This paper presents a method for analyzing slope stability in anisotropic and heterogeneous clay using a strength reduction finite element method (SRFEM) integrated with the level set method (LSM). Anisotropy refers to the inherent anisotropy in the clay's strength, while heterogeneity describes the spatial variability in strength parameters. The static LSM uses a zero level set function to model heterogeneous clay slopes. The method is validated through undrained slope stability analyses on different types of anisotropic clay and heterogeneous fields, showing its effectiveness in modeling anisotropic shear strength and capturing the characteristics of heterogeneous regions. The results indicate that the proposed method accurately predicts factors of safety and slip surfaces across various soil conditions, accounting for both anisotropic and heterogeneous characteristics.

Soil heterogeneity, due to variations in the subsurface stratigraphy or properties within a layer, can trigger or amplify differential settlements that affect buildings and infrastructure and can thus lead to (increase in) damage. The state-of-the-art mainly focuses on the effect of heterogeneous properties within a layer on engineering problems. From this, it is known that the variation in properties can increase the vulnerability of a structure. However, nearly always variations in the soil lithological conditions are disregarded, while they can influence subsidence potentially even more. Lithological variations are relevant both at the scale of individual buildings as well as different scales (city, regional, country), for which often detailed soil information is not available. Thus, for a better prediction of potential building damage related to subsidence, knowledge about the scale and influence of lithological variations is needed. This paper describes an approach to quantify and investigate the influence of lithological heterogeneity at the scale of a single building. Moreover, this exploratory study evaluates the influence of lithological heterogeneity on the spatial variability of settlements, intending to upscale the approach to regional application. Two independent datasets at high resolution (site-specific) and low resolution (national level) are used to retrieve the stratigraphic conditions for the area selected for the analyses. One-, Two- and Three-dimensional numerical models, based on the collected information are used to simulate the consolidation process and settlement due to a uniform load imposed on the surface level of the study area. Additional analyses investigate the influence of loading conditions and groundwater table. The parameter correlation length is used to quantify the spatial variability of the soil layer thickness and then of the computed settlements. The analyses reveal that the spatial variability of the soil strata thickness matches that of the computed settlements, ranging from 2 to 10 meters. In other words, the lithological variability of the soil leads to differential settlements occurring at the scale of man-made structures such as houses, roads, and embankments. Thus, the results encourage including the contribution of lithological heterogeneity in models and predictions of differential settlement at the scale of individual structures. Moreover, the statistical properties, in terms of mean, spread and distribution shape, of the settlement computed through in-situ specific models, match with those derived at the national scale. These results are expected to support the identification of areas potentially influenced by lithological soil heterogeneity, thus showing potential for upscaling to regional or national levels.

Particle crushing usually occurs in granular materials and affects their structural and mechanical properties. To investigate the mechanical behavior and crushing characteristics of heterogeneous particles, this study conducts both laboratory tests and numerical simulations for a macro-microscopic analysis of the heterogeneous particles. The laboratory tests results demonstrate that the single particle crushing strength and crushing pattern have obvious size effect. In numerical simulations, the heterogeneous crushable particle model was constructed by using Gaussian distribution and Voronoi tessellation, and the degree of heterogeneity (d) is defined as the ratio of the standard deviation to the expected value. The numerical findings demonstrate that the size effect of crushing strength is mainly attributed to heterogeneity. The degree of heterogeneity weakens the particle crushing strength. As the d value increases, the force-displacement curve of the particle exhibits stronger nonlinear characteristics, and the macroscopic failure pattern changes from brittle failure to ductile failure. Additionally, with the increase in d, the deformation coordination between child particles decreases, which leads to enhanced local stress concentration, causing a reduction in the crack initiation stress. This change causes the crack propagation mode to evolve from a sharp angle to a blunt angle, and ultimately determines the crushing strength and crushing pattern of particles. (c) 2025 Published by Elsevier B.V. on behalf of The Society of Powder Technology Japan. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Concrete gravity dams, forming a quarter of the ICOLD database with over 61,000 dams, often surpass 50 years of service, necessitating increased maintenance and safety scrutiny. Given the aging and advancing seismic safety methods, reevaluating their seismic resilience, considering material degradation and concrete heterogeneity, is imperative. This study conducts a comprehensive seismic fragility assessment of the Pine Flat Dam at lifecycle stages of 1, 50 and 100 years, accounting for material degradation due to aging and uncertainties from concrete heterogeneity. It develops a 2D dam-foundation-reservoir model with fluid-structure-soil interaction and material nonlinearity using the concrete damage plasticity model. The assessment includes 55 ground motions, selected via the conditional mean spectrum method, representing five return periods from 475 to 10,000 years. Fragility curves are developed by fitting a lognormal distribution to failure probabilities at varying intensities. These curves are compared using damage indices like crest displacement and stress at the dam's neck and heel. Aging increases failure probability, correlating with age and return period, as shown by the leftward shift of fragility curves, while concrete heterogeneity adds uncertainty. The results emphasize the critical need for ongoing seismic fragility reassessments, accounting for aging, environmental exposure, and seismic demands on dam safety.

