The introduction of chlorine atoms into the main chain of chloroprene rubber (CR) strengthens intermolecular interactions, restricts molecular?chain mobility, and gives this rubber strong polarity. At low temperatures, molecular motion slows, causing CR molecular chains to arrange more regularly and crystallize, which increases hardness and reduces elasticity. To improve the low?temperature resistance of CR, the green low?temperature plasticizer tributyl citrate (TBC) was introduced for modification. The effects of TBC mass fraction on the vulcanization characteristics, Mooney viscosity, mechanical properties, glass?transition temperature (Tg), and brittle temperature (Tb) of CR composites were investigated. The results show that, with increasing TBC mass fraction, the Mooney viscosity of the CR compound decreases significantly, scorch time is prolonged, and the processing performance and low?temperature resistance of the vulcanizate are significantly improved. When the TBC mass fraction is 5%, the tensile strength of CR reaches its maximum value of 12.16 MPa, resilience reaches its maximum value of 50.65%, permanent compression set decreases to its minimum value of 9.64%, elongation at break increases to 497.59%, and Tg decreases to -34.5 ℃. These results indicate that the modified CR exhibits simultaneous improvements in low?temperature resistance and mechanical properties, thereby expanding its applicability under low?temperature operating conditions.
Using Ce(NO3)3·6H2O, Cu(NO3)2·3H2O, and SnCl4·5H2O as raw materials, and NaOH as the precipitant, CuSnCe⁃C, CuSnCe⁃PI, and CuSnCe⁃CH catalysts were prepared by co⁃precipitation, precipitation⁃impregnation, and co⁃precipitation⁃hydrothermal methods, respectively. The catalysts were characterized using characterization techniques such as XRD, BET, H2⁃TPR, and XPS, and their CO preferential oxidation performance was evaluated under a hydrogen⁃rich atmosphere. The results show that changes in preparation methods significantly affect the physical and chemical properties as well as the catalytic performance of the catalysts. Among them, the CuSnCe⁃CH catalyst prepared by the co⁃precipitation⁃hydrothermal method exhibits the best catalytic performance. Under atmospheric pressure, at a reaction temperature of 140 ℃, an oxygen excess factor of 2.6, and a mass space velocity of 20 244 mL/(g·h), the CO conversion rate reaches a maximum of 94.9%, with a CO oxidation selectivity of 43.2%. Consistent with the characterization results,catalysts with smaller average grain size, larger specific surface area, higher CuO dispersion, lower reduction temperature, and higher oxygen vacancy content exhibit the best CO preferential oxidation performance.
To address the poor wettability between the reinforcing phases and the aluminum matrix, as well as the tendency to form brittle Al4C3 phase during the preparation of (B4C+Cf)/Al composites, Ti particles with high melting point and immiscible with aluminum were used as the inducing infiltration agent, and chemical plating was also employed to coat the surface of carbon fibers with Cu. Thus the efficient and low?cost near?final forming preparation of this composite material was achieved through the metal?induced in?situ reactive infiltration technology. (B4C+Cf)/Al composite materials were prepared by holding at 850 ℃, 900 ℃, and 950 ℃ for 90 minutes, respectively. The microstructure, produced phases, compressive properties, and bending resistance of the composites were characterized using SEM, XRD, and a universal testing machine respectively. The results show that the aluminum melt can successfully infiltrate the ceramic preform to produce lightweight aluminum matrix composites with a density ranging from 2.80 g/cm3 to 2.85 g/cm3. XRD test on the composites revealed the presence of Al, B4C, AlB2, Al3BC, TiB2, and TiC phases, but no brittle Al4C3 phase was observed. As the preparation temperature increased from 850 ℃ to 950 ℃, the compressive strength of the composites decreased from 290 MPa to 172 MPa, while the bending strength increased from 233.69 MPa to 375.44 MPa. The bending fracture morphology of the composites indicates that the higher the preparation temperature, the more tear edges are present in the prepared composites, and the location where cracks initiate gradually shifts from the interface between the reinforcing phases and the matrix to the interior of the matrix or the reinforcing phases.
