Geotechnics

This paper presents a comprehensive study in which non-destructive testing utilizing ultrasonic pulse velocity (UPV), considering both pressure (P) waves and shear (S) waves, was used to assess the compressive strength (CS) of rubberized bricks. These innovative bricks were manufactured by blending lime kiln dust (LKD) waste with ground granulated blast furnace slag (GGBFS), sand, and fine waste tire crumb rubber (WTCR). This study introduces mathematical models to explain the relationships between the results of destructive tests (DTs), specifically compression strength (CS) tests, and non-destructive tests (NDTs) employing UPV. These models were subsequently used to conduct validation exercises to accurately predict the strength of the rubberized bricks produced. The outcomes of the validation tests underscore the effectiveness of the UPV method in predicting the CS of rubberized eco-friendly bricks produced using an LKD-GGBFS blend. Importantly, the prediction using the power model exhibited minimal errors, confirming the utility of the UPV method as a reliable tool for assessing the compressive strength of such sustainable construction materials. This research contributes to advancing the field of eco-friendly construction materials and highlights the practical applicability of non-destructive ultrasonic testing in assessing their structural properties. Full article

Constructing embankments over soft soils is a challenge for geotechnical engineers due to large settlements. Among diverse ground-improvement methods, combining piles and geosynthetics (e.g., geosynthetic-reinforced piles, deep cement mixing columns, geotextile-encased columns) emerges as a reliable solution for time-bound projects and challenging ground conditions. While stress distribution within pile-supported embankments has been extensively studied, the load transfer efficiency of piled solutions with geosynthetic reinforcement remains less explored. The novelty in this study lies in the investigation of three different inclusion solutions from a common control case in the numerical model considering the role of geosynthetic reinforcement. This study investigates the load transfer mechanisms in embankments supported by various techniques including geosynthetic-reinforced piles, deep cement mixing columns, and geosynthetic-encased granular columns. Two-dimensional axisymmetric finite element models were developed for three cases of embankments supported by vertical inclusions. Numerical findings allow clarification of the soft ground and embankment characteristics which influence the arching and membrane efficiencies. Rigid piles outperform deep cement mixing (DCM) columns and geotextile-encased columns (GEC) in reducing settlements of soft ground. Geosynthetic reinforcements are particularly helpful for rigid pile solutions in high embankments due to their load transfer capability. Additionally, physical properties of fill soil can impact the inclusion solutions, with high shear resistance enhancing the arching effect and lower modulus subsoils showing better arching performance. Full article

Understanding the dynamic interaction between piles and the surrounding soil under vehicular impacts is essential for effectively designing and optimizing soil-embedded vehicle barrier systems. The complex behavior of pile–soil systems under impact loading, attributed to the soil’s nonlinear behavior and large deformation experienced by both components, presents significant simulation challenges. Popular computation techniques, such as the updated Lagrangian finite element method (UL-FEM), encounter difficulties in scenarios marked by large soil deformation, e.g., impacts involving rigid piles. While mesh-free particle and discrete element methods offer another option, their computational demands for field-scale pile–soil impact simulations are considerable. We introduce the erosion method to bridge this gap by integrating UL-FEM with an erosion algorithm for simulating large soil deformations during vehicular impacts. Validation against established physical impact tests confirmed the method’s effectiveness for flexible and rigid pile failure mechanisms. Additionally, this method was used to examine the effects of soil mesh density, soil domain sizes, and boundary conditions on the dynamic impact response of pile–soil systems. Our findings provide guidelines for optimal soil domain size, mesh density, and boundary conditions. This investigation sets the stage for improved, computationally efficient techniques for the pile–soil impact problem, leading to better pile designs for vehicular impacts. Full article

