Geotechnics

Understanding rockfall behavior is essential for accurately predicting hazards in both natural and engineered environments, yet prior research has predominantly focused on spherical rocks or single-impact scenarios, leaving critical gaps in highlighting the dynamics of non-spherical rocks and multiple impacts. This study addresses these shortcomings by investigating the influence of rock shape and release angle on motion, energy dissipation, and impact behavior. To achieve this, an innovative approach rooted in the Video-Assisted Rockfall Kinematics Analysis (VARKA) procedure was introduced, integrating a custom-designed apparatus, controlled experimental setups, and sophisticated data analysis techniques. Experiments utilizing a pendulum-based release system analyzed various scenarios involving different rock shapes and release angles. These tests provided comprehensive motion data for multiple impacts, including trajectories, translational and angular velocities, and the coefficient of restitution (COR). Results revealed that non-spherical rocks exhibited significantly more erratic trajectories and greater variability in COR values compared to spherical rocks. The experiments demonstrated that ellipsoidal and octahedral shapes had substantially higher variability in runout distances than spherical rocks. COR values for ellipsoidal shapes spanned a wide range, in contrast to the tighter clustering observed for spherical rocks. These findings highlight the pivotal influence of rock shape on lateral dispersion and energy dissipation, reinforcing the need for data-driven approaches to enhance and complement traditional physics-based predictive models. Full article

Two-dimensional viscoplastic nonlinear analyses of the 2019 Feijão Dam 1 failure are performed using the finite difference program FLAC 8.1 with the user-defined constitutive models PM4SiltR and PM4Sand to assess how a series of commonly used engineering approaches can approximate the observed failure. A brief history of Feijão Dam 1, its failure, and the findings from two previous independent failure investigations are summarized. The present study uses the site characterization from those prior studies to develop the dam cross section, obtain material index properties, and establish groundwater conditions but uses alternative techniques for characterizing undrained shear strengths. The simulations show that the dam was marginally stable against long-term consolidated, undrained conditions and that modest loading changes were sufficient to trigger failure with deformation patterns consistent with the observed failure. The simulations further show that the collapse could have been triggered by a modest wetting event, ongoing drilling activities, or a combination of both mechanisms. Result sensitivity to choices in the calibration process and the numerical solution scheme are evaluated. The implications of these results on the use of commonly used engineering approaches for system-level time-dependent analyses and on long-term slope stability assessment procedures in practice are discussed. The results of this study provide support for the use of these analysis methods and engineering procedures in practice despite their simplifications and associated limitations. Full article

The accurate modeling of dynamic soil–structure interaction processes under impact loading is critical for advancing the design of soil-embedded barrier systems. Full-scale crash testing remains the benchmark for evaluating barrier performance; however, such tests are costly, logistically demanding, and subject to variability that limits repeatability. Recent advancements in computational methods, particularly the development of large-deformation numerical schemes, such as the multi-material arbitrary Lagrangian–Eulerian (MM-ALE) and smoothed particle hydrodynamics (SPH) approaches, offer viable alternatives for simulating soil behavior under impact loading. These methods have enabled a more realistic representation of granular soil dynamics, particularly that of the Manual for Assessing Safety Hardware (MASH) strong soil, a well-graded gravelly soil commonly used in crash testing of soil-embedded barriers and safety features. This soil exhibits complex mechanical responses governed by inter-particle friction, dilatancy, confining pressure, and moisture content. Nonetheless, the predictive fidelity of these simulations is governed by the selection and implementation of soil constitutive models, which must capture the nonlinear, dilatant, and pressure-sensitive behavior of granular materials under high strain rate loading. This review critically examines the theoretical foundations and practical applications of a range of soil constitutive models embedded in the LS-DYNA hydrocode, including elastic, elastoplastic, elasto-viscoplastic, and multi-yield surface formulations. Emphasis is placed on the unique behaviors of MASH strong soil, such as confining-pressure dependence, limited elastic range, and strong dilatancy, which must be accurately represented to model the soil’s transition between solid-like and fluid-like states during impact loading. This paper addresses existing gaps in the literature by offering a structured basis for selecting and evaluating constitutive models in simulations of high-energy vehicular impact events involving soil–structure systems. This framework supports researchers working to improve the numerical analysis of impact-induced responses in soil-embedded structural systems. Full article

