Search Results (301)

Construction on soft, highly compressible soils increasingly requires reliable ground improvement solutions. Among these, Rigid Inclusions (RIs) have emerged as one of the most efficient soil-reinforcement techniques. This paper synthesizes evidence from over 180 studies to provide a comprehensive state-of-the-art review of RI technology encompassing its governing mechanisms, design methodologies, and field performance. While the static behavior of RI systems has now been extensively studied and is supported by international design guidelines, the response under cyclic and seismic loading, particularly in liquefiable soils, remains less documented and subject to significant uncertainty. This review critically analyzes the degradation of key load-transfer mechanisms including soil arching, membrane tension, and interface shear transfer under repeated loading conditions. It further emphasizes the distinct role of RIs in liquefiable soils, where mitigation relies primarily on reinforcement and confinement rather than on drainage-driven mechanisms typical of granular columns. The evolution of design practice is traced from analytical formulations validated under static conditions toward advanced numerical and physical modeling frameworks suitable for dynamic loading. The lack of validated seismic design guidelines is high-lighted, and critical knowledge gaps are identified, underscoring the need for advanced numerical simulations and large-scale physical testing to support the future development of performance-based seismic design (PBSD) approaches for RI-improved ground. Full article

Phosphorus (P) is an essential nutrient in plant development, but its availability in the soil is often limited due to chemical fixation and poor solubility. This study presents the development, characterization and evaluation of a novel granular bioinoculant formulated with Aspergillus tubingensis (P-solubilizing) and Trichoderma virens (P-mineralizing) using clinoptilolite (CZ) as a carrier to improve P bioavailability. The formulation process included the evaluation of the proposed components, the standardization of conidia production in different media cultures and conditions, the elaboration and characterization of the bioinoculant and its evaluation in plants. In this study, in vitro analysis demonstrated the synergistic effect of the components, showing that in all treatments with dual inoculation and CZ, the amount of soluble phosphorus (SP) was higher than in their counterparts (from 27.8 to 36.8 mg·L⁻¹). A concentration greater than 1 × 10⁹ CFU·mL⁻¹ was obtained by standardizing the production of conidia in different media (PDA, V8-Agar and Molasses Agar), which were then used to produce granular batches containing at least 2 × 10⁷ CFU·g⁻¹. Furthermore, the size (88% of the granules measured <4.5 mm), purity (<2 CFU·g⁻¹ in 10⁻⁴ dilution), and moisture content of the prototype granules (3.3–3.8%) were confirmed to be within established international quality parameters. Plant evaluations in chili and tomato demonstrated the formulation efficacy, showing an increase in both soluble and foliar P content (with at least 30% more than controls), alongside improvements in all parameters evaluated that are related to plant growth promotion (with at least 15% more growth than controls). The development of this formulation prototype represents a focused effort toward process standardization and optimization required to validate developed formulations, thus promoting the advancement of applied biotechnology. Full article

The presented dataset contains spatial models of cones formed from lunar soil simulants. The cones were formed in a laboratory by allowing the soil to fall freely through a funnel. Then, the cones were measured using three methods: a high-precision handheld laser scanner (HLS), photogrammetry, and a low-cost LiDAR system integrated into an iPad Pro. The dataset consists of two groups. The first group contains raw measurement data, and the second group contains the geometry of the cones themselves, excluding their surroundings. This second group was prepared to support the calculation of the cones’ volume. All data are provided in standard 3D file format (.STL). The dataset enables direct comparison of resolution and geometric reconstruction performance across the three techniques and can be reused for benchmarking 3D processing workflows, segmentation algorithms, and shape reconstruction methods. It provides complete geometric information suitable for validating automated extraction procedures for parameters such as cone height, base diameter, and angle of repose, as well as for further research into planetary soil and granular material morphology. Full article

