Search Results (97)

In this cross-disciplinary investigation, we uncover a suite of previously unexamined factors and their intricate interplay that hold causal relationships with the distribution of Trachurus japonicus in the northern reaches of the South China Sea, thereby extending the existing research paradigms. Leveraging advanced machine learning algorithms and causal inference, our robust experimental design uncovered nine key global and regional factors affecting the distribution of T. japonicus density. A robust experimental design identified nine key factors significantly influencing this density: mean sea-level pressure (msl-0, msl-4), surface pressure (sp-0, sp-4), Summit ozone concentration (Ozone_sum), F10.7 solar flux index (F10.7_index), nitrate concentration at 20 m depth (N3M20), sonar-detected effective vertical range beneath the surface (Height), and survey month (Month). Crucially, stable causal relationships were identified among Ozone_sum, F10.7_index, Height, and N3M20. Variations in Ozone_sum likely impact surface UV radiation levels, influencing plankton dynamics (a primary food source) and potentially larval/juvenile fish survival. The F10.7_index, reflecting solar activity, may affect geomagnetic fields, potentially influencing the migration and orientation behavior of T. japonicus. N3M20 directly modulates primary productivity by limiting phytoplankton growth, thereby shaping the availability and distribution of prey organisms throughout the food web. Height defines the vertical habitat range acoustically detectable, intrinsically linking directly to the vertical distribution and availability of the fish stock itself. Surface pressures (msl-0/sp-0) and their lagged effects (msl-4/sp-4) significantly influence sea surface temperature profiles, ocean currents, and stratification, all critical determinants of suitable habitats and prey aggregation. The strong influence of Month predominantly reflects seasonal changes in water temperature, reproductive cycles, and associated shifts in nutrient supply and plankton blooms. Rigorous robustness checks (Data Subset and Random Common Cause Refutation) confirmed the reliability and consistency of these causal findings. This elucidation of the distinct biological and physical pathways linking these diverse factors leading to T. japonicus density provides a significantly improved foundation for predicting distribution patterns globally and offers concrete scientific insights for sustainable fishery management strategies. Full article

Quasicrystalline coatings based on Al₆₅Cu₂₀Fe₁₅ are of increasing interest as potential alternatives to conventional wear-resistant materials due to their unique structural and tribological properties. This study explores the influence of air pressure during high-velocity oxy-fuel (HVOF) spraying on the phase composition, morphology, and wear behavior of Al₆₅Cu₂₀Fe₁₅ coatings deposited on U8G tool steel. Coatings were applied at a fixed spraying distance of 350 mm using three air pressures (1.9, 2.1, and 2.3 bar), with constant propane (2.0 bar) and oxygen (2.1 bar) supply. X-ray diffraction analysis identified the formation of Al₇₈Cu₄₈Fe₁₄ and Al_0.5Fe_1.5 phases, while scanning electron microscopy revealed a dense, uniform microstructure with low porosity and homogeneous element distribution across all samples. Tribological testing using the ball-on-disk method showed wear track widths ranging from 853.47 to 952.50 µm, depending on the air pressure applied. These findings demonstrate that fine-tuning the air pressure during HVOF spraying significantly influences the structural characteristics and wear resistance of the resulting quasicrystalline coatings, highlighting their promise for advanced surface engineering applications. Full article

The timing accuracy of eLoran systems is susceptible to meteorological fluctuations, with medium-to-long-range propagation delay variations reaching hundreds of nanoseconds to microseconds. While conventional models have been widely adopted for short-range delay prediction, they fail to accurately characterize the coupled effects of multiple factors in long-range scenarios. This study theoretically examines the influence mechanisms of temperature, humidity, and atmospheric pressure on signal propagation delays, proposing a hybrid prediction model integrating meteorological data with a back-propagation neural network (BPNN) through path-weighted Pearson correlation coefficient analysis. Long-term observational data from multiple differential reference stations and meteorological stations reveal that short-term delay fluctuations strongly correlate with localized instantaneous humidity variations, whereas long-term trends are governed by cumulative temperature–humidity effects in regional environments. A multi-tier neural network architecture was developed, incorporating spatial analysis of propagation distance impacts on model accuracy. Experimental results demonstrate enhanced prediction stability in long-range scenarios. The proposed model provides an innovative tool for eLoran system delay correction, while establishing an interdisciplinary framework that bridges meteorological parameters with signal propagation characteristics. This methodology offers new perspectives for reliable timing solutions in global navigation satellite system (GNSS)-denied environments and advances our understanding of meteorological–electromagnetic wave interactions. Full article

