Search Results (4,479)

With the growing global demand for renewable energy, the pump as turbine (PAT) exhibits significant potential in the micro-hydropower sector. To reveal its internal unsteady flow characteristics and energy loss mechanisms, this study analyzes the internal flow field of an ultra-low specific speed pump as turbine (USSPAT) by employing a combined approach of entropy generation theory and dynamic mode decomposition (DMD). The results indicate that the outlet pressure pulsation characteristics are highly dependent on the flow rate. Under low flow rate conditions, pulsations are dominated by low-frequency vortex bands induced by rotor-stator interaction (RSI), whereas at high flow rates, the blade passing frequency (BPF) becomes the absolute dominant frequency. Energy losses within the PAT are primarily composed of turbulent and wall dissipation, concentrated in the impeller and volute, particularly at the impeller inlet, outlet, and near the volute tongue. DMD reveals that the flow field is governed by a series of stable modes with near-zero growth rates, whose frequencies are the shaft frequency (25 Hz) and its harmonics (50 Hz, 75 Hz, 100 Hz). These low-frequency modes, driven by RSI, contain the majority of the fluctuation energy. Therefore, this study confirms that RSI between the impeller and the volute is the root cause of the dominant pressure pulsations and periodic energy losses. This provides crucial theoretical and data-driven guidance for the design optimization, efficient operation, and stability control of PAT. Full article

To address the issue of existing automatic irrigation systems’ excessive reliance on electrical power and communication networks, a one-inlet, four-outlet Hydraulically Actuated Irrigation Control Valve (HAICV) was designed that operates based on water pressure variations. Its hydraulic characteristics and flow field features were investigated through experimental and numerical simulation methods. The results indicated that power–function relationships exist between pressure and flow rate, as well as between flow rate and head loss. The flow coefficient and resistance coefficient were found to range within [77.46, 81.06] and [15.94, 17.46], respectively. Dynamic simulations based on User-Defined Functions (UDF) revealed that during the opening process, the internal pressure of the valve spool remains high, with the primary pressure drop concentrated in the outlet region, and the low-pressure zone shrinks as the opening degree increases. A high-velocity band forms at the outlet, with jet flow and turbulence observed at small to medium openings, while the flow field stabilizes after full opening. The unique spool shape and non-straight flow passage structure of the HAICV result in relatively high energy loss, making it suitable for self-pressure irrigation systems. This study provides a theoretical foundation for evaluating its performance and broader applications. Full article

Reverse osmosis (RO) water purifiers produce a large volume of reject water, which is typically discarded, leading to water wastage and resource inefficiency. This work proposes a novel approach to reusing RO effluent as a cooling medium in a water-cooled condenser integrated into a residential hot-and-cold water purifier. The system replaces a conventional air-cooled condenser with a water-cooled unit and was evaluated under controlled laboratory conditions (ambient temperature 25 °C). Experiments were conducted at various RO effluent flow rates ranging from 0.5 to 2.5 L per minute (LPM). Key performance metrics, including the coefficient of performance (COP), cooling time, and energy consumption, were measured and compared. Results showed that replacing a conventional air-cooled condenser with a water-cooled condenser configuration reduces energy consumption by up to 37.5% and shortens cooling times by up to 33%. Performance was maintained under intermittent RO effluent supply. However, an excessive flow rate (2.0 LPM) caused evaporator frosting and efficiency loss, indicating the importance of flow control. These findings demonstrate that internally reusing an RO effluent offers a sustainable, compact, and energy-efficient solution for next-generation water purifiers. Full article

