Landslides pose a recurring threat to human settlements, infrastructure, and ecosystems in the seismically active Chamoli district of Uttarakhand, India. This study presents a comparative landslide susceptibility assessment using three distinct models: Frequency Ratio (FR), Shannon Entropy (SE), and Analytical Hierarchy Process (AHP). Twenty-four geo-environmental and anthropogenic conditioning factors were integrated to develop landslide susceptibility maps (LSMs) tailored to the region’s complex terrain. Multicollinearity analysis was conducted to ensure statistical robustness, and model performance was validated using the Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC) metric. The FR model achieved the highest predictive accuracy (AUC = 0.819), followed by AHP (0.789) and SE (0.594). While FR demonstrated superior data-driven reliability, AHP offered interpretability grounded in expert judgment. Thematic analysis revealed slope, geology, rainfall, proximity to roads, and land use changes as key landslide triggers. Susceptibility zonation showed significant spatial variability across models, with high-risk zones concentrated near road corridors, riverbanks, and deforested slopes. The study underscores the value of methodological triangulation in landslide prediction and recommends FR as a reliable framework for future hazard planning. These findings provide actionable insights for disaster mitigation, infrastructure planning, and sustainable land use management in Himalayan regions.
In geotechnical engineering, the angle of repose (AoR) is widely adopted as an indicator of soil stability and particle interaction. However, AoR can arise from different combinations of inter-particle sliding and rolling friction, each representing different mechanical characteristics. This study systematically investigates the influence of sliding and rolling friction coefficients on AoR using the Discrete Element Method (DEM). Lifting cylinder tests were simulated while varying both sliding and rolling coefficients from 0.1 to 0.9 to examine their combined effects on AoR formation. Additionally, a stress wave propagation model was developed to simulate laboratory stress wave testing and to explore the relationship between inter-particle friction and wave response characteristics. The results reveal that while sliding and rolling frictions significantly influence stress wave responses, such as stress magnitude, particle velocity, and displacement, the AoR alone does not exhibit a consistent correlation with these dynamic properties. These findings suggest that AoR, although it is useful for static stability, may not be a reliable standalone indicator of dynamic soil behavior.
The Representative Elementary Volume (REV) is a key concept in the analysis and simulation of jointed rock masses, playing a crucial role in selecting the dimensions of laboratory samples and the domain size of numerical models. However, a precise understanding of the influence of joint geometric and mechanical parameters on the REV remains limited. In this study, the scale dependency of the mechanical properties of jointed rock masses was systematically investigated using three-dimensional numerical modeling. The REV was defined based on the convergence of peak strength and deformation modulus within a 5
Abstract Pavement foundations are critical for structural longevity, yet current evaluation methods lack the capability for real-time, continuous monitoring of resilient modulus, particularly in subgrade layers where distress frequently originates. While Bender Element field sensors have been successfully deployed in unbound base layers, assessment tools for low-stiffness subgrades remain underexplored. This study presents the development and optimization of a Subgrade Stiffness Monitoring sensor designed specifically for weak granular subgrades. The sensor integrates Bender Elements and Piezo Disc Elements to measure shear and compressional wave velocities, enabling the direct calculation of Poisson’s ratio and small-strain modulus. Large-scale laboratory tests were conducted in a testbed filled with sandy subgrade material to optimize transducer geometry. Experimental results indicated that a 30-cm sensor spacing yields an optimal Signal-to-Noise Ratio (SNR) for both wave types. Concurrently, repeated load triaxial tests established a robust correlation between the sensor-measured small-strain modulus and the design-relevant resilient modulus, capturing the stress-hardening behavior of the material. The study demonstrates that the optimized subgrade stiffness monitoring sensor can effectively evaluate subgrade stiffness variations under diverse static loading conditions. These findings highlight the sensor’s laboratory-demonstrated potential for the continuous monitoring of transportation infrastructure foundations.
