Search Results (157)

The use of nonlinear, large-deformation, dynamic finite element analysis (FEA) has become a cornerstone in crash test simulations, playing a pivotal role in evaluating the safety performance of critical civil infrastructures, including soil-embedded vehicle barrier systems. This review paper offers a detailed examination of numerical modeling methodologies employed for simulating dynamic soil–structure interactions in crash test simulations, with a particular focus on dynamic impact pile–soil interaction. This interaction is a critical determinant in assessing the effectiveness of soil-embedded barrier systems during vehicular impacts. Our extensive review methodically categorizes and critically evaluates four prevalent modeling methodologies: the lumped parameter method, the subgrade reaction method, the modified subgrade reaction approach, and the direct or mesh-based continuum method. We explore each methodology’s underlying philosophy, strengths, and shortcomings in accurately simulating the dynamic interaction between soil and piles under impact loading. This technical review aims to provide a thorough understanding of the critical and distinctive aspects of modeling soil’s dynamic responses under impact loading conditions. Moreover, this paper is envisioned to serve as a foundational reference for future research endeavors, steering the advancement of innovative simulation techniques for tackling the dynamic impact soil–structure interaction problem. Full article

The interface friction between granular materials and continuum surfaces is fundamental in civil engineering, especially in geotechnical projects where sand of varying sizes and shapes contacts surfaces with different roughness and hardness. The aim of this research is to investigate the parameters that influence the peak interface friction, taking into consideration the properties of both sand and continuum surfaces. This will be accomplished by employing a combination of experimental and machine learning techniques. In the experiment, a series of interface shear tests were conducted using a direct shear apparatus under differing levels of normal stress and density. Utilising machine learning techniques, the study considered eleven input features: mean particle size, void ratio, specific gravity, particle regularity, coefficient of uniformity, coefficient of curvature, granular rubber content, carpet fibre content, normal stress, surface roughness, and surface hardness. The output measured was the peak interface friction. The machine learning techniques enable us to explore the complex relationships between the input features and the peak interface friction, and to develop an empirical equation that can accurately predict the interface friction. The experiment findings reveal that density, inclusion of recycled material, and normalised roughness impact peak interface friction. The machine learning findings validate the efficacy of both multiple linear regression and random forest regression models in predicting the peak interface friction, with the latter outperforming the former in terms of accuracy when compared to the experiment results. Furthermore, the most important features from both models were identified. Full article

The ability to precisely monitor soil moisture is highly valuable in industries including agriculture and civil engineering. As soil moisture is a spatially erratic and temporally dynamic variable, rapid, cost-effective, widely applicable, and practical techniques are required for monitoring soil moisture at all scales. If a consistent numerical relationship between soil moisture content and soil reflectance can be identified, then soil spectroscopic models may be used to efficiently predict soil moisture content from proximal soil reflectance and/or remotely sensed data. Previous studies have identified a general decrease in visible–NIR soil reflectance as soil moisture content increases, however, the strength, best wavelengths for modelling, and domain of the relationship remain unclear from the current literature. After reviewing the relevant literature and the molecular interactions between water and light in the visible–NIR (400–2500 nm) range, this review presents new analyses and interprets new 1 nm resolution soil reflectance data, collected at >20 moisture levels for ten soil samples. These data are compared to the results of other published studies, extending these as required for further interpretation. Analyses of this new high-resolution dataset demonstrate that linear models are sufficient to characterise the relationship between soil moisture and reflectance in many cases, but relationships are typically exponential. Equations generalising the relationship between soil MC and reflectance are presented for a number of wavelength ranges and combinations. Guidance for the adjustment of these equations to suit other soil types is also provided, to allow others to apply the solutions presented here and to predict soil moisture content in a much wider range of soils. Full article

Given the abundance and importance of earth retention structures, the problem of seismic earth pressure has attracted not only the research community but also industry and government establishments. The dynamic response, even in the case of the simplest retaining wall, presents a complex problem of soil–structure interaction, encompassing a multitude of competing and complementary factors. This article presents a thorough and critical evaluation of notable analytical and field studies related to the dynamic earth pressures acting on retaining walls. Despite numerous studies spanning nearly a century regarding seismically induced lateral earth pressures, there remains a noticeable disparity between theoretical understanding and the actual field performance of retaining structures during seismic events. This review underscores the necessity for a more meticulous examination of dynamic analysis techniques and the existing design methodologies for retaining structures. Full article

A series of laboratory and large-scale field model footing tests were conducted to assess the modulus and stress distribution behavior of a clayey soil foundation, both with/without geogrid reinforcement, deviating from the conventional approach of evaluating the strength performance, such as bearing capacity. The modulus was evaluated at three settlement ratios of s/B = 1, 3, and 5%, while the stress distribution angle $\left(\alpha \right)$ was estimated at three applied surface pressures of 234 kPa, 468 kPa, and 936 kPa. The results indicated a stiffer load-settlement response when geogrid reinforcement was included. The modulus of reinforced clayey soil remained nearly constant for test sections with the same reinforced ratio, with the modulus improvement increasing as the reinforced ratio (R_r) increased. The modulus improvement also increased with the settlement ratio (s/B). These results demonstrated that the stress distribution improvement decreased as the surface pressure increased. Generally, both the modulus and stress distribution improvement exhibited an increase with an increase in the tensile modulus of the geogrid. While laboratory model tests consistently provided a higher improvement in the modulus than large-scale field model tests in this study due to a higher reinforced ratio, the stress distribution improvement was similar for both. Full article

