Soft soil subgrades often present significant geotechnical challenges under cyclic loading conditions associated with major infrastructure developments. Moreover, there has been a growing interest in employing various recycled tire derivatives in civil engineering projects in recent years. To address these challenges sustainably, this study investigates the performance of granular piles incorporating recycled tire chips as a partial replacement for conventional aggregates. The objective is to evaluate the cyclic behavior of these tire chip-aggregate mixtures and determining the optimum mix for enhancing soft soil performance. A series of laboratory-scale, stress-controlled cyclic loading tests were conducted on granular piles encased with combi-grid under end-bearing conditions. The granular piles were constructed using five volumetric proportions of (tire chips: aggregates) (%) of 0:100, 25:75, 50:50, 75:25, and 100:0. The tests were performed with a cyclic loading amplitude (qcy) of 85 kPa and a frequency (fcy) of 1 Hz. Key performance indicators such as normalized cyclic induced settlement (Sc/Dp), normalized excess pore water pressure in soil bed (Pexc/Su), and pile-soil stress distribution in terms of stress concentration ratio (n) were analyzed to assess the effectiveness of the different mixtures. Results indicate that the ordinary granular pile (OGP) with (25 % tire chips + 75 % aggregates) offers an optimal balance between performance and sustainability. This mixture reduced cyclic-induced settlement by 86.7 % compared to the OGP with (0 % TC + 100 % AG), with only marginal losses in performance (12.3 % increase in settlement and 2.8 % reduction in stress transfer efficiency). Additionally, the use of combi-grid encasement significantly improved the overall performance of all granular pile configurations, enhancing stress concentration and reducing both settlement and excess pore water pressure. These findings demonstrate the viability of using recycled tire chips as a sustainable alternative in granular piles, offering both environmental and engineering benefits for soft soil improvement under cyclic loading.

In geotechnical engineering, the development of efficient and accurate constitutive models for granular soils is crucial. The micromechanical models have gained much attention for their capacity to account for particle-scale interactions and fabric anisotropy, while requiring far less computational resources compared to discrete element method. Various micromechanical models have been proposed in the literature, but none of them have been conclusively shown to agree with the critical state theory given theoretical proof, despite the authors described that their models approximately reach the critical state. This paper modifies the previous CHY micromechanical model that is compatible with the critical state theory based on the assumption that the microscopic force-dilatancy relationship should align with the macroscopic stress-dilatancy relationship. Moreover, under the framework of the CHY model, the fabric anisotropy can be easily considered and the anisotropic critical state can be achieved with the introduction of the fabric evolution law. The model is calibrated using drained and undrained triaxial experiments and the results show that the model reliably replicates the mechanical behaviors of granular materials under both drained and undrained conditions. The compatibility of the model with the critical state theory is verified at both macroscopic and microscopic scales.

This study presents a novel micromorphic continuum model for sand-gravel mixtures with low gravel contents, which explicitly accounts for the influences of the particle size distribution, gravel content, and fabric anisotropy. This model is rigorously formulated based on the principle of macro-microscopic energy conservation and Hamilton's variational principle, incorporating a systematic analysis of the kinematics of coarse and fine particles as well as macro-microscopic deformation differentials. Dispersion equations for plane waves are derived to elucidate wave propagation mechanisms. The results demonstrate that the model effectively captures normal dispersion characteristics and size-dependent effects on wave propagation in these mixtures. In long-wavelength regimes, wave velocities are governed by macroscopic properties, whereas decreasing wavelengths induce interparticle scattering and multiple reflections, attenuating velocities or inhibiting waves, especially when wavelengths approach interparticle spacing. The particle size, porosity, and stiffness ratio primarily influence the macroscopic average stiffness, exhibiting consistent effects on dispersion characteristics across all wavelength domains. In contrast, the particle size ratio and gravel content simultaneously influence both macroscopic mechanical properties and microstructural organization, leading to opposing trends across different wavelength ranges. Model validation against experiments confirms its exceptional predictive ability regarding wave propagation characteristics, including relationships between lowpass threshold frequency, porosity, wave velocity, and coarse particle content. This study provides a theoretical foundation for understanding wave propagation in sand-gravel mixtures and their engineering applications.

