Search Results (487)

This study investigates the seasonal dynamics of energy balance, evapotranspiration (ET), and Net Ecosystem Production (NEP) in the Dengkou desert ecosystem of Inner Mongolia, China. Using eddy covariance and meteorological data from 2019 to 2022, the research focuses on understanding how these processes interact in one of the world’s most water-limited environments. This arid research area received an average of 109.35 mm per annum precipitation over the studied period, classifying the region as a typical arid ecosystem. Seasonal patterns were observed in daily air temperature, with extremes ranging from −20.6 °C to 29.6 °C. Temporal variations in sensible heat flux (H), latent heat flux (LE), and net radiation (Rn) peaked during summer season. The average ground heat flux (G) was mostly positive throughout the observation period, indicating heat transmission from atmosphere to soil, but showed negative values during the winter season. The energy balance ratio for the studied period was in the range of 0.61 to 0.80, indicating challenges in achieving energy closure and ecological shifts. ET exhibited two annual peaks influenced by vegetation growth and climate change, with annual ET exceeding annual precipitation, except in 2021. Net ecosystem production (NEP) from 2019 to 2020 revealed that the Dengkou desert were a net source of carbon, indicating the carbon loss from the ecosystem. In 2021, the Dengkou ecosystem shifted to become a net carbon sink, effectively sequestrating carbon. However, this was sharply reversed in 2022, resulting in a significant net release of carbon. The study findings highlight the complex interactions between energy balance components, ET, and NEP in desert ecosystems, providing insights into sustainable water management and carbon neutrality strategies in arid regions under climate change effect. Full article

Mesoscale coastal eddies are key components of ocean circulation, mediating the transport of heat, nutrients, and marine debris. The Surface Water and Ocean Topography (SWOT) mission provides high-resolution sea surface height data, offering a novel opportunity to improve the observation and characterization of these features, especially in coastal regions where conventional altimetry is limited. In this study, we investigate a mesoscale anticyclonic coastal eddy observed southwest of Mallorca Island, in the Balearic Sea, to assess the impact of SWOT-enhanced altimetry in resolving its structure and dynamics. Initial eddy identification is performed using satellite ocean color imagery, followed by a qualitative and quantitative comparison of multiple altimetric datasets, ranging from conventional nadir altimetry to wide-swath products derived from SWOT. We analyze multiple altimetric variables—Sea Level Anomaly, Absolute Dynamic Topography, Velocity Magnitude, Eddy Kinetic Energy, and Relative Vorticity—highlighting substantial differences in spatial detail and intensity. Our results show that SWOT-enhanced observations significantly improve the spatial characterization and dynamical depiction of the eddy. Furthermore, Lagrangian transport simulations reveal how altimetric resolution influences modeled transport pathways and retention patterns. These findings underline the critical role of SWOT in advancing the monitoring of coastal mesoscale processes and improving our ability to model oceanic transport mechanisms. Full article

In this study, a computational thermo-fluid dynamics simulation of a wide-slot jet impingement heating process is performed. The present configuration consists of a turbulent incompressible air jet impinging orthogonally on an isothermal cold plate at a Reynolds number of around 11,000. The two-dimensional mean turbulent flow field is numerically predicted by solving Reynolds-averaged Navier–Stokes (RANS) equations, where the two-equation eddy viscosity k-$\omega$ model is utilized for turbulence closure. As the commonly used shear stress transport variant overpredicts heat transfer at the plate due to excessive turbulent diffusion, the recently developed generalized k-$\omega$ (GEKO) model is considered for the present analysis, where the primary model coefficients are suitably tuned. Through a comparative analysis of the various solutions against one another, in addition to reference experimental and numerical data, the effectiveness of the generalized procedure in predicting both the jet flow characteristics and the heat transfer at the plate is thoroughly evaluated, while determining the optimal set of model parameters. By improving accuracy within the RANS framework, the importance of model adaptability and parameter tuning for this specific fluid engineering application is demonstrated. This study offers valuable insights for improving predictive capability in turbulent jet simulations with broad engineering implications, particularly for industrial heating or cooling systems relying on wide-slot jet impingement. Full article