Maintaining an effective facial seal is critical for the performance of tight-fitting industrial respirators used in high-risk sectors such as mining, manufacturing, and construction. Traditional fit verification methods—Qualitative Fit Testing (QLFT) and Quantitative Fit Testing (QNFT)—are limited to periodic assessments and cannot detect fit degradation during active use. This study presents a real-time fit detection system based on embedded breath sensors and machine learning algorithms. A compact sensor module inside the respirator continuously measures pressure, temperature, and humidity, transmitting data via Bluetooth Low Energy (BLE) to a smartphone for on-device inference. This system functions as a multimodal biosensor: intra-mask pressure tracks flow-driven mechanical dynamics, while temperature and humidity capture the thermal–hygrometric signature of exhaled breath. Their cycle-synchronous patterns provide an indirect yet reliable readout of respirator–face sealing in real time. Data were collected from 20 healthy volunteers under fit and misfit conditions using OSHA-standardized procedures, generating over 10,000 labeled breathing cycles. Statistical features extracted from segmented signals were used to train Random Forest, Support Vector Machine (SVM), and XGBoost classifiers. Model development and validation were conducted using variable-size sliding windows depending on the person’s breathing cycles, k-fold cross-validation, and leave-one-subject-out (LOSO) evaluation. The best-performing models achieved F1 scores approaching or exceeding 95%. This approach enables continuous, non-invasive fit monitoring and real-time alerts during work shifts. Unlike conventional techniques, the system relies on internal physiological signals rather than external particle measurements, providing a scalable, cost-effective, and field-deployable solution to enhance occupational safety and regulatory compliance. Full article

Misconceptions about sound are common among primary-school pupils, but research on voice-interactive game-based learning remains limited, especially regarding the role of scaffolding. We investigated whether a voice-interactive 2D platformer with a three-tier scaffolding model improves learning about loudness, pitch, and echo. In a classroom-feasible randomized comparison, 45 third-graders were assigned to a scaffolded serious game (SSG), a non-scaffolded serious game (NSG), or traditional hands-on materials instruction (TRAD) on matched sound content. Outcomes were an immediate eight-item knowledge test and learner-centered ratings of perceived learning, flow, intrinsic motivation, and extraneous cognitive load (ECL). The knowledge test showed low internal consistency, so results involving this measure should be interpreted with caution. SSG yielded higher immediate learning than NSG and matched traditional instruction. Across experience measures, only intrinsic motivation differed, favoring NSG. Hierarchical regression revealed a motivation-by-structure effect: scaffolding strengthened the positive association between intrinsic motivation and test scores, whereas ECL was not predictive. Findings indicate that voice-interactive serious games can match near-term learning achieved with physical materials, and well-calibrated scaffolds help convert motivation into accurate encoding. We also map sound constructs to gameplay mechanics and provide a compact, classroom-feasible, replicable evaluation design for primary classrooms. Full article

Airplane cabin temperature is a critical environmental factor governing the safety and reliability of airborne equipment. Compared with measuring temperature, predicting temperature is more cost- and time-saving and can cover an extreme flight envelope. Physics-informed neural networks (PINNs) offer a promising prediction solution whose performance hinges on the availability of precise governing differential equations. However, building governing differential equations between flight parameters and cabin temperature is a great challenge, as it is comprehensively influenced by aerodynamic heat, avionic heat, and internal flow. To solve this, a new PINN framework based on “a priori monotonicity” is proposed. Underlying physical trends (monotonicity) from flight data are extracted to construct the loss function as a data-driven constraint, thus eliminating the need for any governing equations. The new PINN is developed to estimate the seven cabin temperatures of an unmanned aerial vehicle. The model was trained on data from four flight sorties and validated on another four independent sorties. Results demonstrate that the proposed PINN achieves a mean absolute error of 1.9 and a root mean square error of 2.6, outperforming a conventional neural network by approximately 35%. The core value of this work is a new PINN framework that bypasses the development of complex governing equations, which enhances its practicality for engineering applications. Full article

The role of sedimentary heterogeneity in reactive transport processes is becoming increasingly important as closed open-pit lignite mines are converted into post-mining lakes or pumped hydropower storage reservoirs. Flooding of the open pits introduces constant oxygen-rich inflows that reactivate pyrite oxidation within internal mine dumps. A reactive transport model coupling groundwater flow, advection–diffusion–dispersion, and geochemical reactions was applied to a 2D cross-section of a water-saturated mine dump to determine the processes governing pyrite oxidation. Spatially correlated fields representing permeability and pyrite distributions were generated via exponential covariance models reflecting the end-dumping depositional architecture, supported by a suite of scenarios with systematically varied correlation lengths and variances. Simulation results covering a time span of 100 years quantify the impact of heterogeneous permeability fields that result in preferential flow paths, which advance tracer breakthrough by ~15 % and increase the cumulative solute outflux up to 139 % relative to the homogeneous baseline. Low initial pyrite concentrations (0.05 wt %) allow for deeper oxygen penetration, extending oxidation fronts over the complete length of the modeling domain. Here, high initial pyrite concentrations (0.5 wt %) confine reactions close to the inlet. Kinetic oxidation allows for more precise simulation of redox dynamics, while equilibrium assumptions substantially reduce the computational time (>10×), but may oversimplify the redox system. We conclude that reliable risk assessments for post-mining redevelopment should not simplify numerical models by assuming average homogeneous porosity and mineral distributions, but have to incorporate site-specific spatial heterogeneity, as it critically controls acid generation, sulfate mobilization, and the timing of contaminant release. Full article

