Risk estimation of soil slope stability problems

Das, G.; Burman, Avijit; Bardhan, Abidhan; Kumar, Sumit; Choudhary, Shiva Shankar; Samui, Pijush

doi:10.1007/s12517-022-09528-y

Cited by 10 publications

(3 citation statements)

References 37 publications

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“…After the in ltration of rainwater, the ne-grained soil body from soil slope face and the upper position gradually to the lower part of the soil slope face and slope pier transport, due to the difference between the upper and lower water pressure, the ne-grained soil body easily gathered in the center of the soil slope face, blocking the pore space, causing the location of the soil permeability reduction and pore pressure rise, soil particle friction and cohesion decreased, ionic rare earth ore body of simulated rainfall on soil slopes' stability in the inverse rare earth mining area. We observed that the decrease of slope safety factor with time was slow and stable for different rainfall intensities (Das et al, 2022). It is also found that the slope safety coe cient decreases more in the pre-storm period, and with rainfall intensity increasing, rainwater's in ltration rate is accelerated, and the faster the saturated water content of selfmade ionic rare earth mineral soil, the faster the change of soil slope stability.…”

Section: Rainfall (1) Soil Water Contentmentioning

confidence: 61%

Exploration and research on ammonium free green leaching agent for ionic rare earth ore and influencing factors of soil slope stability

dengy,

Kang,

Yang

et al. 2023

Preprint

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This study analyzes the factors affecting the stability of soil slopes in the mining process of ammonium-free green leach of ionic rare earth ore through the research exploration related to ammonium-free green leach on the indoor similar simulation test, this paper sets up the research exploration of several ammonium-free green leach indoor similar simulation factors according to the role of soil particles, groundwater, etc., comparing and analyzing the role of ammonium-free green leach on seepage, time, and the role of precipitation on friction and cohesion. According to these three intrinsic influencing factors of ionic rare earth ore soil slope stability, combined with the relevant extrinsic influencing factors, the mine landslide was studied, which contributes to the exploration research of ammonium-free green leaching agent for ionic rare earth ore and analyzing influencing factors of soil slope stability, and provides an important theoretical basis for ammonium-free green, safe mining of ionic rare earth ore.

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Section: Rainfall (1) Soil Water Contentmentioning

confidence: 61%

Exploration and research on ammonium free green leaching agent for ionic rare earth ore and influencing factors of soil slope stability

dengy,

Kang,

Yang

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…After a large amount of data analysis and model comparison, three different base models, including a linear model (LM), a support vector machine (SVM), and a neural network (NN), were selected to analyze the performance of the DWS-GM. The root-mean-square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and mean square error (MSE) were used as the evaluation criteria for the model [ 34 , 35 ].…”

Section: Experimental Regression Analysismentioning

confidence: 99%

Reuse of Drilling Waste Slurry as the Grouting Material for the Real-Time Capsule Grouting Technique

et al. 2023

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A large amount of waste slurry is generated during construction, but direct sedimentation and transportation increase construction costs. Improper treatment leads to ecological and environmental pollution. This paper proposes to reuse drilling waste slurry (DWS) as a raw material from a particular project as a grouting material for the real-time capsule grouting technique (RCG) to replace cement grouting material. This not only deals with DWS but also solves the material demand of RCG. An orthogonal experimental design evaluated the performance of the DWS grouting material (DWS-GM). The five levels for the three factors of this experiment were selected, including the fluidity, bleeding rate, initial setting time, and compression strength. A linear model, support vector machines, and neural networks were used to construct regression models, and the effects of different contents of cement, bentonite, and fly ash on the DWS-GM performance were analyzed. The SVM regression model had better performance in describing the laws of fluidity, bleeding rate, and 28-day compressive strength. Furthermore, the optimization model is proposed to obtain the optimal formulation of the DWS-GM under specific constraints. The optimization results show that the optimal formulation of the DWS-GM was 5.6% cement and 6.9% bentonite. The BL, FL, IST, and 28DCS were 1.61%, 21.87 cm, 27.05 h, and 0.22 MPa to meet the functional requirements of the DWS-GM. The above research fully proves the feasibility of the DWS reuse application. We will further reuse DWS to develop other multifunctional material applications in combination with the control needs of RCG technology and technology from other fields.

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“…Eight different performance indices (Equations (3)–(10)), namely the determination coefficient (R 2 ), the performance index (PI), the variance account factor (VAF), Willmott’s index of agreement (WI), the root mean square error (RMSE), the mean absolute error (MAE), the RMSE observation standard deviation ratio (RSR) and the weighted mean absolute percentage error (WMAPE), were determined to evaluate the performance of the developed models [ 38 , 44 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 ]. For a flawless prediction model, the values of these indices should be identical to their ideal values, as shown in Table 2 .…”

Section: Data Processing and Analysismentioning

confidence: 99%

A Hybrid SVR-Based Prediction Model for the Interfacial Bond Strength of Externally Bonded FRP Laminates on Grooves with Concrete Prisms

et al. 2022

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The current work presents a comparative study of hybrid models that use support vector machines (SVMs) and meta-heuristic optimization algorithms (MOAs) to predict the ultimate interfacial bond strength (IBS) capacity of fiber-reinforced polymer (FRP). More precisely, a dataset containing 136 experimental tests was first collected from the available literature for the development of hybrid SVM models. Five MOAs, namely the particle swarm optimization, the grey wolf optimizer, the equilibrium optimizer, the Harris hawks optimization and the slime mold algorithm, were used; five hybrid SVMs were constructed. The performance of the developed SVMs was then evaluated. The accuracy of the constructed hybrid models was found to be on the higher side, with R2 ranges between 0.8870 and 0.9774 in the training phase and between 0.8270 and 0.9294 in the testing phase. Based on the experimental results, the developed SVM–HHO (a hybrid model that uses an SVM and the Harris hawks optimization) was overall the most accurate model, with R2 values of 0.9241 and 0.9241 in the training and testing phases, respectively. Experimental results also demonstrate that the developed hybrid SVM can be used as an alternate tool for estimating the ultimate IBS capacity of FRP concrete in civil engineering projects.

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Risk estimation of soil slope stability problems

Cited by 10 publications

References 37 publications

Exploration and research on ammonium free green leaching agent for ionic rare earth ore and influencing factors of soil slope stability

Exploration and research on ammonium free green leaching agent for ionic rare earth ore and influencing factors of soil slope stability

Reuse of Drilling Waste Slurry as the Grouting Material for the Real-Time Capsule Grouting Technique

A Hybrid SVR-Based Prediction Model for the Interfacial Bond Strength of Externally Bonded FRP Laminates on Grooves with Concrete Prisms

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