Rock Mechanics
RADHA TOMAR; SMITA TUNG
Abstract
Slope failures are prevalent issue in the construction sector. Thus the engineers must use appropriate slope stabilization techniques to reduce the risk of human life and property. This work investigates the efficacy of multiple regression analysis in predicting slope stability, specifically focusing ...
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Slope failures are prevalent issue in the construction sector. Thus the engineers must use appropriate slope stabilization techniques to reduce the risk of human life and property. This work investigates the efficacy of multiple regression analysis in predicting slope stability, specifically focusing on the slopes in the Kullu district, Himachal Pradesh, India. A total of 160 cases with different parameters were analyzed by using the well-known Limit Equilibrium Method (LEM), Morgenstern and Price on PLAXIS LE. Numerical analysis was performed using different nail lengths (6 m, 8 m, 10 m, and 12 m) and nail inclinations (0°, 5°, 10°, 15°, 20°, 25°, 30°, and 35°), applied to a homogeneous soil slope with 45°, 50°, 60°, and 70° inclinations, respectively. The limit equilibrium analysis may not offer predictive capabilities for future scenarios directly. In contrast, Multiple Regressions (MR) can provide predictive insights based on the historical data, allowing for forecasting of stability under different conditions or design scenarios. The utilization of MR provides the coefficients that quantify the influence of each variable on slope stability, enabling a detailed understanding of how each factor contributes. To develop the prediction models using Multiple Regression Analysis (MRA), the factor of safety values obtained by the numerical method were used. The accuracy of this model was evaluated against the conventional LE methods. The results indicate that multiple regression provides a good predictive performance with an R2 value equal to 0.774, offering a more nuanced and accurate assessment of slope stability compared to the traditional LE techniques.