Abstract Flysch marls are soft rocks highly susceptible to weathering under atmospheric conditions, primarily due to repeated wetting–drying cycles. As these cycles are closely linked to the unsaturated state, their influence on water retention behaviour is critical for understanding marl degradation. In this study, thirty marl and calcareous marl samples with calcium carbonate (CaCO₃) contents ranging from 39 to 83% were collected and tested for physical–mechanical properties and mineralogical composition. Three unsaturated test methods—the axis translation technique, dew point method, and vapour equilibrium technique—were applied to both intact and reconstituted (weathered/fully disintegrated) samples. Soil–water characteristic curves (SWCCs) were modelled using Brooks-Corey, van Genuchten, and Fredlund-Xing equations, with the Fredlund-Xing model giving the best performance based on its ability to capture high-suction behaviour. Intact marls with CaCO₃ < 65% showed higher saturated gravimetric water contents and lower air-entry suctions (≈215–1 500 kPa), whereas calcareous marls with CaCO₃ > 65% had higher air-entry values (≈5 100—40 000 kPa) and lacked a distinct residual zone. Reconstituted samples displayed an inverse trend, with low CaCO₃ marls having higher air-entry values. These findings highlight the impact of mineralogy on the water retention behaviour and weatherability of marls, influencing their physical and mechanical properties. The novelty of this research lies in applying unsaturated testing methods to intact marls and explicitly assessing mineralogical effects on SWCCs—an aspect not previously addressed. The findings advance understanding of marl weathering and provide a basis for more reliable evaluation of slope stability and durability of soft rock terrains.
Abstract This study investigated the impact of seasonal ground freezing on the generation of shear-wave velocity ( V S ) profiles through ambient noise Horizontal-to-Vertical Spectral Ratio (HVSR) inversion from a numerical analysis perspective. To this end, the CRB seismic station located in Wonju, Republic of Korea, was selected as the study site. Ambient noise data acquired during winter and summer as well as borehole logs were utilized for the analysis. Comparative analyses were conducted by designing scenarios for unconstrained inversion and constrained inversion. The research results confirmed that in the unconstrained inversion process, stiffness changes caused by surface freezing led to numerical artifacts. This resulted in numerical artifacts where the velocity of the deep bedrock was calculated to be higher in summer than in winter. In contrast, performing constrained inversion by fixing the bedrock boundary successfully eliminated these deep artifacts. The numerical interpretation revealed that the dramatic stiffening of the surface layer, representing a more than four-fold increase in V S , caused the expansion of the effective resonance depth. This mechanism rationally explains the low-frequency shift of the peak frequency observed during the freezing period. The frost penetration depth of approximately 1.0 m showed a very high correlation with regional empirical formulas and field measurement results. Finally, this study suggests that setting constraints based on borehole information is an essential prerequisite for ensuring the physical reliability of V S profiles in seasonally frozen ground.
