Search Results (1,404)

Amid the global transition to carbon neutrality, tidal current energy has become a strategic sustainable energy resource due to its high predictability, power density, and environmental compatibility. Horizontal-axis turbines show great potential for marine energy harvesting, yet the large-scale commercialization of tidal turbines is severely hindered by complex wake dynamics and the lack of reliable, efficient prediction tools for out-of-distribution (OOD) operating conditions. Traditional high-fidelity CFD methods are computationally prohibitive for engineering optimization, while conventional data-driven surrogate models suffer from poor extrapolation performance, extrapolation collapse near training parameter boundaries, and the absence of uncertainty quantification. To address these bottlenecks, this study focuses on the OOD extrapolation of wake flow prediction across tip speed ratio (TSR) distributions for a single horizontal-axis tidal turbine. A CFD-generated spatiotemporal benchmark dataset is constructed for comparative OOD evaluation across various TSR conditions with 9504 total samples. A novel physics-constrained Fourier neural operator framework named TSR-FNO is proposed to improve OOD generalization. The model integrates TSR–Lipschitz regularization to suppress extrapolation collapse and Monte Carlo Dropout to provide reliable uncertainty estimation. Extensive experiments demonstrate that the proposed method effectively reduces prediction error in unseen TSR regimes, mitigates performance degradation in far-field extrapolation, and produces well-calibrated uncertainty estimates consistent with actual prediction confidence. This work provides a data-driven surrogate modeling strategy for fast and reliable wake prediction on a common CFD-generated benchmark, supporting the efficient design, array layout optimization, and engineering deployment of tidal current energy systems. Full article

This wind farm study provides a detailed and deep investigation into numerous aspects of both wind dynamics and the associated wind turbine performance via a wind data analysis utilizing an extrapolated timeframe of 50 years. The major wind characteristics assessed included wind speed and direction, flow inclination, turbulence intensity, and wind speed (average based on extremes) over the entire duration of the evaluated data set. A majority of study results indicated only narrow wind speed ranges (6.3 m/s to 7.0 m/s) for turbine operation within the wind farm. Higher turbine operation speeds than the average measured wind speed may significantly increase turbine energy output. Turbines were evaluated across numerous geographic locations, resulting in average flow inclination (−4.12° to 1.57°) from the vertical to horizontal directions. The variation in flow inclination indicates that there is a geographic component that likely creates a localized terrain impact on turbine performance. Similarly, the measurement of turbulence intensity was also assessed, which indicated elevated levels of turbine mechanical stress and additional requirements for turbine maintenance. Energy production analyses from each turbine in the wind farm exhibited various regions of energy loss, with the highest energy losses associated with select turbines. Full article

Additive manufacturing (AM), particularly Fused Deposition Modeling (FDM), has revolutionized polymer-based fabrication through design freedom and material efficiency. This work presents a comprehensive statical optimization of FDM parameters affecting the flexural properties of acrylonitrile/butadiene/styrene (ABS) specimens. The effects of layer thickness (0.15–0.25 mm), infill density (30–70%), printing speed (35–95 mm/s), and build orientation (Flat, On-edge, Vertical) were investigated following ASTM D790 standards. A Taguchi L9 orthogonal array coupled with ANOVA analysis was employed to quantity parameter significance. According to the ANOVA analysis, infill density was identified as the most influential parameter, accounting for 61.3% of the variation in flexural strength (σ_f) and 60.1% in flexural modulus (E_b). The optimal configuration (0.25 mm layer thickness, 70% infill, 65 mm/s speed, horizontal orientation) yielded a flexural strength of 84.9 MPa and modulus of 2.54 GPa. Microstructural observations confirmed that higher infill and moderate speed improved interlayer fusion and reduced void formation. The developed Taguchi–ANOVA framework offers quantitative insights for tailoring process–structure–property relationships in polymer-based additive manufacturing. Full article

This study investigates, at a microscale, urban sensible heat flux and Kolmogorov entropy in locations with varying degrees of urban densification according to regular geometries, and examines their effect on fractal dimension. To this end, an ultrasonic anemometer was installed in each of four locations spread across a 648 km² area within a basin geomorphology. This anemometer measures the horizontal and vertical components of wind speed and sonic temperature. The measurements for each variable constitute hourly time series of 3968 data points. From the time series of vertical wind speed and sonic temperature, the hourly sensible heat flux was calculated using the statistical technique of covariances. The total heat calculated for each location during the measurement period indicates which location contributes the greatest heat flux to the boundary layer. Applying chaos theory to the hourly sensible heat time series shows that all series are chaotic, and the Kolmogorov entropy can be obtained for each. The chaotic analysis of data from different locations reveals a proportional relationship between heat flux emissions, Kolmogorov entropy, and urban densification, amplifying the Kolmogorov cascade effect. The vertical components of the wind studied result from the interaction of the wind with the geometric regularity of the buildings, which causes increases in both heat flow and Kolmogorov entropy, suggesting a relationship of these quantities with the decay of the fractal dimension. Full article