This paper discusses the principal sources of uncertainty in the execution and interpretation of Bender Element (BE) tests conducted on reconstituted sand samples. Based on the experience accumulated by the Geotechnical Laboratory of the University of Coimbra, the study addresses three critical stages of the testing process: sample preparation, test execution, and result interpretation. For each stage, the key challenges are identified, and potential solutions are proposed. Particular emphasis is placed on the control of relative density and sample saturation during preparation, as well as on factors affecting signal quality and time lag of the system during test execution. The interpretation of the results is analyzed with respect to the limitations of currently employed methods. The overall reliability of the procedures employed throughout the testing process is also assessed, with the results providing guidance for improving the accuracy and consistency of BE test outcomes. Full article

Heat storage in compacted soil embankments is a promising technology in energy geotechnics, but its impact on the thermo-hydraulic behavior of unsaturated soils remains insufficiently understood. This paper investigates coupled heat and moisture transfer in unsaturated soil under different thermal conditions using a new bottom-heating method. The thermo-hydraulic response is monitored along the soil column and compared to an isothermal drying test. Variations in suction and water content were analyzed to determine water retention curve and to derive unsaturated hydraulic conductivity using the instantaneous profile method. The water retention curve exhibited deviations under thermal conditions, with reduced water contents observed only at intermediate suctions. Unsaturated hydraulic conductivity decreased significantly at moderate suctions but increased by up to one order of magnitude at high suctions. Heat-driven moisture redistribution was examined through flux calculations, highlighting that vapor-phase transport contributed significantly, up to 88%, to the upward water migration. These findings contribute to a better understanding of thermo-hydraulic interactions in unsaturated soils, which is essential for optimizing thermal storage applications in compacted embankments. Full article

Two properties that are commonly used in the analysis of debris-flow motion and behavior are viscosity and yield strength; however, many of the techniques to measure these properties are tedious, highly theoretical, and use only the finer fraction of debris. The purpose of this study is to develop a practical and consistent method of determining the influence that coarse particles, up to 25.4 mm, have on the viscosity and yield strength of debris flows, using more accessible testing methods. Samples were tested at various sediment concentrations and with increasing maximum grain sizes of particles. Values for viscosity and yield strength of each mixture were measured and compared using four separate, previously derived laboratory tests: an inclined flume box, a slump test, a simple inclined plane, and a rolling sleeve viscometer. The slump test and rolling sleeve viscometer produced the most consistent and reasonable results, particularly as the maximum grain size was increased. In general, the sediment concentration required to produce a given yield strength increased as coarser particles were added to a slurry. While viscosity changes with grain size distribution, its variation can be predicted by sediment concentration alone. Both yield strength and viscosity could be predicted from the finer fraction of sediment, and a proposed method to predict the addition of coarse material is described. Including coarse material, yield strength and viscosity values are expected to be within 25 and 100%, respectively, of values measured by other methods. Full article

Rockfall poses a significant hazard in steep terrain, where complex ground interactions cause falling boulders to deviate from straight-line paths. While lateral dispersion is commonly used to describe the distribution of deposited boulders from rockfall events, it does not provide any insight into the complexity of boulder trajectories while in motion. This study introduces tortuosity, a metric typically applied in porous media hydraulic analysis, as a novel approach for quantifying the deviation of rockfall paths from linearity. Using high-resolution UAV-based LiDAR data and RocFall3 (Version 1.017) simulation software, this research investigates the effects of terrain model resolution, boulder shape, and boulder mass on tortuosity values for 20,000 simulated rockfalls on a columnar jointed basalt slope in Boise, ID, USA. Results show that increasing terrain resolution leads to higher tortuosity values due to the increased presence of terrain asperities. Spherical boulders exhibited higher tortuosity than hexagonal ones, and tortuosity decreased with increasing mass for spheres, likely due to their momentum overcoming minor terrain features. Hexagonal boulders, constrained by their angular shape, showed less variability in tortuosity across resolutions and sizes. These findings emphasize the limitations of low-resolution publicly available LiDAR data and highlight the critical influence of accurate boulder representation in simulation models. Full article

