Joint Element and Strength Reduction Method

Zhang, Ke

doi:10.1007/978-981-15-5743-9_10

Cited by 4 publications

(5 citation statements)

References 15 publications

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“…Yang et al [27] analyzed the stability of an actual strength reduction method (SRM) slope, developed a digital image processing technology suitable for the SRM slope, and used the strength reduction numerical manifold method to evaluate the stability of the SRM slope. Zhang et al [28] used Flac 3D software to study the stability of slops under different slope heights using the Bishop method, Spencer method, and reduced strength method, respectively. The results showed that the safety factor of the slope decreased with the increase in the slope height, and the relative error of each scheme was less than 2%.…”

Section: Finite Element Reduction Methods Of Unified Strength Criterionmentioning

confidence: 99%

Three-Dimensional Stability Analysis of Ridge Slope Using Strength Reduction Method Based on Unified Strength Criterion

Wang

Liu

et al. 2023

Applied Sciences

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Ridge slopes often occur in highway or railway engineering. The initial stress distribution of a ridge slope is important for the original slope and an excavation slope. In this paper, a wire-frame model of ridge slope was established. Numerical simulations on the 3D stability analysis were performed using the strength reduction method based on unified strength theory. The influences of ridgeline dip angle α, flank slope angle β, and slope height H on the deformation and failure mode of ridgeline slopes were analyzed. When α was small, cracking failure easily occurred at the front edge of the ridge slope and the area near the ridge line. When α was large, shear failure was prone to occur at the trailing edge of the ridge slope. Under the same reduction coefficient, the larger the flank slope angle β, the larger the slope displacement of the ridge. The plastic zone gradually concentrated near the ridge. When H was small, the displacement mainly occurred at the trailing edge of the slope, and the slopes were generally prone to cracking damage at the trailing edge. The front edge of the slope experienced a large displacement when the height of the ridge slope increased. The bottom of the flank slope was also displaced, and a plastic zone was observed at the foot of the slope. When the excavation slope ratio of the ridge slope was small, the plastic zone was mainly located on the side slope. When the excavation rate increased, the plastic zone appeared on the excavation slope surface, and its stability decreased significantly.

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Section: Finite Element Reduction Methods Of Unified Strength Criterionmentioning

confidence: 99%

Three-Dimensional Stability Analysis of Ridge Slope Using Strength Reduction Method Based on Unified Strength Criterion

Wang

Liu

et al. 2023

Applied Sciences

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“…The stability of the slope is quantitatively investigated by the safety factor [20,21,[26][27][28]. Zhao [9] took the abrupt change of node strain or displacement on the sliding surface as the sign of slope instability. In the numerical method, the safety factor can be determined by the inflection point in the curves of the relationship between the GA displacement of the slope toe and the strength reduction coefficient.…”

Section: Safety Coefficient Discriminationmentioning

confidence: 99%

“…The anchoring of a highway slope is not a permanent guarantee of safety and stability. As the external load of the rock and soil mass and the internal structure change, the slope retains some risk of instability and failure [7][8][9][10][11]. Early warning research on slopes is significant for disaster prevention and mitigation [12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

An early warning method for a slope based on the increment ratio of anchor cable internal force

2023

Archives of Civil Engineering

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Prestressed anchor cables are active reinforcement to improve slope stability. However, the anchoring is not a permanent guarantee of stability, and the slope retains a potential risk of instability. From the perspective of the internal force of anchor cables, a new early warning method for the safety of the slope is provided, and a slope analysis model is established. With the increase in the strength reduction factor, the internal force increment curves of anchor cables under different prestresses are obtained. The point corresponding to strength reduction factors 𝜆 1 and 𝜆 2 represents a warning point. Key conclusions are drawn as follows: (1) The internal force of an anchor cable can be used to judge the stability of the slope strengthened by a prestressed anchor cable. (2) A warning index based on the internal force increment ratio of anchor cables is established. (3) The internal force increment ratio of anchor cables eliminates the influence of the initial prestress and is convenient for engineering applications.

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“…Many methods for slope stability analysis have been developed successively in recent decades, such as engineering geological analysis methods [1], analogy methods [2], LEMs [3], numerical analysis methods [4], genetic algorithms [5][6][7], machine learning (ML) methods, etc. Among them, numerical analysis methods have been widely studied and applied [8][9][10][11][12][13][14][15][16], but they still face many problems.…”

Section: Introductionmentioning

confidence: 99%

Stability Prediction of Soil Slopes Based on Digital Twinning and Deep Learning

et al. 2023

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This paper proposes a slope stability prediction model based on deep learning and digital twinning methods. To establish a reliable slope database, 30 actual slopes were collected, and 100 digital twin (DT) models were generated for each actual slope by fine-tuning the slope profiles. The safety factors of all slope samples were calculated using the Limit Equilibrium Methods (LEMs). A convolutional neural network (CNN) regression model was established, and the root mean square error (RMSE) was used as the evaluation indicator. In order to find an excellent CNN model, the K-fold (K = 10) cross-validation was used to compare the predictive effect of 1D CNN and 2D CNN on the slope safety factor. On this basis, CNN models with different network depths were compared. The results showed that the 2D CNN model with six convolutional layers had the best network prediction effect for the slope dataset. To validate the generalization ability of the model, an actual slope was input into the CNN model; its prediction result was 1.0229, and the absolute error with its real safety factor (1.0197) was 0.0032. With the slope stability prediction model proposed in this paper, the safety factor of slopes can be obtained from their geological and physical data, which greatly simplifies the calculation of the safety factor and has great engineering significance.

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Joint Element and Strength Reduction Method

Cited by 4 publications

References 15 publications

Three-Dimensional Stability Analysis of Ridge Slope Using Strength Reduction Method Based on Unified Strength Criterion

Three-Dimensional Stability Analysis of Ridge Slope Using Strength Reduction Method Based on Unified Strength Criterion

An early warning method for a slope based on the increment ratio of anchor cable internal force

Stability Prediction of Soil Slopes Based on Digital Twinning and Deep Learning

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