Search Results (5,996)

Daily groundwater-level prediction in arid inland basins is driven by complex meteorological–hydrological conditions, water supply, pumping, and irrigation demand. Using data from the Zhangye Basin (2018–2025), this study selected 10 representative wells from 51 candidates to build a one-day-ahead framework with a 60-day input window. Dempster–Shafer evidence theory fused five criteria (Pearson, Spearman, lagged correlation, mutual information, and tree-model importance) to screen external variables. Long short-term memory network (LSTM), temporal convolutional network (TCN), and Transformer served as first-level sequence models; extreme gradient boosting (XGBoost) as the second-level stacking learner; and SHapley Additive exPlanations (SHAP) to quantify feature contributions. Dempster–Shafer evidence theory (D-S evidence theory) results indicated that groundwater pumping proxy variable (GPV), irrigation water-demand intensity proxy variable (IWD), surface-water supply proxy variable (SWS), canal-diversion proxy variable (CDV), air temperature (AT), runoff, vapor pressure deficit (VPD), and canal irrigation supply–demand coupling intensity (CISDCI) exhibited high process-representation relevance. During the 90-day test period, Stacking achieved the lowest RMSE for six of 10 wells. Regional average RMSE, MAE, and NSE values were 0.1596 m, 0.0772 m, and 0.9326 for the Zhangye group, and 0.0185 m, 0.0133 m, and 0.9177 for the Gaotai group. SHAP showed historical groundwater-level data dominated contributions, accounting for 64.17% and 43.96% in the Zhangye and Gaotai groups, respectively, and indicating model dependence rather than direct hydrological causality. This framework provides a cautious reference for short-term groundwater forecasting and input selection under the given data conditions. Full article

Single-use pyrotechnic and compressed-gas actuators currently meet industrial safety tasks that demand rapid response and high force. An integrated hydrogen production and combustion-driven actuation system is proposed as a clean and reusable alternative. Hydrogen is generated on demand inside the unit by water electrolysis. It is stored in a metal hydride module and burned with air under controlled conditions to drive a double-piston mechanism. A combined approach of modeling, such as thermodynamic analysis, ideal gas laws, and Engineering Equation Solver (EES) simulations, was used to predict the hydrogen demand and system performance. In addition, the combustion behavior and chamber pressure distribution were investigated using COMSOL Multiphysics. It was shown that hydrogen–air combustion allows for more stable and controllable operating conditions than hydrogen–oxygen combustion, while still satisfying the required in-cylinder pressure of about 350 bar. The designed proton exchange membrane (PEM) electrolyzer consumes about 221 W of power from a 24 V DC power source and produces 0.16 g of hydrogen in 135 s, which is sufficient for a high-force actuation stroke. Unlike conventional pyrotechnic cartridges and pneumatic and hydraulic actuators, the suggested system generates no solid combustion residues and does not require single-use consumables. It is reusable for many cycles, with water vapor as the main combustion product. Overall, the findings support hydrogen-powered actuation on demand as a viable and clean option for high-force safety tasks, ranging from closing emergency shut-off valves at oil and gas facilities to pressurizing fire protection and other safety systems, making it particularly attractive for remote facilities without a continuous grid power supply. Full article

When high-energy particles of cosmic origin penetrate the atmosphere, they collide with atmospheric atoms and molecules, triggering cascades of secondary particles that can propagate down to the surface. These energetic particles constitute a radiation background in the atmosphere with direct implications for aviation exposure safety and influence atmospheric chemistry through the ionization of ambient air. For these reasons, the development of secondary particle showers has been extensively studied, and considerable effort has been devoted to Monte Carlo-based models capable of computing secondary particle fluxes in the atmosphere. However, the atmospheric models in which particle transport is simulated are generally standard atmospheric models, which can differ substantially from actual atmospheric conditions. In this work, the Atmospheric Radiation Interaction Simulator (AtRIS) is used in conjunction with the NRLMSIS-2.1 atmospheric model to investigate the effects of varying density, pressure, and temperature profiles on secondary particle fluxes at different atmospheric levels. For a given incident radiation spectrum, the AtRIS simulations reveal substantial differences between atmospheric profiles when a uniform vertical cutoff rigidity is prescribed across all latitudes, effectively isolating atmospheric effects from geomagnetic shielding. Below ∼20 km, secondary particle fluxes are consistently higher in the polar atmosphere than at the equator. At ∼7 km, the difference between the equatorial and southern polar winter profiles reaches ∼40% for protons, photons, electrons, and positrons, and ∼30% for neutrons and muons. Full article

