Search Results (3,979)

In view of the lack of accurate model in the discrete element study during straw comprehensive utilization (crushing, mixing, and baling), wheat straw was taken as the research object to calibrate the simulation parameters using EDEM 2023. The intrinsic and contact mechanical parameters of wheat straw were measured, and a test of the angle of repose (AOR), extrusion test and bending test were carried out. On this basis, a discrete element model (DEM) of hollow flexibility by using cylindrical particles was developed. The optimal combination of contact mechanical parameters was obtained through AOR tests based on the Box–Behnken design (BBD), coefficients of static friction, rolling friction, and restitution between wheat straw and wheat straw-45 steel are separately 0.227, 0.136, 0.479, 0.271, 0.093, and 0.482, AOR is 18.66°. Meanwhile, optimal combinations of bond contact parameters were determined by the BBD. The calibrated parameters were used to conduct extrusion and bending tests. Results show that the average values of peak extrusion force and peak bending pressure are 23.20 N and 3.92 N, which have relative discrepancy of 3.25% and 3.59% compared to physical test measurements. The results can provide model reference for the optimization design such as feed processing equipment, baler, and mixer. Full article

High semen quality is vital for reproductive success in the swine industry; however, seasonal fluctuations often compromise this quality. The molecular mechanism underlying these seasonal effects on semen quality remains largely unclear. This study employed untargeted metabolomic profiling of boar seminal plasma (SP) to identify metabolites and metabolic pathways associated with semen quality during the summer and winter months. Semen samples were collected from mature Duroc boars at a commercial boar stud and classified as Passed or Failed based on motility and morphology. SP from five samples per group was analyzed using ultra-high-performance liquid chromatography–mass spectrometry (UHPLC-MS). In total, 373 metabolites were detected in positive ion mode and 478 in negative ion mode. Several differentially expressed metabolites (DEMs) were identified, including ergothioneine, indole-3-methyl acetate, and avocadyne in the summer, as well as LysoPC, dopamine, and betaine in the winter. These metabolites are associated with key sperm functions, including energy metabolism, antioxidant defense, and capacitation. KEGG pathway analysis indicated enrichment in starch and sucrose metabolism, pyrimidine metabolism, and amino acid metabolism across the seasons. Overall, the results reveal that SP metabolomic profiles vary with the season, thereby influencing semen quality. The identified metabolites may serve as potential biomarkers for assessing semen quality and enhancing reproductive efficiency in swine production. Full article

Synthetic Aperture Radar (SAR) images and optical imagery have high potential for extracting digital elevation models (DEMs). The two main approaches for deriving elevation models from SAR data are interferometry (InSAR) and radargrammetry. Adapted from photogrammetric principles, radargrammetry relies on disparity model estimation as its core component. Matching strategies in radargrammetry typically follow local, global, or semi-global methodologies. Local methods, while having higher accuracy, especially in low-texture SAR images, require larger kernel sizes, leading to quadratic computational complexity. Conversely, global and semi-global models produce more consistent and higher-quality disparity maps but are computationally more intensive than local methods with small kernels and require more memory (RAM). In this study, inspired by the advantages of local matching algorithms, a computationally efficient and novel model is proposed for extracting corresponding pixels in SAR-intensity stereo images. To enhance accuracy, the proposed two-stage algorithm operates without an image pyramid structure. Notably, unlike traditional local and global models, the computational complexity of the proposed approach remains stable as the input size or kernel dimensions increase while memory consumption stays low. Compared to a pyramid-based local normalized cross-correlation (NCC) algorithm and adaptive semi-global matching (SGM) models, the proposed method maintains good accuracy comparable to adaptive SGM while reducing processing time by up to 50% relative to pyramid SGM and achieving a 35-fold speedup over the local NCC algorithm with an optimal kernel size. Validated on a Sentinel-1 stereo pair with a 10 m ground-pixel size, the proposed algorithm yields a DEM with an average accuracy of 34.1 m. Full article

