Indian Geotechnical Journal

Asghari Pari, Seyed Ali; Asghari Pari, Seyed Amin

doi: 10.1007/s40098-026-01489-3pmid: N/A

Rapid Drawdown may have a significant impact on the stability of the upstream slope of earthen dams. To avoid potential hazards, it is important to calculate the slope safety factor changes during the Rapid Drawdown process. However, considering the resistance parameters of the dam body definitively and ignoring the existing uncertainties does not lead to an accurate analysis of the slope stability conditions. Embracing the probabilistic characteristics of soil properties, instead of depending exclusively on fixed deterministic values, offers a more precise portrayal of the system’s performance and supports better-informed engineering choices. Moreover, the stability of earth dams remains a vital issue, given that their failure could result in severe and lasting impacts. This study aims to provide a comprehensive understanding of the probabilistic stability of earth dams, focusing on Rapid drawdown conditions. Seydon Dam in Iran was analyzed using the slide Rocscience software for this research. The results show that the dam discharge time in Rapid Drawdown conditions has a significant impact on the stability and reliability of the upstream slope. On the other hand, the seismic analysis of the dam shows that determining the appropriate dam discharge interval is very important in the stability of the upstream slope of the dam. Also, the results of the spatial variation analysis show the importance of the length correlation on the reliability results of the upstream slope during the Rapid Drawdown process.

Kordrostami, Fatemeh; Bolandraftar, Faraz; Aftabi Hossein, Saeid; Eshghi, Payam

doi: 10.1007/s40098-026-01483-9pmid: N/A

Leachate contamination significantly alters the geotechnical properties of clay, leading to reduced strength and stability in waste containment and foundation systems. Addressing this challenge, the present study explores the stabilization of natural and leachate-contaminated clay using micro-silica and nano-silica as environmentally friendly additives. The objective was to evaluate their effects on compaction behavior, unconfined compressive strength (UCS), and stiffness, with particular emphasis on comparing the relative effectiveness of micro- and nano-silica and identifying the governing stabilization mechanisms. Experimental tests included Standard Proctor compaction, and UCS performed on samples prepared with varying dosages of micro-silica (3, 6, 9, 12%) and nano-silica (0.3, 0.6, 0.9, 1.2%). All specimens were cured for 28 days before testing. The results revealed that leachate exposure considerably decreased the UCS and stiffness of clay. However, both micro- and nano-silica improved the mechanical response. Notably, nano-silica showed higher efficiency at lower contents, with 0.9% producing the greatest strength gain, whereas micro-silica required around 9% for similar improvement. Compaction outcomes indicated a reduction in maximum dry density (MDD) and an increase in optimum moisture content (OMC), mainly due to particle replacement and higher water affinity of silica. The enhancement in strength and stiffness is attributed to pozzolanic reactions, void filling, and the formation of cementitious products that stabilized the soil fabric. It is concluded that micro- and nano-silica can effectively mitigate the adverse effects of leachate on clay, offering a promising technique for soil stabilization. Future research should address long-term durability, cyclic environmental loading, and the combined use of silica with other additives to optimize field applications.