Geotechnical rockmass characterization is a key task for design of underground and open pit excavations. Hydrothermal veins influence excavation performance by contributing to stress-driven rockmass failure. This study investigates the effects of vein orientation and thickness on stiffness and peak strength of laboratory scale specimens under uniaxial and triaxial compression using finite element numerical experiments of sulfide veined mafic igneous complex (CMET) rocks from El Teniente mine, Chile. The initial numerical models are calibrated to and validated against physical laboratory test data using a multi-step calibration procedure, first of the unveined Lac du Bonnet granite to define the model configuration, and second of unveined and veined CMET. Once calibrated, the numerical experiment involves varying the vein geometry in the veined CMET models by orientation (5 to 85°) and thickness (1, 4, 8 mm). This approach enables systematic investigation of any vein geometry without limitations of physical specimen availability or complexity of physical materials. This methodology greatly improves the value of physical laboratory test data with a limited scope of vein characteristics by using calibrated numerical models to investigate the effects of any other vein geometry. In this study, vein orientation and thickness were both found to have a significant impact on the specimen stiffness and peak strength. Full article

Over the past decades, numerical modelling has become a powerful tool for rock mechanics applications. However, the accurate estimation of rock mass input parameters remains a significant challenge. Machine learning (ML) tools have recently been integrated to enhance and accelerate numerical modelling processes. In this paper, we demonstrate the novel use of ML tools for calibrating a state-of-the-art three-dimensional (3D) finite-element (FE) model of a kinematic structurally controlled failure event in an open-pit mine. The failure event involves the detachment of a large wedge, thus allowing for the accurate identification of the geometry of the rock joints. FE models are automatically generated according to estimated ranges of joint input parameters. Subsequently, ML tools are used to analyze the synthetic data and calibrate the strength parameters of the rock joints. Our findings reveal that a relatively small number of models are needed for this purpose, rendering ML a highly useful tool even for computationally demanding FE models. Full article

The fracture network largely determines the efficiency of heat extraction from fractured geothermal reservoirs. Fracture openings are influenced by thermo-poroelastic stresses during cold fluid flow, with the interplay between fracture length and fracture opening regulating heat transfer. The lack of field data concerning fluctuating fracture openings underscores the necessity for computational models. This work emphasizes the impact of such gaps in the literature. Factors such as temperature, pressure, stress, thermal breakthrough time, and cumulative energy are evaluated to analyze the system’s behavior. A sensitivity analysis is employed to ascertain the significance of stress on fracture opening, compared with thermo-hydraulic behavior. The results show that stress field alterations, due to intersections with minor fractures, can cause up to a 15% variation in the largest fracture’s opening. The impact of thermoelastic stress outweighs the impact of poroelastic stress approximately threefold. Such stress-induced variations in fracture openings can lead to an up to 30% increase in cumulative heat extraction, while the drop in production temperature is limited to around 50%. Full article

Accurate measurements and predictions of near-surface soil drying and evaporation following heavy rainfall events are often needed for research in agriculture and hydrology. However, such measurements and predictions at mine waste pile and tailing settings are limited. The prediction of evaporation at mine waste piles is essential for many problems in geotechnical engineering, including the design of soil cover systems for the long-term closure of hazardous waste sites, and thus mitigates, for example, the generation of acid mine drainage (AMD) and metal leaching. AMD is one of mining’s most serious threats to the environment. This study investigated the short-term (8 days) and medium-term (27 days) drying rates and evaporative fluxes at the surface and near-surface of the Deilmann South waste-rock (DSWR) pile at the Key Lake uranium mine, northern Saskatchewan, using the gravimetric (GV) method and SoilCover (SC) model, respectively, during and following heavy rainfall events for the environment. The SC simulation results showed that during the weather-controlled stage (Stage I) of the first 5-day period of rainfall events, while the surface was wet, the potential evaporation (PE) was equal to the actual evaporation (AE) (i.e., AE/PE = 1). As the surface became drier on Day 6, the cumulative PE began to separate from the cumulative AE and the surface’s drying rate rapidly diverged from those at the deeper depths. This occurrence signaled the onset of the soil profile property-controlled stage (Stage II). As the drying continued, the surface became desiccated and the slow-rate drying stage (Stage III) was established from Day 7 onward. The SC-simulated AE results were compared to those measured using the eddy covariance (EC) method for the same test period at the DSWR pile in a different study. The comparison showed that the two methods yielded similar AE results, with 18% relative errors. The results of this study provided the opportunity to validate the SC model using actual data gathered under field conditions and to ascertain its ability to accurately predict the PE and AE at the surfaces of mine waste piles. Full article