Aiming to resolve the problem of the poor peanut seed-filling effect under high-speed operation when developing high-speed peanut sowing with precision, a peanut precision seed-metering machine with an auxiliary air-suction seed-filling device was designed. Focusing on the force analysis of peanuts in the seed chamber, the peanut seed disturbance principle in the seed-metering machine for the blowing structure of an auxiliary air-suction seed-filling device was clarified. The seed-filling process was analyzed via DEM-CFD coupled simulation, and three factors affecting the seed-filling effect were identified, namely the seed-filling chamber ‘V’ angle γ, the bottom blow-air-hole cross-sectional area S, and the bottom blow-air-hole airflow velocity v_q, and the ranges of values of the three factors were determined. The Box–Behnken test was conducted using the seed-filling index and leakage index as the indexes. The results show that the seed-filling chamber ‘V’ angle γ is 56.59°, the bottom blowhole cross-sectional area S is 1088.4 mm², and the blowhole air velocity v_q is 12.11 m·s⁻¹. At this point, the peanut seed suction qualification index and leakage index are optimal, the seed suction qualification index is 96.33%, and the seed leakage index is 2.59%. At the same time, the field test shows that a sowing operation speed of 8–12 km·h⁻¹, a qualified index > 93%, and a leakage index < 4.5% are required to meet the agronomic requirements of peanut precision sowing. Full article

With the rapid increase in global lithium demand, the exploration of newly discovered lithium in the bauxite of the Wenshan area in southeastern Yunnan has become increasingly important. However, the current research on clay-type lithium in the Wenshan area has primarily focused on local exploration, and large-scale predictive metallogenic studies remain limited. To address this, this study utilized multi-source remote sensing data from ZY1-02D and ASTER, combined with ALOS 12.5 m DEM and Sentinel-2 imagery, to carry out remote sensing mineral identification, structural interpretation, and prospectivity mapping for clay-type lithium in the Wenshan area. This study indicates that clay-type lithium in the Wenshan area is controlled by NW, EW, and NE linear structures and are mainly distributed in the region from north of the Wenshan–Malipo fault to south of the Guangnan–Funing fault. High-value areas of iron-rich silicates and iron–magnesium minerals revealed by ASTER data indicate lithium enrichment, while montmorillonite and cookeite identification by ZY1-02D have strong indicative significance for lithium. Field verification samples show the highest Li₂O content reaching 11,150 μg/g, with six samples meeting the comprehensive utilization criteria for lithium in bauxite (Li₂O ≥ 500 μg/g) and also showing an enrichment of rare earth elements (REEs) and gallium (Ga). By integrating stratigraphic, structural, mineral identification, geochemical characteristics, and field verification data, ten mineral exploration target areas were delineated. This study validates the effectiveness of remote sensing technology in the exploration of clay-type lithium and provides an applicable workflow for similar environments worldwide. Full article

Wet areas, which are locations in the landscape that consistently retain moisture, and channel networks are important landscape compartments, with key hydrological and ecological functions. Hence, defining their spatial boundaries is an important step towards sustainable watershed management. In catchments of developing countries, wet areas and small order channels of river networks are rarely mapped, although they represent a crucial component of local livelihoods and ecosystems. In this study, topographic attributes generated with a 30 m SRTM DEM were used to map wet areas and stream networks of two tropical catchments in Central Brazil. The topographic attributes for wet areas were the local slope and the slope curvature, and the Topographic Wetness Index (TWI) was used to delineate the stream networks. Threshold values of the selected topographic attributes were calibrated in the Santa Maria catchment, comparing the synthetically generated wet areas and drainage networks with corresponding reference (map) features, and validated in the nearby Santa Maria basin. Drainage network and wet area delineation accuracies were estimated using random basin transects and multi-criteria and confusion matrix methods. The drainage network accuracies were 67.2% and 70.7%, and wet area accuracies were 72.7% and 73.8%, for the Santa Maria and Gama catchments, respectively, being equivalent or higher than previous studies. The mapping errors resulted from model incompleteness, DEM vertical inaccuracy, and cartographic misrepresentation of the reference topographic maps. The study’s novelty is the use of readily available information to map, with simplicity and robustness, wet areas and channel initiation in data-scarce, tropical environments. Full article

