EVALUATING THE IMPACT OF SOIL NAILING ON SLOPE STABILITY: INSIGHTS FROM MULTIPLE REGRESSION ANALYSIS
DOI:
https://doi.org/10.21837/pm.v23i39.1911Keywords:
Slope stability, Slope/W, soil shear strength parameter, soil nailingAbstract
Slope stability is a major issue in Malaysia because of the nation's varied topography and unpredictable weather. Landslides or slope failures can happen without warning even after years of apparent stability. The ineffectiveness of conventional slope stabilization procedures may call for investigating advanced methods like soil nailing. This numerical study exclusively focused on the systematic analysis of slope stability reinforced with soil nailing. Geo-Studio 2018 (SLOPE/W) is used to determine the slope’s FOS with soil nails. Nail lengths of 6m, 9m, 12m, and 15m were evaluated, with a constant drillhole diameter of 150mm and a nail inclination of 10º. Slope angles of 30º, 60º, and 90º were considered, along with various soil types characterized by cohesion values of 0, 5, 10, and 15 kN/m² and friction angles of 5º, 15º, 35º, and 45º. The unit weight of the soil was consistently maintained at 17 kN/m³. Multiple regression analysis was employed to optimize the dataset, yielding an R-squared value of 0.80. The results demonstrated that the efficacy of soil nailing in enhancing slope stability was significantly influenced by nail length, slope angle, and soil properties. It was observed that longer nails and higher cohesion values contributed to improved stability, whereas steeper slopes and lower friction angles presented more significant challenges. These results highlighted the need to take into consideration a variety of elements in order to obtain optimal stability and offered crucial insights for developing and putting into practice soil nailing systems in a range of geotechnical settings. The study shows the impact of multiple regression analysis on geotechnical design optimization, especially in nail optimization. The study used this statistical technique to determine and measure the most important variables influencing soil nail performance. This method not only improved the accuracy of the design parameters but also provided a strong foundation for further study and real-world slope stabilization applications. A more sophisticated knowledge of the relationships between different design elements is made possible by the application of multiple regression analysis, which results in soil nailing solutions that are more dependable and efficient.
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References
Abbas, J. M. (2014). Slope stability Analysis using numerical method. Journal of Applied Sciences, 14(9), 846–859. https://doi.org/10.3923/jas.2014.846.859
Alfat, S., Zulmasri, L. O. M., Asfar, S., Rianse, M. S., & Eso, R. (2019). Slope stability analysis through variational slope geometry using Fellenius Method. Journal of Physics Conference Series, 1242(1), 012020. https://doi.org/10.1088/1742-6596/1242/1/012020
Ali, S., Kasim, N., Anuar, A. a. S., Ruslan, M. I., Azahar, W. N. a. W., & Ramli, A. B. (2023). Development Of Cumulative Rainfall Threshold for Landslide Occurrence In Peninsular Malaysia. Planning Malaysia, 21. https://doi.org/10.21837/pm.v21i30.1417
Bathini, D. J., & Krishna, V. R. (2022). Performance of Soil Nailing for Slope Stabilization-A Review. IOP Conference Series Earth and Environmental Science, 982(1), 012047. https://doi.org/10.1088/1755-1315/982/1/012047
Braun, M., & Wang, X. (2020). A review of fatigue test data on weld toe grinding and weld profiling. International Journal of Fatigue, 145, 106073. https://doi.org/10.1016/j.ijfatigue.2020.106073
Chakraborty, A., & Goswami, D. (2017). Prediction of slope stability using multiple linear regression (MLR) and artificial neural network (ANN). Arabian Journal of Geosciences, 10(17). https://doi.org/10.1007/s12517-017-3167-x
Dixon, N., Spriggs, M. P., Smith, A., Meldrum, P., & Haslam, E. (2014). Quantification of reactivated landslide behaviour using acoustic emission monitoring. Landslides, 12(3), 549–560. https://doi.org/10.1007/s10346-014-0491-z
Elahi, T. E., Islam, M. A., & Islam, M. S. (2022). Parametric assessment of soil nailing on the stability of slopes using numerical approach. Geotechnics, 2(3), 615–634. https://doi.org/10.3390/geotechnics2030030
FHWA, 1998, "Manual for Design & Construction Monitoring of Soil Nail Walls", FHWA-SA-96-69R U.S. Department of Transportation, Federal Highway Administration, Washington, D.C.
