Silt is widely utilized as a filling material in transportation construction, However, it frequently suffers from problems, such as excess pore water pressure buildup, settlement, and mud pumping. Wicking geotextiles have emerged as a sustainable solution by improving both drainage and reinforcement capacities, yet their optimal design parameters remain unclear. To address this gap, a series of tests were performed to investigate the effects of compaction degree, reinforcement configuration (number, spacing, position), and specimen geometry on the mechanical and consolidation of silt reinforced with wicking geotextiles. The results reveal that the failure mechanism of reinforced silt progresses through four distinct stages, which the wicking geotextile improved interparticle contact, delays crack initiation, and improves post-peak stability. Wicking geotextiles significantly improve strength, particularly at lower compaction degrees, by restraining crack propagation and promoting uniform stress distribution. Optimal mechanical performance was achieved with three reinforcement layers and compaction degrees of 93-95 %. Mid-depth placement of a single layer or uniform spacing of multiple layers produced the best outcomes. Although non-uniform spacing provided advantages at early deformation stages, it ultimately induced premature failure, whereas uniform spacing (= 1.27 exhibited improved ductility, while larger specimens with multiple layers demonstrated improved post-peak stability. Wicking geotextiles accelerated drainage and void ratio reduction but concurrently decreased the compression modulus. These findings contribute to a more comprehensive understanding of the mechanical and hydraulic responses of wicking geotextile-reinforced silt and provide practical insights for the design and optimization of reinforced subgrades.

This study investigates the strain-rate-dependent mechanical properties of unsaturated red clay under varying temperatures and matric suction conditions through triaxial shear tests on red clay fill materials from the Sichuan-Tibet Railway region. The tests were conducted with multiple shear strain rates, complemented by advanced microstructural analysis techniques such as mercury intrusion porosimetry (MIP), nuclear magnetic resonance (NMR), and scanning electron microscopy (SEM), to examine the evolution of pore structure. The results indicate that high matric suction significantly reduces the rate-dependency of strength in red clay fill materials, whereas temperature has a relatively smaller effect. As matric suction increases, the strain-rate parameter decreases across different temperatures, with a diminishing rate effect observed at higher suction levels. Compared to temperature, strain rate has a more pronounced influence on failure time. An increase in strain rate leads to a significant reduction in failure time. At low strain rates, failure time exhibits substantial variability, while at high strain rates, the effects of temperature and matric suction on failure time become less significant. Under high-temperature conditions, the strength of red clay is enhanced, and failure time is delayed. These findings provide critical theoretical support for controlling settlement deformation and predicting failure times of subgrade fill materials under complex climatic conditions, offering valuable insights for engineering applications.

Soil desiccation cracks and crack networks significantly influence the mechanical properties of soils. Accurate modeling and prediction of crack development are essential for both laboratory research and practical applications in geotechnical engineering and environmental science. In this study, a Desiccation Crack Simulation Program (DCSP) was developed on the MATLAB platform to simulate the evolution of soil desiccation cracks. Based on comprehensive statistical analyses of crack network images from previous studies and detailed observations of crack propagation, we propose a stochastic crack network generation model informed by geometric parameters and crack development processes. The model encompasses five key steps: (1) selection of crack initiation points, (2) crack propagation and intersection, (3) termination of crack growth, (4) secondary crack generation, and (5) final network formation. Key parameters include crack step size, randomized propagation direction, number of initial development points, and crack attraction distance. The DCSP enables both the rapid generation of random crack networks and the prediction of partially developed networks. The program was validated using two soil types, Xiashu soil and Pukou soil, demonstrating its effectiveness in simulating crack evolution. Prediction accuracy improves as crack network develops, highlighting the model's potential for predicting soil desiccation crack patterns.