To address the challenges in the collaborative control of strong mine pressure and surface damage during fully mechanized shallow soft coal seam top-coal caving mining, this study takes the 22,031 working face of Xindeng (Zhengzhou, China) Coal Mine as the research background. By combining analytical modeling and discrete-element granular flow simulation, this research elucidates how overburden fractures evolve and how the ground surface responds throughout the mining of shallow, soft coal seams. This research shows that the mechanical model analysis based on plate theory indicates that the first fracture of the immediate roof occurs 0.5 m from the goaf side of the mined-out area. Numerical simulations demonstrate that when the working face advances 80 m, the mining-induced influence extends to the surface. The displacement field of the overburden undergoes a dynamic temporal evolution law following the sequence of “rectangle–trapezoid” → “hyperbola-like” → “trapezoid”. During the advancement of the working face, the fracture pattern of the overburden evolves from “rectangle–trapezoid” to “trapezoid”, and the affected range on the surface transforms from an “inverted trapezoid” to a “trapezoid”. This study ultimately clarifies the dynamic law of collaborative deformation between the overburden and the surface, providing a theoretical basis for the safe mining of shallow coal seams, the prevention of roof accidents, and the optimization of mining technology. Full article

Swelling pressure is a key geotechnical property that influences the behaviour and stability of engineering structures built on expansive clayey soils. This pressure can be measured directly through laboratory tests or estimated using indirect methods. This paper analyses a dataset of undisturbed clay samples from southeastern Spain using advanced symbolic regression techniques, namely: deep symbolic regression (PhySO), high-performance symbolic regression (PySR), multi-objective symbolic regression (MOSR), and physics-guided symbolic regression (PGSR). These methods provide interpretable results as equations, unlike standard machine learning models. All generated equations showed high performance (R² > 0.91 and MAE < 23 kPa) and simplicity, making them suitable for practical engineering applications. PySR yielded the best overall metrics (R² = 0.933, MAE = 20.49 kPa), particularly excelling in high-pressure ranges, while PhySO demonstrated the most balanced performance, especially for low to medium pressures. MOSR minimized edge-case bias, and PGSR, despite lower overall performance, remained competitive. The plasticity index (PI) was identified as the most influential factor in all models, followed by the percentage of fines. The use of undisturbed samples enhanced the reliability of the findings, and the resulting equations enable a flexible estimation of swelling pressure based on commonly available geotechnical parameters. Full article

This study presents a pneumatic proportional pressure valve employing a silicon microfluidic chip (SMC) integrated with a V-shaped electrothermal microactuator, aiming to address the limitations of traditional solenoid-based valves in miniaturization and high-precision control. The SMC, fabricated via MEMS technology, leverages the thermal expansion of microactuator ribs to regulate pressure through adjustable orifices. A first-order transfer function between input voltage and displacement of the microactuator was derived through theoretical modeling and validated via COMSOL Multiphysics 5.2a simulations. Key geometric parameters of the actuator ribs—cross-section, number, inclination angle, width, span length and thickness—were analyzed for their influence on lever mechanism displacement, actuator displacement, static gain and time constant. AMESim 16.0-based simulations of single- and dual-chip valve structures revealed that increasing ζ shortens step-response rise time, while reducing τ improves hysteresis. Experimental validation confirmed the valve’s static and dynamic performance, achieving a step-response rise time of <40 ms, linearity within the 30–60% input voltage range, and effective tracking of sinusoidal control signals up to 8 Hz with a maximum pressure deviation of 0.015 MPa. The work underscores the potential of MEMS-based actuators in advancing compact pneumatic systems, offering a viable alternative to conventional solenoids. Key innovations include geometry-driven actuator optimization and dual-chip integration, providing insights into high-precision, low-cost pneumatic control solutions. Full article