A systematic sensitivity analysis using three-dimensional discrete element models with discrete fracture networks (DEM-DFN) was conducted to evaluate underground excavation support in jointed rock masses at the CLAB2 site in Southeastern Sweden. The site features a joint network comprising six distinct joint sets, each with unique geometrical properties. The study examined 10 DFNs and 19 rock bolt patterns, both conventional and unconventional. It covered 200 scenarios, including 10 unsupported and 190 supported cases. Technical and economic criteria for stability were assessed for each support system. The results indicated that increasing rock bolt length enhances stability up to a certain point. However, multi-length rock bolt patterns with similar consumption can yield significantly different stability outcomes. Notably, the arrangement and properties of rock bolts are crucial for stability, particularly in blocks between bolting sections. These blocks remain interlocked in unsupported areas due to the induced pressure from supported sections. Although equal-length rock bolt patterns are commonly used, the analysis revealed that triple-length rock bolts (3, 6, and 9 m) provided the most effective support across all ten DFN scenarios. Full article

Steel is an important product in many engineering sectors; however, steelmaking remains one of the largest ${\mathrm{CO}}_2$ emitters. Therefore, new governmental policies drive the steelmaking industry toward a cleaner and more sustainable operation such as the gas-based direct reduction–electric arc furnace process. To become carbon neutral, utilizing more scrap is one of the feasible solutions to achieve this goal. Addressing knowledge gaps regarding scrap heterogeneity (size, shape, and composition) is essential to evaluate the effects of increased scrap ratios in basic oxygen furnace (BOF) operations. This review systematically examines heat and mass transfer correlations relevant to scrap melting in BOF steelmaking, with a focus on low Prandtl number fluids (thick thermal boundary layer) and dense particulate systems. Notably, a majority of these correlations are designed for fluids with high Prandtl numbers. Even for the ones tailored for low Prandtl, they lack the introduction of the porosity effect which alters the melting behavior in such high temperature systems. The review is divided into two parts. First, it surveys heat transfer correlations for single elements (rods, spheres, and prisms) under natural and forced convection, emphasizing their role in predicting melting rates and estimating maximum shell size. Second, it introduces three numerical modeling approaches, highlighting that the computational fluid dynamics–discrete element method (CFD–DEM) offers flexibility in modeling diverse scrap geometries and contact interactions while being computationally less demanding than particle-resolved direct numerical simulation (PR-DNS). Nevertheless, the review identifies a critical gap: no current CFD–DEM framework simultaneously captures shell formation (particle growth) and non-isotropic scrap melting (particle shrinkage), underscoring the need for improved multiphase models to enhance BOF operation. Full article

Landslides are among the most hazardous natural phenomena affecting Greater Abidjan, causing significant economic and social damage. Strategic planning supported by geographic information systems (GIS) can help mitigate potential losses and enhance disaster resilience. This study evaluates landslide susceptibility using logistic regression and frequency ratio models. The analysis is based on a dataset comprising 54 mapped landslide scarps collected from June 2015 to July 2023, along with 16 thematic predictor variables, including altitude, slope, aspect, profile curvature, plan curvature, drainage area, distance to the drainage network, normalized difference vegetation index (NDVI), and an urban-related layer. A high-resolution (5-m) digital elevation model (DEM), derived from multiple data sources, supports the spatial analysis. The landslide inventory was randomly divided into two subsets: 80% for model calibration and 20% for validation. After optimization and statistical testing, the selected thematic layers were integrated to produce a susceptibility map. The results indicate that 6.3% (0.7 km²) of the study area is classified as very highly susceptible. The proportion of the sample (61.2%) in this class had a frequency ratio estimated to be 20.2. Among the predictive indicators, altitude, slope, SE, S, NW, and NDVI were found to have a positive impact on landslide occurrence. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), demonstrating strong predictive capability. These findings can support informed land-use planning and risk reduction strategies in urban areas. Furthermore, the prediction model should be communicated to and understood by local authorities to facilitate disaster management. The cost function was adopted as a novel approach to delineate hazardous zones. Considering the landslide inventory period, the increasing hazard due to climate change, and the intensification of human activities, a reasoned choice of sample size was made. This informed decision enabled the production of an updated prediction map. Optimal thresholds were then derived to classify areas into high- and low-susceptibility categories. The prediction map will be useful to planners in helping them make decisions and implement protective measures. Full article