This technical note presents a quantitative image-based framework for evaluating the packing and compressibility of granular soils, specifically applied to building foundation design in civil infrastructure projects. The Sedimaging system replicates hydraulic sedimentation in a controlled column, equipped with a high-resolution camera, to visualize particle orientation after deposition. Grayscale images of the settled bed are analyzed using Haar Wavelet Transform (HWT) decomposition to quantify directional intensity gradients. A new descriptor, termed the sediment index (B), is defined as the ratio of vertical to horizontal wavelet energy at the dominant scale, representing the preferential alignment and anisotropy of particles during sedimentation. Experimental investigations were conducted on fifteen granular materials that include natural sands, tailings, glass beads and rice grains with different shapes. The results demonstrate strong correlations between B and both microscopic shape ratios (d₁/d₂ and d₁/d₃) and macroscopic properties. Linear relationships predict the limiting void ratios (e_max, e_min) with mean absolute differences of 0.04 and 0.03, respectively. A power-law function relates B to the compression index (C_c) with an average deviation of 0.02. These findings confirm that the sediment index effectively captures the morphological influence of particle shape on soil packing and compressibility. Compared with conventional physical testing, the Sedimaging-based approach offers a rapid, non-destructive, and high-throughput solution for estimating soil packing and compressibility of cohesionless, sand-sized granular soils directly from post-settlement imagery, making it particularly valuable for preliminary site assessments, geotechnical screening, and intelligent monitoring of granular materials in building foundation design and other infrastructure applications, such as earth–rock dams. Full article

Space exploration is a major global focus, advancing knowledge and exploiting new resources beyond Earth. Bioinspired design—drawing principles from nature—offers systematic pathways to increase the capability and intelligence of space robots. Prior reviews have emphasized on-orbit manipulators or lunar rovers, while a comprehensive treatment across application domains has been limited. This review synthesizes bioinspired capability and intelligence for space exploration under varied environmental constraints. We highlight four domains: adhesion and grasping for on-orbit servicing; terrain-adaptive mobility on granular and rocky surfaces; exploration intelligence that couples animal-like sensing with decision strategies; and design methodologies for translating biological functions into robotic implementations. Representative applications include gecko-like dry adhesives for debris capture, beetle-inspired climbers for truss operations, sand-moving quadrupeds and mole-inspired burrowers for granular regolith access, and insect flapping-wing robots for flight under Martian conditions. By linking biological analogues to quantitative performance metrics, this review highlights how bioinspired strategies can significantly improve on-orbit inspection, planetary mobility, subsurface access, and autonomous decision-making. Framed by capability and intelligence, bioinspired approaches reveal how biological analogues translate into tangible performance gains for on-orbit inspection, servicing, and long-range planetary exploration. Full article

The reinforcement of high-water-content, low-permeability soft soils presents a critical challenge in marine and coastal engineering. While electroosmotic dewatering is a promising technique, its widespread application is often hindered by issues such as high energy consumption and limited strength gain. However, the specific mechanisms by which marine-derived biopolymers modify soil properties and microstructure to enhance electroosmotic efficiency and significantly improve the post-treatment bearing capacity remain insufficiently understood. To address this gap, this study investigates the use of Sodium Alginate (SA) to enhance the electroosmotic dewatering performance of coastal soft soil. Laboratory experiments were conducted using carbon felt electrodes with varying SA mass fractions (0.0%, 0.2%, 0.5%, and 1.0%). The study integrated macroscopic monitoring with Scanning Electron Microscopy (SEM) to evaluate the electroosmotic efficiency and mechanical property evolution. The results demonstrate that the cross-linked structure of SA gel effectively bridges soil particles and fills inter-granular pores, significantly increasing the liquid limit (from 32.34% to 49.15% at 1.0% SA) and mitigating soil cracking. This microstructural alteration enhanced electrical conductivity and accelerated drainage; the average water content reduction increased from 12.78% (0.0% SA) to 20.86% (1.0% SA). Notably, the 0.5% SA treatment improved the average bearing capacity to approximately 86 kPa (about 7 times that of 0.0% SA) with only a 21% increase in the energy consumption coefficient. This study confirms that utilizing SA for electroosmotic reinforcement effectively modifies soil properties to provide a marine solution for coastal soft soil foundation treatment. Full article

The present work develops an explicit dynamic finite element model of soil–disc interaction for a notched harrow disc, aiming to quantify how APS coatings, soil type and disc–soil friction influence stresses in the disc and surrounding soil. The model reproduces a four-gang offset harrow operating at 7 km/h, 0.15 m working depth, with 18°disc angle and 15° tilt angle, and compares an uncoated steel disc with three APS-coated variants (P1 Metco 71NS, P2 Metco 136F, P3 Metco 45C-NS). Mechanical properties of the substrate and coatings are obtained from micro-indentation tests and introduced via a bilinear steel model and Johnson–Cook plasticity for the coatings, while disc–soil friction coefficients are calibrated from microscratch measurements. Soil behaviour is described using the AUTODYN Granular model for four representative agricultural soils, spanning sandy loam to saturated heavy clay. Results show that the uncoated disc develops von Mises stresses in the disc–soil contact region of ≈150–220 MPa, with intermediate-stiffness soils being most critical. APS coatings significantly alter both the level and distribution of stresses: P2, the stiffest ceramic, yields the highest stresses (≈421–448 MPa), P1 keeps stresses near the baseline while shielding the substrate through extended plastic zones, and P3 provides an intermediate, more uniformly distributed stress regime. Increasing disc–soil friction systematically amplifies von Mises stresses in the contact region, especially for P2. Overall, the calibrated explicit model captures the coupled influence of soil properties, coating stiffness and friction, and indicates that P1 is better suited for light-to-medium soils, P3 offers the most balanced response in medium-to-stiff soils, whereas P2 should be reserved for highly abrasive conditions and used with caution in cohesive soils. Full article

