Search Results (77)

The primary purpose of this paper is to investigate the impact of traffic wander on road pavement life for application in connected and autonomous vehicles. Research shows that in autonomous vehicles, drivers often follow the same path, leading to significant pavement damage on specific, well-defined paths. The paper examined the impact of traffic wander on pavement life by analysing two different wander distributions: normal and uniform. Based on the estimated pavement life for various pavement structures, a model that predicts the increase in pavement life due to traffic wander was developed for cracking and rutting prediction. The result of the research is the determination of relative pavement life influence functions, in which the variables are the traffic wander, asphalt layer thickness and subgrade stiffness. The obtained equations can be easily implemented for pavement service life extension evaluation. The model was also used to estimate the asphalt layer thickness as a function of the traffic expressed in terms of Equivalent Single Axle Load (ESALs). An analysis of the implications of the lateral distribution of traffic on the pavement thickness was presented. Significant reductions in the asphalt layer thickness of the pavement are achieved when wander is considered. Full article

The interaction between raft foundations and soils is generally modeled with the help of linear elastic springs. The design of structural elements can only be computed when the modulus of subgrade reaction is accurately determined, which is a time-consuming process for raft foundations with relatively large sizes due to the input of many structural loads. In the present work, an approximate procedure is studied based on the relative stiffnesses of soil–foundation systems suggested by DIN—Technical Report 130. To estimate the behavior of soil–foundation systems (rigid or flexible), the limit values of relative stiffness are first determined for raft foundations on elastic soils with the stiffness moduli obtained from one-dimensional consolidation tests by using finite element analyses. Subsequently, the values of subgrade reaction moduli obtained from the FE analyses are compared and discussed with the subgrade reaction moduli determined by using the analytical method considering the relative stiffnesses of soil–foundation systems. It is shown that for a soil–foundation system with a relative stiffness ≥ 0.174, the subgrade reaction modulus obtained from the analytical method assuming a rigid system is about 1.5 to 2 times higher than that in the FE analyses. For a soil–foundation system with a relative stiffness ≤ 0.0004, the analytical method assuming a flexible system and the FE method yield a similar value of subgrade reaction modulus in the central area of the raft foundation. Full article

During railway operations, changes in the support conditions of sleepers, owing to various internal and external factors, can damage rails and concrete sleepers and alter the structural characteristics of gravel-ballasted tracks. However, current methods for evaluating gravel ballast conditions primarily rely on visual inspection. This study proposes a quantitative approach using modal testing to assess ballast conditions. This is achieved by analyzing and experimentally verifying the relationship between track ballast loosening (caused by subgrade deformation) and track support performance. Finite element analysis results and field experimental values were compared using spring stiffness as a parameter. The results showed that natural frequencies and mode shapes changed in response to variations in the vertical spring stiffness of the gravel-ballasted track. Therefore, the sleeper support condition of a gravel-ballasted track can be readily identified by analyzing the natural frequency corresponding to different sleeper support conditions. Full article

This study aims to explore the dynamic response of ballastless tracks under various temperatures of the cement-emulsified asphalt (CA) mortar layer and other environmental factors. CA mortar is the key material in the ballastless track structure, exhibiting notably temperature-dependent viscoelastic properties. It can be damaged or even fail due to the continuous loads from trains. However, the dynamic behaviors of ballastless tracks considering the temperature-dependent viscoelasticity of CA mortar have been insufficiently studied. This paper captures the temperature-dependent viscoelastic characteristics of CA mortar by employing the fractional Maxwell model and applying it to finite element simulations through a Prony series. A vehicle–track–subgrade (VTS) coupled CRTS I ballastless track model, encompassing Hertz nonlinear contact and track irregularity, is established. The model is constrained symmetrically on both of the longitudinal sides, and the bottom is fixed on the infinite element boundary, which can reduce the effects of reflected waves. After the simulation outcomes in this study are validated, variations in the dynamic responses under different environmental factors are analyzed, offering a theoretical foundation for maintaining the ballastless tracks. The results show that the responses in the track subsystem will undergo significant changes as the temperature rises; a notable effect is caused by the increase in speed and fastener stiffness on the entire system; the CA mortar layer experiences the maximum stress at its edge, which makes it highly susceptible to damage in this area. The original contribution of this work is the establishment of a temperature-dependent vehicle–track–subgrade coupled model that incorporates the viscoelasticity of the CA mortar, enabling the investigation of dynamic responses in ballastless tracks. Full article