This study investigates the influence of shallow water-bearing sand layers on surface subsidence characteristics in coal mining areas with thick loose strata, with the ultimate goal of contributing to sustainable environmental protection. Firstly, a numerical simulation test was designed to analyze and study the influence of the loose layer thickness, mining height, bedrock slope, and sand inclusion on the surface movement and deformation characteristics. Secondly, the mechanical model of seepage flow in the sand layer was established to study the influence mechanism of the internal stress distribution of the sand layer and the seepage of the water body after mining on the surface subsidence. Finally, by studying the law of surface subsidence corresponding to the mining of 3205 working face in a mine, it was found that mining caused the partial overlying soil layer to move integrally and generate a large displacement difference with the adjacent layer, which verifies the conclusions of numerical simulation and mechanical analysis. The results of the study show that the thickness of the loose layer is the main control factor that causes the surface subsidence range and the building damage to increase; the shallow water-bearing sand-bearing layer has two types of movements: displacement and flow. The critical hydraulic slope has not reached the sand. The layer has a linearly increasing horizontal displacement value in the thickness direction; when the critical hydraulic slope is reached, the sand layer cannot transmit the frictional force, causing the overlying soil layer to slide as a whole. Both forms are prone to tensile damage on the surface. The research results provide a theoretical basis and practical case for surface subsidence reduction and green mining under similar geological conditions. Full article

The angular momentum flowmeter addresses critical challenges in aviation fuel flow measurement during commercial flight operations. This study designed a visualization platform to observe the dynamic responses of internal components under varying flow conditions. By employing the sliding mesh method coupled with an angular momentum algorithm, it enabled the dynamic rotation simulation of the upstream straight-bladed rotor and provided calculation of the deflection angle in the downstream straight-bladed rotor of an angular momentum flowmeter. Experimental results categorize the flow process into three distinct regimes based on flat and spiral spring response states: pre-spring, single-spring, and dual-spring regimes. Under a flow condition of 0.091 kg/s, the upstream straight-bladed rotor maintained stable rotation at a speed of 1.1 rad/s. At a flow rate of 0.20 kg/s, the flat spring initiated outward expansion, and with further increase in flow rate, the rotational speed of the upstream straight-bladed rotor remained within the range of 25.34–26.21 rad/s. Mathematical analysis demonstrates that the flat spring configuration extends the lower measurement limit and promotes dissipation of the secondary vortex through dominant kinetic energy of the primary vortex during dual-spring operation, thereby improving high-pressure zone stability. This work elucidates the operational mechanism of angular momentum flowmeters and provides a theoretical basis for structural optimization. Full article

