Search Results (3,463)

The cohesive properties of lunar regolith, combined with a low-gravity environment, result in it having a distinct mechanical behavior from sandy soil on Earth. Consequently, empirical formulas derived from cone penetration tests (CPTs) for calculating the shear strength parameters of Earth’s sand cannot be directly applied to lunar regolith. This study utilized the three-dimensional discrete element method (DEM) to numerically simulate triaxial shear tests and cone penetration tests in a lunar environment. The particle contact model for lunar regolith in the discrete element method (DEM) simulation incorporated the hysteresis effect of van der Waals forces, thereby simulating the cohesive properties of lunar regolith in a lunar environment. We proposed a relationship for calculating the shear strength index of lunar regolith based on normalized cone tip resistance using the results from triaxial and CPT simulations and referencing empirical formulas derived from ground-based CPT data. The results of this study provide a valuable reference for future lunar CPTs. Full article

As an important construction material, the mechanical and deformation properties of marine coral sand determine the safety and stability of related island and coastal engineering construction. The porous and easily broken characteristics of coral sand often make it difficult to meet engineering construction needs. In particular, coral sand undergoes a large amount of particle breakage under high-stress conditions, which in turn negatively affects its mechanical and deformation properties. In this study, the macro- and micro-mechanical behavior of geosynthetic-reinforced coral sand under high confining pressure was investigated and compared with unreinforced cases using the three-dimensional discrete element method (DEM), which was verified by indoor triaxial tests. The results showed that the stress–strain responses of unreinforced and reinforced coral sand under high confining pressure showed completely different trends, i.e., the hardening tendency shown in the reinforced case. Geosynthetic reinforcement can significantly inhibit the stress–strain softening and bulging deformation of coral sand under high confining pressure, thus improving the shear mechanical performance of the reinforced sample. At the microscopic scale, high confining pressure and reinforcement affected the contact force distribution pattern and stress level between particles, determining the macroscopic mechanical and deformation performance. In addition, the breakage of particles under high confining pressure was mainly affected by shear strain and reinforcement. The particle fragment distribution, particle gradation, and relative breakage index exhibited different trends at different confining pressure levels. These breakage characteristics were closely related to the deformation and stress levels of unreinforced and reinforced samples. Full article

For improving the adaptability of a tracked vehicle equipped with a symmetrical suspension system on complex hilly terrain, based on the coupling method of multi-body dynamics (MBD) and discrete element method (DEM), an MBD-DEM coupling model was built and verified to explore its dynamic behaviors on soil. Firstly, according to the basic parameters of the tracked vehicle equipped with a symmetrical suspension system, a corresponding MBD model was built in Recurdyn V9R4 software. Based on the Euler–Lagrange method, the mathematical structure of the symmetrical suspension system was analyzed, and a corresponding mathematical simulation model was built in Matlab2016/Simulink to verify the MBD model. Secondly, based on the DEM theory and the parameter of the soil in a hilly area, a granular pavement model was built. Then, based on the coupling method of MBD and DEM, the corresponding MBD-DEM coupling model was built. Finally, using the MBD-DEM coupling model, the dynamic behaviors of the tracked vehicle equipped with a symmetrical suspension system under horizontal condition, the climbing condition and the obstacle crossing condition were obtained and discussed. The study results show that the proposed MBD-DEM coupling model could be used effectively to analyze the dynamic characteristics of the tracked vehicle. In addition, according to the analysis of the dynamic characteristics of the proposed tracked vehicle, the tracked vehicle equipped with a symmetrical suspension presents good adaptabilities under various working conditions. Full article