The precise forecasting of mesoscale eddy trajectories holds significant importance for understanding their mechanisms in driving global oceanic mass and heat transport. However, mesoscale eddies are influenced by numerous stochastic and uncertain factors, leading to substantial fluctuations in their attribute variables. Additionally, the trajectories of eddies are related to historical trends and interact with surrounding eddies. These render the accurate forecasting of mesoscale eddy trajectories a formidable challenge. This study proposes a novel dynamic forecasting framework for eddies’ trajectories, termed EddyGnet, a dual graph neural network framework that synergistically models the complex multivariable association and the spatiotemporal eddy association. In this framework, the dynamic association among eddy attribute variables is first explored by a multivariable association graph (MAG) learning module. Subsequently, the spatial and temporal association among eddies are concurrently analyzed using a spatiotemporal eddy association graph (STEAG) learning module. Finally, a decayed volatility loss function is designed to properly handle the complex and variable data features and improve the forecasting performance. The experimental results on the eddy dataset verify the effectiveness of our proposed EddyGnet, demonstrating superior predictive accuracy and stability compared with existing classical methods. The findings advance the mechanistic understanding of eddy dynamics and provide a transferable paradigm for geoscientific spatiotemporal modeling. Full article

Investigating the coupled hydrodynamic and thermal wakes induced by underwater vehicles is vital for non-acoustic detection and environmental monitoring. Here, the standard SUBOFF model is simulated under eight operating conditions—speeds of 10, 15, and 20 kn; depths of 10, 20, and 30 m; and both with and without thermal discharge—using Delayed Detached Eddy Simulation (DDES) coupled with the Volume of Fluid (VOF) method. Results indicate that, under heat emission conditions, higher speeds accelerate wake temperature decay, making the thermal wake difficult to detect downstream; without heat emission, turbulent mixing dominates the temperature field, and speed effects are minor. With increased speed, wake vorticity at a fixed location grows by about 30%, free-surface wave height rises from 0.05 to 0.15 m, and wavelength remains around 1.8 m, all positively correlated with speed. Dive depth is negatively correlated with wave height, decreasing from 0.15 to 0.04 m as depth increases from 5 to 20 m, while wavelength remains largely unchanged. At a 10 m submergence depth, the thermal wake is clearly detectable on the surface but becomes hard to detect beyond 20 m, indicating a pronounced depth effect on its visibility. These results not only confirm the positive correlation between vessel speed and wake vorticity reported in earlier studies but also extend those findings by providing the first quantitative evaluation of how submergence depth critically limits thermal wake visibility beyond 20 m. This research provides quantitative evaluations of wake characteristics under varying speeds, depths, and heat emissions, offering valuable insights for stealth navigation and detection technologies. Full article

Under the trend of lightweight and high-efficiency development in industrial equipment, precise regulation of lubrication in gear reducers is a key breakthrough for enhancing transmission system efficiency and reliability. This study establishes a three-dimensional numerical model for high-speed gear jet lubrication using computational fluid dynamics (CFD) and dynamic mesh technology. By implementing the volume of fluid (VOF) multiphase flow model and the standard k-ω turbulence model, the study simulates the dynamic distribution of lubricant in gear meshing zones and analyzes critical parameters such as the oil volume fraction, eddy viscosity, and turbulent kinetic energy. The results show that reducing the oil injection distance significantly enhances lubricant coverage and continuity: as the injection distance increases from 4.8 mm to 24 mm, the lubricant shifts from discrete droplets to a dense wedge-shaped film, mitigating lubrication failure risks from secondary atomization and energy loss. The optimized injection distance also improves the spatial stability of eddy viscosity and suppresses excessive dissipation of turbulent kinetic energy, enhancing both the shear-load capacity and thermal management. Dynamic data from monitoring point P show that reducing the injection distance stabilizes lubricant velocity and promotes more consistent oil film formation and heat transfer. Through multiphysics simulations and parametric analysis, this study elucidates the interaction between geometric parameters and hydrodynamic behaviors in jet lubrication systems. The findings provide quantitative evaluation methods for structural optimization and energy control in gear lubrication systems, offering theoretical insights for thermal management and reliability enhancement in high-speed transmission. These results contribute to the lightweight design and sustainable development of industrial equipment. Full article

The accurate estimation of evapotranspiration ($ET$) and its components are vital for water resource management and irrigation planning. This study models tree transpiration ($T$) and $ET$ for grapefruit, litchi, and mango orchards using light gradient-boosting machine (LightGBM) optimized using the Bayesian hyperparameter optimization. Grounds $T$ and $ET$ for these crops were measured using the heat ratio method of monitoring sap flow and the eddy covariance technique for quantifying $ET$. The Sentinel 2 satellite was used to compute field leaf area index ($LAI$). The modelled data were used to partition the orchard $ET$ into beneficial ($T$) and non-beneficial water uses (orchard floor evaporation—$E_s$). We adopted the 10-fold cross-validation to test the model robustness and an independent validation to test performance on unseen data. The 10-fold cross-validation and independent validation on $ET$ and $T$ models produced high accuracy with coefficient of determination ($R^2$) $\ge$ 0.88, Kling–Gupta efficiency ($KGE$) $\ge$ 0.91, root mean square error ($RMSE$) $\le$ 0.04 mm/h, and mean absolute error ($MAE$) $\le$ 0.03 mm/h for all the crops. The study demonstrates that LightGBM can accurately model the transpiration and evapotranspiration for subtropical tree crops using Sentinel 2 data. The study found that $E_s$ which combined soil evaporation and understorey vegetation transpiration contributed 35, 32, and 31% to the grapefruit, litchi and mango orchard evapotranspiration, respectively. We conclude that improvements on orchard floor management practices can be utilized to minimize non-beneficial water losses while promoting the productive water use ($T$). Full article