In some cases, the water content in granular soil increases to the extent that it becomes saturated, which noticeably alters its responses. For example, the pore water pressure within saturated granular soil would increase rapidly under sudden external loading, which is equivalent to undrained or constant volume conditions. This reduces the effective stress in soil dramatically and may result in catastrophic failure. There have been different numerical approaches to analyse such a failure mechanism of soil to provide a deeper understanding of soil behaviour at the microscopic level. One of the most common numerical tools for such analysis is the discrete element method (DEM) due to its advantage in obtaining microscopic properties (e.g., statistics on particle contacts and fabric), reproducibility and simple feedback control. However, most DEM studies ignore the fluid phase and merely consider the solid particles while the fluid pressure is indirectly calculated by mimicking undrained condition to a constant volume condition. Note that fluid’s influence does not limit to the change of pore water pressure. For example, the external loading would induce the movement of fluid, and the fluid-solid interaction could subsequently drag the solid particles to shift within the system. In addition, the state of soil could change from solid to suspension under an excess hydraulic gradient. Therefore, the study of the fluid-solid mixture is essential as it is a typical scenario in geotechnical practice, and the simulations of saturated sand should be conducted in numerical forms in which both the solid and fluid phases can be modelled. Full article

Vehicle restraint systems are vital hardware elements in road safety engineering. The certification process of a vehicle restraint system includes full-scale crash tests, component testing and numerical simulation of these tests. To achieve reliable crash test simulation results, the soil–post interaction must be modelled to capture the behaviour realistically. There is no standardised approach for modelling the soil–post interaction in the praxis. In this study, the finite element method is utilised to investigate the soil–post response under quasi-static and dynamic impact loading. Two different modelling techniques are applied for this purpose. The first technique is the finite element continuum method, with the soil modelled using the advanced hypoplastic constitutive relation and calibrated using laboratory test data. The second technique is a lumped-parameter model, for which a systematic parameters calibration routine using basic soil properties is introduced. The numerical models are validated using a series of full-scale field tests performed by the authors on single posts in standard road shoulder materials. The performance comparison of the investigated modelling techniques shows that the hypoplastic constitutive relation can capture the post behaviour realistically under different loading conditions using the same parameter set. The introduced lumped-parameter model adequately simulates the post behaviour with high computational efficiency, which is very important when simulating several posts. The conducted parametric study elucidates that the soil’s relative density, the post’s embedment length, and the post-section modulus govern the single post’s lateral load-bearing behaviour and energy dissipation capacity. Full article

Slope instability issues could cause severe damage and endanger the population, especially when dams are concerned. Over the past years, more and more refined numerical approaches have been proposed to evaluate the slope stability. However, a criterion based on the lack of numerical convergence is generally considered to compute the safety factor with this kind of approaches, which may result in a dramatic increase in the overall computation time for the probabilistic assessment of the safety factor (e.g., using Monte Carlo simulations that require the automation of a large number of simulations). This paper proposes an original approach coupling the shear strength reduction technique with the second-order work criterion. This approach is implemented in the open finite element software Cast3M, version 22.0. The relevance and efficiency of the developed approach is illustrated with two case studies: a heuristic slope and an existing earth dam. Safety factors similar to those calculated by classical approaches are obtained, but without pushing the calculation to the point of non-convergence. Among other advantages described in the paper, the proposed approach makes it possible to compute safety factors using a rational and physically based criterion, while facilitating probabilistic calculations. Full article

To evaluate the importance of the site effects of large structures such as the new Belvedere Bridge (L’Aquila), which crosses a 25 m deep and 100 m valley in the city, one-dimensional and two-dimensional analyses were used to model the seismic response. The results indicate that the valley effects and the geometry of the bridge construction section have a significant influence on ground motions, especially at the points where the natural morphology has been altered by civil works carried out over time. In the presence of vertically propagating shear waves (SVs), the synthetic parameters of seismic motion, such as the maximum ground acceleration (PGA), the amplification factors (AFs), and the elastic acceleration response spectra (Ses), are crucial aspects to identify. The different motions generated between the anchorage points of the bridge foundations, even though they exhibit reduced proportions, and the site effects should be considered in bridge design. Full article