Air duct contamination in HVAC systems degrades indoor air quality and reduces energy efficiency by increasing aerodynamic resistance, pressure drop, and electricity consumption. This study systematically analyzes contamination causes and their effects on indoor health, system performance, and energy use. It examines physical, biological, and chemical pollutants and their accumulation mechanisms. Emphasis is placed on inspection and diagnostic methods to guide effective monitoring strategies. Ten methods were evaluated using five criteria: reliability, applicability, speed, cost efficiency, and diagnostic value. Optical camera inspection with image processing and pressure drop measurement ranked highest, highlighting the importance of continuous monitoring for preventive maintenance and energy optimization. Full article

Short drilling distances in soft coal seams prone to gas outbursts are mainly caused by drillpipe jamming from the accumulation of drill slag. This poses a gas hazard and limits gas utilization. A novel borehole-protection and pressure-relief (BPPR) drillpipe with three channels is proposed to solve this problem. However, the structural principle of the BPPR drillpipe differs significantly from that of conventional drillpipes, and the migration mechanisms of drill slag and airflow inside the borehole remain unclear. In this paper, the migration behavior of drill slag and its influencing factors during BPPR drillpipe drilling were investigated based on mechanical analysis and CFD-DEM coupling simulations. The results show that when air velocity exceeds the minimum suspension velocity of slag, the slag entering through sieveholes can be smoothly discharged by airflow. Small vortices form at the sieveholes but do not block slag discharge. The key factors affecting slag discharge are air velocity, slag volume, and particle size. Higher air velocity increases the slag transport speed and discharge rate. A larger slag volume reduces the average transport speed at the same air velocity. Larger particles need greater air velocity, or they settle at the bottom. Drillpipe rotation speed has little effect on slag transport. To ensure effective slag discharging, air pressure and velocity should be increased. In addition, the sieveholes on the BPPR drillpipe surface can regulate the slag volume and particle size entering the inner discharge channel. This matches the slag load with the airflow capacity and prevents blockages in the inner discharge channel. Full article

Carbon dioxide (CO₂/R744) is a natural refrigerant that has been widely studied as a replacement for conventional hydrofluorocarbon-based refrigerants in HVAC&R systems. However, the performance of CO₂ heat pumps depends strongly on the system architecture, component parameters, operating conditions, and pressure control. This study examines a CO₂-based heat pump integrated into an AHU with two-stage heat recovery. Heat recovery from the exhaust air is initially performed using a regenerative sorption wheel and then in an R744 heat pump with fin-and-tube heat exchangers located directly in the airflows. The operating performance of the heat pump was evaluated through system-level simulation based on commercially available component data and iterative balancing of the refrigeration cycle and air-side processes. For the investigated configuration and selected components, the proposed R744 system is compared with a conventional R410A-based reference system under the same air-side boundary conditions. Therefore, this comparison is interpreted as a system-level benchmark rather than an isolated effect of the refrigerant itself, since performance depends on the refrigerant’s properties, compressor performance, heat exchanger configuration, system architecture, and the operating limitations of the components. Simulations are performed for both heating and cooling modes, while preliminary experimental measurements from a physical prototype are presented for qualitative comparison with the simulated heating-mode trend. Full article