Forest–atmosphere interactions through mass and energy fluxes significantly influence climate processes. However, due to anthropogenic actions, native Araucaria forests in southern Brazil, part of the Atlantic Forest biome, have been drastically reduced. This study quantifies CO₂ and energy flux contributions from each forest stratum to improve understanding of surface–atmosphere interactions. Eddy covariance data from November 2009 to April 2012 were used to assess fluxes in an Araucaria forest in Paraná, Brazil, across the ecosystem, understory, and overstory strata. On average, the ecosystem acts as a carbon sink of −298.96 g C m⁻² yr⁻¹, with absorption doubling in spring–summer compared to autumn–winter. The understory primarily acts as a source, while the overstory functions as a CO₂ sink, driving carbon absorption. The overstory contributes 63% of the gross primary production (GPP) and 75% of the latent heat flux, while the understory accounts for 94% of the ecosystem respiration (RE). The energy fluxes exhibited marked seasonality, with higher latent and sensible heat fluxes in summer, with sensible heat predominantly originating from the overstory. Annual ecosystem evapotranspiration reaches 1010 mm yr⁻¹: 60% of annual precipitation. Water-use efficiency is 2.85 g C kgH₂O⁻¹, with higher values in autumn–winter and in the understory. The influence of meteorological variables on the fluxes was analyzed across different scales and forest strata, showing that solar radiation is the main driver of daily fluxes, while air temperature and vapor pressure deficit are more relevant at monthly scales. This study highlights the overstory’s dominant role in carbon absorption and energy fluxes, reinforcing the need to preserve these ecosystems for their crucial contributions to climate regulation and water-use efficiency. Full article

In semi-arid regions, seasonally dry tropical forests are essential for regulating the surface energy balance, which can be analyzed by examining air heating processes and water availability control. The objective of this study was to evaluate the ability of the Brazilian Developments on the Regional Atmospheric Modelling System (BRAMS) model in simulating the seasonal variations of the energy balance components of the Caatinga biome. The surface measurements of meteorological variables, including air temperature and relative humidity, were also examined. To validate the model, we used data collected in situ using an eddy covariance system. In this work, we used the BRAMS model version 5.3 associated with the Joint UK Land Environment Simulator (JULES) version 3.0. The model satisfactorily represented the rainfall regime over the northeast region of Brazil (NEB) during the wet period. In the dry period, however, the coastal rainfall pattern over the NEB region was underestimated. In addition, the results showed that the surface fluxes linked to the energy balance in the Caatinga were impacted by the effects of rainfall seasonality in the region. The assessment of the BRAMS model’s performance demonstrated that it is a reliable tool for studying the dynamics of the dry forest in the region, providing valuable support for sustainable management and conservation efforts. Full article

Heat exchangers are critical components in various industrial applications, requiring efficient thermal management to enhance thermal performance and energy efficiency. Longitudinal vortex generators (LVGs) have emerged as a potent mechanism to enhance heat transfer within these devices. A precise knowledge of the thermal performance enhancement of HE through LVGs is missing in the literature. Therefore, this study aims to provide a critical review of both numerical simulations and experimental studies focusing on the enhancement of heat transfer through LVGs to further enhance the knowledge of the field. It begins with elucidating the fundamental principles behind LVGs and delineating their role in manipulating flow patterns to augment heat transfer. This is followed by an exploration of the various numerical methods employed in the field, including computational fluid dynamics techniques such as Reynolds-Averaged Navier–Stokes (RANS) models, Large Eddy Simulation (LES), and Direct Numerical Simulation (DNS). Various experimental methods are then summarised, including differential pressure measuring instruments, temperature measurements, velocity measurements, heat transfer coefficient measurements, and flow visualisation techniques. The effectiveness of these methods in capturing the complex fluid dynamics and thermal characteristics induced by LVGs is critically assessed. The review covers a wide range of LVG configurations, including their geometry, placements, and orientations, and their effects on the thermal performance of heat exchangers. Different from previous reviews that mainly focus on classical configurations and historical studies, this review also emphasizes recent developments in computational fluid dynamics and progress in interdisciplinary fields such as innovative materials, additive manufacturing, surface finishing, and machine learning. By bridging the gap between fluid dynamics, thermal enhancement, and emerging manufacturing technologies, this paper provides a forward-looking, comprehensive analysis that is valuable for both academic and industrial innovations. Full article