This study assesses the accuracy of flood extent predictions in five U.S. watersheds. We generated flood maps for four return periods using various digital elevation models (DEMs)—FABDEM, SRTM, ALOS, and USGS 3DEP—and two versions of the GEOGLOWS River Forecast System (RFS) hydrography. These comparisons are notable because they build on operational global hydrology models so subsequent work can develop global modeled flood products. Models were made using the Automated Rating Curve (ARC) and Curve2Flood tools. Accuracy was measured against USGS reference maps using the F-statistic. Our results show that flood map accuracy generally increased with higher return periods. The most consistent and reliable improvements in accuracy occurred when both the DEM and hydrography datasets were upgraded to higher-resolution sources. While DEM improvements generally had a greater impact, hydrography refinements were more important for lower return periods when flood extents were the smallest. Generally, DEM resolution improved accuracy metrics more as the return period increased and hydrography and bare earth DEMs mattered more as the return period decreased. There was a 38.9% increase in the mean F-statistic between the two principal pairings of interest (FABDEM-RFS2 and SRTM 30 m DEM-RFS1). FABDEM’s bare-earth representation combined with RFS2 sometimes outperformed higher-resolution non-bare-earth DEMs, suggesting that there remains a need for site-specific investigation. Using ARC and Curve2Flood with FABDEM and RFS2 is a suitable baseline combination for general flood extent application. Full article

This study comprehensively compares the performance of two non-destructive testing (NDT) techniques—active thermography (AT) and digital shearography (DS)—for identifying various damage types in composite structures. Three distinct composite specimens were inspected: a carbon-fiber-reinforced polymer (CFRP) plate with flat-bottom holes, an aluminum honeycomb core sandwich plate with a circular skin-core disbond, and a CFRP plate with two low-energy impacts damage. The research highlights the significant role of post-processing methods in enhancing damage detectability. For AT, algorithms such as fast Fourier transform (FFT) for temperature phase extraction and principal component thermography (PCT) for identifying significant temperature components were employed, generally making anomalies brighter and easier to locate and size. For DS, a novel band-pass filtering approach applied to phase maps, followed by summing the filtered maps, remarkably improved the visualization and precision of damage-induced anomalies by suppressing background noise. Qualitative image-based comparisons revealed that DS consistently demonstrated superior performance. The sum of DS filtered phase maps provided more detailed and precise information regarding damage location and size compared to both pulsed thermography (PT) and lock-in thermography (LT) temperature phase and amplitude. Notably, DS effectively identified shallow flat-bottom holes and subtle imperfections that AT struggled to clearly resolve, and it provided a more comprehensive representation of the impacts damage location and extent. This enhanced capability of DS is attributed to the novel phase map filtering approach, which significantly improves damage identification compared to the thermogram post-processing methods used for AT. Full article

Based on the limited hepatic hydroxylation efficiency of dietary VD3 in teleosts and the superior bioavailability of its metabolite, 25(OH)D3, this study investigated the regulatory mechanisms of dietary 25(OH)D3 supplementation in yellow catfish—an economically significant species lacking prior nutritional data on this metabolite. A total of 360 fish were divided into three groups—control (basal diet), VD3 (2500 IU/kg VD3), and 25(OH)D3 (2500 IU/kg 25(OH)D3)—and fed for 8 weeks. Compared to the control, both supplemented groups showed elevated superoxide dismutase (SOD), total antioxidant capacity (T-AOC), catalase (CAT), and transforming growth factor-β (TGF-β) activities, alongside reduced malondialdehyde (MDA), interleukin-1β (IL-1β), and tumor necrosis factor-α (TNF-α) levels. The 25(OH)D3 group exhibited higher T-AOC and CAT activities and lower TNF-α than the VD3 group. Metabolomic and transcriptomic analyses identified 65 differentially expressed metabolites (DEMs) and 3515 differentially expressed genes (DEGs). Enrichment analysis indicated that the DEMs (e.g., indole compounds, organic acids, aldosterone, L-kynurenine) and DEGs (pgd, mthfr, nsdhl, nox5, prdx2, mpx, itih2, itih3, eprs1) that were highly and significantly expressed in the 25(OH)D3 group were primarily associated with antioxidant defense and inflammatory responses. Dietary 25(OH)D3 was more effective than VD3 in promoting antioxidant capacity and modulating inflammation in yellow catfish. Full article