The shallow-water delta-front reservoir in Member II of the Oligocene Dongying Formation (Ed2), located in an oilfield within the Bohai Bay Basin, is a large-scale composite sedimentary system dominated by subaqueous distributary channels and mouth bars. Within this system, reservoir sand bodies exhibit significant thickness, complex internal architecture, poor injection–production correspondence during development, and an ambiguous understanding of remaining oil distribution. To enhance late-stage development efficiency, it is imperative to deepen the understanding of the genesis and evolution of the subaqueous distributary channel–mouth bar system, analyze the internal reservoir architecture, and clarify sand body connectivity relationships. Based on sedimentary physical modeling experiments, integrated with core, well logging, and seismic data, this study systematically reveals the architectural characteristics and spatial stacking patterns of the mouth bar reservoirs using Miall’s architectural element analysis method. The results indicate that the study area is dominated by sand-rich, shallow-water delta front deposits, which display a predominantly coarsening-upward character. The main reservoir units are mouth bar sand bodies (accounting for 30%), with a vertical stacking thickness ranging from 3 to 20 m, and they exhibit lobate distribution patterns in plan view. Sedimentary physical modeling reveals the formation mechanism and stacking patterns of these sand-rich, thick sand bodies. Upon entering the lake, the main distributary channel unloads its sediment, forming accretionary bodies. The main channel then bifurcates, and a new main channel forms in the subsequent unit, which transports sediment away and initiates a new phase of deposition. Multi-phase deposition ultimately builds large-scale lobate complexes composed of channel–mouth bar assemblages. These complexes exhibit internal architectural styles, including channel–channel splicing, channel–bar splicing, and bar–bar splicing. Reservoir architecture analysis demonstrates that an individual distributary channel governs the formation of an individual lobe, whereas multiple distributary channels control the development of composite lobes. These lobes are laterally spliced and vertically superimposed, exhibiting a multi-phase progradational stacking pattern. Dynamic production data analysis validates the reliability of this reservoir architecture classification. This research elucidates the genetic mechanisms of thick sand bodies in delta fronts and establishes a region-specific reservoir architecture model. This study clarifies the spatial distribution of mudstone interlayers and preferential flow pathways within the composite sand bodies. It provides a geological basis for optimizing injection–production strategies and targeting residual oil during the ultra-high water-cut stage. The findings offer critical guidance for the efficient development of shallow-water delta front reservoirs. Full article

This work presents a study on the fabrication of polymethyl methacrylate (PMMA) coatings on NiTi alloys using the spin-coating technique, combining numerical simulation with COMSOL Multiphysics 6.3 and experimental validation. This study provides a numerical framework and parametric study of a COMSOL-based simulation framework for estimating the PMMA coating thickness during the spin-coating process. We present an axisymmetric numerical framework, consistent with classical analytical trends; we provide parametric maps (viscosity, rpm, volume) to delimit thickness ranges (e.g., 100–300 μm). Limitations with no experimental validation are included and evaporation is not modeled; therefore, the figures are indicative estimates. The spin-coating parameters, such as the rotation speed, internal pressure, viscosity of the PMMA solution, and initial volume of the polymer solution, are considered important factors for the simulation process. The coating parameters determine the thickness of the coating layer achieved during the process of spin coating. The 2D axisymmetric flow considers internal factors of a surface tension of 0.07 N·m, a contact angle of 90°, and a density of 1150 kg/m³ for the coating process without evaporation effects. The moving mesh (coating layer) is considered a free surface without any slip boundary with the substrate surface. The coating thickness was determined by various rotations and dynamic viscosities, using a simulation method. The experimental findings and simulation output of the coating thickness as a function of various dynamic viscosities and rotations match well. The final coating thickness ranged from 100 to 300 μm, depending on a viscosity of 11 mPa·s and 100, 500 rpm. Full article

This study investigates factors influencing migrants’ decisions to enter Europe via Bulgaria or Greece along the Balkan route, using logistic regression and machine learning models on data from the International Organization for Migration (IOM) Flow Monitoring Survey (August 2022–June 2025, $n=5536$). We examine demographic variables (age), push factors (economic reasons, war/conflict, personal violence, limited access to services, and avoiding military service), and governance clusters derived from the World Bank’s Worldwide Governance Indicators (WGIs). An adapted migration gravity model incorporates corruption control as a key push–pull factor. Key findings indicate that younger migrants are significantly more likely to choose Bulgaria ($\beta \approx -0.021$, $p<0.001$), and governance clusters show that migrants from high-corruption origins (e.g., Syria and Afghanistan) prefer Bulgaria, likely due to governance similarities and facilitation costs. The Cluster Model achieves a slight improvement in fit (McFadden’s $R^2=0.008$, AIC = 7367) compared to the Base (AIC = 7374) and Interaction (AIC = 7391) models. Machine learning extensions using LASSO and Random Forests on a subset of data ($n=4429$) yield similar moderate performance (AUC: LASSO = 0.524, RF = 0.515). These insights highlight corruption’s role in route selection, offering policy recommendations for origin, transit, and destination phases. Full article