Vertical axis wind turbines (VAWTs) are promising systems for urban wind energy applications because of their compact layout, omni-directional operation, and favorable integration potential. However, their broader deployment remains limited by poor self-starting capabilities and relatively low aerodynamic efficiency compared to horizontal axis wind turbines. In this study, a passive flow control concept for a straight-bladed VAWT is numerically investigated using a NACA0012 airfoil modified with 45° inclined perforations on the extrados. Four perforated configurations were generated and compared with the baseline profile through a two-stage computational approach. First, steady 2D computational fluid dynamics (CFD) simulations of the isolated airfoils were performed at a free stream velocity of 12 m/s over an angle of attack range of 0–180°. Subsequently, the most relevant aerodynamic trends were assessed at rotor level using transient 2D Moving Mesh simulations for a three-bladed wind turbine with tip speed ratios (TSRs) between 0.5 and 3.5. All perforated variants exhibited higher lift than the baseline airfoil, while the configuration with smaller, denser perforations distributed over the downstream two-thirds of the extrados provided the best overall aerodynamic performance. At TSR = 2.5, this geometry increased the mean moment coefficient from 0.044 to 0.0525 and the power coefficient from 0.109 to 0.131, corresponding to an increase in power output of approximately 20%. These results indicate that inclined extrados perforations constitute a promising passive strategy for improving the aerodynamic performance of small straight-bladed VAWTs, although further 3D and experimental validations are required. Full article

This study involves the design of an integrated machine dedicated to the core processes of classifying, shelling, and cleaning to address the critical drawbacks of existing Camellia oleifera fruit processing equipment, including the high manual labor requirement, low operating efficiency, unsatisfactory shelling and cleaning performance, and severe camellia seed damage. The classifying system employed a slat drum structure, and response surface methodology (RSM) was utilized to determine and optimize its operating parameters: spiral blade speed: 20 rpm; drum speed: 10 rpm; and rise angle: 9.6°. The shelling system employed a horizontal flexible structure, and polyurethane was the core material. We determined through single-factor experiments that the shelling drum rotation speed was 200 rpm. For the cleaning system, a composite mode integrating drum screening and friction separation was adopted, and single-factor experiments further determined the optimal operating parameters: cleaning drum rotation speed: 20 rpm; friction conveyor shaft rotation speed: 150 rpm; and cleaning inclination angle: 25°. The performance test verified that the integrated machine achieved outstanding results: the shelling rate reached 97.52%, the camellia seed breakage rate did not exceed 2.42%, the impurity content rate did not exceed 1.99%, the loss rate was less than 3.66%, and the processing capacity reached 2614 kg/h. Full article

The transition to smart cities is accelerating distributed wind and solar deployment. However, their intermittency challenges grid operation, thereby making accurate machine-learning-based prediction of wind speed and global horizontal irradiance (GHI) crucial. This study presents a cost-effective approach that enhances prediction accuracy by extracting additional features from timestamp records for deep learning models used to forecast GHI and wind speed. Unlike conventional methods that require onsite meteorological measurements, the proposed approach uses only date and time information as inputs to multivariate deep neural networks, including recurrent neural networks, gated recurrent units, long short-term memory (LSTM), bidirectional LSTM, and convolutional neural networks. For wind speed prediction, the proposed configuration achieves R² up to 0.9987, with RMSE as low as 0.067 m/s for 3 d ahead forecasting, outperforming univariate baselines and matching models. For GHI forecasting, the time-based configuration attains R² values above 0.9994 in 12 h ahead predictions, with the RMSE reduced to approximately 4.47 W/m², representing a substantial improvement over univariate models. The proposed framework maintains strong performance, particularly under clear and sunny conditions. These results demonstrate that timestamp-engineered features can deliver forecasting accuracy comparable to conventional multivariate meteorological models while significantly reducing infrastructure requirements, making the approach well-suited for scalable smart city energy management. Full article