Constructing high-precision subsidence basins is of paramount importance for mining subsidence monitoring. Traditional unmanned aerial vehicle (UAV) photogrammetry techniques typically construct subsidence basins by directly differencing digital elevation models (DEMs) from different monitoring periods. However, this method often neglects the influence of horizontal displacement on the accuracy of the subsidence basin. Taking a mining area in Ordos, Inner Mongolia, as an example, this study employed the normalized cross-correlation (NCC) matching algorithm to extract horizontal displacement information between two epochs of a digital orthophoto map (DOM) and subsequently corrected the horizontal position of the second-epoch DEM. This ensured that the planar positions of ground feature points remained consistent in the DEM before and after subsidence. Based on this, the vertical displacement in the subsidence area (the subsidence basin) was obtained via DEM differencing, and the parameters of the post-correction subsidence basin were inverted using the probability integral method (PIM). The experimental results indicate that (1) the horizontal displacement was influenced by the gully topography, causing the displacement within the working face to be segmented on both sides of the gully; (2) the influence of the terrain on the subsidence basin was significantly reduced after correction; (3) the post-correction surface subsidence curve was smoother than the pre-correction curve, with abrupt error effects markedly diminished; (4) the accuracy of the post-correction subsidence basin increased by 43.12% compared with the total station data; and (5) comparing the measured horizontal displacement curve with that derived using the probability integral method revealed that the horizontal displacement on the side of an old goaf adjacent to the newly excavated working face shifted toward the advancing direction of the new working face as mining progressed. This study provides a novel approach and insights for using low-cost UAVs to construct high-precision subsidence basins. Full article

In recent years, land subsidence has become a crucial factor affecting urban safety and sustainable development, especially in Wan’an Town. To accurately monitor and analyze the land subsidence in Wan’an Town, this study uses the PS-InSAR technique combined with an improved DEM for detailed research on land subsidence in Wan’an Town. PS-InSAR, or Permanent Scatterer Interferometric SAR, is suitable for high-precision monitoring of surface deformation. The natural neighbor interpolation method optimizes DEM data, improving its spatial resolution and accuracy. In this study, multiple periods of SAR imagery data of Wan’an Town were collected and preprocessed through radiometric calibration, phase unwrapping, and other steps. Using the PS-InSAR technique, the phase information of permanent scatterers (PS points) on the surface was extracted to establish a deformation model and preliminarily analyze the land subsidence in Wan’an Town. Concurrently, the DEM data were optimized using the natural neighbor interpolation method to enhance its accuracy. Finally, the optimized DEM data were combined with the surface deformation information extracted through the PS-InSAR technique for a detailed analysis of the land subsidence in Wan’an Town. The research results indicate that the DEM data optimized by the natural neighbor interpolation method have higher accuracy and spatial resolution, providing a more accurate reflection of the topographical features of Wan’an Town. The research found that the optimized DEM provided a more accurate reflection of Wan’an Town’s topographical features. By combining PS-InSAR data, subsidence information from 2016 to 2024 was calculated. The study area showed varying degrees of subsidence, with rates ranging from 6 mm/year to 10 mm/year. Four characteristic deformation areas were analyzed for causes and influencing factors. The findings contribute to understanding urban land subsidence, guiding urban planning, and providing data support for geological disaster warning and prevention. Full article

In this study, a multilayer composite rolling model consisting of a rolling wheel, a protective layer, a GCL, and a support layer was constructed by the discrete element method (DEM). Soil compaction and gravel migration, and their effects on the GCL, were analyzed from a fine viewpoint, and three key indexes for the safety assessment of the GCL were proposed: local elongation, gravel embedment value, and bentonite allotment number. The results show that the soil porosity and cumulative settlement do not decrease all the time with the number of rolling passes, and there exists an optimal number of rolling passes during the rolling process; the protective layer of gravel soil moves more frequently than the support layer; and the nearly rectangular and nearly elliptical gravels are more likely to rotate. The maximum local elongation of the GCL was 3.79% during the lapping process, and all gravels in contact with the upper boundary of the GCL extruded the GCL to varying degrees during the lapping process. The distribution of bentonite particles is closely related to the contact mode between gravel and GCL. Full article

