917).Therefore,the former has a higher prediction accuracy and better data fitting.This study innovatively applies the sparrow search algorithm to predict the slope safety factor,showcasing its advantages over traditional methods.Additionally,our proposed stacking-SSAOP model integrates multiple regression algorithms to enhance prediction accuracy.This model not only refines the prediction accuracy of the slope safety factor but also offers a fresh approach to handling the intricate soil composition and other influencing factors,making it a precise and reliable method for slope stability evaluation.This research holds importance for the modernization and digitalization of slope safety assessments.

Stability analysis of an unsaturated soil slope considering rainfall infiltration based on the Green-Ampt model

Based on the principle of saturated infiltration and the Green-Ampt model,an unsaturated infiltration model for a soil slope surface was established for either constant moisture content,or depth-varying moisture content and the slope.Infiltration parameters in the partially saturated slope were revealed under sustained rainfall.Through analysis of the variation of initial moisture content in the slope,the ponding time,infiltration depth,and infiltration rate were deduced for an unsaturated soil slope subject to rainfall infiltration.There is no ponded water on the surface of the slope under sustained low-intensity rainfall.The results show that the infiltration parameters of an unsaturated slope are influenced by the initial moisture content and the wetting front saturation,the soil cohesion and rainfall intensity under sustained rainfall.More short-term slope failures can occur with the decrease of cohesion of the soil of the slope.The ponding time and infiltration depth differ considering constant or different initial moisture content respectively in the soil slope.Then,best-fit curves of the infiltration rate,ponding time,and infiltration depth to the wetting front saturation were obtained with constant or different initial moisture contents.And the slope failure time is roughly uniform when subject to a rainfall intensity I>5 mm/h.

Slope Stability Considering the Top Building Load

Slope stability is one of the most important subjects of geotechnics. The slope top-loading plays a key role in the stability of slopes in hill slope areas. When the building load is too large or the point of action from the shoulder is too close, the shear stress of the slope will be significantly greater than its shear strength, resulting in reduced slope stability. Therefore, it is of great importance to study the relationship between the building load and the stability of the slope. This study aims to analyze the influence of different building loads applied at different distances on the top of the slope and deduces their effects on the slope stability. For this purpose, a three-dimensional slope model under different building loads with different distances to the slope shoulder was established using the finite-difference analysis software Flac3D. The results show that the loads applied at different distances on the top of the slope have different effects on the slope stability. The slope factor of safety (FOS) increases with the increase of the distance between the top-loading and the slope shoulder;it varies from 1.37 to 1.53 for the load P = 120 KPa, 1.27 to 1.53 for the load P = 200 KPa, and from 1.18 to 1.44 for P = 300 KPa, resulting in the decrease of the coincidence area between the load-deformation and the potential sliding surface. The slope is no longer affected by the potential risk of sliding at approximately 20 m away from the slope shoulder.

Failure of levees induced by toe uplift:Investigation of post-failure behavior using material point method

Levees are essential structures in flood defense systems,and their failures can lead to devastating consequences on the surrounding territories.One of the failure mechanisms mostly controlled by the foundation soil stratigraphy is the instability of the land side slope,triggered by the development of high uplift pressures in the foundation.This complex phenomenon has been investigated experimentally with centrifuge tests or large-scale tests and numerically with the limit equilibrium method(LEM)and the finite element method(FEM).In this work,we applied a multiphase formulation of the material point method(MPM)to analyze the development of toe uplift instability mechanism,from the onset of failure to large displacements.The numerical model is inspired by an experiment carried out in a geotechnical centrifuge test by Allersma and Rohe(2003).The comparison with the experiment allows for understanding critical pore pressure triggering large displacements in the foundation soils.Moreover,we numerically evaluated the impact of different values of foundation soils’hydraulic conductivity on the failure mechanism.The results show that hydraulic conductivity mainly influences the time of failure onset and the extension of shear localization at depth.Finally,the advantages of using large displacement approaches in the safety assessment of earth structures are discussed.Unlike FEM,there are no issues with element distortions generating difficulties with numerical convergence,allowing for full postfailure reproduction.This capability permits precise quantification of earth structure damages and post-failure displacements.The ensuing reinforcement systems’design is no longer over-conservative,with a significant reduction in associated costs.