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.

Seismic risk assessment of code-noncompliant reinforced concrete (RC) frames faces significant challenges due to structural heterogeneity and the complex interplay of site-specific hazard conditions. This study aims to introduce a novel framework that integrates three key concepts specifically targeting these challenges. Central to the methodology are fragility fuses, which employ a triplet of curves-lower bound, median, and upper bound-to rigorously quantify within-class variability in seismic performance, offering a more nuanced representation of code-noncompliant building behavior compared to conventional single-curve approaches. Complementing this, spectrum-consistent transformations dynamically adjust fragility curves to account for regional spectral shapes and soil categories, ensuring site-specific accuracy by reconciling hazard intensity with local geotechnical conditions. Further enhancing precision, the framework adopts a nonlinear hazard model that captures the curvature of hazard curves in log-log space, overcoming the oversimplifications of linear approximations and significantly improving risk estimates for rare, high-intensity events. Applied to four RC frame typologies (2-5 stories) with diverse geometries and material properties, the framework demonstrates a 15-40 % reduction in risk estimation errors through nonlinear hazard modeling, while spectrum-consistent adjustments show up to 30 % variability in exceedance probabilities across soil classes. Fragility fuses further highlight the impact of structural heterogeneity, with older, non-ductile frames exhibiting 25 % wider confidence intervals in performance. Finally, risk maps are presented for the four frame typologies, making use of non-linear hazard curves and spectrumconsistent fragility fuses accounting for both local effects and within-typology variability.

Microbial Induced Calcium Carbonate Precipitation (MICP), recognized as a low-carbon and environmentally sustainable consolidation technique, faces challenges related to inhomogeneous consolidation. To mitigate this issue, this study introduces activated carbon into uranium tailings. The porous structure and adsorption capacity of activated carbon enhance bacterial retention time, increase the solidification rate, and promote the growth and distribution of calcium carbonate, resulting in more uniform consolidation and improved mechanical properties of the tailings. Additionally, a novel independently developed grouting method significantly enhances the mechanical strength of the tailing sand samples. To perform a micro-scale analysis of the samples, distinct activated carbon-tailings DEM models are constructed based on varying activated carbon dosages. Physical experiments and parameter calibration are employed to investigate the micro-mechanical properties, such as velocity field and force chain distribution. Experimental and simulation results demonstrate that incorporating activated carbon increases the calcium carbonate production during the MICP process. As the activated carbon content increases, the peak stress of the tailings initially rises and then declines, reaching its maximum at 1.5 % activated carbon content. At 100 kPa confining pressure, the peak stress is 2976.91 kPa, 1.23-1.59 times that of samples without activated carbon and 6.08-7.86 times that of unconsolidated samples. Micro-scale motion analysis reveals that particle movement is predominantly axial at the ends and radial near the central axis. The initial direction of the primary force chains aligns with the loading direction. Following failure, some primary force chains dissipate, while new chains form, predominantly along the axial direction and secondarily in the horizontal direction. Compared with samples without activated carbon, those containing activated carbon exhibit more uniform force chain distribution, higher stress levels, and greater peak stress. This study offers a novel approach to enhance the stabilization and solidification efficiency of MICP and establishes a DEM model that provides valuable insights into the structural deformation and micro-mechanical characteristics of MICPcemented materials.

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

This study evaluates dykes stability of bauxite residue storage facility using limit equilibrium (LEM) and finite element methods (FEM), considering diverse construction phases. In LEM, steady state seepage is simulated using piezometric line while factor of safety (FOS) is determined by Morgenstern-Price method using SLOPE/W. In FEM, actual loading rates and time dependent seepage is modelled by coupled stress-pore water pressure analysis in SIGMA/W and dyke stability is assessed by stress analysis in SLOPE/W, referencing SIGMA/W analysis as a baseline model. Both the analysis incorporated suction and volumetric water content functions to determine FOS. FEM predicted pore pressures are validated against in-situ piezometer data. The results highlight that coupled hydro-mechanical analysis offers accurate stability assessment by integrating stress-strain behaviour, pore pressure changes, seepage paths, and dyke displacements with time. It is found that inclusion of unsaturated parameters in Mohr-Coulomb model improved the reliability in FOS predictions.

In this study, we present an on-chip analytical method using a microfluidic device to characterize the mechanical properties in growing roots. Roots are essential organs for plants and grow under heterogeneous conditions in soil. Especially, the mechanical impedance in soil significantly affects root growth. Understanding the mechanical properties of roots and the physical interactions between roots and soil is important in plant science and agriculture. However, an effective method for directly evaluating the mechanical properties of growing roots has not been established. To overcome this technical issue, we developed a polydimethylsiloxane (PDMS) microfluidic device integrated with a cantilevered sensing pillar for measuring the protrusive force generated by the growing roots. Using the developed device, we analyzed the mechanical properties of the roots in a model plant, Arabidopsis thaliana. The root growth behavior and the mechanical interaction with the sensing pillar were recorded using a time-lapse microscopy system. We successfully quantified the mechanical properties of growing roots including the protrusive force and apparent Young's modulus based on a simple physical model considering the root morphology. (c) 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Offshore structures typically experience multiple storms during their service life. The soil around the foundations of offshore structures is subjected to cyclic loading during storm and reconsolidates between storms. Therefore, it is essential to understand the fundamental soil behaviour under episodic cyclic loading and reconsolidation to evaluate the long-term serviceability of offshore foundations. This paper presents experimental results of a comprehensive suite of cyclic DSS tests on a normally consolidated silty clay. The tests explore the soil response under different cyclic loading patterns (e.g., one-way or two-way), different cyclic amplitudes and number of cycles. A theoretical model, which combines the conventional cyclic contour diagram approach and principles of the critical state soil mechanics, is proposed and validated for predicting the cyclic soil response during undrained cyclic loading and hardening after reconsolidation. The model proposed in this paper paves a critical step for developing long-term soil-structure interaction models that are fundamentally linked to soil element level responses.

