Search Results (1,135)

To mitigate the spatiotemporal mismatch between renewable energy supply and building heating demand, this study proposes a novel non-pressurized shell-and-tube latent heat storage (NP-LHS) device coupled with an air-source heat pump (ASHP) system. To overcome the inherent low thermal conductivity of organic phase change materials (PCMs), the thermal performances of plain, corrugated, and finned tubes were systematically compared using both computational fluid dynamics (CFD) simulations and full-scale experiments. Numerical results indicate that the optimal tube spacing ratio ranges from 1.0 to 1.5. Among the evaluated geometries, the finned tube configuration exhibited superior comprehensive performance. It achieved an exceptionally high PCM volume fraction of 92.5% and dramatically reduced the complete melting time to 180 min—significantly faster than both corrugated (280 min) and bare tubes—while attaining a higher terminal temperature. Full-cycle dynamic experiments further demonstrated that integrating the finned tube NP-LHS into the ASHP system yielded a peak-shaving power reduction rate of 98.0%, effectively maintaining indoor thermal comfort. These findings conclude that expanding the conductive surface area via fins is practically more effective than inducing fluid turbulence for low-conductivity PCMs in non-pressurized storage applications. Full article

This study numerically investigates the aerodynamic and thermal interactions between a full-scale metro train and the surrounding airflow within a confined tunnel environment using steady-state Reynolds-averaged Navier–Stokes (RANS) simulations. The six-car train, with a total length of 108 m and a cross-sectional area of 5.97 m², operates in a tunnel with a 9.83 square meter cross-section, resulting in a high blockage ratio of approximately 60 percent. The Shear Stress Transport (SST) k–ω turbulence model and a high-resolution finite-volume mesh comprising over 8.5 million elements were employed to capture detailed near-wall phenomena. Six representative motion scenarios were analyzed, including early acceleration, peak cruising, and deceleration phases, with realistic thermal boundary conditions applied by assigning the tunnel air temperature as 29.2 °C and the train surface temperature as 35.0 °C. Velocity, pressure, temperature, and turbulence kinetic energy distributions were extracted from both longitudinal and cross-sectional planes. In addition to visual contour assessments, pointwise and spatially averaged field data were examined to quantify the development of airflow structures, pressure distribution, and thermal behavior. The results reveal speed-dependent aerodynamic resistance, pronounced recirculation and stagnation zones around the train nose and tail, and variations in convective heat transfer rates that evolve with train velocity. These findings provide insights into tunnel ventilation design and thermal management for underground metro operations, representing a novel integration of full-scale computational fluid dynamics (CFD) with thermal characterization under realistic conditions. Full article

Top Submerged Lance (TSL) technology is widely used in non-ferrous smelting, yet in-situ bath dynamics remain challenging to quantify because the process operates in a closed, high-temperature, highly turbulent and optically inaccessible environment. The absence of direct diagnostics limits the ability to relate operating conditions to bubble dynamics, gas penetration and bath agitation and constrains validation of multiphase CFD models under realistic conditions. This study introduces a multimodal sensing framework that combines spectral acoustic analysis with lance-mounted inertial motion sensing to characterize dynamic bath behavior across cold-model, laboratory-scale and pilot-scale systems. Water-glycerin experiments establish repeatable acoustic signatures of individual bubble-collapse events, with dominant emission bands in the 300–900 Hz range and higher-frequency components extending into the kilohertz domain. High-temperature laboratory trials using fayalitic slag reproduce these frequency regions while exhibiting depth-dependent attenuation and clear spectral separation between submerged and non-submerged lance operation. Power Spectral Density (PSD) and cumulative spectral power analyses resolve the influence of gas flow rate and lance submersion depth on acoustic spectral power distribution, while inertial measurements capture corresponding increases in vertical lance acceleration associated with back-pressure fluctuations. Pilot-scale trials at 120 Nm³/h air and 13 L/h diesel confirm that shallow lance submersion substantially increases measured acoustic spectral power below 3 kHz, whereas deeper penetration enhances periodic vertical acceleration response measured by the inertial sensor. The combined acoustic-inertial methodology provides a physically interpretable and cross-scale framework for assessing bubble collapse activity, plume interaction and bath agitation under high-temperature TSL conditions. The approach enables frequency-based diagnostics that can be systematically compared with CFD predictions of plume oscillation and collapse-related dynamics. Once baseline frequency ranges are established for a given slag system, the method can support process monitoring and may provide indirect indicators related to changes in surface agitation or foaming tendency, enabling structured data-driven analysis. The framework thus provides a practical bridge between cold-model experiments, high-temperature measurements, multiphase modeling and industrial TSL operation. Full article