Expansive soils change volume due to changes in moisture content, which results in ground movement. Lightweight shallow-depth structures such as pavements, residential footings, and pipelines can suffer distress as they face additional stresses from the moving ground. The soil reactivity (the ability of soil to expand or contract due to change in moisture content) and the interactions at the soil-atmosphere-vegetation boundary are two of the major contributing factors to the ground movement. The current methodology used in design to account for ground movement is based on limited field and laboratory observations. Aiming at a better understanding of the interaction at the soil-atmosphere-vegetation boundary and its correlation with ground movement, this paper presents results from a field study. The research site was located in a semi-arid climate area and consisted of moderately to highly reactive clay soils. Part of the site was vegetated with mature trees, and part was occupied by grass. The order of 10 s of mm difference was observed in the magnitude of movement across the site owing to site soil variability as well as differences in vegetation. The areas with large trees showed relatively lower ground movement over the study period compared to the area occupied by grass, which was attributed to the microclimate created by the tree canopy and the already established deeper drying of the soil near the trees. Full article

Building information modeling (BIM) in the planning and construction of infrastructure projects, such as roads, tunnels, and excavations, requires the generation of comprehensive 3D subsoil models that encompass relevant geological and geotechnical information. Presently, this process relies on the deterministic interpolation of discrete data points obtained from exploratory boreholes and soundings, resulting in a single deterministic prediction. Commonly employed interpolation methods for this purpose include radial basis function and kriging. This contribution introduces probabilistic methods for quantifying prediction uncertainty. The proposed modeling approach is illustrated using simple examples, demonstrating how to use sequential Gaussian and Indicator Simulation techniques to model sedimentary processes such as erosion and lenticular bedding. Subsequently, a site in Munich serves as a case study. The widely used industry foundation classes (IFC) schema allows the integration of the model into the BIM environment. A mapping procedure allows transferring voxel models to the IFC schema. This article discusses the significance of incorporating uncertainty quantification into subsoil modeling and shows its integration into the BIM framework. The proposed approach and its efficient integration with evolving BIM standards and methodologies provides valuable insights for the planning and construction of infrastructure projects. Full article

The cementation medium for ureolytic microbially induced calcium carbonate precipitation (MICP) typically consists of urea and a calcium source. While some studies have augmented this basic medium, the effects of adding substrates such as ammonium chloride are unclear. The studies detailed in this paper sought to quantify the effect of the ammonium chloride augmentation of cementation medium (CM) on the process of MICP. An aqueous MICP study was initially carried out to study the effects of adding ammonium chloride to the urea–calcium cementation medium. This batch test also explored the effect of varying the concentration of calcium chloride dihydrate (calcium source) in the CM. A subsequent sand column study was undertaken, whereby multiple treatments of CM were injected over several days to produce a biocement. Six columns were prepared using F65 sand bioaugmented with Sporosarcina pasteurii, half of which were injected with the basic medium only and half with the augmented medium for treatment two onwards. Effluent displaced from columns was tested using ion chromatography and Nesslerisation to determine the calcium and ammonium ion concentrations, respectively, and hence the treatment efficiency. Conductivity and pH testing of effluent gave insights into the bacterial urease activity. The addition of 0.187 M ammonium chloride to the CM resulted in approximately 100% chemical conversion efficiency within columns, based on calcium ion measurements, compared to only 57% and 33% efficiency for treatments three and four, respectively, when using the urea–calcium medium. Columns treated with the CM containing ammonium chloride had unconfined compressive strengths which were 1.8 times higher on average than columns treated with the urea–calcium medium only. Full article

One common method of estimating e_max and e_min for mixtures of sand and silt requires that the values of several empirical constants be determined. These empirical constants are the filling coefficients, a, and embedment coefficients, b, which can be determined either via lab testing or correlations. The study reported here developed simple correlations for estimating the filling and embedment coefficients using readily obtained laboratory data. These models were found to be excellent in producing filling and embedment coefficients that accurately predicted values of the index void ratios for sand and silt mixtures, with most R² values being 0.94 or greater. Full article