When predicting cavitation erosion risk in practical engineering bearings, traditional vapor cavitation models neglect the effect of dissolved air in the lubricant and fail to account for its precipitation and dynamic evolution in local low-pressure regions, leading to deviations in the prediction of cavitation extent, intensity, and distribution. Taking the main bearing of a certain type of diesel engine as the research object, a coupled cavitation model combining the Schnerr–Sauer vapor cavitation model and a Henry’s law-based gas dissolution model is established. Together with large eddy simulation (LES), the accuracy of the numerical model is verified by constructing a visualization experimental platform. Numerical analysis is then carried out to investigate the effect of dissolved air in the lubricant on the cavitating flow field of the bearing oil film under initial conditions ranging from undersaturated to saturated states (air mass concentration of 0–0.4 g/L). The results show that as the mass concentration increases, the amount of air precipitation in the near-wall region gradually increases and extends downstream. When the mass concentration reaches 0.1 g/L, the precipitated air mass reaches 50% of the vapor cavitation mass, significantly expanding the cavitation range. In the critical mass concentration range of 0.24–0.28 g/L, intense air precipitation occurs inside the oil hole and covers the entire region. Through the synergistic effects of inhibiting high-speed jets, altering the local pressure field, and competing for cavitation nuclei, the precipitated air significantly suppresses the development of near-wall vapor cavitation, and the vapor cavitation mass decreases by 83.1% at saturation. In summary, within the practical mass concentration range, the presence of dissolved air significantly enhances the gas phase intensity near the bearing bush surface and expands the cavitation range, thereby exacerbating the risk of cavitation erosion damage in this region, while having little effect on the oil supply performance of the oil hole. Full article

Wide-scale, spatio-temporal quantification of soil CO₂ efflux is essential for understanding terrestrial carbon dynamics, predicting climate change, and evaluating the carbon balance in managed and natural ecosystems. Rising global temperatures, changing land use patterns, and other activities aimed at boosting crop productivity have resulted in an increase in microbial activity, increasing the impact of soil on gas exchange. Therefore, it is important to measure ${\mathrm{CO}}_2$ gas exchange in situ, over wide areas and extended periods without manual intervention. However, current approaches such as remote sensing lacks sufficient spatial and depth resolution, while other direct measurements such as eddy covariance demand expensive infrastructure, limiting wide-scale deployment. In this work, we propose a low-cost, battery-operated ${\mathrm{CO}}_2$ sensing system that provides long-term and scalable monitoring of soil respiration and carbon flux, with the promise for high-resolution measurements. Our innovative design features a PVC-based gas chamber that periodically opens and closes to allow for gas exchange, and a sensor module with low-cost temperature, moisture, pressure, and ${\mathrm{CO}}_2$ sensors, with a low-power wireless LoRa network for real-time monitoring. Our system was rigorously validated through multiple outdoor deployments, over long periods to demonstrate its practicality. We observe that temperature, air pressure, and humidity trends show responsiveness to the environment. We also observe that ${\mathrm{CO}}_2$ emission flux rate vary significantly across different modules, underscoring the need for fine-grained spatial and temporal resolution in monitoring. Full article

In response to ecological degradation caused by uncontrolled dust emissions from open-pit mines, this study selected the Hequ open-pit coal mine as the study area and established a monitoring system to collect data on TSP, PM10, PM2.5, and environmental indicators across three zones: the mining pit, the main haul road, and the coal yard. The necessity of zoning was validated using the least significant difference (LSD) method. Pollutant correlations were examined using the individual air quality index (IAQI), Pearson correlation matrix analysis, and grey relational analysis. Univariate models, multiple linear regression (MLR), and principal component analysis–multiple linear regression (PCA–MLR) were applied to quantitatively analyze dust evolution patterns and the influence of environmental factors, with model accuracy verified by the mean relative error (MRE) method. The results showed significant differences in dust concentrations among the three zones. Dust concentrations of all particle sizes in the mining pit and coal yard exceeded the secondary standard limit, whereas those on the haul road only exceeded the primary limit, with pollution intensity ranked as mining pit > coal yard > haul road and PM2.5 identified as the core pollutant in all zones. Linear relationships were significant in univariate models, and multivariate fitting outperformed univariate fitting, with MLR prediction accuracy ranked as coal yard (3.02%) > haul road (9.46%) > mining pit (10.75%). In the mining pit, TSP and PM10 exhibited a strong positive correlation with atmospheric pressure, while PM2.5 showed a strong negative correlation with relative humidity. On the haul road, all particle size fractions displayed strong negative correlations with temperature and wind speed. In the coal yard, only a strong negative correlation with temperature was observed. The PCA–MLR model improved prediction accuracy by 56.63% and 13.41% compared to the direct MLR model. Comprehensive analysis indicates that the atmospheric environment of the Hequ open-pit mine urgently requires proactive restoration measures to optimize the sustainability of the ecological environment. Full article