Building upon our previous aerodynamic characterizations of skewed jets, this study extends the investigation to systematically evaluate their thermal performance. Turbulent air jets are produced by unilaterally supplying coolant and forcing it through a series of concave perforated blockages having varying relative inner diameters (D_in/D_j = 3.0, 4.0 and 5.0) or relative thicknesses (t/D_j = 0.5, 2.0, 4.0, 6.0 and 8.0), with the jet diameter and Reynolds number fixed at D_j = 21 mm and Re_j = 20,000, respectively. The results demonstrate that the skewed jets exhibit pronounced asymmetric velocity profiles in both the x–z and y–z planes. Unlike the Gaussian distributions characteristic of conventional axisymmetric jets, these profiles manifest as distinctly skewed or saddle-shaped topologies. This topological distortion is exacerbated by reducing either D_in/D_j or t/D_j, albeit through fundamentally different mechanisms: the former only leads to jet deflection from the geometric axis, with the deflection angle increasing non-linearly from α = 4°, 5° to 12°; whilst the latter induces asymmetric internal flow development and exit momentum redistribution. The thermal performance of these jets on an iso-flux target flat plate, characterized by Nusselt number distributions at different jet-to-target spacings (H/D_j = 0 to 8.0), is shown to significantly differ from conventional axisymmetric jets. Full article

An approximate analytical model for the variation of A-weighted broadband sound levels with distance over flat acoustically soft ground from a source of known sound power depends on the reduction in low frequency content in noise spectra due to A-weighting. Also, it assumes a weak linear sound speed gradient and a frequency independent attenuation coefficient for air absorption. The model introduces adjustable frequency independent parameters for ground effect, turbulence and atmospheric refraction. An additional parameter allows for the source being located over acoustically hard ground. Predictions of the model are compared with measurements over several ground surfaces. The approximate model predicts a more rapid reduction in sound attenuation due to ground effect with increasing mean propagation path height than the simplified method in a widely used international standard. Moreover, predictions of A-weighted sound levels from onshore wind turbines using the approximate analytical method compare with data and numerical simulations better than the simplified and octave band methods in the international standard and the Swedish standard method. Full article

Future aircraft propulsion concepts (e.g., water-enhanced engines and fuel cells) will depend on efficient water recovery to enhance cycle efficiency and environmental performance. Operating conditions commonly involve droplet (mist) transport in turbulent air and wall-bounded films formed by droplet–wall interactions. This work develops an Eulerian–Lagrangian model within the RANS/URANS framework that accounts for air–droplet–wall phenomena—interfacial shear, impingement, and film advection. A dynamic contact-angle model, implemented and calibrated from static contact angle measurements performed in this study, represents wall wetting at the liquid–solid interface. The model is validated against experiments using two design metrics: pressure loss across the unit and recovered water mass fraction. At a low Mach number ($Ma=0.1$), saturated and dry air produce nearly identical pressure losses in the circular test section, whereas the separation lip geometry exerts a strong influence via local acceleration and separation. The simulations reproduce measured pressure drops and water mass recovery with close agreement. Full article

High-pressure airless spray coating can atomize high-viscosity, high-solids coatings without compressed air and is widely used for large-scale anticorrosion applications, but robotic operation often produces substantial overspray that increases material waste, environmental burden, and lowers deposition efficiency. In this work, air-curtain blowing is investigated as an overspray control strategy for wall-climbing robotic airless spraying. A validated CFD framework was established using the realizable k–ε turbulence model coupled with a discrete-phase model (DPM) to simulate particle atomization, transport, impact, and escape, and to examine the effects of blowing angle and gap distance on the flow field and particle trajectories. Overspray performance was quantified using the wall deposition rate, hood collection rate, and particle escape rate. Experiments using a transparent spray hood with a mass collection system were conducted to validate the numerical predictions. The CFD results captured the measured trends in deposition and escape across the tested conditions. Among the evaluated parameters, a 60° blowing angle provided the most effective overspray reduction by redirecting particles toward the target surface. Overall, combining CFD analysis with experimental validation offers a practical methodology for designing and optimizing air-curtain systems to improve coating efficiency in automated high-pressure airless spray applications. Full article