We utilized remote sensing and ground cover data to predict soil organic carbon (SOC) content across a vast geographic region. Employing a combination of machine learning and deep learning techniques, we developed a novel data fusion approach that integrated Digital Elevation Model (DEM) data, MODIS satellite imagery, WOSIS soil profile data, and CHELSA environmental data. This combined dataset, named GeoBlendMDWC, was specifically designed for SOC prediction. The primary aim of this research is to develop and evaluate a novel optimization algorithm for accurate SOC prediction by leveraging multi-source environmental data. Specifically, this study aims to (1) create an integrated dataset combining remote sensing and ground data for comprehensive SOC analysis, (2) develop a new optimization technique that enhances both machine learning and deep learning model performance, and (3) evaluate the algorithm’s efficiency and accuracy against established optimization methods like Jaya and GridSearchCV. This study focused on India, Australia, and South Africa, countries known for their significant agricultural activities. We introduced a novel optimization technique for both machine learning and deep neural networks, comparing its performance to established methods like the Jaya optimization technique and GridSearchCV. The models evaluated included XGBoost Regression, LightGBM, Gradient Boosting Regression (GBR), Random Forest Regression, Decision Tree Regression, and a Multilayer Perceptron (MLP) model. Our research demonstrated that the proposed optimization algorithm consistently outperformed existing methods in terms of execution time and performance. It achieved results comparable to GridSearchCV, reaching an R² of 90.16, which was a significant improvement over the base XGBoost model’s R² of 79.08. In deep learning optimization, it significantly outperformed the Jaya algorithm, achieving an R² of 61.34 compared to Jaya’s 30.04. Moreover, it was 20–30 times faster than GridSearchCV. Given its speed and accuracy, this algorithm can be applied to real-time data processing in remote sensing satellites. This advanced methodology will greatly benefit the agriculture and farming sectors by providing precise SOC predictions. Full article

Jet pumps are widely used in petrochemical processes, nuclear cooling, and wastewater treatment due to their simple structure, high reliability, and stable performance under extreme conditions. However, when transporting solid-laden two-phase flows, they face severe erosion problems, leading to reduced efficiency, malfunctions, or even failure. Therefore, optimizing jet pump performance and extending its service life is crucial. In this study, an experimental platform was established to conduct experiments on wall erosion in jet pumps. The CFD-DEM method was used to simulate the solid–liquid two-phase flow in the jet pump, comparing six erosion models for predicting erosion rates. The Grey Wolf Optimization algorithm was applied to calibrate model coefficients. The results indicate that the Neilson erosion model shows the best consistency with the experimental results. The inlet flow rate significantly influenced the erosion rates, while the flow rate ratio had a smaller effect. The particle concentration exhibited a nonlinear relationship with erosion, with diminishing impact beyond a certain threshold. As the factors varied, the erosion distribution tended to be uniform, but high erosion areas remained locally concentrated, indicating intensified localized erosion. Full article

Obtaining metallic parts via Additive Manufacturing can yield several advantages over using other traditional manufacturing methods such as machining. Material extrusion (MEX) can handle complex shapes with porous structures and, at the present time, much low-end and desktop equipment is available. In the present work, different industrial and medical applications of metallic Fused Filament Fabrication (FFF) parts are presented. First, an overview of the process, equipment, and of the metal-filled filaments currently available is provided. Then, the properties of parts and different applications are shown. For example, metal-filled filaments with a low metal content that can be used to obtain plastic parts with metallic appearance (with either steel, copper, or bronze), and filaments with a high metallic content allow obtaining metallic parts with high mechanical strength after a sintering operation. The present contribution aims to be an up-to-date panorama for current industrial and medical results and lessons learnt from the application of FFF to obtain metallic parts. Full article