This study focuses on determining the high-frequency decay parameter kappa (k) and its site component (k₀) for sixteen accelerometric stations installed in suitable locations in North Macedonia. Kappa characterizes the attenuation of ground motion at high frequencies, describing the decrease in the acceleration amplitude spectrum. It is defined using a regression line in log-linear space, starting from the point where the S-wave amplitude spectrum begins to decay rapidly. The site characteristics of the stations are determined through geophysical and borehole investigations, as well as HVSR mean curves derived from earthquake data. The strong-motion data used in this analysis originate from earthquake events with a moment magnitude greater than 3 (M_W > 3), an epicentral distance less than 120 km (R_epi < 120 km), and a focal depth lower than 30 km (h < 30 km). The records undergo visual inspection and filtering, with those having a signal-to-noise ratio (SNR) below 3 excluded from further analysis. The study examines the correlation between kappa values and various parameters, including magnitude, epicentral distance, average shear-wave velocity in the top 30 m depth (V_S30), and fundamental site frequency (f₀). The importance of this study is the application in the future evaluation/update of seismic hazard analysis of the region. Full article

The geometry of rock mass fractures is typically characterized through geological and geotechnical investigations. Detailed descriptions of granitic host rock can yield valuable data for constructing fracture network models. However, significant discrepancies often arise between data representing the mechanical and hydraulic properties of rocks. At the study site, fracture geometry data were gathered through surface and underground surveying, borehole logging, and underground mapping. Three-dimensional photogrammetry was utilized alongside traditional rock mass classification methods (Q-system, RMR, GSI) to derive key parameters of fracture networks, such as orientation, size, and intensity. This study focuses on Rock Quality Designation (RQD), a measure of fracture density derived from tunnel face mapping. Findings indicate that variations in fracture frequency are significantly affected by how fracture sets are defined and by the orientation distribution of fractures. Furthermore, using the D parameter (the 2D fractal dimension of fracture frequency) as a validation measure for RQD may lead to misleading interpretations if it aggregates fracture sets on the tunnel scale. Full article

Soil carbon remote sensing has become a popular topic amongst scientists, policy makers, landholders, and others in recent years, as pragmatic perspectives on climate change, land productivity, and food security become increasingly important. Unfortunately, more than fifty years of existing research has not provided clarity or consensus on the best soil carbon remote sensing methods. A reliable, widely applicable, robust, and cost-effective means of soil carbon modelling remains elusive. As evidenced by aggregated data from 259 papers and 503 models published since 1969, much experimentation has been undertaken and soil carbon remote sensing shows promise, but the situation remains unresolved. First, this review and meta-analysis shows that soil carbon remote sensing model accuracy (via Pearson’s correlation coefficient R²) has decreased on average since 1969, and more rapidly since the year 2000. Second, the model R² does not correlate strongly with the spatial (airborne platforms compared with satellite platforms) or spectral (multispectral compared with hyperspectral) resolution of data. Third, no significant relationship between the model R² and the number of samples included in the training/test dataset is apparent. Fourth, the R² of non-parametric models (mean R² in 2022 = 0.58, n = 117) has declined more rapidly (decrease of 1.3% per year) since 1969 (mean R² in 1969 = 0.74, n = 1) than the R² of parametric models (decrease of 0.4% per year), suggesting that the algorithm applied during soil carbon modelling may be of importance. Finally, data compiled in this meta-analysis demonstrate a correlation between declining model R² and the increased use of satellite multispectral data and non-parametric algorithms, particularly machine learning, since the year 2000. There is no other evidence to suggest that prediction models prepared with multispectral data perform worse than other models, however. Hence, for the purpose of experimentation, it may be valuable to continue experimenting with the use of machine learning models for soil carbon prediction. However, when model performance is the priority, it is recommended that simple, parametric models (such as linear regression) are applied. Full article