Liquefaction resistance and post-liquefaction shear deformation are key aspects of the liquefaction behavior for granular soil. In this study, 3D discrete element method (DEM) is used to conduct undrained cyclic triaxial numerical tests on specimens with diverse initial fabrics and loading history to associate liquefaction resistance and post-liquefaction shear deformation with the fabric of granular material. The influence of several fabric features on liquefaction resistance is first analyzed, including the void ratio, particle orientation fabric anisotropy, contact normal fabric anisotropy, coordination number, and redundancy index. The results indicate that although the void ratio and anisotropy strongly influence liquefaction resistance, the initial coordination number or redundancy index can uniquely determine liquefaction resistance. Regarding post-liquefaction shear deformation, the above quantities do not dictate the shear strain induced after initial liquefaction. Instead, the mean neighboring particle distance (MNPD), a fabric measure previously introduced in 2D and extended to 3D in this study, is the governing factor for post-liquefaction shear. Most importantly, a unique relationship between the initial MNPD and ultimate saturated post-liquefaction shear strain is identified, providing a measurable state parameter for predicting the post-liquefaction shear of sand.

In practical engineering, earthquake-induced liquefaction can occur more than once in sandy soils. The existence of low-permeable soil layers, such as clay and silty layers in situ, may hinder the dissipation of excess pore pressure within sand (or reconsolidation) after the occurrence of liquefaction due to the mainshock and therefore weaken the reliquefaction resistance of sand under an aftershock. To gain more mesomechanical insights into the reduced reliquefaction resistance of the reconsolidated sand under aftershock, a series of discrete element simulations of undrained cyclic simple shear tests were carried out on granular specimens with different degrees of reconsolidation. During both the first (mainshock) and second (aftershock) cyclic shearing processes, the evolution of the load-bearing structure of the granular specimens was quantified through a contact-normal-based fabric tensor. The interplay between mesoscopic structure evolutions and external loadings can well explain the decrease in reliquefaction resistance during an aftershock.

The stress state and density of soil have been considered as the key factors to determine the liquefaction resistance. However, the results of seismic liquefaction case histories, laboratory tests and centrifuge model tests show that the fabric characteristics also influence liquefaction resistance, even more significantly than the contributions of stress state and density. In this study, anisotropic specimens with different consolidation histories were prepared using the 3D Discrete Element Method (DEM) to investigate the influence of fabric characteristics on the mechanical behavior of granular materials and the underlying mechanisms. The simulations revealed that under monotonic shear conditions, horizontally anisotropic specimens exhibited strain hardening and dilatancy characteristics, as well as higher peak strength. Under cyclic shear condition, the normalized liquefaction resistance of the specimens showed a strong linear relationship with the degree of anisotropy, independent of confining pressures and density. Microscopic results indicate that the fabric arrangement aligned with the loading direction leads to the evolution of the mechanical coordination number and average contact force in a manner favorable to resisting loads, which is the underlying mechanism influencing macroscopic mechanical properties. Additionally, the evolution patterns of contact normal magnitude and angle in anisotropic granular materials under cyclic loading conditions were also analyzed. The results of this study provided a new perspective on the macroscopic mechanical properties and the evolution of the microstructure of granular soils under anisotropic conditions.

A tensor-type capillary stress, instead of a scalar suction, has been proposed to serve as a stress-like state variable to capture the effects of capillarity in the mechanics of unsaturated granular soils. However, the influence of water content on the evolution of capillary stress in such soils remains insufficiently understood. This study performs numerical simulations of unsaturated granular soils in the pendular regime using the Discrete Element Method (DEM) involving a volume-controlled capillary bridge model. In these simulations, water content is maintained constant by redistributing the water from ruptured capillary bridges to adjacent ones. The evolution of capillary stress with varying water contents during triaxial and biaxial loading conditions is systematically examined. The DEM simulation results show that, under both loading conditions, the mean component of the capillary stress generally decreases, while its deviatoricity gradually develops. These changes are observed to become less significant as the initial degree of saturation increases. At low saturation levels, capillary bridges between non-contacting particle pairs rupture due to soil deformations, and the water from these ruptured bridges redistributes to existing contacts. This redistribution leads to an anisotropic distribution of pore water aligned with the contact network. At higher saturation levels, non-contacting capillary bridges persist due to their ability to sustain large relative displacements between particles, allowing the spatial distribution of pore fluids to remain less constrained by the solid contact network. Additionally, at higher water contents, relative sliding and particle rearrangement are the primary factors influencing the directional distribution of capillary bridges.