With growing recognition of the ecological importance of grasslands, efforts to prevent their degradation, enhance the soil quality, and maintain ecological balance have become central to temperate grassland management. However, many temperate grasslands experience varying intensities and modes of grazing. Effective grazing management is crucial to avoid damage and promote the sustainable development of temperate grasslands. This study adopts a variety of research methods. Firstly, through the collection and sorting of data, it is clear that the research content mainly focuses on more than 70 response variables. Secondly, the comprehensive effects of different grazing intensity, grazing mode, and grazing history on these response variables were studied, and then detailed studies were conducted to analyze the effects of different grazing intensity and grazing mode under different temperate grassland types on these response variables. According to the analysis of the comprehensive effects and effects of different temperate grassland types, significant heterogeneity was found in 13 response variables (H, R, E, Height, Coverage, Density, TB, PB-PF, SWC, TK, OK, and N(20-60 cm)). Finally, in order to study the source of heterogeneity of these 13 response variables, subgroup analysis was carried out to analyze whether it was caused by environmental factors (MAP, MAT, MAP xMAT), and then publication bias test and Egger's test were carried out to prove the reliability of the research results. The results showed that the heterogeneity of 12 response variables (R, H, E, height, coverage, density, TB, PB, PF, SWC, OK and N (20-60 cm)) was attributed to environmental factors. However, due to insufficient data after subgroup analysis, the heterogeneity of TK cannot be determined.

A sustainable use of croplands should utilize beneficial services provided by their resident soil microbiome. To identify potentially adverse environmental effects on soil microbiomes in the future, a better understanding of their natural variability is fundamental. Here, we characterized the abundance and diversity of soil microbial communities over 2 years at two-week intervals on three neighboring fields at an operational farm in Northern Germany. Field soils differed in texture (clay, loam) and tillage (soil conservation vs. conventional). PCRamplicon analyses of soil DNA revealed distinct temporal variations of bacteria, archaea, fungi, and protists (Cercozoa and Endomyxa). Annual differences and seasonal effects on all microbial groups were detected. In addition to soil pH, prokaryotic communities varied with total soil C and N, but fungi with temperature and precipitation. The C/N ratio had contrasting effects on prokaryotic phyla and protistan classes, but all fungal phyla responded positively. Irrespective of the sampling date, prokaryotic and fungal but not protistan community compositions from the three soils were distinct. Compositional turnover rates were higher for fungi and protists than for prokaryotes and, for all, lower in clay. Conventional tillage had the strongest effect on protist diversity. In co-occurrence networks, most nodes were provided by prokaryotes, but highly connected nodes by predatory protists in the first, and by saprotrophic fungi in the second year. The temporal variation established here can provide insights of what is natural and thus below the limits of concern in detecting adverse effects on the soil microbiome.

Landslides, a prevalent natural disaster, wreak havoc on both human lives and vital infrastructure, making them a significant global concern. Their devastating impact is immeasurable, necessitating proactive measures to minimize their occurrence. The ability to accurately forecast the severity of a landslide, including its potential fatality rate and the scale of destruction it may cause, holds tremendous potential for prevention and mitigation to reduce the risk and the damage caused by a landslide to infrastructure and life. In this study, the spatial variability in severity of landslides (in terms of mortality rates) and its dependence on various meteorological, geographical and soil composition has been attempted to be established. To do this, Ordinary Least Squares (global) and various Geographically Weighted (local) models have been employed to observe the varying relation between mortality rates and its various causative factors. Existence of geographical heterogeneity in the relationships is also investigated. The spatial pattern of landslide mortality and its associations with various causative variables in the South Asian Region are investigated and analysed. Through this, insights into targeting of prevention and mitigation measures for landslides based on a given location can be obtained by studying the various forms of heterogeneous spatial associations observed. The outcomes highlight that the local models in the form of Gaussian GWR and Poisson GWR outperform their global counterparts by a huge margin with better R2 and Adj R2 values. In comparison with Poisson GWR and Gaussian GWR, it is seen that Poisson GWR outperforms Gaussian GWR in terms of Mean Absolute Error, Mean Squared Error and Corrected Akaike Information Criterion. Furthermore, several intriguing local relationships patterns are also noted.

