Search Results (3,767)

To elucidate the contact performance and friction force variation characteristics of VL seals for aviation actuators under high-pressure conditions, this study adopted a fluid–structure interaction (FSI)-coupled finite element model to analyze the maximum contact pressure and contact width and their respective variation trends across varying oil pressures and reciprocating velocities. Subsequently, friction force tests of the seals were conducted under matching operating parameters, and the friction coefficients of polytetrafluoroethylene (PTFE) were measured and compared under different normal pressures. The results demonstrate that the friction force of the seals during both extending and retracting strokes increases with rising oil pressure, which is highly correlated with the theoretically predicted conclusion that the seal contact width expands as oil pressure increases. Further analysis confirms that reciprocating velocity exerts no significant influence on the aforementioned variation trends. This study provides a critical basis for the selection and optimal design of VL seals used in high-pressure aviation hydraulic actuators. Full article

In the field of logistics distribution, the two-echelon vehicle routing problem has long been a critical focus. Against the backdrop of global warming, enterprises conducting logistics operations must now prioritize not only delivery costs but also the environmental impact of carbon emissions. To address these challenges, this study integrates occasional drivers into the two-echelon vehicle routing framework, centering on carbon emission reduction. First, Affinity Propagation (AP) clustering is applied to assign customer points to transfer centers. Subsequently, an optimization model is formulated to minimize both vehicle routing costs and carbon emission costs through a collaborative delivery system involving specialized and crowdsourced vehicles. An enhanced Sparrow–Whale Optimization Algorithm (S-WOA) is proposed to solve the model. The algorithm is tested against traditional heuristic methods on three datasets of different scales. Experimental results demonstrate that the two-echelon logistics and distribution model combining specialized vehicles and occasional drivers achieves a significant reduction in total delivery costs compared to models relying solely on specialized vehicles. Further analysis reveals that, with a fixed crowdsourced compensation coefficient, increasing the crowdsourced detour coefficient leads to a decline in total delivery costs. Conversely, when the detour coefficient remains constant, raising the compensation coefficient results in an upward trend in total costs. These insights provide actionable strategies for optimizing cost-efficiency and sustainability in logistics operations. Full article

Against the backdrop of carbon quota trading policies and Energy Performance Contracting (EPC), Energy Service Companies (ESCOs) engage in supply chain emission reduction via embedded low-carbon services. However, the impact mechanism of their financing mode selection on emission reduction efficiency and economic benefits has not been fully revealed, and there is a lack of support from a systematic theoretical and engineering design framework. Therefore, this study innovatively constructs a multi-agent Stackelberg game model with bank financing, green bond financing, and internal factoring financing. We incorporate the embedding degree, emission reduction cost coefficient, and financing mode selection into a unified analysis framework. The research findings are as follows: (1) There is a significant positive linear relationship between supply chain profit and the embedding degree. In contrast, the profit of ESCOs shows an inverted “U-shaped” change trend. Moreover, there is a sustainable cooperation threshold for each of the three financing modes. (2) Green bond financing can significantly increase the overall emission reduction rate of the industrial supply chain in high-embedding-degree scenarios. However, due to emission reduction investment cost pressure, ESCOs tend to choose bank financing. (3) The dynamic change of the emission reduction investment cost coefficient will trigger a reversal effect on the financing preferences of the supply chain and ESCOs. This study unveils the internal mechanism of multi-party decision-making in the low-carbon industrial supply chain and is supported by cross-country institutional evidence and comparative case-based analysis, providing a scientific basis and engineering design guidance for optimizing ESCO financing strategies, crafting incentive contracts, and enhancing government subsidy policies. Full article