The most common classification method of drill cores is the Rock Quality Designation (RQD) value, which indicates the percentage of rock cores longer than 10 cm in a given core section. This core logging procedure is the basic parameter in the most useful rock mass classification methods like Rock Mass Rate (RMR) and Rock Mass Quality (Q). It is also used to determine the Geological Strength Index (GSI), which has become widely used in the last 20 years. One of the basic problems of the RQD value is that it does not distinguish different rock cores longer than 10 cm (100% is obtained for one piece of 1 m length and 10 pieces of 10 cm length) and a uniform result is obtained for shorter units. In this paper, the so-called Integrated RQD (Int_RQD) factor is introduced to eliminate these problems and to provide a better description of fracture density in the core logging procedure. As it uses the original core logging procedure, historical RQD data can also be reevaluated. Considering that RQD is an input parameter for most rock engineering classifications, these systems such as GSI can be reviewed based on the new RQD definition proposed herein. Full article

This study evaluates the effectiveness of the previously proposed Standard Penetration Test (SPT) N and shear wave velocity (V_S) models in relation to the geological attributes of the Busan region, situated in the southeastern part of the Korean peninsula. The multiple empirical N-V_S models, which used datasets collected from different regions in South Korea, resulted in distinct N-V_S trends across models. To validate the predictive capabilities of each model, this study gathered boring logs containing SPT N and V_S measurements within the Busan region, followed by a thorough residual analysis. The Busan area encompasses a delta region to the west and erosion basins within the mountains and hills to the east. Despite the relatively confined geographical scope, we found that models developed using data from fill areas exhibit superior performance for the delta region (western Busan), while models constructed from datasets within erosion basins perform better for the erosion basin region (eastern Busan). This comparative examination supports the dependence of the N-V_S model on geologic attributes and offers the valuable insight that N-V_S models developed with analogous geological attributes should be employed when estimating V_S from SPT N values. Full article

The challenge of maintaining ride quality and serviceability in flexible pavements built over expansive soil deposits remains a critical concern for transportation agencies. These expansive subgrades exhibit swell-shrink behavior in response to moisture fluctuations, leading to differential heaving and subsequent costly maintenance. This paper explores the effectiveness of a Hybrid Geosynthetic Reinforcement System (HGRS)—a composite of geocell and geogrid—as a targeted mitigation strategy for differential heaving induced by expansive soils. A large-scale box test was designed to simulate a flexible pavement section, consisting solely of a base course layer and the underlying expansive subgrade. Four test conditions were investigated: an unreinforced control, a geocell-reinforced section, a geogrid-reinforced section, and an HGRS-reinforced section. Vertical displacements on the surface of the base course layer were longitudinally monitored and compared against the control. The results reveal that the use of geosynthetic reinforcements, and HGRS in particular, significantly mitigates both maximum surficial heave and differential swelling. Among the systems tested, flexible pavements featuring HGRS demonstrated the most effective performance in alleviating the challenges posed by expansive soil deposits. Full article

Rock mechanics and the estimation of their material properties through field tests are important aspects and challengees in civil and geotechnical engineering. However, this procedure is expensive and difficult to attain, while the machine learning and neural network theory provide a computational tool for estimating the material properties with limited data. In this work, an estimation of the Young Modulus and the cohesion of a clayey-originated rock through feed-forward neural networks constructed from in situ data measurements is given. The input values come from the Geological Strength Index (GSI) proposed values of the point load index $I_{s50}$, the uniaxial compression strength ${\sigma }_s$, as well as the specific gravity $\gamma$ of the rock mass. The convergence analysis revealed that the convergence occurs at approximately 2000 epochs, with the largest $L_2$ mean square error norm being no greater than ${10}^{-5}$. In addition, it is demonstrated that augmenting $\gamma$ results in the estimation of rock that is stiffer and stronger. The aforementioned increase in the specific site may be up to 20% for the stiffness and up to 25% for the cohesion. This model, aside from readability and accuracy, offers the convenience of enriching it with more in situ data, thereby enhancing the flexibility of the proposed numerical tool proposed. However, its applicability is limited to the specific data acquired from the particular site, so a more general estimation requires a substantially larger dataset. Finally, the justification of the proposed model has been carried out based on suggestions from the literature for common values of clayey-oriented rock, which is fairly disintegrated as seen in the field. Full article