Under the influence of climate change, extreme rainfall events (EREs) have become increasingly frequent. The urban waterlogging caused by these events has a particularly significant impact on cities with flat terrain and inadequate surface runoff dynamics. This study proposes a Coordinated Regulation of Storage and Discharge Mode (CRSD) tailored for plain cities. It establishes an evaluation system for CRSD based on regional rainwater flood carrying capacity, drainage capacity, and regional value, thereby assigning customized storage and drainage strategies to different urban areas. The model optimizes the relationship between storage and drainage across regions based on the fundamental principles of CRSD and establishes dynamic cross-regional water distribution rules according to optimization objectives. Finally, CRSD is validated using the MIKE models. The results indicate that as the rainfall return period increases, the area affected by urban waterlogging expands, though the proportion of waterlogging across various severity levels remains stable. CRSD can effectively alleviate urban waterlogging caused by EREs, with waterlogging reduction percentages ranging from 12.21% to 18.50%. Among the optimization schemes, Safe Consumption (SC) delivers the best overall performance, reducing waterlogging by up to 1.80 km² under 500 yr. The Average Pressure (AP) performs best in high-value areas, reducing waterlogging by up to 1.96 km² under the same return period. This study advances urban flood management by integrating cross-regional coordination mechanisms with blue–green–grey infrastructure, providing a replicable strategy for flatland cities to cope with the increasing challenges of EREs. Full article

The ongoing research in Environmental Scanning Electron Microscopy (ESEM) is contributed to in this paper. Specifically, this study investigates supersonic flow in a nozzle aperture under low-pressure conditions at the continuum mechanics boundary. This phenomenon is prevalent in the differentially pumped chamber of an ESEM, which separates two regions with a significant pressure gradient using an aperture with a pressure ratio of approximately 10:1 in the range of 10,000 to 100 Pa. The influence of nozzle wall roughness on the boundary layer characteristics and its subsequent impact on the oblique shock wave behavior, and consequently, on the static pressure distribution along the flow axis, is solved in this paper. It demonstrates the significant effect of varying inertial-to-viscous force ratios at low pressures on the resulting impact of roughness on the oblique shock wave characteristics. The resulting oblique shock wave distribution significantly affects the static pressure profile along the axis, which can substantially influence the scattering and loss of the primary electron beam traversing the differential pumping stage. This, in turn, affects the sharpness of the resulting image. The boundary layer within the nozzle plays a crucial role in determining the overall flow characteristics and indirectly affects beam scattering. This study examines the influence of surface roughness and quality of the manufactured nozzle on the resulting flow behavior. The initial results obtained from experimental measurements using pressure sensors, when compared to CFD simulation results, demonstrate the necessity of accurately setting roughness values in CFD calculations to ensure accurate results. The CFD simulation has been validated against experimental data, enabling further simulations. The research combines physical theory, CFD simulations, advanced experimental sensing techniques, and precision manufacturing technologies for the critical components of the experimental setup. Full article

Carasau bread (CB) is a traditional Sardinian flatbread with significant market potential, driving the need for advanced quality monitoring solutions in its production. Recent advancements in automation and engineering have enhanced process control, but a comprehensive understanding of CB dough properties remains essential. Dielectric spectroscopy (DS), particularly in the microwave (MW) range, has emerged as a non-destructive, cost-effective tool for food characterization, providing insights into microstructure and composition. MW DS has been applied to assess fermentation dynamics and ingredient influence in CB doughs, with previous studies modeling dielectric properties using a third-order Cole–Cole model up to 8.5 GHz and later extending to 20 GHz. Despite these advancements, the repeatability, reliability, and consistency of MW DS measurements on CB doughs have not been systematically assessed. This study aims to fill this gap by analyzing MW DS measurements on ten CB dough samples with standard composition (water 50%, yeast 1.5%, salt 1.5%) in the 0.5–6 GHz range, both before and after leavening, for 10 different samples and a total of 100 measurements. Even though the correlation between spectra is high, and even if the coefficient of variation is below 5% before leavening, the z-score analysis and the kernel density estimation highlighted that the distribution of dielectric data is heterogeneous, showing that variability across samples exists, especially after leavening. Finally, the influence of pressure, temperature, and relative humidity was excluded. This statistical evaluation of MW DS measurement provided critical insights into the robustness of MW DS for industrial applications. Full article