Uneven distribution of passenger flows across metro entrances/exits is prevalent. Previous studies primarily examined built-environment factors influencing established exit-level flow disparities from an objective perspective. This study, however, incorporates passengers’ subjective preferences to provide a more comprehensive understanding of the environment–behavior mechanisms shaping entrance/exit choice. A visual stated preference method was employed to construct choice scenarios with 12 environmental attributes grouped into two complementary dimensions of path accessibility and environmental quality. Multinomial logit models were then applied to estimate passengers’ entrance/exit choice preferences, and the results informed a two-dimensional exit-level evaluation framework, demonstrated through a case study of Xujiahui Station in Shanghai. Compared with empirical studies, this study employs a discrete choice experiment, which circumvents the modeling challenges posed by the limited number of entrances/exits at individual stations and systematically integrates a range of station-internal and urban environmental attributes into a unified utility-based framework to evaluate their contributions. The results reveal the relative importance of various environmental attributes, together with their varying levels, in shaping passengers’ entrance/exit choices and indicate that path accessibility exerts a stronger influence on decision-making than environmental quality. The proposed exit-level evaluation framework also serves as a practical tool for assessing resource allocation status at individual station areas, providing a foundation for policy formulation to support more human-centered, equitable, and fine-grained station-area governance. Full article

Background/Objectives: The Kocher–Langenbeck approach is widely used for surgical fixation of posterior acetabular wall fractures. While previous studies have focused on mechanical outcomes and the risk of post-traumatic osteoarthritis, the effects on peripheral circulation and neuromuscular recovery remain underexplored. This study aimed to evaluate dynamic changes in neuromuscular function and microcirculation following open reduction and internal fixation (ORIF) using this approach. Methods: A retrospective analysis was conducted on 34 patients (aged 23–75) treated for posterior acetabular wall fractures between 2014 and 2022. All patients underwent ORIF via the Kocher–Langenbeck approach. Assessments at 8 and 12 months postoperatively included electromyography (EMG), chronaximetry, and rheovasography (RVG). Asymmetry coefficients were calculated to quantify blood flow and functional differences. Results: At 12 months postoperatively, significant microcirculatory asymmetry persisted in the operated limb, with arterial and venous coefficients exceeding 25% (27.5% and 26.8%, respectively). EMG revealed sustained reductions in gluteus maximus and rectus femoris activity (asymmetry ~39%). Chronaximetry showed delayed nerve conduction recovery, particularly in the common peroneal nerve (AC = 44%). The femoral segment demonstrated the most severe impairment in both arterial inflow and venous outflow. Conclusions: ORIF via the Kocher–Langenbeck approach is associated with long-term disturbances in neuromuscular function and regional circulation. Further research should explore alternative surgical approaches (e.g., ilioinguinal, Stoppa) in prospective studies, assess vascular integrity using advanced imaging (e.g., contrast-enhanced ultrasound), and incorporate long-term functional outcomes. Studies on neurovascular-sparing techniques and optimised rehabilitation protocols may help reduce postoperative morbidity and improve recovery. Full article

Background and Aims: Decreased cerebrovascular reactivity (CVR) in patients with significant internal carotid artery stenosis (ICAS ≥ 70%) is an independent risk factor for cerebral infarction. To evaluate CVR, changes in cerebral perfusion pressure and blood flow velocity (BFV) of the middle cerebral artery (MCA) can be estimated by CO₂- (hyperventilation—HV and breath-holding—BH) and pressure–flow-based (Common Carotid Artery Compression—CCC and Valsalva Maneuver—VM) stimuli. We used a multimodal approach to characterize CVR in patients before carotid endarterectomy (CEA). Methods: HV, BH, CCC, and VM tests were performed on 31, 26, and 34 patients. BFV of MCAs was monitored by transcranial Doppler, and continuous arterial blood pressure was registered non-invasively. CVR was compared between the operated significantly stenotic and the contralateral sides. Results: The extent of HV- and BH-induced CVR was similar, but the time to the lowest HV-induced BFV was shorter on the side with significant ICAS. The response to CCC was sensitive to hemodynamic asymmetry in the transient hyperemic response ratio and in the cumulative change in the (mean arterial blood pressure)/(mean BFV) ratio. In VM, the slope of BFV increased in the ascending (2b) phase, and the time to overshoot correlated with the side of the stenosis. Conclusions: These results suggest that in patients with significant ICAS, in addition to CO₂ reactivity measurements, a more complex estimation of CVR, by using hemodynamic tests (CCC and VM), should also be used to better quantify cerebral ischemic risk. Full article