Soil-rock mixtures (SRM) from mine overburden form heterogeneous dump slopes, whose stability relies on their shear strength properties. This study investigates the shear strength properties and deformation characteristics of SRM in both in-situ and laboratory conditions. Total twelve in-situ tests were conducted on SRM samples with a newly developed large scale direct shear apparatus (60 cm x 60 cm x 30 cm). The in-situ moist density and moisture content of SRM are determined. Particle size distribution is performed to characterize the SRM in laboratory. The bottom bench has the highest cohesion (64 kPa) due to high compaction over time while the other benches have consistent cohesion values (25 kPa to33 kPa). The laboratory estimated cohesion values are high compared to in-situ condition. It is further observed that for in-situ samples, the moist density notably affects the cohesion of SRM, with cohesion decreasing by 3 to 5 % for every 1 % increase in moist density. At in-situ condition, internal friction angles are found to be 1.5 to 1.7 times compared to laboratory values which is due to the presence of the bigger sized particles in the SRM. The outcomes of the research are very informative and useful for geotechnical engineers for slope designing and numerical modeling purpose.

Copper (Cu) is a toxic metal that accumulates in soil due to agricultural and industrial activities, potentially impacting plant growth and productivity. Our study examined the phytotoxic effects of Cu on Vigna radiata L. by exposing plants to a series of Cu concentrations (1, 4 and 7 mM) under controlled conditions. Growth parameters, photosynthetic performance, biochemical traits, and oxidative stress indicators were analyzed in 21-day-old Cu-treated plants and compared with control plants. The results demonstrated a concentration-dependent decline in shoot and root biomass, relative water content (RWC), pigment content, photosynthetic efficiency, carbohydrates, and lipid content. Conversely, oxidative stress markers such as malondialdehyde (MDA), electrolyte leakage, superoxide dismutase (SOD) and ascorbate peroxidase (APX) activity and proline accumulation increased significantly with increasing Cu concentrations, indicating cellular damage. Notably, protein levels increased with increased Cu concentrations, which may contribute to their tolerance to metal stress, however, it was insufficient to mitigate stress. Further research is needed to validate these findings and explore the mechanisms underlying copper stress tolerance.

In transparent soil model experiments, fused quartz stands out as the most promising substitute for natural sand. However, there is still a lack of a comprehensive evaluation system to assess the similarity of its mechanical properties to natural sand. Therefore, a similarity evaluation method based on constitutive model simulation is proposed. First, due to the high friction angle characteristic of fused quartz in transparent soil model tests, multiple oedometer compression and shear box tests were conducted on various gradations of fused quartz. Subsequently, a hypoplastic sand model, which is abundant in natural sand data, stable, and has a straightforward calibration process, was then selected for parameter calibration of fused quartz. Finally, the substitutability of fused quartz for natural sand was evaluated by comparing constitutive parameters and shear box simulation, considering factors such as initial void ratio and confining pressure. The results indicate that the hypoplastic sand model accurately captures the shear behavior of fused quartz. Particles with grain sizes ranging from 0.5 to 2 mm weaken the strength of well-graded fused quartz. The findings also suggest that well-graded fused quartz maintains consistent shear behavior with various natural sands. By contrast, the applicability of single-sized fused quartz is limited.

This study focuses on the challenge of identifying the most destructive earthquakes to minimize earthquakeinduced damage, with particular attention to the seismic behavior of special reinforced concrete moment frames (RCMFs) and the influence of soil-structure interaction (SSI). To achieve this objective, a numerical model was developed in OpenSEES platform to analyze RCMFs with heights of 2, 6 and 10 stories on four different soil types (Site Classes B to E). Also, to consider the effect of SSI, the study utilized a Beam on Nonlinear Winkler Foundation approach (BNWF), incorporating springs and dashpots. An extensive set of earthquake records, including 274 horizontal ground motion records, categorized based on shear wave velocity for each site class, was employed. Incremental dynamic analysis (IDA) was used to identify the most destructive earthquake scenarios, with maximum inter-story drift serving as the damage measure (DM) for the four seismic performance levels proposed by HAZUS and peak ground acceleration (PGA) as the intensity measure (IM). After performing correlation analysis between the 57 ground motion parameters (GMPs) and the maximum inter-story drift, followed by an inter-correlation analysis among the candidate GMPs, it was ultimately determined that the GMPs: Vmax/Amax, Tm and F5PSD, accurately represent the potential for seismic damage. IDA results highlighted the significant influence of SSI on the seismic performance of structure, especially in taller buildings constructed on softer soil types. Finally, two equations were developed based on the identified GMPs to determine and rank destructive earthquakes for both SSI and no-SSI (NSSI) conditions.