Kármán vortex streets are quintessential phenomena in fluid dynamics, manifested by the periodic shedding of vortices as airflow interacts with obstacles. The genesis and characteristics of these vortex structures are significantly influenced by various atmospheric parameters, including temperature, humidity, pressure, and wind velocities, which collectively dictate their formation conditions, spatial arrangement, and dynamic behavior. Although deep learning methodologies have advanced the automated detection of Kármán vortex streets in remote sensing imagery, existing approaches largely emphasize visual feature extraction without adequately incorporating critical atmospheric variables. To overcome this limitation, this study presents an innovative auxiliary network framework that integrates essential atmospheric physical parameters to bolster the detection performance of Kármán vortex streets. Utilizing reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF-ERA5), representative atmospheric features are extracted and subjected to feature permutation importance (PFI) analysis to quantitatively evaluate the influence of each parameter on the detection task. This analysis identifies five pivotal variables: geopotential, specific humidity, temperature, horizontal wind speed, and vertical air velocity, which are subsequently employed as inputs for the auxiliary task. Building upon the YOLOv8s object detection model, the proposed auxiliary network systematically examines the impact of various atmospheric variable combinations on detection efficacy. Experimental results demonstrate that the integration of horizontal wind speed and vertical air velocity achieves the highest detection metrics (precision of 0.838, recall of 0.797, mAP50 of 0.865, and mAP50-95 of 0.413) in precision-critical scenarios, outperforming traditional image-only detection method (precision of 0.745, recall of 0.745, mAP50 of 0.759, and mAP50-95 of 0.372). The optimized selection of atmospheric parameters markedly improves the detection metrics and reliability of Kármán vortex streets, underscoring the efficacy and practicality of the proposed methodological framework. This advancement paves the way for more robust automated analysis of atmospheric fluid dynamics phenomena. Full article

Aerostatic thrust bearings are widely used in advanced equipment such as lithography machines due to their excellent lubrication performance. In this study, computational fluid dynamics (CFD) was employed for the analysis of errors in the calculation of static characteristics of bearings based on the pressure behind the orifice. We put forth an analytical model for calculating the static characteristics of bearings utilizing the average pressure (P_dAVE) within the area surrounded by orifice. By analyzing the influence of various structural parameters, film thickness, and gas supply pressure on P_dAVE in aerostatic bearings, we derived an approximate expression for the average pressure coefficient, which was subsequently verified through experiments. The findings demonstrate that the analytical model for aerostatic bearings, formulated using P_dAVE, can accurately predict the static characteristics of the bearings. The working range corresponding to the optimal stiffness of the bearings is entirely consistent, and the prediction error of the bearing capacity within the optimal working range is less than 5%. This provides a more precise and effective performance prediction model for rectangular aerostatic thrust bearings in engineering design. Full article

The study of river backwater points (bpts) is pivotal for understanding the interactions between riverine and coastal systems, including brackish water dynamics, coastal flooding, and ecosystem processes. Despite extensive research, the global spatio-temporal dynamics of bpts, particularly in rivers with minimal human intervention, remains underexplored. This study investigates backwater lengths and shifts in 18 major global rivers (discharge > 5000 m³/s) from 2000 to 2020, uncovering significant hydrological and geographical patterns. In 2000, backwater lengths ranged from 113.16 km (Salween) to 828.75 km (Amur), with bpts consistently positioned upstream of apex points. By 2020, all rivers exhibited upstream retreats of their bpts, ranging from 10.43 km (Salween) to 132.51 km (Amazon), and retreat ratios typically falling between 0% and 20%. The Salween, Niger (60%), and Irrawaddy (38%) demonstrated the most significant proportional shifts. Geographical transitions of bpts varied widely: rivers such as the Ganges and Amur shifted toward urbanized areas, while the Amazon and Orinoco remained in remote regions, reflecting the differential impact of human activity and natural processes. There was a general correlation between backwater length and river discharge, with exceptions like the Amur indicating the influence of other factors such as geomorphic settings and sediment dynamics. While sea-level rise (0.019–0.115 m) affected estuarine conditions, it showed no consistent relationship with bpt retreat at the global scale, but a regional-scale analysis indicates that sea-level rise can lead to the retreat of bpts for those rivers with macro-tidal environments and high sediment yields with less human intervention, suggesting localized interactions dominate backwater dynamics. These findings highlight the complex interplay of environmental and anthropogenic pressures on global river systems. They provide a critical foundation for advancing hydrological modeling, improving river management strategies, and understanding the broader implications of spatio-temporal bpt dynamics under changing climatic and human influences. Full article