The Caspian region represents a complex and unique system of terrestrial, coastal, and aquatic environments, marked by an exceptional landscape and biological diversity. This diversity, however, is increasingly threatened by substantial anthropogenic pressures. One notable impact of this human influence is the rising concentration of pollutants atypical for the atmosphere. Advances in science and technology now make it possible to detect certain atmospheric pollutants using remote Earth observation techniques, specifically through data from the Sentinel-5 satellite, which provides continuous insights into atmospheric contamination. This article investigates the dynamics of atmospheric pollution in the southwestern part of the Caspian Sea basin using Sentinel-5P satellite data and the cloud-computing capabilities of the Google Earth Engine (GEE) platform. The study encompasses an analysis of concentrations of seven key pollutants: nitrogen dioxide (NO₂), formaldehyde (HCHO), carbon monoxide (CO), ozone (O₃), sulfur dioxide (SO₂), methane (CH₄), and the Aerosol Index (AI). Spatial and temporal variations in pollution fields were examined for the Caspian region and the basins of the seven rivers (key areas) flowing into the Caspian Sea: Sunzha, Sulak, Ulluchay, Karachay, Atachay, Haraz, and Gorgan. The research methodology is based on the use of data from the Sentinel-5 satellite, SRTM DEM data on absolute elevations, surface temperature data, and population density data. Data processing is performed using the Google Earth Engine cloud-computing platform and the ArcGIS software suite. The main aim of this study is to evaluate the spatiotemporal variability of pollutant concentration fields in these regions from 2018 to 2023 and to identify the primary factors influencing pollution distribution. The study’s findings reveal that the Heraz and Gorgan River basins have the highest concentrations of nitrogen dioxide and Aerosol Index levels, marking these basins as the most vulnerable to atmospheric pollution among those assessed. Additionally, the Gorgan basin exhibited elevated carbon monoxide levels, while the highest ozone concentrations were detected in the Sunzha basin. Our temporal analysis demonstrated a substantial influence of the COVID-19 pandemic on pollutant dispersion patterns. Our correlation analysis identified absolute elevation as a key factor affecting pollutant distribution, particularly for carbon monoxide, ozone, and aerosol indices. Population density showed the strongest correlation with nitrogen dioxide distribution. Other pollutants exhibited more complex distribution patterns, influenced by diverse mechanisms associated with local emission sources and atmospheric dynamics. Full article

Landslides are geological disasters that are harmful to both humans and society. Digital elevation model (DEM) time series data are usually used to monitor dynamic changes or surface damage. To solve the problem of landslide deformation monitoring without ground control points (GCPs), a multidimensional feature-based coregistration method (MFBR) was studied to achieve accurate registration of multitemporal DEMs without GCPs and obtain landslide deformation information. The method first derives the elevation information of the DEM into image pixel information, and the feature points are extracted on the basis of the image. The initial plane position registration of the DEM is implemented. Therefore, the expected maximum algorithm is applied to calculate the stable regions that have not changed between multitemporal DEMs and to perform accurate registrations. Finally, the shape variables are calculated by constructing a DEM differential model. The method was evaluated using simulated data and data from two real landslide cases, and the experimental results revealed that the registration accuracies of the three datasets were 0.963 m, 0.368 m, and 2.459 m, which are 92%, 50%, and 24% better than the 12.189 m, 0.745 m, and 3.258 m accuracies of the iterative closest-point algorithm, respectively. Compared with the GCP-based method, the MFBR method can achieve 70% deformation acquisition capability, which indicates that the MFBR method has better applicability in the field of landslide monitoring. This study provides an idea for landslide deformation monitoring without GCPs and is helpful for further understanding the state and behavior of landslides. Full article

Quinoa (Chenopodium quinoa Willd.) is an annual broadleaf plant belonging to the Amaranthaceae family. It is a nutritious food crop and is considered to be drought-tolerant, but drought is still one of the most important abiotic stress factors limiting its yield. Quinoa responses to drought are related to drought intensity and genotype. This study used two different drought-responsive quinoa cultivars, LL1 (drought-tolerant) and ZK1 (drought-sensitive), to reveal the important mechanisms of drought response in quinoa by combining physiological, transcriptomic, and metabolomic analyses. The physiological analysis indicated that Chla/Chlb might be important for drought tolerance in quinoa. A total of 1756 and 764 differentially expressed genes (DEGs) were identified in LL1 and ZK1, respectively. GO (Gene Ontology) enrichment analysis identified 52 common GO terms, but response to abscisic acid (GO:0009737) and response to osmotic stress (GO:0006970) were only enriched in LL1. KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis revealed that glycerophospholipid metabolism (ko00564) and cysteine and methionine metabolism (ko00270) ranked at the top of the list in both cultivars. A total of 1844 metabolites were identified by metabolomic analysis. “Lipids and lipid-like” molecules had the highest proportions. The DEMs in LL1 and ZK1 were mainly categorized 6 and 4 Human Metabolome Database (HMDB) superclasses, respectively. KEGG analysis revealed that the ‘α-linolenic acid metabolism’ was enriched in both LL1 and ZK1. Joint KEGG analysis also revealed that the ‘α-linolenic acid metabolism’ pathway was enriched by both the DEGs and DEMs of LL1. There were 17 DEGs and 8 DEMs enriched in this pathway, and methyl jasmonate (MeJA) may play an important role in the drought response of quinoa. This study will provide information for the identification of drought resistance in quinoa, research on the molecular mechanism of drought resistance, and genetic breeding for drought resistance in quinoa. Full article