The soil moisture content (SMC) of moist clay directly affects the traction performance of off-road tire. This study set up a high-fidelity interaction model between off-road tire and moist clay with various moisture content, developed by coupling the finite element method (FEM) and smoothed particle hydrodynamics (SPH) algorithm. The interaction behavior between pneumatic tire and moist clay is studied. Firstly, a finite element model of tire which can characterize the complex structure and nonlinear mechanical properties is established. The Drucker-Prager (D-P) constitutive model parameters of clay with various moisture levels are calibrated by soil mechanical test. The moist clay with various moisture content is modeled through the SPH algorithm. The hybrid FEM-SPH interaction model is used to define the tire-moist clay interaction. Moreover, a traction performance test device suitable for tire-moist clay is developed to verify the accuracy of the interaction model. The influence of soil moisture content and tire operating conditions include vertical load and inflation pressure on the longitudinal traction coefficient, rolling resistance coefficient and instantaneous sinkage of tire center are quantitatively analyzed. The purpose of this study is to provide accurate tire force information under moist clay for unmanned ground vehicle (UGV), which can improve the problem of wheel instantaneous sinkage of tire center and slip under moist clay, and effectively reduce the yaw phenomenon in the path tracking process.

Tree architecture is an important component of forest community dynamics - taller trees with larger crowns often outcompete their neighbors, but they are generally at higher risk of wind-induced damage. Yet, we know little about wind impacts on tree architecture in natural forest settings, especially in complex tropical forests. Here, we use airborne light detection and ranging (LiDAR) and 30 yr of forest inventory data in Puerto Rico to ask whether and how chronic winds alter tree architecture. We randomly sampled 124 canopy individuals of four dominant tree species (n = 22-39). For each individual, we measured slenderness (height/stem diameter) and crown area (m2) and evaluated whether exposure to chronic winds impacted architecture after accounting for topography (curvature, elevation, slope, and soil wetness) and neighborhood variables (crowding and previous hurricane damage). We then estimated the mechanical wind vulnerability of trees. Three of four species grew significantly shorter (2-4 m) and had smaller crown areas in sites exposed to chronic winds. A short-lived pioneer species, by contrast, showed no evidence of wind-induced changes. We found that three species' architectural acclimation to chronic winds resulted in reduced vulnerability. Our findings demonstrate that exposure to chronic, nonstorm winds can lead to architectural changes in tropical trees, reducing height and crown areas. La arquitectura de los & aacute;rboles es un componente importante de la din & aacute;mica de la comunidad forestal: los & aacute;rboles m & aacute;s altos con copas m & aacute;s grandes suelen sobrepasar a sus vecinos, pero por lo general corren m & aacute;s riesgo de sufrir da & ntilde;os inducidos por el viento. Sin embargo, es poco lo que se sabe sobre el impacto del viento en la arquitectura de los & aacute;rboles en entornos forestales naturales, sobre todo en bosques tropicales complejos. En este caso, utilizamos LiDAR y 30 a & ntilde;os de datos de campo en Puerto Rico para preguntarnos si los vientos cr & oacute;nicos alteran la arquitectura de los & aacute;rboles. Se tom & oacute; una muestra aleatoria de 124 individuos del dosel de cuatro especies arb & oacute;reas dominantes (n = 22-39). De cada individuo, medimos la esbeltez (altura/di & aacute;metro) y el & aacute;rea de la copa (m2) y evaluamos si la exposici & oacute;n a vientos cr & oacute;nicos influ & iacute;a en la arquitectura teniendo en cuenta la topograf & iacute;a (curvatura, elevaci & oacute;n, pendiente, humedad del suelo) y las variables del vecindario (aglomeraci & oacute;n y da & ntilde;os previos por huracanes). Luego, estimamos la vulnerabilidad mec & aacute;nica de los & aacute;rboles al viento. En los lugares expuestos a vientos cr & oacute;nicos, tres de las cuatro especies crecieron mucho menos (2-4 m) y tuvieron & aacute;reas de copa m & aacute;s peque & ntilde;as. Cecropia schreberiana, en cambio, no mostr & oacute; indicios de cambios inducidos por el viento. La aclimataci & oacute;n arquitect & oacute;nica de tres especies a los vientos cr & oacute;nicos llevaba a una reducci & oacute;n de la vulnerabilidad. Nuestros hallazgos demuestran que la exposici & oacute;n a vientos cr & oacute;nicos puede provocar cambios arquitect & oacute;nicos en los & aacute;rboles tropicales, reduciendo su altura y la superficie de sus copas.