Subsurface characterisation is a fundamental aspect of the planning and design of hydroelectric projects, as it enables the assessment of the technical and geotechnical feasibility of the proposed infrastructure, ensuring its stability and functionality. This study focuses on the characterisation of rock masses from boreholes in the “Santa Rosa” and “El Rosario” areas, located in Morona Santiago, Ecuador, to determine key parameters for the design of hydroelectric projects. Field and laboratory tests were conducted, including uniaxial compression tests, indirect tensile–Brazilian tests, point load tests, tilt tests, and geomechanical classifications using the RMR and Q systems. The results show that igneous rocks, such as basalt and andesite, exhibit mechanical properties ranging from moderate to high, with uniaxial compressive strengths exceeding 120 MPa in the case of basalt, classifying it as a strong rock. In contrast, metamorphic rocks, such as chert, exhibit lower strength, with values ranging between 69.69 MPa and 90.63 MPa, classifying them as moderately strong. The RMR and Q index values indicate a variable rock mass quality, ranging from excellent in diorite and granite sectors to low in areas with significant discontinuities and alterations. Additionally, variations in basic friction angles were identified, ranging from 18° to 38°, which directly influence the stability of the proposed structures. In conclusion, this study highlights the importance of geomechanical characterisation in ensuring the technical feasibility of hydroelectric projects, providing key information for the design and development of safe and sustainable infrastructure in the region. Full article

This study investigates rainfall-induced slope instability in fine-grained clayey soils through a probabilistic and sensitivity analysis framework that integrates spatial variability. Moving beyond traditional deterministic methods, Monte Carlo simulations were employed to quantify uncertainty in geotechnical parameters—unit weight, cohesion, and friction angle—modeled as random fields with a 1 m spatial resolution. This approach realistically captures natural soil heterogeneity and its influence on slope behavior during rainfall events. Transient seepage and slope stability analyses were performed using SEEP/W and SLOPE/W, respectively, with the Spencer method ensuring full equilibrium. This study examined how slope height, inclination, rainfall intensity and duration, and soil properties affect the factor of safety (FS). The results showed that higher rainfall intensity and longer durations significantly increase failure risk. For example, under 9 mm/h rainfall for 48 h, slopes taller than 10 m at 45° inclination exhibited failure probabilities over 30%. At 20 m, FS dropped to 0.68 with a 100% probability of failure. Sensitivity analysis confirmed cohesion and friction angle as key stabilizing factors, though their impact diminishes with infiltration. A dataset of 9984 slope scenarios was generated, supporting future machine learning applications for risk assessment and climate-resilient slope design. Full article

The breaching of river levees can have dramatic economic and human impacts. In many countries, including France, laws and regulations require the assessment and inspection of hydraulic structures. Methods are required to carry out these missions. The following article presents a method for assessing the impacts of tree vegetation on the resistance of river levees to internal erosion. Indeed, the presence of trees—particularly following the decomposition of their roots—may cause damage in the structure through contact erosion, concentrated erosion, backward erosion or suffusion. The proposed method takes into account the possible presence of trees and especially roots in different parts of the levee. The method is based on the formalization and aggregation of expert knowledge. It permits the calculation of a performance indicator, which is obtained by aggregating criteria determined using formalized status indicators. The entire method is available in the article. The method was tested on two real cases. Full article

Geotechnical centrifuge modeling is a powerful tool for investigating the behavior of geo-structural systems under realistic stress conditions. To accurately replicate the radial nature of the centrifugal acceleration field, the model surface is often curved—a detail that can significantly influence soil response. This study explores the effectiveness and limitations of incorporating surface curvature in centrifuge models through a series of nonlinear finite element analyses, utilizing an advanced constitutive model for liquefiable soils. Focusing on mildly sloping ground, the numerical models are carefully calibrated and verified for convergence to ensure accurate simulation of soil cyclic behavior. The analysis reveals that neglecting surface curvature can lead to artificially dilative responses and underestimation of liquefaction-induced lateral spreading. By modeling several centrifuge experiments under varied scaling conditions, we demonstrate that including surface curvature yields pore pressure and deformation patterns more consistent with full-scale, gravity-driven responses. These findings underscore the critical role of geometric accuracy in both physical and numerical centrifuge modeling of seismic soil behavior. Full article

In geotechnical engineering, an accurate prediction is essential for the safety and effectiveness of construction projects. One example is the prediction of over/under-excavation volumes during drill and blast tunneling. Using machine learning (ML) models to predict over-excavation often results in low accuracy, especially in complex geological settings. This study explores how the pre-processing of measurement while drilling (MWD) data impacts the accuracy of ML models. In this work, a correlational analysis of the MWD data is used as the main pre-processing procedure. For each drilling event (single borehole), correlation coefficients are calculated and then supplied as inputs to the ML model. It is shown that the ML model’s accuracy improves when the correlation coefficients are used as inputs to the ML models. It is observed that datasets made from correlation coefficients help ML models to obtain higher generalization skills and robustness. The informational content of datasets after different pre-processing routines is compared, and it is shown that the correlation coefficient dataset retains information from the original MWD data. Full article