Gue, S.S. & Tan, Y.C. (2006), “Landslides: Abuses of The Prescriptive Method”, International Conference on Slope 2006, KL, 7-8 Aug 2006
Gupta, A., Stead, T. S., & Ganti, L. (2024). Determining a meaningful R-squared value in clinical medicine. Deleted Journal. https://doi.org/10.62186/001c.125154
Hamilton, D. F., Ghert, M., & Simpson, A. H. R. W. (2015). Interpreting regression models in clinical outcome studies. Bone and Joint Research, 4(9), 152–153. https://doi.org/10.1302/2046-3758.49.2000571
Ihnatov, S. (2022). The sands of medium density and sandy loam density differences investigation while cement injection and pressuremetry crimping. Budownictwo I Architektura, 21(4), 043–050. https://doi.org/10.35784/bud-arch.3048
Islam, F., Iqbal, M. F., Mahmood, I., Shahzad, M. I., & Shah, S. U. (2022). Application of frequency ratio, information value, and weights-of-evidence models and their comparison in landslide susceptibility mapping in Murree region, Sub-Himalayas. Research Square (Research Square). https://doi.org/10.21203/rs.3.rs-2218881/v1
Ja’afar, N. S., & Mohamad, J. (2021). Application Of Machine Learning in Analysing Historical and Non-Historical Characteristics Of Heritage Pre-War Shophouses. Planning Malaysia, 19. https://doi.org/10.21837/pm.v19i16.953
Jamaluddin, T. A. (2006). Human factors and slope failures in Malaysia. Bulletin of the Geological Society of Malaysia, 52, 75–84. https://doi.org/10.7186/bgsm52200611
Jambo, U. M., Khanan, M. F. A., Baharuddin, Z., Rahman, M. Z. A., Azmy, S. N., & Kadir, W. H. W. (2023). Geospatial approach for Landslides Vulnerability Assessment of Physical Infrastructures in Sireh Park, Johor Bahru. Malaysian Journal of Society and Space, 19(4). https://doi.org/10.17576/geo-2023-1904-04
Johari, A., & Javadi, A. (2012). Reliability assessment of infinite slope stability using the jointly distributed random variables method. Scientia Iranica, 19(3), 423–429. https://doi.org/10.1016/j.scient.2012.04.006
Khan, M. I., & Wang, S. (2021). Slope Stability Analysis to Correlate Shear Strength with Slope Angle and Shear Stress by Considering Saturated and Unsaturated Seismic Conditions. Applied Sciences, 11(10), 4568. https://doi.org/10.3390/app11104568
Khan, M., & Wang, S. (2021). Slope Stability Analysis to Develop Correlations between Different Soil Parameters and Factor of Safety Using Regression Analysis. Polish Journal of Environmental Studies, 30(5), 4021–4030. https://doi.org/10.15244/pjoes/131203
Kumar, V., Cauchie, L., Mreyen, A., Micu, M., & Havenith, H. (2021). Evaluating landslide response in seismic and rainfall regime: a case study from the SE Carpathians, Romania. European Geosciences Union Journal. https://doi.org/10.5194/nhess-2021-230
Majid, N. A. (2020). Historical landslide events in Malaysia 1993-2019. Indian Journal of Science and Technology, 13(33), 3387–3399. https://doi.org/10.17485/ijst/v13i33.884
Mizal-Azzmi, N., Mohd-Noor, N., & Jamaludin, N. (2011). Geotechnical approaches for slope stabilization in residential area. Procedia Engineering, 20, 474–482. https://doi.org/10.1016/j.proeng.2011.11.190
Mohamed, M. H., Ahmed, M., Mallick, J., & AlQadhi, S. (2023). Finite element modeling of the Soil-Nailing process in Nailed-Soil slopes. Applied Sciences, 13(4), 2139. https://doi.org/10.3390/app13042139
Montuori, P., Cennamo, L. M., Sorrentino, M., Pennino, F., Ferrante, B., Nardo, A., Mazzei, G., Grasso, S., Salomone, M., Trama, U., Triassi, M., & Nardone, A. (2023). Assessment on practicing correct body posture and determinant analyses in a large population of a metropolitan area. Behavioral Sciences, 13(2), 144. https://doi.org/10.3390/bs13020144