A machine-learning framework was established to predict the axial bearing capacity of fully grouted rock bolts using an experimental database of 84 pull-out tests on fibreglass and steel rock bolts. The models incorporated six input parameters, embedment length (EL, 50–150 mm), confinement diameter (CD, 23–50 mm), bolt diameter (BD, 16–25 mm), water-to-grout ratio (W/G, 30–40
Fully grouted cable bolts are widely used in underground mining; however, the cementitious grouts governing their load-transfer performance remain predominantly Portland-cement based and are rarely optimised for sustainability. This study evaluates the mechanical and bonding performance of newly developed “green” grouts incorporating partial cement replacement with waste glass powder (WGP), tyre rubber waste (TRW), and construction and demolition waste (CDW), with the aim of promoting circular-economy principles in underground reinforcement systems. Following preliminary mechanical screening, selected grout formulations were used to encapsulate cable-bolt specimens. A total of 20 pull-out tests were conducted using 70-t, 12-wire Sumo cable bolts embedded in rifled steel confinements and tested in a custom single-embedment pull-out testing (SEPT) rig incorporating a rotation-mitigation system to isolate axial bond–slip behaviour. The mixtures included WGP with four particle-size bands (< 75–425 μm) at 2.5–20
Abstract Aims/hypothesis The seismic observation network on the Korean Peninsula is being modernized and densified to support rapid earthquake detection. This study aims to propose operational strategies for producing seismic intensity information using the recently upgraded network. Methods We first review the modernization of the Korean seismic observation network, focusing on the transition from surface stations to borehole stations and the recent deployment of MEMS-based sensors. We then examine representative far-field records from Japan-sourced earthquakes to discuss the period-dependent applicability of Korean ground motion models. Finally, we discuss how sensor installation conditions, including building-mounted MEMS deployments, affect the reliability of seismic intensity information. Results The densification of the borehole sensor network improves detection stability by reducing background noise and supporting reliable early-waveform acquisition. However, the operational production of seismic intensity information remains constrained by (i) site and structural effects and (ii) the limited applicability of Korean crustal GMMs when Japan-sourced subduction earthquakes dominate long-period ground-motion demand across the Korean Peninsula. Conclusions Response-grade intensity mapping requires standardized metadata and quality control, together with appropriate GMMs (including subduction-specific models) for Japan-sourced events.
The interaction between mat foundations and the supporting soil is often simplified in design practice by assuming that the mat rests on Winkler springs. Most of the previous studies aimed at determining the spatial variation of the spring constants or the modulus of subgrade reaction that is needed to obtain realistic and accurate results regarding the bending of the mat, assuming that the soil behaves as a purely linear elastic material. This paper investigates the effects of plastic strains and volume changes that happen due to the consolidation of clayey soils under long-term conditions on the distribution of the equivalent spring constants and the bending moment diagrams. For this purpose, three-dimensional finite element analyses are performed for fully drained conditions with the soil simulated using the Modified Cam-Clay constitutive model. The results show that the presence of plastic yielding significantly influences the mat-soil interaction, and the assumption of a linear elastic soil overpredicts the soil stiffness and the bending moments in the mat foundation. The semi-analytical Discrete Area Method could be adopted to obtain comparable results to those generated by elastoplastic finite element analysis.
Fracture self-sealing in clay-rich mudrocks plays an important role in controlling fluid migration in subsurface engineering and geoenergy applications, yet the factors governing permeability reduction remain difficult to quantify in a unified manner. In this study, laboratory experiments were performed on synthetic kaolinite-based mudrock specimens to investigate fracture permeability evolution under controlled effective stress, overconsolidation ratio (OCR), and pore-fluid conditions. Artificial fractures were introduced into resedimented specimens with prescribed stress histories, and permeability evolution was monitored during sealing of the fracture. A phenomenological bi-exponential model was employed to quantitatively describe the observed permeability reduction, separating the contribution of rapid mechanically driven closure and slower time-dependent sealing behavior. The results showed that increasing effective stress accelerates permeability reduction, while higher OCR suppresses late-time sealing under identical current stress. Pore-fluid composition further altered the sealing behavior, with brine-saturated fractures exhibiting stronger permeability reduction than oil-saturated fractures. Additional experiments showed that the model parameters evolve over time, reflecting the intrinsically time-dependent and non-linear nature of the self-sealing response. These results provide a practical framework for systematically interpreting fracture self-sealing behavior in low-swelling clay systems relevant to subsurface sealing and geoenergy operations.