Kayen, Robert E.; Ko, Kil-Wan

doi: 10.1007/s40098-026-01480-ypmid: N/A

This paper reviews recent work on energy-based methodologies for estimating pore water pressure rise and the timing of initial soil liquefaction. Unlike stress-based methods, energy-based approaches use a scalar, cumulative parameter—making them well suited to modeling pore pressure buildup and the timing of liquefaction onset. The rise in pore pressure and onset of liquefaction can be estimated by summing cumulative dissipated hysteretic strain energy normalized by effective stress, which correlates strongly with the pore-pressure ratio \documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$${r}_{u}$$\end{document}. As such,, normalized energy is a complex parameter that combines the demand and capacity sides of the liquefaction problem into one term. Energy dissipated beyond the liquefaction boundary maintains \documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$${r}_{u}=1.0$$\end{document}, and likely is correlated with the potentially large shear and volumetric strains associated with liquefaction damage. However, one practical challenge of applying the method is that it requires empirical hysteretic relationships between normalized cumulative energy and excess pore pressure ratio, that are difficult to obtain in the laboratory and almost never available in the field. Proxy models for dissipated work—using Arias Intensity, Cumulative Absolute Velocity (CAV), and soil parameters, relative density or the state parameter of Been and Jeffries (1985)—appear to be the most practical path forward. However, these parameters are hampered by their elevated predictive uncertainties. The key benefit of the scalar and cumulative nature of energy-based methods are that they lead to improved estimation of liquefaction timing. Therefore, we can use just the the post-initial liquefaction time history to correlate with shear and volumetric strains. Three independent methods are currently used: the hysteretic strain-energy method, the Spectral Energy Ratio (SER) method, and Arias Intensity timing. These approaches aim to link total energy demand (Arias Intensity) to partial absorbed work (hysteretic strain energy). Parallel research investigates shear and volumetric strains before, during, and after \documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$${r}_{u}=1.0$$\end{document}. Liquefaction timing estimates based on Arias Intensity and SER can recalibrate soil models for \documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$G/{G}_{max}$$\end{document}, energy absorption, and pore pressure rise. Future work will establish relationships between hysteretic strain energy, Arias Intensity, and CAV with field penetration resistance, relative density, and initial shear stress. If successful, simplified energy demand parameters could assess liquefaction potential and act as proxies for dissipated work. Ultimately, well-documented case histories and robust proxy models will provide the foundation for energy-based, performance-oriented liquefaction assessment methods.

Liu, Gan; Xiao, Shuangshuang; Zhang, Kai; Li, Hongbo

doi: 10.1007/s40098-026-01496-4pmid: N/A

To elucidate the influence mechanism of multi-source dynamic disturbances on slope stability in open-pit coal mines, this study focuses on the west slope of the first mining area in Hesigewula South Open-pit Coal Mine. A blasting vibration monitoring system (with MEMS triaxial accelerometers and a cloud-based platform) was deployed from January 1 to June 28, 2025, recording 740 vibration events. Dynamic parameters including vibration duration, peak acceleration, peak velocity, amplitude, and dominant frequency were systematically analyzed. A Geo-slope numerical model incorporating lithological weak planes and hydrogeological conditions was established based on the Mohr-Coulomb constitutive model, simulating 19 typical vibration scenarios. The results indicate: (1) Vibration durations ranged from 78 to 9448 ms, with peak accelerations up to 92.472 mg (Z-direction), peak velocities up to 1.908 cm/s, maximum amplitude of 31.019 cm (Y-direction), and dominant frequencies concentrated between 20 and 60 Hz. (2) Numerical simulations show that vibration accelerations significantly reduce the slope stability factor, with the lowest value of 1.161 under the scenario of June 5, 2025 (horizontal 30.184 mg, vertical 25.833 mg). (3) The vibration peak acceleration increased significantly during the summer construction peak, and the impact on the stability of the slope was intensified. Based on the analysis between vibration parameters and stability coefficients, it is recommended to set a threshold value of vibration acceleration (e.g., > 20 mg) as an early warning indicator, to control the distance of vibration source, blasting quantity value, etc., so as to achieve active prevention and control of the slope under disturbance. This study provides theoretical and support for the monitoring and prevention of dynamic disasters of open-pit coal mine slopes. .