Using calcium carbide slag as raw material and isocaprylic acid as the calcium extraction agent, nano calcium carbonate was prepared through CO2 carbonization and characterized. Under the conditions of 80% saponification rate, 80 ℃ saponification temperature, 40 min saponification time, 80 ℃decomposition temperature, 60 min decomposition time, 0.5 mol/L calcium chloride concentration, and the volume ratio of the oil phase to the water phase is 2.0∶1.0, the extraction rate of calcium ions from calcium carbide slag reached 96.40%. Nano calcium carbonate was then prepared using the gas?liquid carbonization method. The optimal carbonization efficiency was achieved at a reaction temperature of 6 ℃, stirring speed of 400 r/min, liquid droplet rate of 35 mL/min, and CO2 flow rate of 100 mL/min. Characterization by X?ray fluorescence spectroscopy, X?ray diffraction, and scanning electron microscopy showed that the nano calcium carbonate product was of the calcite type, with a particle size of 78.8 nm, calcium content was 94.10%, and uniform particle size. This study optimizes the process of producing nano calcium carbonate from calcium carbide slag, enabling high?value reuse of solid waste and CO2 emission reduction, providing new insights for the preparation of nano calcium carbonate products.
To address concentration stratification during pipeline transportation of hydrogen?blended natural gas and improve mixing efficiency over short distances, a multicomponent turbulent?flow model was established using computational fluid dynamics. The mixing characteristics, flow?field evolution, and pressure loss of three spiral static mixer structures?right?handed blades, crossed blades, and crossed perforated blades were compared. The coefficient of variation and mixing uniformity were used as quantitative indicators for comprehensive evaluation. The results show that the crossed perforated?blade structure satisfies industrial mixing requirements (uniformity≥95%) within 2 m through the synergistic effects of swirl, jet flow, and secondary flow. The mixing uniformity reaches 99.66% at 5 m, with a concentration?mixing influence factor of 9.14 and a pressure loss of 189.3 Pa. It is concluded that the synergy among swirl, jet flow, and secondary flow is the core mechanism for achieving efficient short?distance mixing. The crossed perforated?blade structure significantly improves mixing efficiency while maintaining low?loss transportation. The findings provide a reference for the selection of static mixer structures.
Staged fracturing of horizontal wells is essential for the effective development of tight sandstone gas reservoirs with low porosity and low permeability, and rational optimization of fracturing treatment parameters is fundamental. The conventional "one-well, one-design" approach has been widely used; however, field practice shows that the correlation between treatment parameters and fracturing effectiveness under this approach is weak. The influence of individual parameters on stimulation performance remains unclear, and the method cannot accommodate the coexistence of multiple reservoir types in strongly heterogeneous tight sandstone gas reservoirs. Taking the JH block of the Jinqiu gas field as the study area, this paper proposes a new concept of "one-stage, one-design, segmented optimization" that considers reservoir quality and sandbody distribution. Following an integrated geology-engineering approach, an efficient design method for optimizing fracturing parameters in horizontal wells in tight sandstone gas reservoirs is established, including reservoir-type-specific optimization, treatment-stage classification, and target-well parameter optimization. A standardized design workflow that can be rapidly reused for different reservoir types is also developed. The results show that, compared with the conventional method, the proposed optimization method shortens the single?well fracturing design cycle by 50%-60%, reduces single?well fracturing cost by 10.6%, increases the post-fracturing stable-production period by 58.3%, and improves estimated ultimate recovery (EUR) by 15.6%. The method can effectively improve the scientific rigor and efficiency of fracturing-parameter optimization in strongly heterogeneous tight sandstone gas reservoirs and provides practical guidance for fracturing stimulation and development-benefit enhancement in reservoirs similar to the JH block.
Numerical simulations were performed to investigate non⁃uniform heat transfer of hydrogen in U⁃shaped microchannels under supercritical conditions. The effects of heat flux and pressure on heat⁃transfer characteristics were analyzed, the mechanism of abnormal heat transfer in non⁃uniform heat⁃flux channels was revealed, and a heat⁃transfer prediction correlation was fitted. The results indicate that, owing to variations in thermophysical properties, pressure and heat flux exhibit opposite effects on heat⁃transfer enhancement in the heating and cooling channels. In the non⁃uniform cooling channel, centrifugal force and buoyancy produce a synergistic effect that significantly promotes heat transfer. In contrast, in the heating channel governed only by centrifugal force, non⁃uniform heating suppresses heat transfer. The findings provide an important reference for the design optimization and theoretical study of supercritical⁃fluid heat⁃transfer systems in hydrogen⁃related applications.
