Slope Stability Analysis to Develop Correlations
between Different Soil Parameters and Factor
of Safety Using Regression Analysis

Khan, Muhammad Israr; Wang, Shuhong

doi:10.15244/pjoes/131203

Cited by 9 publications

(2 citation statements)

References 12 publications

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“…With advances in computational technology and the development of geomechanical calculations, numerical modeling methods have made it possible to understand complex geotechnical problems (Hussain et al, 2018;Schweiger et al, 2019;Khan and Wang, 2021). Numerical calculations can mathematically solve a pattern of relationships between variables or parameters described in the form of functions.…”

Section: Creating the Modelsmentioning

confidence: 99%

Geotechnical study for analyzing slope stability between two mining pit boundary

Zulfahmi¹

2022

IMJ

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This paper is a new concept to increase the safety and mining conservation on PT-X and PT-Y with no boundary gap between the two areas. To optimize coal recovery as a basis of supporting conservation, the two companies needed to adjust coal production in terms of avoiding technical problems at the mining time process due to the rock structure and coal seam at the border were the same. PT-X plans to produce 2 million tons of coal, but the government only approved 1 million tons, while PT-Y still approved 2 million tons. This paper discusses the instability of mining in border locations due to the differences of coal production. The applied methodology is conducting geotechnical modeling by considering statistical aspects of data distribution and the probability of failure. Based on the results of geotechnical modeling by numerical methods on the basis of 2D and 3D for the difference in the production level of 1 million tons in all cross-sections, the FK value is 0.992 - 1.248 with a probability of failure (PI) of 5.40 - 48.00%. Results of modeling analysis show that both single and overall slopes are at a critical level and are not safe. If this difference is narrowed by increasing PT-X's coal production by 1.5 million tons, the border location's mining conditions will stabilize. Therefore, it is necessary to propose to the government for PT-X's coal production to be added by at least 500.000 tons so that the production process of each company runs safely.

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Section: Creating the Modelsmentioning

confidence: 99%

Geotechnical study for analyzing slope stability between two mining pit boundary

Zulfahmi¹

2022

IMJ

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“…Hence there is a need of analyzing slope stability under seismic loading.Marrapu and Jakka [1] created two distinct multiple regression models, verified their precision in the estimation using actual field data, and were satisfied with the findings. Wang and Khan [2] found correlations between various soil and slope parameters using the SLIDE software to forecast slope stability assessment. Zhou et al [3] investigate slope prediction using logistic regression and conclude that it is the best predictive approach for slope stability prediction.Huang and Peng [4] conducted a seismic slope stability analysis for saturated and unsaturated soil and found that dynamic pore water pressure influence is significant towards stability.…”

Section: Introductionmentioning

confidence: 99%

Parametric Study on the Stability of Slopes Subjected to Earthquake Forces

Boruah,

Chakraborty

2023

IOP Conf. Ser.: Mater. Sci. Eng.

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For thousands of years, engineers have been grappling with slope instability as an issue in geotechnical and geological engineering. Earthquake loading has a great impact in slope stability. The present study is to investigate the impact of various soil properties and slope geometry on FOS in the presence as well as in the absence of seismic loading. Here, pseudo-static methods are used to analyses seismic slope stability under earthquake loading. From parametric studies, present work concluded that the FOS values start to decline drastically with earthquake impact. Moreover, various prediction models have been developed using Multiple Linear Regression (MLR) & Multiple Non-Linear Regression (MNLR) considering all the data. The input data of slope stability estimation consists of the values of soil parameter, slope parameter and earthquake loading parameters. As an output, MLR and MNLR predict FOS values as a function of these parameters. The model is then checked by comparing the results to another ten actual situations. It was found that the predicted FOS using MNLR gives satisfactory results.

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Back analysis of shear strength parameters of slope based on BP neural network and genetic algorithm

Deng,

Xiang

2024

Engineering Reports

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Efficient and accurate acquisition of slope shear strength parameters is the key to slope stability analysis and landslide prevention engineering design. This paper establishes a back analysis method based on uniform design, artificial neural network, and genetic algorithm. It can obtain the shear strength parameters of slopes based on information such as the radius and center coordinates of the slip surface obtained from on‐site investigations. This method has been applied to engineering practice. The research results indicate that the stability of the waste dump slope is most sensitive to the response of the internal friction angle of the loose body, followed by cohesion, and least sensitive to the response of the soil volume weight. This method can effectively reduce the number of network training samples and efficiently and quickly determine the initial weights of the BP (abbreviation for back‐propagation) neural network. This method can efficiently and quickly conduct back analysis to obtain the shear strength parameters of slopes. Using the obtained shear strength parameters for slope stability calculation, the most dangerous slip surface abscissa error, ordinate error, and slip surface radius error are only 3.59%, 0.95%, and 1.83%. It is recommended to promote the back analysis method of shear strength parameters in engineering practice in the future.

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Slope Stability Analysis to Develop Correlations between Different Soil Parameters and Factor of Safety Using Regression Analysis

Cited by 9 publications

References 12 publications

Geotechnical study for analyzing slope stability between two mining pit boundary

Geotechnical study for analyzing slope stability between two mining pit boundary

Parametric Study on the Stability of Slopes Subjected to Earthquake Forces

Back analysis of shear strength parameters of slope based on BP neural network and genetic algorithm

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