Petroleum hydrocarbons are pervasive soil pollutants that detrimentally affect the soil structure, nutrients, and microbial ecosystems. However, the effect of biochar particle size on the remediation effectiveness remains a critical, unresolved parameter. Here, a soil remediation experiment was conducted to evaluate the synergy between biochars of different particle sizes and nutrient addition. Total petroleum hydrocarbons (TPHs) were quantified gravimetrically, and specific hydrocarbon fractions were analysed via gas chromatography mass spectroscopy (GC-MS) while the microbial community composition was analysed via high-throughput sequencing. The results revealed that granular bulrush straw biochar (0.85 mm) with nutrients achieved the greatest TPH degradation (73.35%), significantly outperforming both powder biochar and soybean straw biochar. This enhanced remediation was associated with a significant shift in the microbial community (p < 0.05), characterized by substantial increases in hydrocarbon-degrading bacteria, particularly Actinobacteria and the genus Mycobacterium. This study revealed that the synergistic application of granular biochar and nutrients is a highly effective, nature-based strategy for petroleum-contaminated soil, which functions by resolving a critical biochar parameter to enhance key microbial degraders. Full article

The railway industry is increasingly pressured to adopt sustainable practices, seeking alternatives to virgin natural aggregates that reduce environmental impact and lifecycle costs. The extraction of slate for ornamental purposes generates significant waste, approximately 30% by mass, which is typically disposed of in landfills, causing environmental and economic concerns. This study comprehensively investigates the potential of slate waste as a primary component in sub-ballast layers for railways. Laboratory tests were conducted on mixtures of slate waste and a clayey soil, with granular contents ranging from 60% to 90%. The key geotechnical parameters evaluated included the California Bearing Ratio (CBR), Resilient Modulus (RM), compaction characteristics, granulometry and Atterberg limits. In addition, the DNIT ISF-212 standard was used to verify compliance with the Brazilian requirements for the use of materials in sub-ballast layers. The results indicate that mixtures with slate waste (SLT) exhibit performance comparable to conventional gneiss aggregate mixtures (REF); however, verification against the DNIT ISF-212 standard showed that only the SLT 80/20 and SLT 90/10 mixtures fully meet the requirements for use as railway sub-ballast. The RM and CBR values for the SLT mixtures increased by 48.5% and 38.4%, respectively, when the slate waste content was raised from 60% to 90%. A non-linear relationship was found between RM and CBR for both material types. Furthermore, the study integrates findings from related research on recycled ballast and tropical soils, highlighting the synergistic benefits of using industrial by-products. It concludes that slate waste presents a viable, high-performance, and sustainable solution for railway sub-ballast, contributing to circular economy principles in railway infrastructure. Full article

The limited availability of phosphorus (P) in soil poses a critical constraint on agricultural productivity, and sustainable P fertilization practices are of great importance for crop production. In this study, we developed a novel dual-function granular material (RMG) derived from red mud, a waste residue from the aluminum industry. This material is capable of adsorbing P in P-rich soils and releasing P in P-deficient soils, thereby enabling the sustainable use of red mud and P fertilizer. The influences of RMG on the migration and transformation of P in soil were investigated. Application of RMG significantly increased the critical threshold for P leaching, thereby effectively mitigating P loss. In the initial stage of leaching, P in the leachate was present predominantly as particulate phosphorus, whereas molybdate-reactive P became the dominant form in later stages. With increasing RMG dosage, the pH of the leachate rose while the total phosphorus concentration declined, indicating that alkaline components in RMG promoted the adsorption and precipitation of phosphates in soil. The release behavior of P from P-enriched RMG was also examined. The results showed that the total soil P content increased progressively with higher RMG dosage and longer cultivation duration. Elevated temperature and soil moisture content were found to enhance the release and migration of P from RMG into the soil. SEM-EDS analyses revealed that released components (e.g., Ca²⁺ and Fe³⁺) from RMG formed relatively stable complexes with free phosphates. Moreover, adsorption of P onto the RMG surface further facilitated its migration and transformation within the soil. The research findings provide valuable insights for the simultaneous pollution remediation and resource utilization of red mud and phosphorus. Full article