This study systematically investigates the effects of the Cu atomic fraction on the mechanical properties and microscopic deformation mechanisms of FeNiCrCoCuₓ high⁃entropy alloys at 1 000 K using molecular dynamics simulations. The results show that, as the Cu atomic fraction increases, the yield stress decreases from 5.61 GPa to 4.99 GPa and Young's modulus decreases from 70.85 GPa to 53.86 GPa. In contrast, the fraction of atoms transformed from face⁃centered cubic (FCC) to hexagonal close⁃packed (HCP) structures decreases, while the frequency of dynamic recrystallization (DRX) increases significantly. The dislocation density is reduced, lattice distortion is relaxed, and the stress distribution becomes more uniform. Further analysis confirms that Cu addition lowers the stacking⁃fault energy and accelerates DRX, thereby markedly improving ductility without compromising high⁃temperature stability. These findings provide an atomic⁃scale theoretical basis for designing novel high⁃entropy alloys with both high strength and toughness and excellent heat resistance.
China has abundant heavy⁃oil resources, but their exploitation is challenging and field recovery is relatively low; therefore, improving recovery efficiency is important for ensuring stable petroleum production. Thermal recovery is widely used in heavy⁃oil production, and steam quality is a key parameter affecting thermal recovery performance. However, real⁃time in⁃situ direct measurement remains difficult. At present, domestic field measurements mainly rely on manual chemical titration, which has a significant time lag and cannot meet online real⁃time monitoring requirements. In this study, a new method for measuring wet saturated steam quality based on the matrix conductance principle is proposed. Under operating conditions of 17 MPa and 310 °C, a primary sensing element was designed for a steam⁃injection pipe with an inner diameter of 64 mm and an outer diameter of 89 mm. Material selection, system sealing, and fixture design were completed to ensure stable data acquisition and accurate measurement. An algorithmic model for the matrix conductance method was then established, and the parameters affecting steam quality were analyzed. The weighted discretization method and the conventional discretization method were compared through calculation and error analysis. The results show that the maximum relative error of the conventional discretization method reaches 11.5%, whereas weighted discretization method, with a maximum relative error of only 3.9%.The weighted discretization method therefore provides higher measurement accuracy than the conventional discretization method.
Small objects in UAV aerial images have low pixel proportions, are vulnerable to interference from complex backgrounds, and exhibit large scale variations, which often lead to missed detections and insufficient accuracy in existing methods. Therefore, an improved algorithm, YOLO11⁃RHO, is proposed for UAV aerial imagery based on YOLOv11. First, online convolutional re⁃parameterization (OREPA) with frequency⁃prior initialization is introduced into the backbone network to enhance the model's representation of high⁃frequency edge and texture information through spatial⁃frequency selectivity. Second, the RepNCSPELAN4_high module is used to optimize gradient propagation paths and construct a direct gradient pathway, thereby alleviating the attenuation of small⁃object features in deep network layers. Third, a hierarchical feature fusion block (HFFB) is integrated into the feature⁃fusion network. By combining a spatial⁃ and channel⁃decoupled adaptive attention mechanism, the block strengthens small⁃object representation and achieves multiscale information alignment. Finally, the overall architecture is designed for lightweight real⁃time deployment. Comparative and ablation experiments on the VisDrone2019 dataset show that the improved model achieves excellent performance, with mAP@0.5=0.401 and mAP@0.50∶0.95=0.245. It also maintains a lightweight architecture with 6.22 M parameters and 15.1 GFLOPs, effectively balancing high detection accuracy with real⁃time edge⁃device operation and satisfying practical end⁃side deployment requirements.
UNet has been widely applied to image segmentation tasks due to its encoder⁃decoder structure and skip⁃connection mechanism. However, traditional downsampling operations (such as max pooling or average pooling) tend to cause loss of spatial detail information during feature compression, while the simple reconstruction approach of the upsampling stage struggles to fully model global contextual semantics. These limitations constrain the network's expressive power and segmentation accuracy. To address this, this paper proposes an enhanced UNet architecture by introducing the Interactive Pooling Module (IPM) and the Global⁃Local Feature Interaction Module (GLFIM) during subsampling and upscaling stages, respectively, to strengthen feature modeling capabilities.Results indicate that in the encoder, the IPM simultaneously integrates max⁃pooling and average⁃pooling branches. Through channel interaction and feature fusion, it effectively enhances feature representation capabilities while preserving more structural and statistical information. In the decoder, the proposed Local Block extracts local details through residual convolutions, while the Global Block combines an attention mechanism based on adaptive pooling with an MLP network to model long⁃range dependencies and global semantic context. Experimental results demonstrate that our method exhibits significant advantages in preserving critical details and enhancing global semantic understanding, achieving superior segmentation performance compared to the standard UNet model. On the WHU dataset, IoU and F1 scores reached 90.73% and 95.14%, respectively.
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