The Chongming Dongtan wetland, a representative coastal wetland in East Asia, faces a significant ecological threat from the invasive species Spartina alterniflora. The mixed ecotone formed between this invasive species and the native Phragmites australis serves as a highly sensitive and critical indicator of alterations in wetland ecosystem structure and function. Using spring and autumn Sentinel-2 imagery from 2016 to 2023, this study developed an integrated method that combines a three-dimensional feature space with multi-threshold Otsu segmentation to accurately extract the mixed S. alterniflora–P. australis ecotone. The spatiotemporal dynamics of the mixed ecotone were analyzed at multiple temporal scales using a centroid migration model and a newly defined Seasonal Area Ratio (SAR) index. The results suggest that: (1) Near-infrared reflectance and NDVI were identified as the optimal spectral indices for spring and autumn, respectively. This approach led to a classification achieving an overall accuracy of 87.3 ± 1.4% and a Kappa coefficient of 0.84 ± 0.02. Notably, the mixed ecotone was mapped with producers’ and users’ accuracies of 85.2% and 83.6%. (2) The vegetation followed a distinct land-to-sea ecological sequence of “pure P. australis–mixed ecotone–pure S. alterniflora”, predominantly distributed as an east–west trending belt. This pattern was fragmented by tidal creeks and micro-topography in the northwest, contrasting with geometrically regular linear features in the central area, indicative of human engineering. (3) The ecotone showed continuous seaward expansion from 2016 to 2023. Spring exhibited a consistent annual area growth of 13.93% and a stable seaward centroid migration, whereas autumn exhibited significant intra-annual fluctuations in both area and centroid, likely influenced by extreme climate events. (4) Analysis using the Seasonal Area Ratio (SAR) index, defined as the ratio of autumn to spring ecotone area, revealed a clear transition in the seasonal competition pattern in 2017, initiating a seven-year spring-dominant phase after a single year of autumn dominance. This spring-dominated era exhibited a distinctive sawtooth fluctuation pattern, indicative of competitive dynamics arising from the phenological advancement of P. australis combined with the niche penetration of S. alterniflora. This study elucidates the multiscale competition mechanisms between S. alterniflora and P. australis, thereby providing a scientific basis for effective invasive species control and ecological restoration in coastal wetlands. Full article

Crop growth and yield are determined by multiple factors, including genotype, environment, and their interactions. The assimilation of remote sensing data with crop growth modeling represents a significant trend for crop monitoring and yield estimation. This study aims to explore an effective data fusion method for estimating soybean yield by utilizing canopy remote sensing data and crop growth models. Based on field experiment data, remote sensing retrieval models for the leaf area index (LAI) and leaf nitrogen accumulation (LNA) were developed using the Principal Component Analysis–Ridge Regression (PCA–Ridge) algorithm. Using remotely sensed estimates as state variables in the DSSAT model, the results indicated that, compared with using only the LAI (V_LAI) or only LNA (V_LNA), the accuracy of soybean yield estimation was superior when both the LAI and LNA (V_LAI+LNA) were used as state variables. Additionally, the Nash–Sutcliffe efficiency (NSE) coefficient was a viable optimization function in optimizing the state variables. In conclusion, these results indicate that assimilating two key physiological and biochemical parameters for soybean, derived from hyperspectral data, with crop growth models provides a viable approach for enhancing the precision of estimating the LAI, LNA, and yield. Full article

Comprehensive monitoring of gas extraction parameters is crucial for the safe production of coal mines. However, it is a challenge to collect the overall gas drainage network parameters with limited sensors due to technical and econoincorporating mic constraints. To address this issue, a nonlinear model for gas confluence structure is construed for the conservation of mass, energy, and gas state properties. Considering exogenous variables such as frictional loss correction coefficient (α) and air leakage resistance coefficient (β), as well as the iterative structure of drainage networks, a hybrid PSO–Newton algorithm framework is designed. This framework realizes iterative solutions for multi confluence structures by combining global optimization (PSO) and local nonlinear solving (Newton’s method). A case study using historical monitoring data from the 11,306 working face of S Coal Mine was conducted to evaluate the proposed algorithm at both branch and drill field scale. The results show that key parameters such as gas flow velocity, concentration, and density align with actual observation trends, with most deviations within 10%, verifying the accuracy and effectiveness of the algorithm. A deviation comparison between the standalone Newton’s method and the PSO–Newton algorithm further demonstrates the stability of the latter. By enabling the derivation of comprehensive network parameters from limited monitoring data, this study provides strong support for the intelligent management of coal mine gas extraction. Full article