Ovarian development significantly influences the laying performance of geese. In this study, the transcriptome analysis was conducted on the ovarian tissues of Wanxi White Geese during the pre-laying (KL), laying (CL), and ceased-laying period (XL). Short Time-series Expression Miner (STEM) analysis and miRNA–mRNA regulatory network construction were performed to identify the key genes and miRNAs regulating laying traits. Comparative analysis of KL vs. CL, CL vs. XL, and XL vs. KL groups resulted in the identification of 337, 136, and 525 differentially expressed genes (DEGs), and 258, 1131, and 909 differentially expressed miRNAs (DEMs), respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis (p < 0.05) revealed that the main enrichment pathways of DEGs and DEMs at different breeding periods were Neuroactive ligand–receptor interaction, GnRH signaling pathway and Wnt signaling pathway, all associated with ovarian development. According to the three groups of common pathways, four DEGs were screened out, including INHBB, BMP5, PRL, and CGA, along with five DEMs, including let-7-x, miR-124-y, miR-1-y, and miR-10926-z, all of them may affect ovarian development. A miRNA–mRNA regulatory network was constructed through integrated analysis of DEGs and DEMs, revealing nine miRNAs highly associated with ovarian development: miR-101-y, let-7-x, miR-1-x, miR-17-y, miR-103-z, miR-204-x, miR-101-x, miR-301-y, and miR-151-x. The dual-luciferase reporter gene verified the target relationship between WIF1 and miR-204-x, suggesting that these miRNAs may influence ovarian development in Wanxi White Goose by regulating the expression levels of their target genes within ovarian tissue. This study provides a theoretical foundation for analyzing the mechanisms of ovarian development across different breeding periods and accelerating the cultivation of new breeds through post-transcriptional regulation levels. Full article

Granular systems, no matter whether they are dry or saturated, are commonly encountered in both natural scenarios and engineering applications. In this work, we tackle the compaction problem of both dry and saturated granular systems under gyratory shearing compaction, where particles are subjected to constant pressure and continuous shear rate, which is quite different from the traditional cyclic shearing compaction. Such phenomena are crucial to the compaction of asphalt mixtures or soils in civil engineering and can be extended to other areas, such as powder processing and pharmaceutical engineering. In this study, we investigated the behavior of both dry and fully saturated mono-dispersed granular materials under gyratory shearing compaction using the discrete element method (DEM) and found that the gyratory speed or interstitial fluid viscosity has almost no impact on the compaction behavior, while the pressure and the particle size play more important roles. Additionally, it is the inertial time scale which dictates the compaction behavior under gyratory shearing in most cases; meanwhile, the viscous time scale can also have influence in some conditions. This work determines the similarity and unity between the granular gyratory compaction and the rheology of granular systems, which has direct relevance to various natural and engineering systems. Full article

High-accuracy geolocation is crucial for high-resolution spaceborne SAR images. Most advanced SAR satellites have a theoretical geolocation accuracy better than 1 m, but this may be unrealizable with less accurate external data, such as atmospheric parameters and ground elevations. To investigate the actual SAR geolocation accuracy in common applications, we analyze the properties of different geolocation errors, propose a geolocation procedure, and conduct experiments on TerraSAR-X images and a pair of Tianhui-2 images. The results show that based on GNSS elevations, the geolocation accuracy is better than 1 m for TerraSAR-X and 2 m/4 m for the Tianhui-2 reference/secondary satellites. Based on the WorldDEM and the SRTM, additional geolocation errors of 2 m and 4 m are introduced, respectively. By comparing the effectiveness of different tropospheric correction methods, we find that the GACOS mapping method has advantages in terms of resolution and computational efficiency. We conclude that tropospheric errors and ground elevation errors are the primary factors influencing geolocation accuracy, and the key to improving accuracy is to use higher-accuracy DEMs. Additionally, we propose and validate a geolocation model for the Tianhui-2 secondary satellite. Full article