Numerical modelling is extensively employed in underground engineering to evaluate excavation-induced deformations and the interaction between tunnels and support systems. In this study, tunnel stability was analysed using a three-dimensional finite-element approach, integrating geostatic initialization with an implicit–dynamic quasi-static step. This methodology enhances post-yield convergence and effectively captures transient mechanical responses during excavation. The framework was applied to a sandstone tunnel section, and the predicted displacements were validated against in-situ monitoring data, showing agreement within 2–12
Abstract This study investigates the influence of realistic summer daily thermal cycles on the mechanical, hydraulic, and microstructural properties of cement-stabilized sensitive marine clay (SMC), a problematic marine soil widely found in Eastern Canada. SMC samples treated with 5% and 20% cement were subjected to two curing regimes: constant temperature (20 °C) and simulated daily thermal cycles, and tested after 1, 3, 7, and 28 days of curing. Unconfined compressive strength (UCS) and secant modulus tests were performed to assess mechanical performance, while matric suction monitoring, thermogravimetric analysis (TG/DTG), and mercury intrusion porosimetry (MIP) were used to evaluate hydration behavior and microstructural evolution. Results show that daily thermal cycles significantly accelerate strength and stiffness development at early curing stages by enhancing cement hydration, leading to finer pore structures and higher matric suction due to rapid self-desiccation. However, a “crossover effect” was observed in TG/DTG results, where prolonged thermal cycling reduced hydration product formation at later stages. MIP results, in contrast, showed continued microstructural densification, likely due to a dilution effect associated with high water-to-cement ratios. These findings provide practical insights for optimizing curing strategies and binder dosages in road and infrastructure projects involving sensitive marine clays under fluctuating thermal conditions.
Abstract Soft clay soils, prevalent in coastal and alluvial regions worldwide, exhibit low shear strength, high compressibility, and poor drainage, posing major challenges for construction. Geotextile-encased sand columns (GESC) offer an effective ground improvement technique by enhancing load-carrying capacity, stiffness, and drainage. A series of small-scale undrained triaxial tests was performed to examine the mechanical response of both ordinary sand columns (OSC) and GESCs, with a focus on the effects of column diameter, area replacement ratio, and cell pressure. Each test comprised saturation, isotropic consolidation under cell pressures of 50, 100, and 150 kPa, and subsequent undrained axial shearing at a constant displacement rate of 0.02 mm/min. Results show that the GESC increased the composite friction angle from 27° for unimproved soil to 30° at a 25% area replacement ratio. The peak stress ratio relative to unimproved soil was consistently higher for GESC (1.69) than for OSC (1.57) at the same area ratio, due to the additional confining stress provided by the encasement, showing about 20% greater settlement reduction compared to the OSC. An increase in the area replacement ratio from 6 to 25% resulted in an approximately 62.5% reduction in the average additional confining stress. While OSC primarily failed by bulging, GESC promoted a more favorable shear failure and reduced bulging deformation. Consolidation times were slightly longer for GESC (about 32% longer at 25% area ratio) due to clogging, but still achieved 430% faster consolidation than unimproved soil. Overall, GESC provide enhanced confinement and stability, making an effective solution for soft clay foundations.
This study presents a comprehensive framework for selecting optimal ground motion intensity measures (IMs) and developing seismic fragility curves for horseshoe tunnels. To do so, a total of 20 candidate IMs were evaluated through nonlinear time history analyses. The two-dimensional finite difference models considering soil-tunnel interaction were developed and validated using the FLAC2D program. The model incorporated varying tunnel embedment depths (10 m, 20 m, and 30 m) and different site conditions (site classes B, C, and D), with 100 input ground motions representing a wide range of seismic characteristics. The performance of each IM was examined based on four statistical criteria: goodness of fit, efficiency, practicality, and proficiency. The findings show that for stiff soil conditions (site B), the most effective intensity measures are peak ground acceleration (PGA), acceleration spectrum intensity, effective design acceleration, and the A95 parameter. In contrast, for tunnels constructed in medium to soft soils (sites C and D), velocity spectrum intensity, Housner intensity, peak ground velocity (PGV), and Arias intensity provide a better correlation with the seismic response. In comparison, predominant period, mean period, and the PGV/PGA ratio consistently exhibited weak correlation, high variability, and limited practical value, rendering them unsuitable for fragility analysis. Fragility curves were then developed based on the proposed optimal IMs. The results reveal that increasing embedment depth significantly reduces seismic vulnerability, and tunnels in soft soils exhibit higher damage probabilities under the same seismic demand. Moreover, comparisons between different tunnel shapes show that rectangular tunnels are the most vulnerable, followed by horseshoe tunnels, while circular tunnels demonstrate the highest seismic resistance. The proposed framework provides a useful reference for performance-based seismic design and risk assessment of underground structures.