Road transportation is a major contributor to global CO₂ emissions, yet the influence of road geometry on vehicular emissions remains insufficiently quantified under real-world conditions. This study investigates the effects of horizontal and vertical alignments on CO₂ emissions of a light-duty gasoline passenger vehicle using Portable Emissions Measurement System (PEMS) data collected along a 62.4 km highway section. Six geometric parameters longitudinal grade, cross slope, horizontal curve radius, horizontal curve length, vertical curve radius, and vertical curve length were analyzed in combination with second-by-second vehicle dynamics. The results indicate that transient CO₂ emissions exhibit substantial variability, with instantaneous emission rates exceeding 7.0 g/s under high-load conditions. Longitudinal slope gradient shows the strongest linear association with emission rate (r = 0.63), while speed and acceleration exhibit weaker but statistically significant correlations (r = 0.21 and r = 0.28, respectively). Vehicle Specific Power (VSP), representing integrated tractive power demand, demonstrates stronger association with instantaneous CO₂ emissions than individual kinematic variables. In contrast, cross slope and horizontal curvature parameters display minimal direct correlations under the tested highway conditions. A nonlinear polynomial regression model modestly improves explanatory performance relative to a linear formulation (R² = 0.21 versus 0.15; RMSE approximately 56 g/km), although a substantial portion of variability remains unexplained, reflecting the complexity of transient real-world processes. Overall, vertical alignment and transient driving conditions dominate CO₂ emission variability, while horizontal parameters play supplementary roles. These findings provide empirical evidence for refining emission models and highlight the importance of incorporating vertical alignment into sustainable roadway design and carbon reduction strategies. Full article

Material-extrusion (MEX) printing with automated filament switching enables single-build multi-material laminates, but interfaces between dissimilar polymers may govern failure. Here, monolithic PETG, monolithic PC–ABS, and an alternating PETG/PC–ABS laminate (COMP) with 0.2 mm laminae (4 mm total) were fabricated and benchmarked. Tensile behavior was measured using ISO 527-2 Type 1B specimens at 5 and 50 mm/min, complemented by three-point bending in horizontal/vertical orientations, unnotched Charpy impact (ISO 179), Shore D hardness (ISO 868), and SEM fractography. COMP delivered the highest horizontal flexural strength (159.82 ± 25.42 MPa), exceeding both single-material baselines, indicating improved bending load capacity in the preferred orientation. In Charpy impact, COMP absorbed more energy than PETG in the horizontal condition (0.86 ± 0.14 J vs. 0.57 ± 0.06 J) but remained below PC–ABS. In tension, COMP strength decreased by ~21–23% relative to PETG and by ~5–6% relative to PC–ABS at both speeds, consistent with interface-controlled damage. SEM revealed void-assisted crack initiation and interfacial debonding aligned with raster paths, highlighting interfacial strengthening and porosity reduction as key routes to improve tensile performance while retaining favorable flexural and impact response. Full article

Low solution accuracy and efficiency are two bottleneck problems in the existing models and methodologies for spatial distance calculations to verify the minimal electrical clearance of overhead transmission lines if a dynamic windage yaw is considered. To address these two issues, the accurate numerical models and the corresponding efficient solution methodologies tailored for different scenarios are proposed. First, a conductor windage yaw surface model incorporating a horizontal specific load coefficient is established, transforming the wire-to-wire minimal distance determination into a multi-dimensional nonlinear constrained optimization problem. An improved gradient-guided crossover genetic algorithm (GGA) is subsequently developed to solve this optimization problem. By integrating the gradient information to guide the crossover operator and combining an adaptive mutation with a dimension mutation strategy, the solution efficiency is enhanced. For the wire-to-tower minimal distance determination, a simplified tower model and a hybrid optimization methodology combining an oriented octree with the GGA are proposed. Numerical results on typical case studies show that, for a wire-to-wire minimal distance calculation, the GGA outperforms both the basic genetic algorithm and particle swarm optimization in terms of both convergence speed and solution accuracy. For a wire-to-tower minimal distance calculation, the oriented octree improves the spatial utilization, and the proposed hybrid methodology substantially improves the computational performance. Full article

To achieve an all-directional and high-speed, high-accuracy autofocus (AF) function, we propose a CMOS image sensor with a Twisted Photodiode (PD) structure. The developed 3D-stacked back-side illuminated (BSI) sensor employs the Twisted PD, which enables equivalent angular response characteristics in both the horizontal and vertical directions for the two PDs integrated within a single pixel, thereby realizing AF detection for all pixels and all directions. This paper describes the Twisted PD structure that enables all-directional AF and presents an analysis of charge transfer behavior in this unique 3D configuration. In this paper, “all-directional” refers to robustness with respect to subject direction. Full article