The macroscopic mechanical properties of granular systems largely depend on the complex mechanical responses of force chains at the mesoscopic level. This study offers an alternative to rapidly identify and predict force chain distributions under different stress states. 100 sets of gradation curves that effectively represent four typical continuous gradation distributions are constructed. Numerical specimens corresponding to these gradation curves are generated using the discrete element method (DEM), and a dataset for deep neural network training is established via biaxial compression numerical simulations. The relationship between particle distribution characteristics and force chain structure is captured by the Pix2Pix conditional generative adversarial network (cGAN). The effectiveness of the generated force chain images in reproducing both particle gradation and spatial distribution characteristics is verified through the extraction and analysis of pixel probability distributions across different color channels, along with the computation of texture feature metrics. In addition, a GoogLeNet-based prediction model is constructed to demonstrate the accuracy with which the generated force chain images characterize the macroscopic mechanical properties of granular assemblies. The results indicate that the Pix2Pix network effectively predicts and identifies force chain distributions at peak stress for different gradation

The study of macroscopic discrete granular materials holds significance in hydraulic engineering, geotechnical engineering, as well as road and bridge engineering. Its foundational scientific exploration bears profound theoretical implications and is of pivotal practical value to engineering endeavors. Within the realm of engineering construction, issues such as dam breakages, earth-rock dam damage, and geological disasters involving loose particles pose substantial threats to the safety of both national livelihoods and property. Thus, delving into the examination of the structural stability of granular materials at the mesoscopic scale becomes an imperative pursuit. In this study, the topological structure of granular materials is identified and segmented based on image processing techniques, and the relationship between the compressive capacity of polygonal structures and the number of polygonal sides is studied. The redundancy function is defined to evaluate the structural stability of granular materials. In addition, the definition of structure tensor is introduced, and redundancy and structure tensor are applied to the study of biaxial compression of shale materials. The research results contribute to improving engineering safety and have guiding merits for the research and application of granular materials. Future work could focus on extending these methods to other types of granular materials and exploring their behavior under different loading conditions. (c) 2025 Published by Elsevier B.V. on behalf of Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences.

The breakage phenomenon has gained attention from geotechnical and mining engineers primarily due to its pivotal influence on the mechanical response of granular soils. Numerous researchers performed laboratory tests on crushable soils and incorporated the corresponding effects into numerical simulations. A systematic review of various studies is crucial for gaining insight into the current state of knowledge and for illuminating the required developments for upcoming research projects. The current state-of-the-art study summarizes both experimental evidence and numerical approaches, particularly focusing on discrete element simulations and constitutive models used to describe the behavior of crushable soils. The review begins by exploring particle breakage quantification, delving into experimental evidence to elucidate its influence on the mechanical behavior of granular soils, and examining the factors that affect the breakage phenomenon. In this context, the accuracy of various indices in estimating the extent of breakage has been assessed through ten series of experiments conducted on different crushable soils. Furthermore, alternative breakage indices are suggested for constitutive models to track the evolution of particle crushing under continuous shearing. Regarding numerical modeling, the review covers different approaches using the discrete element method (DEM) for simulating the behavior of crushable particulate media, discussing the advantages and disadvantages of each approach. Additionally, different families of constitutive models, including elastoplasticity, hypoplasticity, and thermodynamically based approaches, are analyzed. The performance of one model from each group is evaluated in simulating the response of Tacheng rockfill material under drained triaxial tests. Finally, new insights into the development of constitutive models and areas requiring further investigation utilizing DEM have been highlighted.