Abstract Large-diameter monopiles are extensively used to support onshore bridges, port terminals, and offshore wind farms due to their high load-bearing capacity, low settlement and excellent seismic performance. Meanwhile, the conventional p–y curves that are primarily derived from tests on small-diameter flexible piles, cannot capture the mechanical behavior of large-diameter rigid monopiles under complex dynamic loads. This study employs validated numerical simulations using OpenSees, calibrated against shaking table test results, to systematically investigate the lateral bearing characteristics of large diameter monopiles in sandy soils. The analysis highlights significant discrepancies in the initial stiffness, ultimate resistance, and displacement prediction when using conventional p–y curves. To address these limitations, a modified p–y curve formulation is proposed by introducing correction factors for initial stiffness ( $$\:\alpha\:$$ ), ultimate resistance ( $$\:\beta\:$$ ), and characteristic displacement ( $$\:\gamma\:$$ ), thereby refining the key parameters of the conventional p–y curve. The proposed model is validated through comparing its predictions with both physical and numerical experiments. The comparison demonstrated its accuracy in representing the pile-soil interaction behavior of large-diameter monopiles embedded in sandy sites.
From macroscopic to microscopic perspectives, the influence laws of the number of freeze-thaw cycles on the physical properties and macro-microscopic damage of the specimens were revealed. It was clarified that 30 freeze-thaw cycles were the inflection point for the specimens to shift from brittle to plastic failure. A damage model under freeze-thaw cyclic loading was developed, and three distinct evolutionary stages of damage were identified: damage quiescence, damage acceleration, and damage stabilization. It was found that the initial damage value is directly influenced by the number of freeze-thaw cycles. Furthermore, it was concluded that the damage acceleration stage represents the critical phase for damage deterioration and sample instability. Due to seasonal variations and diurnal temperature fluctuations, cold regions develop distinct frozen rock masses. With seasonal transitions, these frozen rock masses undergo phase changes into thawed states, generating substantial tensile and compressive stresses that induce irreversible damage to the rock structures—particularly in sandy rock formations, where the effects are more pronounced. Once initiated, such damage can trigger a “domino effect,” leading to severe economic losses and potential casualties. In light of this, the present study systematically employs experimental techniques, including nuclear magnetic resonance and acoustic emission monitoring, integrated with damage mechanics theory, to investigate sandy rock samples collected from a specific open-pit mine in a cold region. The research focuses on the behavior of these samples under freeze-thaw cycles ranging from − 30 °C to 30 °C, with experimental analyses conducted under combined freeze-thaw and mechanical loading conditions. Several innovative findings have been achieved: The evolution characteristics of acoustic emission (AE) signals and the fracture morphology of specimens under freeze-thaw and loading conditions exhibit distinct patterns. The variations in cumulative event count and frequency band distribution are generally consistent with the trend observed in the stress-strain curve. However, both strength and structural stability progressively deteriorate with an increasing number of freeze-thaw cycles, leading to a reduction in macroscopic fracture time. A critical threshold is observed at 30 freeze-thaw cycles, marking the transition point from brittle to plastic failure behavior. Following 40 freeze-thaw cycles, brittle failure is no longer present, and a well-defined macroscopic fracture surface emerges. The number of freeze-thaw cycles directly influences the initial damage level of specimens under load, with higher cycle counts corresponding to greater initial damage. After 40 cycles, the initial damage value reaches as high as 0.68. Furthermore, the damage evolution process under combined freeze-thaw and mechanical loading can be classified into three distinct stages: damage quiescence, damage acceleration, and damage stabilization. Notably, the damage acceleration stage represents the critical phase preceding unstable rupture.