Shallow foundations supporting high-rise structures are often subjected to extreme lateral loading from wind and seismic activities. Nonlinear soil–foundation system behaviors, such as foundation uplift or bearing capacity mobilization (i.e., rocking behavior), can act as energy dissipation mechanisms, potentially reducing structural demands. However, such merits may be achieved at the expense of large residual deformations and settlements, which are influenced by various factors. One key factor which is highly influential on soil deformation mechanisms during rocking is the foundation embedment depth. This aspect of rocking foundations is investigated in this study under varying subgrade densities and initial vertical factors of safety (FSv), using the PIV technique and appropriate instrumentation. A series of reduced-scale slow cyclic tests were performed using a single-degree-of-freedom (SDOF) structure model. This study first examines the deformation mechanisms of strip foundations with depth-to-width (D/B) ratios of 0, 0.25, and 1, and then explores the effects of embedment depth on the performance of square foundations, evaluating moment capacity, settlement, recentering capability, rotational stiffness, and damping characteristics. The results demonstrate that the predominant deformation mechanism of the soil mass transitions from a wedge mechanism in surface foundations to a scoop mechanism in embedded foundations. Increasing the embedment depth enhances recentering capabilities, reduces damping, decreases settlement, increases rotational stiffness, and improves the moment capacity of the foundations. This comprehensive exploration of foundation performance and soil deformation mechanisms, considering varying embedment depths, FSv values, and soil relative densities, offers insights for optimizing the performance of rocking foundations under lateral loading conditions. Full article

Mining activities generate large volumes of waste, posing environmental and economic challenges, particularly in Brazil’s Quadrilátero Ferrífero region. This study assesses the potential reuse of iron ore waste from Samarco Mineração S.A. in road pavement layers by blending it with phyllite residual soil (PRS) and lateritic clayey soil (LCS). The addition of 50% waste to PRS led to substantial improvements, increasing the resilient modulus (RM) by up to 130% under medium stress and reducing expansibility from 6.1% to 1%, meeting Brazilian standards for sub-base applications. These enhancements make the PRS-waste blend a viable and sustainable option for reinforcing subgrade and sub-base layers. In contrast, the LCS with 20% waste showed moderate RM improvements under high-stress conditions, while higher waste contents reduced stiffness, indicating that higher dosages may adversely affect performance. This study highlights the potential of inert, non-hazardous mining waste as a safe and efficient solution for pavement applications, promoting the sustainable use of discarded materials. Full article

The resilient modulus (M_R) and the backcalculated modulus from the FWD testing (E_FWD) of the unbound layers are critical inputs in the analysis/design of pavements. Several studies have tried to develop a conversion factor between these two parameters, while the nonlinear stress dependency of unbound materials and the pavement strain response are mostly missing from the literature. This study aims to compare the laboratory-measured M_R of recycled aggregate base (RAB) materials and a virgin aggregate base using field-based E_FWD and tries to establish pavement’s responses to loading using vertical strains from both the M_R and E_FWD values of the respective materials as comparability parameters between the two. For this purpose, a control virgin aggregate (VA, limestone) and three types of RAB materials were selected to construct four test sections. The test sections were modeled in layered elastic- and finite-element-based pavement response models to calculate the vertical strains at the mid-depth of the base and top of the subgrade layers. A comparison of the lab-calculated vertical strains using M_R with actual vertical strains in the field from E_FWD showed that there was no relationship between the two stiffness parameters in all tested RABs. The vertical strains, based on the lab M_R, undermined the stiffness of the recycled aggregates in the field. In contrast, the values of E_FWD based on the vertical strains remained close to the M_R strains of limestone (VA) throughout the testing period, establishing an E_FWD vs. M_R relationship (M_R = 0.87 E_FWD). The results also show that fine RCA was a better-performing material over three years. This research not only explores how the hydration process in RABs limits the development of M_R-E_FWD correlations but also underscores the need to consider real-world conditions when assessing their performance. Full article