Morgenstern, N. R., & Price, V. E. (1965). The analysis of the stability of general slip surfaces. Géotechnique, 15(1), 79–93. https://doi.org/10.1680/geot.1965.15.1.79
Nguyen, Q. H., Ly, H., Ho, L. S., Al-Ansari, N., Van Le, H., Tran, V. Q., Prakash, I., & Pham, B. T. (2021). Influence of data splitting on performance of machine learning models in prediction of shear strength of soil. Mathematical Problems in Engineering, 2021, 1–15. https://doi.org/10.1155/2021/4832864
Noor, M. M., & Jamain, M. F. (2019). Pull out and creep behaviour of soil nailing – a case study. Journal of Mechanical Engineering, 16(1), 189–211. https://doi.org/10.24191/jmeche.v16i1.6072
Patil, U. D., Shelton, A. J., III, & Aquino, E. (2021). Bioengineering solution to prevent Rainfall-Induced slope failures in tropical soil. Land, 10(3), 299. https://doi.org/10.3390/land10030299
Pun, W. K., & Shiu, Y. K. (2007). Design practice and technical developments of soil nailing in Hong Kong. Geotechnical Engineering Office, Civil Engineering and Development Department, Hong Kong.
Rashad, A., Mahmoud, A., Hasham, M., & Mahmoud, T. (2023). EFFECT OF SOIL NAILING ON THE SLOPE STABILITY OF ROAD EMBANKMENTS UNDER TRAFFIC LOAD USING THE OPTIMIZED LEM. Journal of Advanced Engineering Trends, 42(2), 219–231. https://doi.org/10.21608/jaet.2022.119755.1139
Sahoo, A. K., Pramanik, J., Jayanthu, S., & Samal, A. K. (2022). Slope stability predictions using machine learning techniques. IEEE Conference Publication, 133–137. https://doi.org/10.1109/icac3n56670.2022.10074079
Sari, M. (2018). Stability analysis of slopes prone to circular failures using logistic regression. In Advances in Science, Technology & Innovation/Advances in science, technology & innovation (pp. 355–357). https://doi.org/10.1007/978-3-030-01665-4_82
Shi, G., Gu, G., Zhou, H., Tao, Z., Pan, H., Tang, T., & Yin, Q. (2020). Stability monitoring and analysis of high and steep slope of a hydropower station. Geofluids, 2020, 1–16. https://doi.org/10.1155/2020/8840269
Shiferaw, H. M. (2021). Study on the influence of slope height and angle on the factor of safety and shape of failure of slopes based on strength reduction method of analysis. Beni-Suef University Journal of Basic and Applied Sciences, 10(1). https://doi.org/10.1186/s43088-021-00115-w
The role of financial ratios in signaling financial distress. (2024). International Research Journal of Economics and Management Studies, 3(1). https://doi.org/10.56472/25835238/irjems-v3i1p148
Tian, W., Ge, J., Zhao, Y., & Zheng, X. (2024). AI Chatbots in Chinese higher education: adoption, perception, and influence among graduate students—an integrated analysis utilizing UTAUT and ECM models. Frontiers in Psychology, 15. https://doi.org/10.3389/fpsyg.2024.1268549
Wisaeng, K., & Muangmeesri, B. (2025). University rankings prediction using hybrid feature selection based on machine learning methods. International Journal of Analysis and Applications, 23, 112. https://doi.org/10.28924/2291-8639-23-2025-112
Wu, T., Yu, J., Lu, J., Zou, X., & Zhang, W. (2020). Research on inversion model of cultivated soil moisture content based on hyperspectral imaging analysis. Agriculture, 10(7), 292. https://doi.org/10.3390/agriculture10070292
Yılmaz, I., & Yuksek, A. G. (2007). An example of artificial neural network (ANN) application for indirect estimation of rock parameters. Rock Mechanics and Rock Engineering, 41(5), 781–795. https://doi.org/10.1007/s00603-007-0138-7
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