Search Results (3,432)

As the prevalence of respiratory diseases continues to rise, inhalation therapy has emerged as a crucial method for their treatment. The effective transmission of medications within the respiratory tract is vital to achieve therapeutic outcomes. Given that most inhaled particles carry electrostatic charges, understanding the electrostatic effect on particle behavior in bifurcated tubes is of significant importance. This work combined Large Eddy Simulation-Lagrangian particle tracking (LES-LPT) technology to simulate particle behavior with three particle sizes (10, 20, and 50 μm) from G2 to G3 (“G” stands for generation) in bifurcated tubes, either with or without electrostatics, under typical human physiological conditions (Re = 1036). The results indicate that the electrostatic force has a significant effect on particle behavior in bifurcated tubes, which increases with particle size. Within the bifurcated tubes, the electrostatic force enhances particle movement in alignment with the secondary flow as well as intensifies the interaction of particles with local turbulent vortices and promotes particle dispersion rather than agglomeration. On the other hand, the distribution of the electrostatic field is influenced by particle behavior. Higher particle concentration presents stronger electrostatic strength, which increases with particle size. Therefore, it can be concluded that the electrostatic interactions among particles can prevent particles from aggregating and enhance the efficiency of inhalation therapy. Full article

Three-dimensional (3D) ocean physical fields are essential for understanding ocean dynamics, but reconstructing them solely from sea-surface remote sensing remains challenging. We present 3DV-Unet, an end-to-end deep learning framework that reconstructs eddy-resolving three-dimensional essential ocean variables (temperature, salinity, and currents) from multi-source satellite data. The model employs a 3D Vision Transformer bottleneck to capture cross-depth and cross-variable dependencies, ensuring physically consistent reconstruction. Trained on 2011–2019 reanalysis and satellite data, 3DV-Unet achieves RMSEs of ~0.30 °C for temperature, 0.11 psu for salinity, and 0.05 m/s for currents, with all R² values above 0.93. Error analyses further indicate higher reconstruction errors in dynamically complex regions such as the Kuroshio Extension, while spectral analysis indicates good agreement at 100 km+ but systematic deviation in the 20–100 km band. Independent validation against 6113 Argo profiles confirms its ability to reproduce realistic vertical thermohaline structures. Moreover, the reconstructed 3D fields capture mesoscale eddy structures and their life cycle, offering a valuable basis for investigating ocean circulation, energy transport, and regional variability. These results demonstrate the potential of end-to-end volumetric deep learning for advancing high-resolution 3D ocean reconstruction and supporting physical oceanography and climate studies. Full article

The systematic economic development of European Union member states has resulted in a dynamic increase in road transport, accompanied by adverse environmental impacts. Consequently, research efforts have focused on identifying technical solutions to reduce fuel and/or energy consumption. One promising approach involves the formation of homogeneous and heterogeneous vehicle platoons. This study presents the results of numerical simulations and analyses of aerodynamic and aeroacoustic phenomena generated by heterogeneous vehicle platoons composed of passenger cars, delivery vans, and trucks. A total of 54 numerical models were developed in various configurations, considering three vehicle speeds and three inter-vehicle distances. The analysis was conducted using Computational Fluid Dynamics (CFD) methods with the following two turbulence models: the k–ω Shear Stress Transport (SST) model and Large Eddy Simulation (LES), combined with the Ffowcs Williams–Hawkings acoustic analogy to determine sound pressure levels. Verification calculations were performed using methods dedicated to environmental noise analysis, supplemented by acoustic field measurements. The results conclusively demonstrate that vehicle movement in specific platoon configurations can lead to significant fuel and/or energy savings, as well as reductions in harmful emissions. This solution may be implemented in the future as an integral component of Intelligent Transportation Systems (ITSs) and Intelligent Environmental Management Systems (IEMSs). Full article

Aluminum alloys under long-term service or repetitive stress are prone to small fatigue cracks (FCs) with arbitrary orientations, necessitating eddy current probes with focused magnetic fields and directional selectivity for reliable detection. This study presents a flexible printed circuit board (FPCB) probe with a double-layer planar excitation coil and a double-layer differential receiving coil. The excitation coil employs a reverse-wound design to enhance magnetic field directionality and focusing, while the differential receiving coil improves sensitivity and suppresses common-mode noise. The probe is optimized by adjusting the excitation coil overlap and the excitation–receiving coil angles to maximize eddy current concentration and detection signals. Finite element simulations and experiments confirm the system’s effectiveness in detecting surface cracks of varying sizes and orientations. To further characterize these defects, two time-domain features are extracted: the peak-to-peak value ($\Delta$P), reflecting amplitude variations associated with defect size and orientation, and the signal width ($\Delta$W), primarily correlated with defect angle. However, substantial overlap in their value ranges for defects with different parameters means that these features alone cannot identify which specific parameter has changed, making prior defect classification using a Transformer-based approach necessary for accurate quantitative analysis. The proposed method demonstrates reliable performance and clear interpretability for defect evaluation in aluminum components. Full article