Kanu, Ibrahim Ahmed; Tholley, Mabinty Sarah; Ding, Mingkang; Liu, Zichen; Sun, Wenbin

doi: 10.1007/s40098-026-01498-2pmid: N/A

Slope instability has caused significant environmental, social, and economic impacts in many mining regions worldwide. Mining-related effects include landslides, soil erosion, and rainfall infiltration, and these activities have altered the geology and influenced soil behaviour. This study aims to provide insights into the macro and micro geotechnical properties affecting mine slope stability in Tonkolili, Northern Sierra Leone. The experimental analysis and results showed that the mine slope soil exhibited an alkaline pH range of 9.65 to 9.98, a low cation exchange capacity of approximately 3 to 3.76 nmol/kg, and a particle composition primarily composed of sandy SILT and clay, which affected contaminant transport. Additionally, the Atterberg tests indicated moderate plasticity. The X-ray fluorescence analysis identified SiO2, Al2O3, Fe2O3, and CaO, with silicon and lead accounting for the majority of the trace metal concentrations. Scanning electron microscopy (SEM) revealed rough, angular particles (724 nm–2.27 μm), indicating reduced porosity, permeability, and contaminant retention. The Stability analysis yielded safety factors of 1.829 (static), 0.671 (seismically drained), 0.105 (undrained), and 0.194 (drained), indicating potential instability. These research findings will provide insights into the macro- and micro-geotechnical properties of mine slope stability, aiding the minimisation of the adverse effects of slope instability, which is essential for sustainable management and risk mitigation at the mine site.

Sharma, Ravi Kumar; Juneja, Gaurav

doi: 10.1007/s40098-026-01488-4pmid: N/A

This study utilises the machine learning approach to predict the dimensionless bearing capacity (UBC)p of square footing placed over geocell reinforced stratified foundation bed containing construction demolition waste infilled in the geocell reinforcement compacted at different relative densities (Rd = 30%, 50%, and 70%) overlying the clay subgrade of different strengths (q = 5 kPa and 50 kPa). Machine Learning models can improve the prediction accuracy of complex and non-linear relationships between soil properties and bearing capacity that are often oversimplified in traditional analytical or empirical methods and reduced the dependence on extensive field testing. A total dataset of 54 cases obtained from the laboratory experimental study were used for the machine learning analysis. The input variables including the average Young’s modulus of elasticity (Eavg) of both soil layer, average friction angle (фavg), average unit weight (γavg), average cohesion (cavg) and incremental cohesion (cr) due to the geocell reinforcement were used to predict the bearing capacity. In this study, five different machine learning models including decision tree (DT), k-nearest neighbour (KNN), artificial neural network (ANN), random forest (RF), extreme gradient boosting (XGB) were used for the analysis. The predicted results of bearing capacity by different machine learning models were accessed using relative comparison of R-square, root mean square error (RMSE), and variance accounted for (VAF) values. The relative comparison of different machine learning models result show that R-square value of different model for training and testing dataset varied from 0.79 to 1 and 0.72 to 0.96. The decision tree (DT) model and extreme gradient boosting (XGB) model gives the best performance (R2 > 90%) among the other machine learning models. Furthermore, the relative impact of each input variable on estimating the bearing capacity is computed by conducting sensitivity analysis.

Zhang, Long; Shi, Hangchuan; Jianie, Yuchi; Hu, Linjie

doi: 10.1007/s40098-026-01484-8pmid: N/A

To investigate the evolution of soil arching in geosynthetic-reinforced pile-supported embankments, this study used PFC2D to establish discrete element models of two-dimensional trapdoor tests, based on the existing literature. Through parameter calibration, the mesoscopic parameters of the soil and geosynthetic materials were determined. Simulations conducted using these parameters demonstrated close agreement with the experimental results. Subsequently, the evolution of the soil arching effect was investigated, followed by a detailed parametric study. The results show that: (1) The soil arching effect in the embankment gradually increased as the trapdoor moved downward, eventually forming a stable soil arching structure. (2) As Δd increased, the vertical stress on the pile cap at the same horizontal position increased, while the vertical stress between piles decreased, leading to a gradual transfer of embankment load to the adjacent pile caps. (3) Linear regression fitting indicated a significant linear relationship between the normalized displacement and the pile-soil stress ratio. (4) As the normalized displacement increased, the soil arching ratio within the embankment increased. Increasing the normalized pile cap width or geosynthetic stiffness further enhanced the soil arching effect.