All-sky meteor radars are widely employed to observe the near-space atmospheric wind field, a crucial parameter of the near-space environment. Owing to the spatiotemporal uncertainty in meteor count distribution, meteor radars may encounter measurement errors and data gaps when retrieving atmospheric wind fields. Using Kalman filter assimilation technology in combination with the HWM14, this study utilizes atmospheric wind field observation data from the Qujing meteor radar (25.6°N, 103.7°E) to study atmospheric horizontal wind fields within the altitude range of 80–100 km. The assimilation results indicate that the accuracy of the HWM14′s atmospheric wind field is significantly improved after Kalman filter-based assimilation. The discrepancy between the assimilated wind field analysis values and the meteor radar wind field values is notably reduced: the average maximum error of zonal wind speed is 12.0 m/s at 90 km altitude, representing a 55.0% improvement compared to the pre-assimilation state; the average maximum error of the meridional wind speed is 14.2 m/s at 100 km altitude, a 53.4% improvement. Furthermore, the standard deviation of the deviation between the assimilated wind field analysis values and the meteor radar wind field values is also substantially decreased. The assimilated atmospheric wind field information holds great significance for further investigating atmospheric disturbance variations and dynamic processes in the near-space region. Full article

Objectives: This study compares linear sprint force–velocity (F–v) mechanical variables between elite Under-19 (U19) academy players and senior professional players. Methods: Thirty-eight senior players (SP; mean age 24.5 ± 4.3 y) and 214 U19 academy players (YP; mean age 17.4 ± 0.5 y) from 14 first-division club academies were tested during October 2023 using a motorized resistance device (1080 Motion). The following F–v variables were assessed: maximal theoretical force (F₀, N·kg⁻¹), maximal theoretical velocity (v₀, m·s⁻¹), maximal ratio of horizontal-to-resultant force (RF_max, %), and decrease in the ratio of forces (DRF, %). Between-group comparisons were performed using the t-test, and Cohen’s d effect sizes were reported. Results: Senior players outperformed U19 players across all F–v variables. F₀ exhibited a mean difference = 0.220 N·kg⁻¹, with a 95% confidence interval (CI) [0.056, 0.384], p = 0.0166, and d = 0.46. v₀ exhibited a mean difference = 0.560 m·s⁻¹, with a 95% CI [0.410, 0.710], p < 0.0001, and d = 1.07. RF_max exhibited a mean difference = 1.470%, with 95% CI [0.830, 2.110], p = 0.0003, and d = 0.69. DRF exhibited a mean difference = 0.260%, with a 95% CI [0.103, 0.417], p = 0.0013, and d = 0.53. Conclusions: U19 players demonstrated lower F₀, lower v₀, and reduced mechanical effectiveness compared with senior players. Regular monitoring of F–v profiles and individualized training interventions (force- or velocity-targeted) may be useful for training and monitoring strategies aimed at supporting physical preparation during the transition to senior soccer. Full article

Destemming is a critical operation in winemaking, determining the proportion of stems, skins, and vegetal fragments that enter the must and influencing both the mechanical integrity of berries and the extraction kinetics during fermentation. Horizontal centrifugal destemmers, which rely on a rotating beater and a stationary perforated cage, represent the most widely adopted technology in modern wineries. Despite their prevalence, the mechanical basis of berry detachment remains poorly quantified, with operational guidelines grounded largely in empirical practices rather than mechanistic understanding. This study develops an extended theoretical–numerical framework describing the forces acting on grape berries during destemming, focusing on the contributions of centrifugal force, tangential shear, and impact loading. Using realistic machine geometry and published distributions of pedicel detachment strength, the governing equations for each force regime are derived, and their interaction is evaluated through Monte Carlo simulations (n = 10,000). Results demonstrate that tangential shear is the dominant mechanism of detachment, particularly at lower rotational speeds where torque is maximized according to mechanical transmission principles. Centrifugal forces contribute modestly, while impact forces are largely ineffective for detachment and are instead associated with berry damage. The work provides a comprehensive reinterpretation of destemming mechanics and offers new guidance for machine design and operational strategies aimed at improving detachment efficiency while reducing berry damage. Full article

Soil degradation due to wind erosion is a major concern in semi-arid agricultural regions, particularly in South Africa’s Overberg area. This study evaluates the effectiveness of an agroforestry windbreak composed of Eucalyptus cladocalyx F. Muell. in reducing wind speed and horizontal dust flux on a wheat farm during the fallow period. Aeolian transport was quantified by using meteorological data, dust collection with MWAC samplers, and remote sensing via aerosol optical depth. Results showed that the windbreak reduced wind speeds by up to 24%, with higher effectiveness under moderate wind conditions (<8 m·s⁻¹) and in areas of denser vegetation. Dust transport was significantly lower on the leeward side, confirming the barrier’s mitigating influence. However, gaps within the windbreak channelled wind and elevated dust transport locally. The findings highlight agroforestry’s potential for soil protection and initiation of dust depositions in erosion-prone drylands, emphasizing the need for design optimization and broader implementation to enhance agricultural resilience under climate variability. Full article