In response to the challenge of insufficient accuracy in short-term air temperature prediction under severe changes in agricultural microclimate, a hybrid prediction model based on GABP-Net (Gated-Attention and BP Parallel Network) neural network and attention mechanism is proposed. The proposed GABP-Net provides a comprehensive feature fusion framework through two parallel branches: the Gated-Attention branch, built on a GRU followed by multi-head attention, captures local temporal dependencies, with the multi-head attention component adaptively reweighting the GRU outputs across multiple heads to capture diverse temporal patterns; meanwhile, the BP branch, a Backpropagation neural network operating on the flattened input, extracts global contextual features. Their parallel combination enables the model to simultaneously leverage both local dynamics and global representations. Taking 28.2 hectares of farmland in Pingdu, Qingdao as the research object, based on observation data collected every 2 h from September to October 2025, combined with meteorological station measurements and background meteorological prediction data, key meteorological factors such as temperature, radiation, and pressure were selected as input features. The results showed that in the 6-h, 12 h, and 24-h prediction tasks, the model’s R² reached 0.9654, 0.9759, and 0.9622, respectively. The MAE was 0.95 °C, 0.84 °C, and 1.04 °C, respectively, and the RMSE was ≤1.32 °C, significantly better than the single BP (Backpropagation) and GRU (Gated Recurrent Unit) models. Research has shown that this hybrid model effectively improves prediction stability under realistic field conditions with naturally imperfect sensor data and wide temperature variations (overall range 39 °C, maximum diurnal difference 21.6 °C), providing reliable technical support for microclimate regulation in precision agriculture. Full article

Directing a stream of air across the tooth when light curing resin-based composites (RBCs) may affect their degree of conversion (DC), maximum rate of polymerization (RP_max), and in vitro intrapulpal temperature. Methods: Filtek One Bulk Fill and VisCalor bulk were preheated according to the manufacturer’s instructions and used to fill a Class I cavity in a molar at 32 °C. A stream of air at either 15 or 30 psi was directed across the tooth from an air-water syringe positioned 1 cm from the buccal surface. The RBCs were light-cured for 20 s using the Bluephase N, and the DC and RP_max were determined from real-time FT-IR data. A T-type thermocouple positioned inside the pulp chamber recorded the temperature. DC and RP_max data were analyzed using one-way ANOVA, whereas temperature was analyzed using two-way ANOVA, followed by Tukey post hoc tests. Results: Directing a stream of air at the tooth produced no significant differences in the DC and RP_max. The temperature change (ΔT) decreased compared to when no air was delivered. No significant difference in ΔT was found between the two air pressures. Conclusions: Directing a stream of air across the tooth when the preheated RBC was inserted did not affect the polymerization kinetics. The air stream reduced the temperature rise inside the pulp chamber as the RBC was light-cured. Clinical Significance: Directing a stream of air across the tooth at either 15 psi or 30 psi during light curing is an easy method to reduce the temperature increase inside the pulp chamber without affecting the polymerization kinetics of the evaluated preheated RBCs in this in vitro model. Full article

This study optimised the thermal performance of an air-cooled weapon turret control computer used in military missions by integrating experimental, numerical, and machine learning methods. To address thermal localisation and heat accumulation in high-power-density electronic components, two heat pipes with high effective thermal conductivity were embedded in the heat sink block. Based on numerical predictions, this configuration yielded an 8% thermal enhancement; however, its experimental verification remains a subject for future work. The accuracy of the three-dimensional Computational Fluid Dynamics model was validated within an acceptable error tolerance using experimental data from a physical prototype. To reduce the high computational cost of the parametric design space, Gaussian Process Regression, notable for its probabilistic nature, was employed as a surrogate model instead of traditional artificial neural networks, which tend to overfit small-scale deterministic data. The GPR model successfully mapped the system variance, demonstrating an extremely high coefficient of determination and a minimal margin of error in predicting the maximum chip temperature and system pressure drop. Cross-validation analyses conclusively demonstrated that the model has high generalisation capability without overfitting the dataset. Multi-objective Pareto optimisation was conducted by scanning a dense design grid generated over the trained continuous surrogate model. The optimal balanced design configuration identified along the Pareto front maintained the chip temperature within the safe zone, below the critical operating limit, while significantly reducing aerodynamic resistance on the fan, energy consumption, and noise issues, without compromising the system’s thermal performance. The developed GPR-based methodology offers a stable and reliable optimisation framework that minimises trial-and-error costs in the design of military thermal management systems. Full article