This paper presents an analytical study of the dynamic responses in the vehicle–pavement–foundation system, where the vehicle is simplified to a two-degree-of-freedom system, the pavement is modeled using both Euler–Bernoulli (E-B) beam and Timoshenko beam with consideration of pavement roughness, and the subgrade is simulated with a Winkler foundation model featuring cubic nonlinear stiffness. The focus is on using approximate analytical solutions of pavement response to discuss the impact of nonlinear stiffness under various parameter conditions. In previous analytical studies of vehicle–pavement–foundation systems, vehicles were typically simplified to a constant moving force, leading to the conclusion that when the applied force is small, the impact of nonlinear stiffness on the pavement’s dynamic response is minimal; whereas when the force is large, the pavement response increases with the increase in nonlinear stiffness. In this study, the force exerted by the vehicle on the pavement is harmonic, and the impact of nonlinear stiffness on the pavement response is different and much more complex. The research finds that there is a critical value for nonlinear stiffness under the given vehicle parameter conditions: when the nonlinear stiffness is less than the critical value, it has almost no effect on the pavement response; when it exceeds the critical value, the pavement’s response first decreases and then increases with the increase in nonlinear stiffness. The critical value of nonlinear stiffness is not fixed and increases as the vehicle velocity and foundation damping. Moreover, an increase in nonlinear stiffness also causes an increase in the offset between the wheel position and the position of maximum pavement deformation. Under the same parameter conditions, the offset in the E-B beam is significantly greater than that in the Timoshenko beam. Our study’s results enhance the understanding of the nonlinear dynamics within the vehicle–pavement interaction. Full article

Biopolymers are polymers of natural origin and are environmentally friendly, carbon neutral and less energy-intense additives that can be used for various geotechnical applications. Biopolymers like xanthan gum, carrageenan, chitosan, agar, gellan gum and gelatin have shown potential for improving subgrade strength, erosion resistance, and as canal liners and in slope stabilization. But minimal research has been carried out on cellulose-based biopolymers, particularly microcrystalline cellulose (MCC), for their application in geotechnical and geo-environmental engineering. In this study, the effect of MCC on select geotechnical properties of kaolin, a weak, highly compressible clay soil, like its liquid and plastic limits, compaction behavior, deformation behavior, unconfined compression strength (UCS) and aging, was investigated. MCC was used in dosages of 0.5, 1.0, 1.5 and 2% of the dry weight of the soil, and the dry mixing method was adopted for sample preparation. The results show that the liquid limit increased marginally by 11% but the plasticity index was nearly 74% higher than that of untreated kaolin. MCC rendered the treated soil stiffer, which is reflected in the deformation modulus, which increased with both dosage and age of the treated sample. The UCS of kaolin increased with dosage and curing period. The maximum UCS was observed for a dosage of 2% MCC at a 90-day curing period. The increase in stiffness and strength of the treated kaolin with aging points out that MCC can be a potential soil stabilizer. Full article