This study establishes an experimental platform consisting of an adjustable inclined surface and a cross-slope wind system. Turbulent diffusion flames are investigated by examining the variation characteristics of flame morphology under slope angles of 10–40°, cross-slope wind velocities of 0.8–2.0 m/s, and heat release rates of 15.38–61.50 kW. The results show that variations in slope angle change the components of buoyancy in the normal and tangential directions. The normal component influences the lifting of the flame perpendicularly to the slope, while the tangential component, together with differences in air entrainment on both sides of the flame, promotes flame inclination and spreading along the slope surface. The cross-slope wind enhances the horizontal stretching and attachment tendency of the flame through inertial shear, while simultaneously suppressing flame height and its development along the slope. The coupled effects of these factors cause the flame morphology to gradually transition from a nearly vertical state to an attached state. Based on dimensionless analysis, empirical correlations of flame morphology parameters are established by introducing the cross-slope wind Froude number, dimensionless heat release rate, the density ratio of propane to air, and a slope function. Within the experimental range of this study, the data under various conditions show good collapse and correlation under the selected dimensionless parameters. Full article

The dynamical tropopause layer pressure (DTLP) represents a key interface characterizing upper-tropospheric stratification and atmospheric dynamical structure. Its spatial morphology and gradient variations directly influence jet stream distribution as well as the intensity and location of clear-air turbulence (CAT). Over the Tibetan Plateau, complex terrain and pronounced dynamical variability result in a significantly lower tropopause height and enhanced horizontal gradients during winter. Aircraft cruising altitudes frequently approach or intersect the tropopause layer in this region, making accurate and fine-scale characterization of DTLP structures critically important for aviation safety. A deep learning-based DTLP retrieval model (Att-ResUNet_DEM) is developed by integrating terrain constraints and an attention mechanism. Using MERRA-2 reanalysis data as supervisory labels, the model incorporates a squeeze-and-excitation (SE) attention mechanism within a residual encoder–decoder framework, while a digital elevation model (DEM) is introduced as an additional input channel and fused with satellite brightness temperature data to explicitly account for terrain effects. A random forest (RF) model is implemented as a baseline for comparison. Compared with the RF model, the Att-ResUNet_DEM reduces the MAE and RMSE by 13.20% and 9.19%, respectively, while increasing the correlation coefficient to 0.76. Over the primary aviation corridors of the Tibetan Plateau, the Att-ResUNet_DEM model achieves a correlation coefficient(R) of 0.87, with markedly reduced gradient dispersion. A representative CAT case further confirms the model’s ability to capture the overall DTLP morphology and gradient enhancement zones. Overall, by combining a regionalized modeling strategy with terrain constraints, this study systematically improves DTLP retrieval accuracy and gradient consistency over complex terrain, providing a new technical pathway for high-resolution tropopause monitoring and aviation operation support. Full article

Severe clear-air turbulence (CAT) remains a relevant hazard to aviation safety, often occurring without visible atmospheric indicators. This study presents a hybrid forecasting framework that integrates Global Forecast System outputs with machine-learning algorithms to predict severe CAT events over Southeast Brazil. To enhance predictive performance and reduce model complexity, a statistically grounded dimensionality reduction approach based on p-value filtering and false discovery rate control was applied, resulting in a compact set of physically interpretable predictors. Several machine-learning classifiers were then evaluated using receiver operating characteristic analysis to assess their predictive skill. The results show that relatively simple models can achieve strong discrimination when combined with rigorous feature selection, outperforming baseline turbulence diagnostics. These findings highlight the value of combining physically consistent diagnostics with data-driven approaches for regional severe CAT forecasting. Overall, the proposed framework provides an efficient and adaptable strategy that can support improved turbulence awareness and contribute to enhanced aviation safety. Full article

One of the engineering applications inspired by nature is bio-inspired wings. The aerodynamic properties and autorotation characteristics of samara wing models have been studied extensively using both experimental and numerical methods. However, the three-dimensional flow behavior and angle of attack interaction around a natural samara wing are not yet fully understood. This study investigates the flow behavior around a samara wing model, with the aim of underlying physics and qualitatively analyzing the flow field, as well as the aerodynamic forces and stresses. Since the samara wing and the flow around it are three-dimensional, the difficulty of experimental investigation was taken into account, and the numerical analysis was performed using Computational Fluid Dynamics techniques. The results obtained from the numerical solution of the governing equations for three-dimensional turbulent flow were verified with experimental data. The calculations were performed by varying the angle of attack of the model wing between 0 and 50 degrees at 10-degree intervals. Depending on the angle of attack, the velocity field around the wing, surface pressure, and stress distributions, vortex structures formed on the wing and streamlines were analyzed, and the results were presented. This study and its results on this model may lead to the development and optimization of the model and its use in turbines or air vehicles. Full article