Since the 1960s, cyclic triaxial tests have been utilized to assess the liquefaction susceptibility of cohesionless soils. While standardized procedures exist for conducting cyclic triaxial tests, there remains no universally accepted criterion for defining liquefaction in a laboratory test. The selection of a liquefaction criterion significantly impacts the interpretation of the test results and subsequent analyses. To quantify these effects, more than 250 cyclic triaxial tests were evaluated using both stress-based and strain-based liquefaction criteria. The analyses performed focused on two aspects of the liquefaction behavior: the number of cycles of loading required to initiate liquefaction and the amount of normalized dissipated energy per unit volume that must be absorbed into the specimen in order for it to liquefy. The findings indicate that for soils susceptible to flow liquefaction failures, the number of loading cycles required to induce liquefaction decreases. They also show that the amount of energy dissipation required to trigger liquefaction remains largely consistent across different failure criteria. However, for soils prone to cyclic mobility failures, both the number of loading cycles and the amount of dissipated energy required to cause liquefaction were found to vary significantly depending on the failure criterion applied. Full article

Accurate prediction of tunneling-induced settlements in shallow tunnels in weak soil is challenging, as advanced constitutive models, such as the small-strain hardening soil model (SS-HSM) require several input parameters. In this study, a case study was used as a benchmark to investigate the sensitivity of the SS-HSM parameters. An automated framework was developed, and 100 finite-element (FE) models were generated, representing realistic input ranges and inter-parameter relationships. The resulting distribution of predicted surface settlements resembled observed outcomes, exhibiting a tightly clustered majority of small displacements (less than 20 mm) alongside a minority of widely scattered large displacements. Subsequently, machine-learning (ML) techniques were applied to enhance data interpretation and assess predictive capability. Regression models were used to predict final surface settlements based on partial excavation stages, highlighting the potential for improved decision-making during staged excavation projects. The regression models achieved only moderate accuracy, reflecting the challenges of precise displacement prediction. In contrast, binary classification models effectively distinguished between small displacements and large displacements. Arguably, classification models offer a more attainable approach that better aligns with geotechnical engineering practice, where identifying favorable and adverse geotechnical conditions is more critical than precise predictions. Full article

For reliable seismic design of earth-retaining structures, it is critical to accurately assess the magnitude and distribution of dynamic earth pressures. Over the years, numerous experimental and numerical studies have sought to clarify the complex soil–structure interactions in backfill–wall systems under seismic loads. This article expands on an earlier review by the authors of analytical and field performance studies addressing the seismic behavior of retaining walls. Despite extensive research, there is still no consensus on a standardized seismic evaluation method or on the necessity of including seismic loads in the design of retaining structures. This review critically examines notable experimental and numerical findings on dynamic lateral earth pressure, highlighting that the current design practices cannot be generally applied to all types of retaining structures. More importantly, these practices often rely on experimental data extrapolated beyond their original applicability. Full article

The influence of local site conditions is important when assessing the distribution of building damage and seismic risk. The average shear-wave velocity of the top 30 m of soil, V_s30, is one of the most commonly used parameters to characterize site conditions. Topographic slope is one of the proxies used to estimate V_s30 and is often used as a preliminary estimate of site conditions since a dataset is available worldwide at a resolution of 30 arc-seconds. This paper first proposes to compare the accuracy of V_s30 derived from topographic slope against detailed V_s30 zonation in five regions of the province of Quebec, Canada. A general underestimation of V_s30 is observed and site class agreement varies between 18 and 36% across the regions. Secondly, an approach is proposed to improve regional estimates of V_s30 where detailed site characteristics are not available other than the local topography and surface geology information. The surface deposit types from the geological map of Quebec are compared to V_s30 data previously obtained for zonation maps of Montreal, Saguenay and Gatineau in order to estimate V_s30 as a function of sediment deposit types as an alternative to the slope approach. A site class map for the province of Quebec is then proposed. Full article