This study analyzed the phenotypic and internal fruit quality diversity of six superior Nai plum trees to provide detailed phenotypic profiles and preliminary relational hypotheses, supporting superior genotype re-selection for breeding. Using leaves and mature fruits, we conducted diversity, correlation, and principal component analysis (PCA) on all quantitative traits. The average Shannon–Wiener index (H′) for qualitative traits was 0.543, and the average coefficient of variation for quantitative traits was 19.98%. Correlation analysis revealed complex trait relationships, including the synchronous variation between the total number of soluble solids (TSS) and reducing sugars (RS) or soluble sugars (SS) and the opposite trends between the TSS and potassium (K), magnesium (Mg), or soluble protein (SP). PCA extracted four principal components (cumulative contribution: 91.074%) from all traits. Based on factor scores, S6 ranked highest, indicating its potential as a comprehensive candidate. The findings offer a theoretical basis for Nai plum cultivation and breeding. Full article

In regions lacking sufficient data, remote sensing (RS) offers a reliable alternative for precipitation estimation, enabling more effective drought management. This study comprehensively evaluates four commonly used RS datasets—Climate Hazards Center InfraRed Precipitation with Station data (CHIRPS), Tropical Applications of Meteorology using Satellite data (TAMSAT), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), and Multi-Source Weighted-Ensemble Precipitation (MSWEP) against ground-based data—with respect to their performance in detecting precipitation and drought patterns in the Great Ruaha River Basin (GRRB), Tanzania (1983–2020). Statistical metrics including the Pearson correlation coefficient (r), mean error (ME), root mean square error (RMSE), and bias were employed to assess the performance at daily, monthly, seasonal (wet/dry), and annual timescales. Most of the RS products exhibited lower correlations (r < 0.5) at daily timestep and low RMSE, bias, and ME. Monthly performance improved substantially (r > 0.8 at most stations) particularly during the wet season (r = 0.52–0.82) while annual and dry-season performance declined (r < 0.5 and r < 0.3, respectively). Performance under RMSE, bias, and ME declined at higher timescales, particularly during the wet season and annually. CHIRPS, MSWEP, and PERSIANN generally overestimated precipitation while TAMSAT consistently underestimated it. Spatially, CHIRPS and MSWEP reproduced coherent basin-scale patterns of drought persistence, with longer dry-spells concentrated in the northern, central, and western parts of the basin and shorter dry-spells in the eastern and southern regions. Trend analysis further revealed that most products captured consistent large-scale changes in dry-spell characteristics, although localized drought events were more variably detected. CHIRPS and MSWEP showed superior performance especially in capturing monthly precipitation patterns and major drought events in the basin. Most products struggled to detect extreme dry conditions with the exception of CHIRPS and MSWEP at certain stations and periods. Based on these findings, CHIRPS and MSWEP are recommended for drought monitoring and water resource planning in the GRRB. Their appropriate use can help water managers make informed decisions, promote sustainable resource use, and strengthen resilience to extreme weather events. Full article

Aimed at improving the mechanical performance of welded joints in stainless steel composite materials, this research investigates the evolutionary characteristics of microstructure at the interface between the transition layer weld and base layer weld through electron backscatter diffraction (EBSD) and X-ray diffraction (XRD) analytical techniques. In addition, molecular dynamics simulation methods are employed to conduct an in-depth study on the atomic diffusion behavior during the welding process. The results show that carbon and chromium atoms undergo asymmetric diffusion at the interface, forming a decarburized and a carburized zone. The diffusion coefficient of carbon atoms was the largest, with the diffusion mechanism being interstitial diffusion. Followed by chromium atoms, the diffusion coefficient of Fe was the smallest. On the base layer weld side, two structural zones with different grain sizes were formed; the zone close to the interface was a coarse ferrite microstructure with the lower geometrically necessary dislocation density, the zone far from the interface was a finer-grained ferrite and pearlite microstructure. As the welding heat input of the transition layer weld increases, the average density of geometrically necessary dislocations, the decarburized layer thickness, the average grain size, and the diffusion coefficients of Cr and C atoms at the interface all exhibit a concomitant upward trend. Concurrently, a carbon–chromium compound precipitates at the interface. Full article