Particle size distribution (PSD), also referred to as grain-size distribution (GSD), is a fundamental characteristic of granular materials, influencing packing density, porosity, permeability, and mechanical behavior across soils, sediments, and industrial powders. Accurate and reproducible representation of PSD is essential for computational modeling, digital twin development (i.e., virtual replicas of physical systems), and machine learning applications in geosciences and engineering. Despite the widespread use of classical distributions (log-normal, Weibull, Gamma), there remains a lack of systematic frameworks for generating synthetic datasets with controlled statistical properties and reproducibility. This paper introduces a unified computational framework for generating virtual PSDs/GSDs with predefined statistical characteristics and a specified number of grain-size fractions. The approach integrates parametric modeling with two histogram-based allocation strategies: the equal-width method, maintaining uniform bin spacing, and the equal-probability method, distributing grains according to quantiles of the target distribution. Both methods ensure statistical representativeness, reproducibility, and scalability across material classes. The framework is demonstrated on representative cases of soils (Weibull), sedimentary and industrial materials (Gamma), and food powders (log-normal), showing its generality and adaptability. The generated datasets can support sensitivity analyses, experimental validation, and integration with discrete element modeling, computational fluid dynamics, or geostatistical simulations. Full article

Accurate and large-scale crop mapping is crucial for global food security, yet its performance is often hindered by domain shift when models trained in one region are applied to another. This is particularly challenging in cross-continental scenarios where variations in climate, soil, and farming systems are significant. To address this, we propose PLCM (PSAE-LTAE + Class-aware MMD), an unsupervised domain adaptation (UDA) framework for crop classification using Sentinel-2 satellite image time series. The framework features two key innovations: (1) a Pixel-Set Attention Encoder (PSAE), which intelligently aggregates spatial features within parcels by assigning weights to individual pixels, enhancing robustness against noise and intra-parcel heterogeneity; and (2) a class-aware Maximum Mean Discrepancy (MMD) loss function that performs fine-grained feature alignment within each crop category, effectively mitigating negative transfer caused by domain shift while preserving class-discriminative information. We validated our framework on a challenging cross-continental, cross-year task, transferring a model trained on data from the source domain in the United States (2022) to an unlabeled target domain in Wensu County, Xinjiang, China (2024). The results demonstrate the robust performance of PLCM. While achieving a competitive overall Macro F1-score of 96.56%, comparable to other state-of-the-art UDA methods, its primary advantage is revealed in a granular per-class analysis. This analysis shows that PLCM provides a more balanced performance by particularly excelling at identifying difficult-to-adapt categories (e.g., Cotton), demonstrating practical robustness. Ablation studies further confirmed that both the PSAE module and the class-aware MMD strategy were critical to this performance gain. Our study shows that the PLCM framework can effectively learn domain-invariant and class-discriminative features, offering an effective and robust solution for high-accuracy, large-scale crop mapping across diverse geographical regions. Full article

The soil–water characteristic curve (SWCC) is essential for understanding hydraulic behavior in geotechnical applications involving coarse granular materials. However, existing models often overlook the coupled effects of key factors. This study systematically investigates the influence of grain size distribution, density, and contact angle on the SWCC using a numerical approach that combines the discrete element method (DEM) with an enhanced pore morphology method incorporating locally variable contact angles (Lvca-PMM). The results show that smaller uniformity coefficients ($C_u$), larger median grain sizes ($D_{50}$), higher porosity ($\phi$), and larger contact angles ($\theta$) shift the SWCC to the left, reducing both the air entry value (${\Psi }_a$) and residual suction (${\Psi }_r$). Specifically, linear relationships were identified between ${\Psi }_a$, ${\Psi }_r$, $C_u$, $\phi$, and cos($\theta$), while a power-law relationship was observed with $D_{50}$. Furthermore, the interaction of these factors plays a critical role, where a change in one property can amplify or diminish the effects of others. Based on these findings, empirical equations for predicting ${\Psi }_a$ and ${\Psi }_r$ were developed, offering practical tools for engineers to efficiently estimate the SWCC. This research provides deeper insight into the water retention properties of coarse soils and supports the optimized design of granular fills and drainage systems. Full article