The high-speed railway subgrade compaction quality is controlled by the compaction degree (K), with the maximum dry density (ρ_dmax) serving as a crucial indicator for its calculation. The current mechanisms and methods for determining the ρ_dmax still suffer from uncertainties, inefficiencies, and lack of intelligence. These deficiencies can lead to insufficient assessments for the high-speed railway subgrade compaction quality, further impacting the operational safety of high-speed railways. In this paper, a novel method for full-section assessment of high-speed railway subgrade compaction quality based on ML-interval prediction theory is proposed. Firstly, based on indoor vibration compaction tests, a method for determining the ρ_dmax based on the dynamic stiffness K_rb turning point is proposed. Secondly, the Pso-OptimalML-Adaboost (POA) model for predicting ρ_dmax is determined based on three typical machine learning (ML) algorithms, which are back propagation neural network (BPNN), support vector regression (SVR), and random forest (RF). Thirdly, the interval prediction theory is introduced to quantify the uncertainty in ρ_dmax prediction. Finally, based on the Bootstrap-POA-ANN interval prediction model and spatial interpolation algorithms, the interval distribution of ρ_dmax across the full-section can be determined, and a model for full-section assessment of compaction quality is developed based on the compaction standard (95%). Moreover, the proposed method is applied to determine the optimal compaction thicknesses (H₀), within the station subgrade test section in the southwest region. The results indicate that: (1) The PSO-BPNN-AdaBoost model performs better in the accuracy and error metrics, which is selected as the POA model for predicting ρ_dmax. (2) The Bootstrap-POA-ANN interval prediction model for ρ_dmax can construct clear and reliable prediction intervals. (3) The model for full-section assessment of compaction quality can provide the full-section distribution interval for K. Comparing the H₀ of 50~60 cm and 60~70 cm, the compaction quality is better with the H₀ of 40~50 cm. The research findings can provide effective techniques for assessing the compaction quality of high-speed railway subgrades. Full article

In shield tunneling, the joint is one of the most vulnerable parts of the segmental lining. Opening of the joint reduces the overall stiffness of the ring, leading to structural damage and issues such as water leakage. Currently, the Winkler method is commonly used to calculate structural deformation, simplifying the interaction between segments and soil as radial and tangential Winkler springs. However, when introducing connection springs or reduction factors to simulate the joint stiffness of segments, the challenge lies in determining the reduction coefficient and the stiffness of the springs. Currently, the hyperstatic reflection method cannot simulate the discontinuity effect at the connection of the tunnel segments, while the state space method overlooks the nonlinear interaction between the tunnel and the soil. Therefore, this paper proposes a numerical simulation method considering the interaction between the tunnel and the soil, which is subjected to compression rather than tension, and the discontinuity of the joints between the segments. The model structure and external load are symmetrical, resulting in symmetrical calculation results. This method is based on the soft soil layers and shield tunnel structures of the Shanghai Metro, and the applicability of the model is verified through deformation calculations using three-dimensional laser scanning point clouds of sections from the Shanghai Metro Line 5. When the subgrade reaction coefficient is 5000 $\mathrm{k}\mathrm{N}/{\mathrm{m}}^3$, the model can effectively simulate the deformation of operational tunnels. By adjusting the bending stiffness of individual connection springs, we investigate the influence of bending stiffness reduction on the bending moment, radial displacement, and rotational displacement of the ring. The results indicate that a decrease in joint bending stiffness significantly affects the mechanical response of the ring, and the extent and degree of this influence are correlated with the joint position and the magnitude of joint bending stiffness. Full article

Sources such as wind or severe seismic activity often exert extreme lateral loading onto the shallow foundations supporting high-rise structures such as bridge piers, buildings, shear walls, and wind turbine towers. Such loading conditions may cause the foundation to exhibit nonlinear responses such as uplift and bearing capacity mobilization of the supporting soil (i.e., rocking behavior). Previous numerical and experimental studies suggest that while such inelastic behaviors may engender residual deformations in the soil–foundation system, they offer potential benefits to the overall integrity of structures through dissipating energy and reducing inertia forces transmitted to the superstructure, thereby limiting seismic demand on structural elements. This study investigates the effect of footing shape on the rocking performance of shallow foundations in different subgrade densities and initial vertical factor of safety (FSv). To this end, a series of reduced-scale slow cyclic tests under 1 g condition were conducted using a single degree of freedom (SDOF) structure model. The performance of different footing shapes was studied in terms of moment capacity, recentering ratio, rocking stiffness, damping ratio, and settlement. For three foundations with different length-to-width ratios, the results indicate that increasing the safety factor and length-to-width ratio leads to thinner, S-shaped moment–rotation curves, mainly owing to the enhanced recentering capability and the P-δ effect. Moreover, across all foundation types, the repetition of a limited loading cycles with consistent rotation amplitude does not cause stiffness degradation or moment capacity reduction. Full article