Yadav, Shrinarayan; Shukla, Dharmendra Kumar; Kumar, Rohit

doi: 10.1007/s40098-026-01497-3pmid: N/A

Rock mass behavior under sustained loading at the edge of slope for discontinuous joints is difficult to assess under unconfined condition. The current study is conducted on rock mass with orthogonal joint sets with one continuous and other discontinuous joint. Rock mass joint sets angles varies from 30° to 90° with the increment of 15° up to 90°. Experimentation shows failure pattern as well as load carrying capacity in such conditions. Mode of failure is the most essential parameter which governs the load carrying capacity of the rock mass specimen. The load intensities were calculated analytically for joint angles of 90°, 75°, and 60° using Euler’s method, resulting in percentage errors with experimental results of 7.93%, 6.92%, and 8.45%, respectively. However, for the joint angle of 45°, which exhibited a sliding mode of failure, the analytically calculated load intensity showed a higher percentage error of 19.7% though the difference in experimental and calculated load intensity was 0.073 MPa only. Load intensities were also calculated by shifting the footing position 150 mm which is equal to the footing width (1B) from the crown of the slope. The increase in the experimental load intensity of at 1B is utilized for the evaluation of equivalent confining pressure (σ3EQ). The values of the equivalent confining pressure constant can be used to predict the load intensity in the field when the footing is placed at a certain distance from the edge of the slope. Based on the experimental and analytical results, a methodology has been recommended to evaluate the load intensity at failure for a anisotropic rock mass. Experimental simulation is also done on the tool Phase2, to assess the mode of failure at failure load.

Vishwakarma, Ragini; Mittal, Satyendra; Sawant, Vishwas A.

doi: 10.1007/s40098-026-01501-wpmid: N/A

With increasing urbanization and limited ground space, deep excavations are crucial for constructing underground structures. Diaphragm walls are widely used to resist lateral earth pressures and maintain excavation stability. To enhance their performance, helical anchors are commonly installed to control lateral displacement and settlement during excavation and service life. This study presents a series of scaled model experiments investigating the behavior of unanchored, single-row anchored, and double-row anchored diaphragm walls subjected to surcharge loading applied at different normalized horizontal offsets from the excavation face (x/H = 0.1, 0.2, 0.3, and 0.4), where x/H represents the ratio of the horizontal distance between the surcharge location and the diaphragm wall to the wall height. The tests also investigate the effects of anchor inclinations ranging from 5° to 20° with respect to the horizontal, as well as two anchor lengths (0.6H and 0.9H). Results demonstrate that a double-row anchored wall significantly reduces lateral pressure, wall deflection, and footing settlement compared to a single-row and unanchored wall. An anchor inclination of 15° provided the most effective reduction in pressures and deformations, while increasing anchor length from 0.6H to 0.9H offered only marginal additional reductions. When the structure is placed closer to the diaphragm wall at x = 0.1H, the higher lateral pressures necessitate the use of more than a single-row anchor to maintain stability. In contrast, at x = 0.4H, where the influence of loading on the wall is reduced, even a single-row anchor or no anchor may be sufficient, as the lateral pressures decrease by up to 41%, thereby enhancing wall stability. Overall, using double-row anchors with an anchor length of 0.6H effectively controls deformations within acceptable limits, while ensuring cost-effectiveness, and offers practical insights for designing safer and more efficient deep excavation support systems.

Kuang, Du-min; Kuang, Feng-lan; Sun, Xing; Ogwu, Ikechukwu

doi: 10.1007/s40098-026-01502-9pmid: N/A

This paper proposes a theoretical model for predicting the particle size evolution of crushable granular materials under one-dimensional compression. A statistical distribution model is employed to calculate the contact forces on individual particles within crushable granular assemblies, and the breakage probability of particles in different size classes is derived using the Weibull distribution model of particle crushing strength. Additionally, a fractal model is adopted to characterize the mass-size distribution of fragmented particles. The proposed theoretical model is further validated against experimental data reported in the literature and is shown to effectively capture the particle size evolution of crushable granular materials during one-dimensional compression.