Aiming at the problems of the high multiple- and missed-seeding index and low operation efficiency of current mechanical potato seed-meters in minituber sowing, this study designed an air-suction roller-type minituber seed-metering device for minitubers (mass between 2 and 4 g) in accordance with the agronomic standards for potato cultivation in the single-cropping area of northern China. An account of the device’s structure and operational principle was made, its working process was theoretically analysed, and the three main factors affecting the airflow suction were determined: the seed roller speed, the suction seeding hole diameter, and the air inlet negative pressure. This study adopted the fluid dynamics simulation method and determined that the ideal location of the air inlet was 30° for horizontal inclination and 60° for vertical inclination. Then, based on the CFD-DEM fluid-structure coupling simulation method, the impact of a range of factors on the functionality of the seed-metering device under different conditions was studied and verification tests were carried out. Design-Expert was used to analyse test results. The results showed that when the pressure at the air inlet was −7000 Pa, the speed of the seeding roller was 40.2 r·min⁻¹, the suction seeding hole diameter was 10.37 mm, and the performance was optimal: the qualified index was 92.95%, the multiple-seeding index was 4.16%, and the missed-seeding index was 2.89%. The research results show that the seed-metering device developed under this scheme exhibited satisfactory seeding performance during operation and was able to meet the demands of minituber sowing. Full article

Unmanned Aerial Vehicles (UAVs) face significant challenges in global path planning within complex terrains, as traditional algorithms (e.g., A*, PSO, APF) struggle to balance computational efficiency, path optimality, and safety. This study proposes a Voronoi–A* fusion algorithm, combining Voronoi-vertex-based rapid trajectory generation with A* supplementary expansion for enhanced performance. First, an adaptive DEM layering strategy divides the terrain into horizontal planes based on obstacle density, reducing computational complexity while preserving 3D flexibility. The Voronoi vertices within each layer serve as a sparse waypoint network, with greedy heuristic prioritizing vertices that ensure safety margins, directional coherence, and goal proximity. For unresolved segments, A* performs localized searches to ensure complete connectivity. Finally, a line-segment interpolation search further optimizes the path to minimize both length and turning maneuvers. Simulations in mountainous environments demonstrate superior performance over traditional methods in terms of path planning success rates, path optimality, and computation. Our framework excels in real-time scenarios, such as disaster rescue and logistics, although it assumes static environments and trades slight path elongation for robustness. Future research should integrate dynamic obstacle avoidance and weather impact analysis to enhance adaptability in real-world conditions. Full article

UAV platforms equipped with RTK positioning and LiDAR sensors are increasingly used for landslide monitoring, offering frequent, high-resolution surveys with broad spatial coverage. In this study, we applied high-frequency UAV-based monitoring to the active Baldiola earthflow (Northern Apennines, Italy), integrating 10 UAV–LiDAR and photogrammetric surveys, acquired at average intervals of 14 days over a four-month period. UAV-derived orthophotos and DEMs supported displacement analysis through homologous point tracking (HPT), with robotic total station measurements serving as ground-truth data for validation. DEMs were also used for multi-temporal DEM of Difference (DoD) analysis to assess elevation changes and identify depletion and accumulation patterns. Displacement trends derived from HPT showed strong agreement with RTS data in both horizontal (R² = 0.98) and vertical (R² = 0.94) components, with cumulative displacements ranging from 2 m to over 40 m between April and August 2024. DoD analysis further supported the interpretation of slope processes, revealing sector-specific reactivations and material redistribution. UAV-based monitoring provided accurate displacement measurements, operational flexibility, and spatially complete datasets, supporting its use as a reliable and scalable tool for landslide analysis. The results support its potential as a stand-alone solution for both monitoring and emergency response applications. Full article