Performance and durability of solid oxide cells are ruled by surface and interface phenomena occurring under operation. Electrode elementary reactions involve adsorption, charge transfer, surface diffusion and incorporation processes that are sensitive to the applied operating conditions and defect concentration. However, key degradation mechanisms such as cation segregation, catalyst deactivation, phase transformations and microstructural evolution originate at/near the electrode surface. Consequently, understanding the surface chemistry of electrode materials is essential for the development of the next generation electrodes. In this frame, Near-Ambient Pressure X-ray Photoelectron Spectroscopy (NAP-XPS) has emerged as a powerful tool to probe chemically active surfaces under more realistic environments, thus correlating surface science and electrochemistry. This review covers the principles of NAP-XPS and its application to solid oxide cell materials, including ceria-based model electrodes, Ni-containing fuel electrodes, exsolved perovskites and mixed ionic-electronic conducting air electrodes. NAP-XPS demonstrated the ability to directly monitor the dynamic state of the electrode surface under controlled operating conditions. Common mechanistic insights and emerging trends are highlighted, together with potential limitations associated with current experimental configurations. Overall, combined NAP-XPS and electrochemical analyses appear to hold the potential for linking surface chemistry with electrode performance and degradation, thus supporting the rational design of the next-generation solid oxide cell materials. Full article

The accuracy of CFD-DEM simulations of particulate systems strongly depends on the proper characterization of particle–particle and particle–wall interaction parameters. In this study, the coefficients of restitution, static friction, and rolling friction for ABS–ABS and ABS–acrylic interactions were experimentally determined for acrylonitrile butadiene styrene (ABS) spheres using free-fall, inclined-plane, and launch-ramp tests, respectively. The obtained parameters were subsequently applied in CFD-DEM simulations of a three-dimensional conical spouted bed operating with different solid loads. In parallel, experimental fluid dynamic tests were conducted to obtain characteristic pressure drop curves and determine the minimum spouting velocity. The experimental results exhibited the typical behavior of spouted beds, including hysteresis between the curves obtained by increasing and decreasing the inlet air velocity and higher minimum spouting velocities at greater solid loads. The CFD-DEM simulations successfully reproduced the main hydrodynamic features of the system, yielding deviations of 0.9%, 6.9%, and 20.5% for the minimum spouting velocities corresponding to solid loads of 400 g, 300 g, and 200 g, respectively. A comparison with the interaction parameters reported in the literature showed that the coefficients obtained through direct measurement provided better agreement between the experimental and simulated results. These findings highlight the importance of accurately characterizing interaction parameters to achieve reliable CFD-DEM simulations of spouted bed systems. Full article

Current industrial standards for gas pipeline leak testing often assume inert testing gases are universally interchangeable, neglecting specific fluid dynamics. This study quantifies how testing gas properties affect integral pressure decay leak tests. Experimental measurements (5000 Pa initial pressure) were conducted on a PE100RC (polyethylene resistant to crack propagation) pipe assembly with artificial capillary defects (0.13 mm diameter) using five media: nitrogen, air, argon, carbon dioxide, and a propane−butane (PB) mixture. Results demonstrate that in the continuous viscous flow regime, leak rates depend strictly on the gas’s dynamic viscosity. For identical defects, PB (the lowest viscosity gas tested) increased the leak rate by up to 129% compared to standard nitrogen. This relationship is statistically validated by a strong negative Pearson correlation (r = −0.92). To facilitate industrial application, a preliminary mathematical correction procedure is proposed for safely extrapolating these trends to infrastructure intended for pure hydrogen operation. To prevent false-positive tightness certifications during the transition to low-viscosity alternative fuels like pure hydrogen, implementing a dynamic viscosity correction factor is essential. Full article