Optimizing fertilizer management is essential for reducing salinity-related risks and improving nutrient efficiency in ornamental plant production. Fertilization enhances plant performance; however, excessive nutrient inputs can disrupt substrate chemistry, elevate salinity, and promote nitrogen leaching—particularly in containerized systems with limited rooting volume. This study evaluated the growth, physiological performance, and soil–plant nutrient dynamics of Sabal palmetto (cabbage palm) cultivated under six fertilization regimes over 180 days in a subtropical shade-house environment. Treatments ranged from a single baseline application of 15 g per plant (T0) to a cumulative 75 g (T5) using granular slow-release fertilizer. Morphological traits (plant height: 26–70 cm; leaf number: 4–18) and physiological indices (atLEAF⁺: 34.3–66.4; NDVI: 0.26–0.77) were monitored every 30 days. Substrate nitrogen and carbon concentrations increased from 0.57% and 41.78% at baseline to 1.24% and 42.94% at 180 days, while foliar nitrogen ranged from 1.46% to 2.57%. Fertilization significantly influenced all parameters (p < 0.05). Higher fertilization levels elevated electrical conductivity, salinity, and nitrogen leaching, with principal component analysis revealing strong positive associations among total nitrogen, electrical conductivity, and salinity. Moderate fertilization (T2 = 45 g) maintained favorable substrate chemistry, high foliar nitrogen, and balanced canopy growth with minimal nutrient losses. Sensor-based chlorophyll indices (atLEAF⁺ and NDVI) correlated strongly (r = 0.71, p < 0.001), confirming their reliability as non-destructive diagnostics for nitrogen management. These findings demonstrate that integrating optical monitoring with adaptive fertilization mitigates substrate salinization, sustains ornamental quality, and promotes the sustainable cultivation of Sabal palmetto in urban horticultural systems. Full article

The spatiotemporal dynamics of soil nutrients in the crop row zone are critical determinants of crop yield, necessitating precision fertilization for optimal plant growth. However, previous studies have predominantly focused on plant-available nutrient status at the scale of entire cropping systems, yet a granular understanding of their distribution patterns across precise temporal and spatial dimensions remains limited. Therefore, this study investigated maize–legume intercropping systems to quantify the dynamics of soil alkaline-hydrolyzable nitrogen (AN), available phosphorus (AP), and available potassium (AK) across distinct growth stages, soil depths, and row positions. The experiment comprised five treatments: maize–soybean intercropping, maize–peanut intercropping, and monocultures of maize, soybean, and peanut. Throughout the two-year study, maize–soybean intercropping significantly enhanced the plant height of both maize and soybean relative to their respective monocultures (p < 0.05). In contrast, within the maize–peanut system, intercropping significantly promoted peanut plant height but suppressed stem diameter in both species (p < 0.05); these effects were consistent across both study years. Both systems exhibited a “benefit-sacrifice” pattern, where dry matter was preferentially allocated to maize, thereby increasing total system productivity despite suppressing legume growth. Furthermore, during the mid-to-late growth stages, intercropped maize showed an enhanced capacity for nitrogen uptake from deeper soil layers. In contrast, the alkaline-hydrolyzable nitrogen content in intercropped soybean and peanut remained lower than in their respective monocultures throughout the growth period, with reductions ranging from 8.49% to 34.79%. Intercropping significantly increased the soil available phosphorus content in the root zones of maize, soybean, and peanut compared to their respective monocultures. The available phosphorus content in the 0–20 cm soil layer was consistently higher than in monoculture systems, with a maximum increase of 41.70%. Moreover, intercropping effectively mitigated soil potassium depletion, resulting in a smaller decline in available potassium. This effect was most pronounced in the maize–peanut intercropping pattern within the 20–40 cm soil layer. The distribution of soil available nutrients (N, P, K) was also influenced by drip tape placement. The levels of these nutrients for soybean and peanut were higher at 50 cm from the drip tape than at 30 cm, while for maize, levels were higher at 80 cm than at 40 cm. Intercropping increased the thousand-kernel weight of maize and soybean but decreased that of peanut. Overall, the strategic row configuration optimized the yield performance of both intercropping systems, resulting in land equivalent ratios greater than 1, which indicates distinct yield advantages for both intercropping patterns. Full article