Soybean oil is the second most consumed vegetable oil worldwide and is recognized as a source of heart-healthy polyunsaturated fatty acids. Optimizing the extraction process in the oil industry is essential for both economic and environmental sustainability. This research aimed to determine the optimal conditions for various extraction parameters—stripper temperature (110–140 °C), stripper pressure (150–210 mbar), and dryer pressure (60–120 mbar)—and their effects on the physicochemical properties of soybean oil. These properties include oil-insoluble fine substances, acidity, the color index, peroxide value, oxidative stability, and moisture content. The results indicated that the stripper temperature significantly influenced oil-insoluble fine substances, acidity, the color index, and peroxide value (p < 0.05). The optimal conditions for oil extraction were found to be a stripper temperature of 110 °C, a stripper pressure of 150 mbar, and a dryer pressure of 120 mbar. Under these conditions, the oil-insoluble fine substances, acidity, the color index, peroxide value, oxidative stability, and moisture content of soybean oil were in the ranges of 0.2–0.58%, 0.63–1.15%, 4.3–5.5, 0.67–1.23 meqO₂/kg, 3–5.5, and 0.05–0.11%, respectively. These findings provide valuable insight for optimizing soybean oil extraction processes to enhance quality and efficiency. Future advancements in industrial oil extraction are expected to focus on integrating efficient, eco-friendly technologies and enhancing precision through automation and data analytics to optimize yield and minimize waste. Full article

The permeability of a coal seam is a crucial factor in coal seam gas extraction. Poor permeability of coal seams can lead to difficulties in over-pumping as well as high gas emissions after mining. This issue is particularly prominent when mining extra-thick coal seams with hard roofs, and it is the major problem that restricts the safe and efficient mining of coal seams. In the context of extra-thick coal seam mining in the Datong mine area, field investigation into the gas emission patterns of the working face reveals that the volume of gas emissions correlates closely with variations in working face pressure, demonstrating a high degree of consistency. The mechanism of irregular gas emission was analyzed, and the influence law of roof breakage on gas emission was obtained. It was found that roof breakage will aggravate gas emission. As a result, an integrated control technology involving “ground fracturing + gas extraction” was innovatively proposed. Based on the characteristics of ground fracture network, the mechanism of pressure relief and permeability enhancement of fractured wells and the characteristics of full time and space extraction were analyzed. Using the 8101 and 8204 working faces of the Tashan Coal Mine as a case study, the results demonstrated that vertical well fracturing of the 8101 working face enabled gas extraction 150 m ahead, with an accelerated increase in gas concentration within a 40 m range. Similarly, the horizontal well of the 8204 working face served as a drainage well after fracturing. Gas concentration at the mining position 50 m away from the horizontal well increased rapidly, and the gas extraction rate stabilized at approximately 30 m³/min. The approach effectively mitigated the problem of uneven gas emission caused by gas accumulation and roof fractures in the working face. Ground fracturing not only reduced the area and intensity of stress concentration in the advanced coal body but also enhanced gas emission. Furthermore, the fracturing well served as a gas drainage well, improving the control and achieving positive application results. Full article

Recent advancements in hydrogen tank technology have favored the use of composites over metals for weight reduction, although at the cost of a narrower operating temperature range. Therefore, this study aims to establish safety standards for charging tube skids—large tanks positioned vertically within hydrogen transport vehicles—by examining the variations in temperature distribution under different charging environments through numerical analysis. A two-dimensional axisymmetric model was developed based on ANSYS Fluent to incorporate the effect of buoyancy by applying gravitational conditions along the axial direction. The study analyzed the impact of various charging and environmental conditions (charging time (0~240 min), inlet temperature, ambient temperature, initial temperature (−20 °C~40 °C), and initial pressure (5~20 bar)) on temperature distribution, ultimately deriving a regression equation to predict the tank’s maximum temperature. The findings indicate that the initial temperature has the most significant correlation with the tank’s temperature, followed by charging time and ambient temperature. Inlet temperature and initial pressure demonstrated minimal influence within the study’s scope. The derivation of predictive formulas for the maximum temperatures of the tank’s three regions, all showing an R² value of 0.99 or higher, highlights the practicality of these results. This study’s insights are expected to contribute to further research aimed at optimizing charging conditions for tube skids and other hydrogen tanks. Full article