Assessing the constrained modulus is a critical step in calculating settlements in granular soils. This paper describes a novel concept of how the constrained modulus can be derived from seismic tests. The advantages and limitations of seismic laboratory and field tests are addressed. Based on a comprehensive review of laboratory resonant column and torsional shear tests, the most important parameters affecting the shear modulus, such as shear strain and confining stress, are defined quantitatively. Also, Poisson’s ratio, which is needed to convert shear modulus to constrained modulus, is strain-dependent. An empirical relationship is presented from which the variation in the secant shear modulus with shear strain can be defined numerically within a broad strain range (10⁻⁴–10^−0.5%). The tangent shear modulus was obtained by differentiating the secant shear modulus. According to the tangent modulus concept, the tangent constrained modulus is governed by the modulus number, m, and the stress exponent, j. Laboratory test results on granular soils are reviewed, based on which it is possible to estimate the modulus number during virgin loading and unloading/reloading. A correlation is proposed between the small-strain shear modulus, G₀, and the modulus number, m. The modulus number can also be derived from static cone penetration tests, provided that the cone resistance is adjusted with respect to the mean effective stress. In a companion paper, the concepts presented in this paper are applied to data from an experimental site, where different types of seismic tests and cone penetration tests were performed. Full article

In recent years, slope failure caused by heavy rainfall from linear precipitation bands has occurred frequently, causing extensive damage. Predicting slope failure is an important and necessary issue. A method used to predict the time of failure has been proposed, which focuses on the tertiary stage of the creep theory, shown as V = A/(t_r − t), where V is the velocity of displacement, A is a constant, and (t_r − t) is the time until failure. To verify this method, indoor model experiments and field monitoring were used to observe the behavior of surface displacement. Seven cases of laboratory experiments were conducted by changing the conditions in the model, such as materials, the thickness of the surface layer, and relative density. Then, two cases of field monitoring slope failure were examined using this method. The results show that, in the tertiary stage of creep theory, the relationship between tilt angle velocity and the time until failure can be expressed as an inversely proportional relationship. When the tilt angle velocity has reached the tertiary creep stage, it initially ranges from 0.01°/h to 0.1°/h; when near failure, it was found to be over 0.1°/h, so, combining this with previous research results, this is a reasonable value as a guideline for an early warning threshold. Full article

An efficient foundation system of single- or double-paddled H-piles (PHPs), which comprises steel H-piles fitted with specially configured steel plates (paddles), is proposed to support sound walls subjected to wind loading. The lateral responses of single-paddled (SPHPs) and double-paddled H-piles (DPHPs) installed in clay is evaluated using a comprehensive assessment of the foundation performance via a full-scale lateral load testing program, alongside extensive three-dimensional (3D) nonlinear finite element (FE) analysis. The comparison between the calculated and measured responses of the PHPs demonstrates that the developed numerical model accurately depicts the response of the PHPs under lateral load. The validated numerical model is then used to evaluate the effect of the soil consistency on the lateral response and capacity of the PHPs. The influence of the paddles’ configuration on the lateral response and capacity of the PHPs is also evaluated. Furthermore, the change in the PHP lateral stiffness due to adding a second paddle is also examined. Finally, the influence of the plates on the surrounding soil is investigated by analyzing the formation of the strain field around the pile and evaluating the extent of the soil influence zone at different plate-width-to-pile-flange-width ratios (W_p/W_f). The result of this study indicates that adding plates contributes significantly to the lateral capacity of PHPs in clay and reduces the maximum bending moment. The parametric study reveals that the top 5–6 W_p of the soil have a significant effect on the lateral response of the proposed H-pile. Based on the outcomes of the field tests and numerical analysis, optimal geometrical parameters for paddles are proposed. Full article

It is now well-known that ground motion characteristics can be influenced significantly by local site characteristics. In general, soil characteristics were classified by considering the time-average velocity down to 30 m (V_s30). However, recent studies have showed that the fundamental site period is a better proxy than V_s30, or the most complementary parameter to V_s30, for this purpose. Recent earthquakes have also revealed that the largest amplifications occur at the fundamental site period and cause heavy damage or the collapse of structures when they have similar vibrational characteristics with the site’s fundamental period, i.e., resonance. Therefore, many studies in the literature have been performed to determine the fundamental periods of layered soil profiles using different analytical, approximate, and data-driven methods. However, there is a requirement to evaluate these methods by following a systematic procedure. Hence, the reader will receive a comprehensive review of the available procedures for determining the site’s fundamental period of layered soil profiles and their applications at different scales, along with an exploration of current research gaps. Full article

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