In this study, the modeling of rough surfaces by eddy-viscosity-based roughness models is investigated, specifically focusing on surfaces representative of deterioration in aero-engines. In order to test these models, experimental measurements from a rough T106C blade section at a Reynolds number of 400 K are adopted. The modeling framework is based on the k-ω-SST with Dassler’s roughness transition model. The roughness model is recalibrated for the k-ω-SST model. As a complement to the available experimental data, a high-fidelity test rig designed for scale-resolving simulations is built. This allows us to examine the local flow phenomenon in detail, enabling the identification and rectification of shortcomings in the current RANS models. The scale-resolving simulations feature a high-order flux-reconstruction scheme, which enables the use of curved element faces to match the roughness geometry. The wake-loss predictions, as well as blade pressure profiles, show good agreement, especially between LES and the model-based RANS. The slight deviation from the experimental measurements can be attributed to the inherent uncertainties in the experiment, such as the end-wall effects. The outcomes of this study lend credibility to the roughness models proposed. In fact, these models have the potential to quantify the influence of roughness on the aerodynamics and the aero-acoustics of aero-engines, an area that remains an open question in the maintenance, repair, and overhaul (MRO) of aero-engines. Full article

Stability theory offers a practical method on parametric studies that encompass scales in the boundary layer typically not captured in Large Eddy (LES) or Reynolds-Averaged Navier–Stokes (RANS) simulations. We investigated the transition modes of a Low-Pressure Turbine (LPT) with Linear Stability Theory (LST) and Linear Parabolized Stability Equations (LPSEs) over a wider parametric space. A parametric study was done to examine the wall-shear stress, shape factor, momentum thickness, as well as the growth rate and N-factor envelope. Additionally, the methodology was applied to active control techniques like suction and blowing. The results are consistent with the expected physical behavior and initial observations, while also offering a quantitative description of trends in frequencies, amplitude growth, and wavelengths. This confirms the suitability of the two stability theories, laying the base for their future validation to ensure accuracy and reliability. Full article

The use of additive manufacturing (AM) has seen increased utilization over the last decade, thanks to well-documented advantages such as lower startup costs, reduced wastage, and the ability to rapidly prototype. The poor surface finish of unprocessed AM components is one of the major drawbacks of this technology, with the research literature suggesting a measurable impact on flow characteristics and burner operability. For instance, surface roughness has been shown to potentially increase resistance to boundary layer flashback—an area of high concern, particularly when utilizing fuels with high hydrogen content. A more detailed understanding of the underlying thermophysical mechanisms is, therefore, required. Computational fluid dynamics can help elucidate the impact of these roughness effects by enabling detailed data interrogation in locations not easily accessible experimentally. In this study, roughness effects on a generic gas turbine swirler were numerically modeled using a low-y+ detached eddy simulation (DES) approach. Three DES models were investigated utilizing a smooth reference case and two rough cases, the latter employing a literature-based and novel equivalent sand-grain roughness (k_s) correlation developed for this work. Existing experimental isothermal and CH₄ data were used to validate the numerical simulations. Detailed investigations into the effects of roughness on flow characteristics, such as swirl number and recirculation zone position, were subsequently performed. The results show that literature-based k_s correlations are unsuitable for the current application. The novel correlation yields more promising outcomes, though its effectiveness depends on the chosen turbulence model. Moreover, it was demonstrated that, for identical k_s values, while trends remained consistent, the extent to which they manifested differed under reacting and isothermal conditions. Full article