This study investigates the vehicle load transfer mechanism and proposes a simplified design method for simply supported reinforced concrete skewed T-girder bridges. Skewed bridges are often necessary due to obstacles in route selection, yet their mechanical behavior under existing design specifications remains inadequately addressed. Theoretical analysis reveals that skewed bridges exhibit a pronounced bending–torsional coupling effect and a rotation trend within the plane, resulting in the maximum bending moment shifting toward the obtuse-angle side and midspan moments decreasing. A refined numerical model utilizing the grillage method is established to validate the theoretical analysis results, demonstrating that load transfer paths deviate perpendicularly from the free edge as the skew angle increases. The bearing force of the skewed bridge with a skew angle of 30° is about 1.35 times that of the straight bridge. To address the lack of practical design methods, a mixed influence line method is proposed. This approach combines the lever principal method and the rigid plate girder method, interpolating transverse distribution coefficients along the span based on the skew angle. The proposed method accounts for the lateral stiffness and skew effects of skewed bridges, and the accuracy is confirmed by field load experimental and numerical validations. It is found that the mid-span bending moment of the straight bridge can be approximately adopted when the skew angle is less than 30°. The reduction coefficient of the bending moment with skew angles of 30° to 45 ° can be safely taken as 0.85 to 0.95. Full article

As a primary economic engine and strategic region in China, the development of the green building industry in the Yangtze River Economic Belt (YREB) holds demonstrative significance for the low-carbon transition of the country’s construction sector. Utilizing panel data from 11 provinces and municipalities within the YREB during 2012–2022, this study constructs a comprehensive evaluation index system to measure the coupling coordination degree (CCD) between the green building industry and the development environment. The spatio-temporal evolution of the CCD is analyzed using methods including kernel density estimation, the Dagum Gini coefficient, spatial autocorrelation, and standard deviational ellipse. A fixed-effects model is further employed to identify its influencing factors. The results show that (1) both the green building industry and its development environment in the YREB exhibited upward trends, with the gap between them gradually narrowing. (2) The CCD across provinces and municipalities showed an overall upward trend, characterized by simultaneous “overall improvement” and “internal gradient differentiation” in spatio-temporal distribution, and displayed a spatial pattern of “higher values in the east and lower in the west.” (3) Urbanization level, government regulation, technological innovation, and consumption capacity exerted significant positive effects on the CCD, whereas the influence of education level and public environmental awareness remained insignificant. This study provides insights for formulating differentiated regional policies and optimizing the development environment for the green building industry. Full article

Under deep mining conditions, coal and rock masses are subjected to high in situ stress and strong mining-induced disturbances, leading to intensified stress unloading, concentration, and redistribution processes. The stability of surrounding rock is therefore closely related to mine safety. Direct, real-time, and continuous monitoring of in situ stress magnitude, orientation, and evolution is a critical requirement for deep underground engineering. To overcome the limitations of conventional stress monitoring methods under high-stress and strong-disturbance conditions, a novel in situ stress monitoring device was developed, and its performance was systematically verified through laboratory experiments. Typical unloading–reloading and biaxial unequal stress paths of deep surrounding rock were adopted. Tests were conducted on intact specimens and specimens with initial damage levels of 30%, 50%, and 70% to evaluate monitoring performance under different degradation conditions. The results show that the device can stably acquire strain signals throughout the entire loading–unloading process. The inverted monitoring stress exhibits high consistency with the loading system in terms of evolution trends and peak stress positions, with peak stress errors below 5% and correlation coefficients (R²) exceeding 0.95. Although more serious initial damage increases high-frequency fluctuations in the monitoring curves, the overall evolution pattern and unloading response remain stable. Combined acoustic emission results further confirm the reliability of the monitoring outcomes. These findings demonstrate that the proposed device enables accurate and dynamic in situ stress monitoring under deep mining conditions, providing a practical technical approach for surrounding rock stability analysis and disaster prevention. Full article