Premature failure and degradation of layers are the main problems for transportation infrastructure. Addressing these issues necessitates implementing structural health monitoring (SHM) for pavement construction layers. To this end, this research investigated the stress/strain and damage detection capabilities of a self-sensing cementitious composite developed for potential utilization in the construction of an intelligent subgrade layer. The prepared self-sensing cementitious composite consisted of 10% cement and hybrid conductive fillers, including multiwalled carbon nanotubes (MWCNTs) and graphene nanoplatelets (GNPs) in sand. Initial findings reveal that the electrical resistivity of the composite is significantly affected by the concentration of MWCNTs/GNPs, with a minimum concentration of more than 0.5% needed to achieve a responsive cementitious composite. Moreover, the piezoresistive analysis indicates that an increase in the concentration of MWCNTs/GNPs and stress levels leads to an improvement in the stress/strain-sensing performance. When the self-sensing cementitious composite is subjected to equivalent stress levels, variations in the fractional changes in resistivity (FCR) exhibit an increasing trend with decreasing resilient modulus, stemming from a decrease in stiffness due to the increased concentration of MWCNTs/GNPs. Additionally, the electrochemical impedance spectroscopy (EIS) analysis demonstrates a contraction for the Nyquist plots under compressive ramp loading prior to failure, followed by the expansion of these curves post-failure. Scanning electron microscopy (SEM) images visually showcase the bridging effects of MWCNTs and the filling effects of GNPs within the composite structure. Full article

To address the uncertainty of optimal vibratory frequency f_ov of high-speed railway graded gravel (HRGG) and achieve high-precision prediction of the f_ov, the following research was conducted. Firstly, commencing with vibratory compaction experiments and the hammering modal analysis method, the resonance frequency f₀ of HRGG fillers, varying in compactness K, was initially determined. The correlation between f₀ and f_ov was revealed through vibratory compaction experiments conducted at different vibratory frequencies. This correlation was established based on the compaction physical–mechanical properties of HRGG fillers, encompassing maximum dry density ρd_max, stiffness K_rd, and bearing capacity coefficient K₂₀. Secondly, the gray relational analysis algorithm was used to determine the key feature influencing the f_ov based on the quantified relationship between the filler feature and f_ov. Finally, the key features influencing the f_ov were used as input parameters to establish the artificial neural network prediction model (ANN-PM) for f_ov. The predictive performance of ANN-PM was evaluated from the ablation study, prediction accuracy, and prediction error. The results showed that the ρ_dmax, K_rd, and K₂₀ all obtained optimal states when f_ov was set as f₀ for different gradation HRGG fillers. Furthermore, it was found that the key features influencing the f_ov were determined to be the maximum particle diameter d_max, gradation parameters b and m, flat and elongated particles in coarse aggregate Q_e, and the Los Angeles abrasion of coarse aggregate LAA. Among them, the influence of d_max on the ANN-PM predictive performance was the most significant. On the training and testing sets, the goodness-of-fit R² of ANN-PM all exceeded 0.95, and the prediction errors were small, which indicated that the accuracy of ANN-PM predictions was relatively high. In addition, it was clear that the ANN-PM exhibited excellent robust performance. The research results provide a novel method for determining the f_ov of subgrade fillers and provide theoretical guidance for the intelligent construction of high-speed railway subgrades. Full article

Intelligent compaction (IC) is an innovative and modified technology used for quality control in subgrade digital construction. However, current intelligent compaction measurement values (ICMVs) cannot provide accurate measurement of the filling layer when the strength of the underlying layer is relatively high. Experimental field tests conducted in the cut to fill subgrade were performed to collect and analyze the variability of ICMV called the vibration modulus (E_vib). Furthermore, a new ICMV called the modulus of vibration compaction (E_vc) that could remove the interference of the underlying layer and reveal the actual compaction state of filling layer is presented based on the theoretical analysis and numerical simulation method. It was also extracted to study the variability of the filling layer’s compaction state. The results of the above research indicate the influence of the underlying layer’s stiffness on overall compaction quality is remarkable. It was found that it is more likely to achieve the variability control of the compaction state of the filling layer by a new ICMV called E_vc. The measured data, improved approaches, and associated conclusions that are presented provide valuable information for researchers and employees considering the use of IC technology. Full article