To meet safety regulations in underground coal mines, wireless power transfer (WPT) systems must house both the transmitter and receiver within explosion-proof enclosures. However, eddy currents induced on the surfaces of these non-ferromagnetic metal enclosures significantly hinder magnetic flux coupling, thereby reducing transmission efficiency. This paper proposes a slotting technique applied to explosion-proof enclosures to suppress eddy currents, along with the integration of magnetic flux focusing materials into the coils to enhance coupling. Simulations were conducted to compare three system configurations: (i) a WPT system without enclosures, (ii) a system with solid (unslotted) enclosures, and (iii) a system with slotted enclosures. The results show that solid enclosures reduce efficiency to nearly zero, whereas slotted enclosures restore efficiency to 90% of the baseline system without enclosures. Joule heating remains low in the slotted explosion-proof enclosures, with energy losses of 2.552 J for the transmitter enclosure and 2.578 J for the receiver enclosure. A conservative first-order estimation confirms that the corresponding temperature rise in the enclosure surfaces remains below 50 °C, which is well within the 150 °C limit stipulated by the Chinese National Standard GB 3836.1-2021 (Explosive Atmospheres—Part 1: Equipment General Requirements). These findings confirm effective eddy current suppression and efficiency recovery without compromising explosion-proof safety. The core innovation of this work lies not merely in the physical slotting approach, but in the development of a precise equivalent circuit model that fully incorporates all mutual inductance components representing eddy current effects in non-ferromagnetic explosion-proof enclosures, and its integration into the overall MCR-WPT system circuit. Full article

This study examines the effects of partial wakes caused by upstream turbine yaw control on the trailing-edge noise of a downstream turbine under stable and neutral atmospheric conditions. Using a combined model coupling the unsteady vortex lattice method (UVLM) with the Curl wake model, calibrated with large eddy simulation data, wake behavior and noise characteristics were analyzed for yaw angles from −30° to +30°. Results show that partial wakes slightly raise overall noise levels and lateral asymmetry of trailing-edge noise, while amplitude modulation (AM) strength is more strongly influenced by yaw control. AM varies linearly with wake deflection at moderate yaw angles but behaves nonlinearly beyond a threshold due to large wake deflection and deformation. Findings reveal that yaw control can significantly increase the lateral asymmetry in the AM strength directivity pattern of the downstream turbine, and that AM characteristics depend on the complex interplay between inflow distribution and convective amplification effects, highlighting the importance of accurate wake prediction, along with appropriate consideration of observer point location and blade rotation, for evaluating AM characteristics of a wind turbine influenced by a partial wake. Full article

Flow dynamics were characterized and stable zones in diversions were quantified using physical modeling, in situ experiments, and 3D numerical simulations. ADV (1 cm spatial resolution) and water-level probes (0.01 cm spatial resolution) were used in the physical experiments in a rectangular channel. ADCP (resolution of 50 cm) was employed for in situ validation at a northern China hub. Numerical simulations using ANSYS 2022R2 Fluent software with RNG k-ε and VOF showed little error (<15%) compared to the experiments. The results quantified the diversion zone into four sub-regions: acceleration (length 0.8–1.2 h); stabilization (1.2–3.5 h); diffusion deceleration (3.5–5.0 h); and stagnation (localized eddies, diameter 0.3–0.8 d). The stable zone length was dominantly controlled by the nonlinear coupling of geometric (B_s/B_m, 42%) and hydraulic (Fr, 28%) parameters. Upstream and downstream stable zone empirical models showed high accuracy (R² = 0.83 and 0.76, p < 0.01), with an average relative error <15%. Based on the proposed zoning principles and flow characteristics, measurement facilities in the irrigation area are presented. These tools enhance irrigation diversion design and management for improved water efficiency. Full article

Objectives: The current work aimed to formulate and optimize a self-emulsifying microemulsion drug delivery system (SEME) for acemetacin (ACM) to increase ACM’s aqueous solubility, improve oral bioavailability, and reduce gastrointestinal complications. Methods: Screening of components capable of enhancing ACM solubility was performed. Pseudo-ternary phase diagrams were performed to choose the optimal formulation ratio. The ACM-SEME formulation’s composition was optimized using D-optimal design. Oil, S_mix, and water percentages were used as independent variables, while globule size, polydispersity index, ACM content, and in vitro ACM release after 90 min were used as dependent variables. Also, thermodynamic stability and transmittance percentage tests were studied. Zeta potential was assessed for the optimized ACM-SEME formulation, which was then subjected to spray drying. The dried ACM-SEME was characterized using field-emission scanning electron microscope, Fourier-transform infrared spectroscopy, X-ray diffraction, and differential scanning calorimetry. The dried ACM-SEME formulation was filled into hard gelatin capsules and coated with Eudragit L100 to achieve pH-dependent release. Results: The antinociceptive activity of ACM-SEME was evaluated in vivo using Eddy’s hot plate test in rats, revealing a significant prolongation of the noxious time threshold compared to control groups. Ex vivo permeation studies across rat intestinal tissue confirmed the enhanced permeation potential of the ACM-SEME. Conclusions: It was concluded that the developed ACM-SEME system demonstrated improved physicochemical properties, enhanced release behavior, and superior therapeutic performance, highlighting its potential as a safer and more effective oral delivery platform for ACM. Full article