Three sizes of copper nanoparticles (1.7 nm, 2.8 nm, 3.4 nm) were synthesized using N902 as a surface-modifying ligand and diesel as the solvent. These nanoparticles were incorporated into biodiesel at volume fractions ranging from 0.005% to 0.20%, and their impacts on the lubrication performance, combustion characteristics, and thermal behavior of biodiesel were systematically investigated. The results indicated that the addition of copper nanoparticles significantly reduced the friction coefficient and wear scar diameter. Specifically, the 1.7 nm Cu nanoparticle sample achieved the most remarkable friction-reducing and anti-wear effects, with the friction coefficient and wear scar diameter decreasing by 16.07% and 20.1%, respectively. The combustion heat value of biodiesel showed a “first increase and then decrease” trend with the increase in nanoparticle addition, with the most significant improvement observed at an addition level of 0.01%. Among the three particle sizes, the 2.8 nm Cu nanoparticle sample effectively promoted the pyrolysis of biodiesel, while the 1.7 nm Cu nanoparticle sample exhibited optimal performance in reducing the oxidation induction time (OIT) and achieving complete combustion—characterized by lower CO emissions and minimal O₂ residue after combustion. Overall, the incorporation of copper nanoparticles realizes a synergistic enhancement, where lubricity improvement and combustion promotion occur concurrently, reflected by reduced OIT, lower CO emissions, and lower O₂ residue. Full article

Levees with double-layered foundations are characterized by a weakly permeable upper layer and a highly permeable sand layer beneath, which makes them susceptible to internal erosion, particularly backward erosion piping (BEP). Therefore, locating BEP channels before the failure of a levee is crucial for ensuring the safety of levee projects. In this study, a novel method is proposed for detecting BEP channels efficiently. This method involves applying the successive linear estimator (SLE) to fuse multipoint measured voltage to characterize the inner levee structure. Therefore, the BEP channels can be recognized from the details of the levee structure. This method is named three-dimensional geostatistical electrical resistivity tomography (3D GERT) in this study. To validate the performance of GERT, a custom-developed indoor sandbox device was used for physical BEP conductivity detection tests, and the results were analyzed via the SLE to assess the accuracy of channel engraving. The tests revealed that the surface sand was initially expelled from the piping exit, followed by the formation of a concentrated piping channel that extended upstream. The erosion depth at the piping exit was observed to be deeper than that of the main channel. This study demonstrated that 3D GERT, when the SLE was used as the inversion algorithm, detected BEP channels and achieved an internal erosion dimension deviation of less than 25.5% and a positional erosion dimension deviation within 16.5%. The accuracy of the SLE in mapping BEP channels improved with the use of a more comprehensive electrode distribution and an increased number of electrodes, thus yielding a more precise representation of the channel scale and pattern. The coefficient of determination (R²) between the acquired data and the simulated data generated by 3D GERT was greater than 0.85, demonstrating the capability of the simulated values to track and reproduce the variation trends observed in the acquired data. Thus, the SLE, when used as the inversion algorithm for 3D GERT, reliably represents BEP channels. Full article

Accurately quantifying the ecological functions of small and micro green spaces in high density urban environments supports urban ecological planning and management. This study assessed 271 pocket parks in the main urban area of Fuzhou, China, using multi-source remote sensing data from the growing seasons of 2019 to 2024. Six indicators were derived, including NDVI, NPP, WET, NDBSI, ISI, and LST. A composite Eco-environmental Index (EEI) was constructed using the entropy weight method. We combined the coefficient of variation, Theil–Sen slope estimation, the Mann–Kendall test, and the Hurst exponent to quantify spatial heterogeneity, interannual stability, and short-term persistence. We also examined climatic associations using correlation analysis. Pocket parks consistently outperformed their surrounding 500 m buffers across all indicators, and park buffer contrasts increased for most indicators. The mean EEI significantly increased from 0.563 in 2019 to 0.650 in 2024, with a pronounced step increase around 2022. At the site level, 261 of 271 parks (96.3%) exhibited an upward trend in EEI, indicating widespread ecological improvement. Specifically, park vegetation greenness (NDVI) rose from 0.413 to 0.578, widening the gap with surrounding areas. Parks consistently maintained a lower land surface temperature (LST) than their buffers, with a cooling magnitude ranging from 3.5 °C to 4.6 °C. Precipitation was positively associated with NDVI and NPP, while LST was positively associated with air temperature and negatively associated with precipitation. These findings support the planning and adaptive management of pocket parks to strengthen urban ecological resilience. Full article