The heterogeneity of a dense sand specimen in triaxial compression has been revealed in many different studies using tools such as x-ray computed tomography. It has been shown that a significant variation of the soil variables already exists at the initial state and that, if shear banding occurs, all variables localise inside the specimen. To resolve the discrepancy between such observations and the assumption of a homogeneous specimen, which is commonly made in the interpretation of triaxial tests, one could either extract the local soil behaviour rather than the global one or use the initial distribution of the variables as the initial state of a boundary value problem. For both purposes, the size of a representative elementary volume (REV) is determined regarding the void ratio, two contact fabric descriptors, the volumetric and deviatoric strain. The size of the REV is either determined for individual loading states or by considering the evolution of deforming elements throughout the triaxial test. At the final loading state, a REV size of 3.6 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_{50}$$\end{document} is identified, which is also the size where the statistical distribution of the variables becomes independent of the element size. The same size is determined for the deforming elements and is therefore used to extract the soil behaviour from the evolving shear band. The local soil behaviour is found to be much simpler than the global one, which suggests that the complexity of the global behaviour mainly results from homogenising the highly different zones inside the specimen.Graphical AbstractExtraction of the soil behaviour inside the evolving shear band with the help of deforming representativeelementary volumes. The volumetric behaviour is represented by the evolution of the void ratio and the evolution ofthe contact fabric anisotropy is closely connected to the stress-strain behaviour. The soil behaviour on the REVscale might form the basis for an alternative approach for the development and calibration of constitutive modelsconsidering the heterogeneity of a soil specimen.

Remediating soils contaminated by per- and polyfluoroalkyl substances (PFAS) is a challenging task due to the unique properties of these compounds, such as variable solubility and resistance to degradation. In-situ soil flushing with solvents has been considered as a remediation technique for PFAS-contaminated soils. The use of non-Newtonian fluids, displaying variable viscosity depending on the applied shear rate, can offer certain advantages in improving the efficiency of the process, particularly in heterogeneous porous media. In this work, the efficacy of ethanol/xanthan mixture (XE) in the recovery of a mixture of perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonate (PFHxS), and perfluorobutane sulfonate (PFBS) from soil has been tested at lab-scale. XE's non-Newtonian behavior was examined through rheological measurements, confirming that ethanol did not affect xanthan gum's (XG) shear-thinning behavior. The recovery of PFAS in batch-desorption exceeded 95 % in ethanol, and 99 % in XE, except for PFBS which reached 94 %. 1D-column experiments revealed overshoots in PFAS breakthrough curves during ethanol and XE injection, due to oversolubilization. XE, (XG 0.05 % w/w) could recover 99 % PFOA, 98 % PFBS, 97 % PFHxS, and 92 % PFOS. Numerical modeling successfully reproduces breakthrough curves for PFOA, PFHxS, and PFBS with the convection-dispersion-sorption equation and Langmuir sorption isotherm.

This study investigates flooding within the campus of the Federal College of Education (Technical), Omoku, and its environs using integrated geophysical methods. Geo-electric resistivity (VES) and Electrical Resistivity Tomography (ERT) were employed to characterize subsurface properties that influence water retention, drainage, and flooding susceptibility. The VES analysis delineated four geo-electric layers with resistivity values ranging from 57.9 to 32,936.7 S2m, revealing significant subsurface heterogeneity. The topsoil (layer 1) exhibited variable resistivity (86.7-824.4 S2m), indicating mixed sandy and clayey materials with poor drainage in low- resistivity zones. The second and third layers demonstrated variable thickness and resistivity, reflecting saturated zones prone to water retention and areas with better drainage properties. The fourth layer, likely compact bedrock, exhibited high resistivity, acting as a barrier to water flow and contributing to surface runoff. Secondary geo-electric parameters including reflection coefficients, transverse resistivity, longitudinal resistivity, and anisotropy, provided additional insights. Low resistivity and high anisotropy zones indicated water-saturated or clay-rich materials associated with flood-prone areas. High resistivity and low anisotropy corresponded to better-draining zones with sandy or gravelly materials. ERT profiles complemented the VES results by mapping lateral and vertical variations in resistivity. Low-resistivity zones in the upper subsurface were linked to water- saturated soils, obstructing drainage and increasing flood risk. High-resistivity regions indicated less permeable materials that could exacerbate runoff and surface water accumulation. The study concludes that the interplay of subsurface heterogeneity, saturated zones, and impermeable layers significantly influences flooding in the area. The findings provide critical data for flood risk management and infrastructural planning, highlighting the need for effective drainage systems and soil stabilization measures in vulnerable regions.