Laser fiber-based collimation straightness measurement can eliminate the intrinsic drift of the laser source while offering a simple configuration and simultaneous measurement of straightness in two orthogonal directions. As a high-precision optoelectronic sensing method, it has been widely used for the measurement of straightness, parallelism, perpendicularity, and multi-degree-of-freedom geometric errors. However, two common issues remain in practical applications. One is the nonlinear response of the four-quadrant detector, the core position-sensitive sensor, which is caused by detector nonuniformity and the quasi-Gaussian distribution of the spot. The other is the degradation of measurement performance by atmospheric inhomogeneity and air turbulence along the optical path, particularly in long-distance measurements. To address these issues, a two-dimensional planar calibration method is first proposed to replace conventional one-dimensional linear calibration. A polynomial surface-fitting model is introduced to correct the nonlinear response and inter-axis coupling errors of the four-quadrant photoelectric sensor. Simulation and experimental results show that the proposed method significantly reduces the standard deviation of calibration residuals and improves measurement accuracy. In addition, based on our previously developed common-path beam-drift digital compensation method, comparative experiments were carried out on double-pass common-path and single-pass optical configurations employing corner-cube retroreflectors, and theoretical simulations were performed to analyze the influence of air-turbulence disturbances on measurement stability. Both theoretical and experimental results show that the double-pass common-path configuration exhibits more pronounced temporal drift. Therefore, a real-time digital compensation method for beam drift in long-distance single-pass common-path measurements is proposed. Experimental results demonstrate that the proposed method effectively suppresses drift induced by environmental air turbulence and thereby improving the accuracy and stability of long-travel geometric-error and related straightness measurement for machine-tool linear axes. Full article

Artificial intelligence and machine learning techniques can be used for performing magnetic testing on spacecraft that has historically been difficult and risky to perform. Some of the difficulty arises from the need to take these measurements from within the turbulent near-field area of the spacecraft. Some methods of testing require the spacecraft to be hoisted in the air and swung while the measurements are being taken so that any magnetic signatures in the test area can be removed. These new artificial intelligence and machine learning techniques can be used to determine the magnetic torque of complex magnetic systems. Here we will describe a test method that collects such data and poses much less risk to the spacecraft. We will also show some combinations of hyper-parameters that can be used to increase the speed and accuracy of the models. Some models were able to achieve over 96.6% accuracy of multipole determination on simulated data and over a 99.99% accuracy of dipole moment determination on simulated data. Applications include attitude control systems (ACS), science instrument locations, and data analysis. Full article

In this work, hydrocyclones with a diameter of 45 mm and cone lengths of 85 mm and 110 mm were employed to investigate the classification behavior of silicon carbide particles. Numerical simulations were carried out using FLUENT based on computational fluid dynamics (CFD). The internal flow characteristics were modeled using the Volume of Fluid (VOF) approach for multiphase flow, coupled with the Large Eddy Simulation (LES) turbulence model. Furthermore, the Discrete Phase Model (DPM) was applied to track particle trajectories and analyze their dynamic behavior within the hydrocyclone. The experimental results showed that, under identical inlet pressure conditions, the hydrocyclone with a cone length of 110 mm achieved superior separation efficiency. Increasing the cone length leads to a reduction in cone angle, which contributes to improved classification performance. However, practical design constraints limit the extent to which the cone length can be increased. To further explore this effect, an extended cone geometry of 150 mm was investigated through numerical simulation. The CFD results indicate that a longer cone structure enhances air core stability, prolongs particle residence time, and decreases the probability of particle misclassification. These findings suggest that optimizing cone length is an effective strategy for improving hydrocyclone performance. The novelty of this study lies in the integration of experimental validation and numerical simulation to systematically evaluate both practical and extended cone designs, thereby providing deeper insights into the relationship between structural parameters and separation efficiency. Full article

Mode division multiplexing (MDM) is an emerging optical communication solution for high-capacity wired–wireless applications. Due to the presence of modal crosstalk and link impairments in MDM, this work aims to design a system that provides low complexity, an improved Shannon Capacity limit, and high spectral efficiency. In this work, a quad modal MDM system using an integrated parabolic index multimode fiber and free-space optics (PIMMF-FSO) link is presented. Four linearly polarized (LP) modes, LP₀₁, LP₂₂, LP₀₃, and LP₁₃ based on a 16 × 10 Gbps MDM system offering different sixteen channels, are realized. Results show that the system can sustain a 7.5 dB insertion loss over 100 m FSO and a 100 m fiber range for different LP modes under the impact of clear air, moderate haze, heavy rain and wet snow climates with weak turbulence. A faithful fiber range of 3000 m can be obtained successfully in the proposed system with a −10 dB link loss, −7.62 dBm received power and 10 dB noise. Compared to existing designs, the proposed design offers optimum performance in terms of high channel capacity and a high traffic rate with low complexity and high spectral efficiency. Additionally, high received power, with acceptable noise, link loss, FSO misalignments and fiber nonlinearities, is successfully obtained. Full article