Under harsh sea states, the dynamic characteristics of ocean mesoscale eddies (OMEs) become significantly more complex, posing substantial challenges to their accurate detection and identification. In this study, we propose an artificial intelligence detection method for OMEs based on the domain adaptation technique to accurately perform pixel-level segmentation and ensure its effectiveness under harsh sea states. The proposed model (LCNN) utilizes large kernel convolution to increase the model’s receptive field and deeply extract eddy features. To deal with the pronounced cross-domain distribution shifts induced by harsh sea states, an adversarial learning framework (ADF) is introduced into LCNN to enforce feature alignment between the source (normal sea states) and target (harsh sea states) domains, which can also significantly improve the segmentation performance in our constructed dataset. The proposed model achieves an accuracy, precision, and Mean Intersection over Union of 1.5%, 6.0%, and 7.2%, respectively, outperforming the existing state-of-the-art technologies. Full article

Low-level wind shear (LLWS) is a critical issue in aviation meteorology, posing serious risks to flight safety—especially at plateau airports with high elevation and complex terrain. This study investigates a convective wind shear event at Xining Airport on 29 May 2021. Multi-source observations—including the Doppler Wind Lidar (DWL), the Doppler weather radar (DWR), reanalysis datasets, and automated weather observation systems (AWOS)—were integrated to examine the event’s fine-scale structure and temporal evolution. High-resolution simulations were conducted using the Large Eddy Simulation (LES) framework within the Weather Research and Forecasting (WRF) model. Results indicate that the formation of this wind shear was jointly triggered by convective downdrafts and the gust front. A northwesterly flow with peak wind speeds of 18 m/s intruded eastward across the runway, generating multiple radial velocity couplets on the eastern side, closely associated with mesoscale convergence and divergence. A vertical shear layer developed around 700 m above ground level, and the critical wind shear during aircraft go-around was linked to two convergence zones east of the runway. The event lasted about 30 min, producing abrupt changes in wind direction and vertical velocity, potentially causing flight path deviation and landing offset. Analysis of horizontal, vertical, and glide-path wind fields reveals the spatiotemporal evolution of the wind shear and its impact on aviation safety. The WRF-LES accurately captured key features such as wind shifts, speed surges, and vertical disturbances, with strong agreement to observations. The integration of multi-source observations with WRF-LES improves the accuracy and timeliness of wind shear detection and warning, providing valuable scientific support for enhancing safety at plateau airports. Full article

For small ectotherms, thermal conditions and habitat structure can drive local adaptations in behavior and habitat use. The water anole, Anolis aquaticus, is a semiaquatic lizard occurring along streams in lowland tropical sites, as well as at higher elevations with greater thermal variability. We studied their thermal ecology, habitat use, and behavior at a high- (~1100 m) and low-elevation (~sea level) site in Costa Rica to assess the relationship between thermal environment and behavioral ecology. We measured behavior through focal observations (rates of movement, head turns, and feeding) and recorded the range of environmental temperatures, body temperatures, air and substrate temperatures of perches, and habitat use (perch location relative to water’s edge and current, substrate, cover, and visibility). The low-elevation site had higher minimum temperatures and a smaller range of available temperatures. Body temperature and size varied with site and sex: low-elevation males had the highest body temperatures, and high-elevation males were largest. Individuals at the high-elevation site were less active, perched closer to the water’s edge (shorter horizontal perch distance), and more often used the ground or rocks near an eddy as a substrate than individuals at the low-elevation site. The temperature and habitat structure of water courses can manifest phenotypic differences in ecology and behavior. Full article

This work presents an analytical 2D model for estimating eddy current losses in the permanent magnets (PMs) of a coaxial magnetic gear (CMG), with a focus on loss minimization through magnet segmentation. The model is applied under various operating conditions, including different rotational speeds, load levels, and segmentation configurations, to derive empirical expressions for eddy current losses in both the inner and outer rotors. A 1D lumped-parameter thermal model is then used to predict the steady-state temperature of the PMs, incorporating empirical correlations for the thermal convection coefficient. Both models are validated against finite element analysis (FEA) simulations. The analytical eddy current loss model exhibits excellent agreement, with a maximum error of 2%, while the thermal model shows good consistency, with a maximum temperature deviation of 5%. The results confirm that eddy current losses increase with rotational speed but can be significantly reduced through magnet segmentation. However, achieving an acceptable thermal performance at high speeds may require a large number of segments, particularly in the outer rotor, which could influence the manufacturing cost and complexity. The proposed models offer a fast and accurate tool for the design and thermal analysis of CMGs, enabling early-stage optimization with minimal computational effort. Full article