Prepulse combined hydraulic fracturing facilitates the development of fracture networks by integrating prepulse hydraulic loading with conventional hydraulic fracturing. The formation mechanisms of fracture networks between hydraulic and pre-existing fractures under different prepulse loading parameters remain unclear. This research investigates the impact of prepulse loading parameters, including the prepulse loading number ratio (C), prepulse loading stress ratio (S), and prepulse loading frequency (f), on the formation of fracture networks between hydraulic and pre-existing fractures, using both experimental and numerical methods. The results suggest that low prepulse loading stress ratios and high prepulse loading number ratios are advantageous loading modes. Multiple hydraulic fractures are generated in the specimen under the advantageous loading modes, facilitating the development of a complex fracture network. Fatigue damage occurs in the specimen at the prepulse loading stage. The high water pressure at the secondary conventional hydraulic fracturing promotes the growth of hydraulic fractures along the damage zones. This allows the hydraulic fractures to propagate deeply and interact with pre-existing fractures. Under advantageous loading conditions, multiple hydraulic fractures can extend to pre-existing fractures, and these hydraulic fractures penetrate or propagate along pre-existing fractures. Especially when the approach angle is large, the damage range in the specimen during the prepulse loading stage increases, resulting in the formation of more hydraulic fractures. (c) 2025 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).

The cohesion and internal friction angle of loess are important macro-mechanical parameters for evaluating the safety and stability of engineering construction. Traditional laboratory measurement methods are time-consuming and difficult to conduct on-site. This study aims to compare the effectiveness of five Machine Learning (ML) methods, namely Random Forest (RF), Support Vector Machine (SVM), Back Propagation Neural Network (BPNN), BPNN optimized by Particle Swarm Optimization (PSO-BPNN) and BPNN optimized by Genetic Algorithm (GA-BPNN), in predicting the macro-mechanical properties of loess. To this end, the study collected data from 89 undisturbed loess samples and 229 remolded loess samples to construct training and testing datasets, and used three correlation analysis methods to analyze the influence of physical parameters on mechanical properties. The study found that the water content has the most significant impact on the mechanical properties of loess. In terms of prediction ability, SVM performs the best among the ML methods used, and the determination coefficient for cohesion of undisturbed loess reaches 0.857. Although the training data is limited, the prediction performance of BPNN is significantly improved after being optimized by PSO or GA. The research results show that ML provides an effective way to study the complex mechanical behavior of loess.

During an earthquake, the strong interaction between the surrounding rock and lining structure causes the lining susceptible to extrusion or shear damage. To evaluate the damping effect of the shock-absorbing layer on seismic loads and mitigate the deformation-induced damage of tunnel structures in loess regions, the dynamic mechanical properties of loess seismic-isolated tunnels subjected to P-wave seismic loading were investigated. In this work, the dynamic behavior of loess seismic-isolated tunnel under seismic loads was converted into a static problem. Analytical methods were employed to derive solution for internal forces within the lining structure using a mechanical analysis model. Additionally, the impact of loess hardness and seismic intensity on the performance of the shock-absorbing layer were analyzed based on the analytical solutions. Numerical methods were then applied to examine the influence of shock-absorbing layer parameters on the mechanical properties of loess seismic-isolated tunnel subjected to P-wave loads. The results indicate that the analytical solutions, simplified numerical solutions, and theoretical results in the literature exhibit strong numerical consistency and similar trends. The analytical results demonstrate that the internal forces in the lining structure increase linearly with seismic intensity, while the effect of loess hardness on the bending moment is more complex. As the loess hardness decreases, the damping effect of the shock-absorbing layer on the internal forces gradually diminishes. Numerical analysis further reveals that reducing the elastic modulus and increasing the thickness of shock-absorbing layer significantly enhance its damping effect on the axial force, although the bending moment slightly increases. Additionally, the shock-absorbing layer effectively reduces the peak stress and strain responses in lining structure, but the peak stress at the hance position increases, with this increase becoming more pronounced as the elastic modulus of the damping material decreases. Moreover, the shock-absorbing layer significantly reduces the peak acceleration response of lining structure but also leads to increased deformation, which progressively intensifies with the thickness of shock-absorbing layer. These findings provide valuable theoretical insights for the seismic design of tunnel structures in loess regions, emphasizing the importance of balancing damping efficiency and deformation control in the lining structure.