The sand compaction pile (SCP) method has been widely utilized for soft ground improvement. However, environmental and economic concerns arising from sand depletion have prompted exploration into alternative solutions. The granular compaction pile (GCP) method, utilizing materials such as crushed stone or recycled concrete, has emerged as a viable substitute. Despite extensive research on GCPs, a comprehensive understanding of how bulging failure influences their efficiency remains limited. This study investigates the load transfer mechanisms and deformation behavior of both tapered and uniform GCPs through static pile load tests and subsequent numerical analyses. The results indicate that applied loads on GCPs are primarily distributed via shaft friction within a depth of approximately 1.0 times the pile diameter. Maximum lateral expansion displacement occurs at a depth of approximately 1.5 times the pile diameter or more, varying with soil stiffness. Furthermore, increased stiffness of the soil strata leads to an expanded stress transfer range, causing ground deformation that extends beyond the surface layer to affect deeper soil layers. These findings enhance the understanding of GCP performance and underscore their potential for sustainable ground improvement applications.
The deformation properties of fractured rock mass are fundamental in engineering design considerations, influencing the stability and performance of structures such as dams, tunnels, and foundations. Accurately determining this parameter is challenging due to the presence of various fractures within the rock mass. Traditional methods, both direct and indirect, have limitations in accounting for the complex geometry and mechanical interactions of these discontinuities. In this study, a numerical framework is presented to evaluate the rock mass deformation modulus using a combined Discrete Fracture Network (DFN) and Distinct Element Method (DEM) framework based on plate loading tests. The modeling is performed using 3DEC, where fracture networks generated from geological surveys are embedded within an intact rock matrix. The model is validated using both continuous and discontinuous rock blocks based on data from the Bazoft and Bakhtiari Dam projects. The Azad pumped-storage power plant site is employed as the primary case study to conduct joint stiffness sensitivity analyses and to investigate scale effects and determine the Representative Elementary Volume (REV). Sensitivity analyses demonstrate the significant influence of joint normal and shear stiffness on the deformation modulus. In addition, the effect of model dimensions on the deformation modulus is also investigated to identify a Representative Elementary Volume (REV), beyond which the deformation modulus becomes stable. These results indicate that the proposed numerical framework provides a practical and reliable numerical approach for simulating plate loading tests and estimating the deformation modulus of fractured rock masses.
Rock masses with certain shear strength are fundamental for ensuring the safety and stability of geotechnical engineering projects for geological disaster prevention. However, serrated jointed rock masses exhibit complex geometries and nonlinear mechanical properties, making accurate predictions of their shear strength challenging. To address this, an innovative machine learning-based prediction framework is proposed, integrating swarm intelligence optimization techniques with explainable data-driven methods to enhance prediction accuracy and reduce costs. This study utilizes experimental data of serrated jointed rock masses, covering key parameters such as internal friction angle, joint normal stress, ratio of normal stress to intact rock tensile strength, joint inclination, and shear strength. Based on this, various models were constructed, including Support Vector Regression (SVR), Backpropagation Neural Network (BPNN), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). Furthermore, the models were optimized using Sparrow Search Algorithm (SSA), Chameleon Optimization Algorithm (CSA), Snake Optimization Algorithm (SO), and Kepler Optimization Algorithm (KOA). Results of statistical performance indicators showed that the KOA-XGBoost model performed best in predicting both the training and testing sets (R2 of 0.992, RMSE of 0.197 and 0.239), significantly outperforming other comparative models (R2 of 0.895 to 0.988, RMSE of 0.248 to 0.808). TreeSHAP analysis revealed that joint normal stress and joint inclination (with a cumulative importance score exceeding 0.6) were the most critical factors influencing shear strength. The findings provide an effective solution for ensuring the safety and stability of geotechnical projects involving serrated jointed rock masses.