Conveyor belts are critical in various industries, particularly in the barrier eddy current separator systems used in recycling processes. However, hidden issues, such as belt misalignment, excessive heat that can lead to fire hazards, and the presence of sharp or irregularly shaped materials, reduce operational efficiency and pose serious threats to the health and safety of personnel on the production floor. This study presents an intelligent monitoring and protection system for barrier eddy current separator conveyor belts designed to safeguard machinery and human workers simultaneously. In this system, a thermal camera continuously monitors the surface temperature of the conveyor belt, especially in the area above the magnetic drum—where unwanted ferromagnetic materials can lead to abnormal heating and potential fire risks. The system detects temperature anomalies in this critical zone. The early detection of these risks triggers audio–visual alerts and IoT-based warning messages that are sent to technicians, which is vital in preventing fire-related injuries and minimizing emergency response time. Simultaneously, a machine vision module autonomously detects and corrects belt misalignment, eliminating the need for manual intervention and reducing the risk of worker exposure to moving mechanical parts. Additionally, a line-scan camera integrated with the YOLOv11 AI model analyses the shape of materials on the conveyor belt, distinguishing between rounded and sharp-edged objects. This system enhances the accuracy of material separation and reduces the likelihood of injuries caused by the impact or ejection of sharp fragments during maintenance or handling. The YOLOv11n-seg model implemented in this system achieved a segmentation mask precision of 84.8 percent and a recall of 84.5 percent in industry evaluations. Based on this high segmentation accuracy and consistent detection of sharp particles, the system is expected to substantially reduce the frequency of sharp object collisions with the BECS conveyor belt, thereby minimizing mechanical wear and potential safety hazards. By integrating these intelligent capabilities into a compact, cost-effective solution suitable for real-world recycling environments, the proposed system contributes significantly to improving workplace safety and equipment longevity. This project demonstrates how digital transformation and artificial intelligence can play a pivotal role in advancing occupational health and safety in modern industrial production. Full article

The eddy dissipation rate (EDR, or turbulence dissipation rate) is a crucial parameter in the study of the atmospheric boundary layer (ABL). However, the existing Doppler lidar-based estimates of EDR seldom offer long-term comparisons that span the entire ABL. Building upon prior research utilizing Doppler lidar wind-field data, we optimized the EDR retrieval algorithm using a genetic adaptive approach. The newly developed algorithm demonstrates enhanced accuracy in EDR estimation. The daily evolution of EDR reveals a distinct diurnal pattern in its variation. A detailed four consecutive days study of turbulence generated via low-level jets (LLJs) indicated that EDR driven by heat flux (~10⁻² m²/s³) is significantly stronger than that produced through wind shear (~10⁻³ m²/s³). Subsequently, we examined seasonal variations in EDR at different mixing layer heights (MLH, Zi): elevated EDR values in summer (~7 × 10⁻³ m²/s³ at 0.1Zi) contrasted with reduced levels in winter (~6 × 10⁻⁴ m²/s³ at 0.1Zi). In the early morning, EDR decreases with height for 1 magnitude, while in later stages, it remains relatively stable within 0.1 order of magnitude across 0.1Zi to 0.9Zi. Notably, the EDR during DJF exceeds that of MAM and SON in the afternoon. This suggests that ML turbulence is not solely dependent on surface fluxes (SHF + LHF) but may also be influenced by MLH. A lower MLH (smaller volume), even with reduced surface fluxes, could potentially result in a stronger EDR. Finally, we compared the evolution of the EDR and MLH in the boundary layer using Doppler lidar data from ARM sites and the PBL (Planetary Boundary Layer) Moving Active Profiling System (PBLMAPS) Airborne Doppler Lidar (ADL). The results show that the vertical wind data exhibit strong consistency (R = 0.96) when the ADL is positioned near ARM Southern Great Plains (SGP) sites C1 or E37. The ADL’s mobility and flexibility provide significant advantages for future field experiments, particularly in challenging environments such as mountainous or complex terrains. This study not only highlights the potential of utilizing Doppler lidar alone for EDR calculations but also extensively explores the development patterns of EDR within the ABL. Full article

Integrating green spaces into urban designs and planning for ecosystem services has become vital; however, in creating these spaces, the growth phase is often overlooked. This study provides insight into the changing energy and carbon dioxide (CO₂) fluxes in a developing forest, “The Forestias” project in Thailand. The eddy covariance technique was applied to determine real-time surface energies and CO₂ fluxes from December 2021 to September 2023. The results suggest that under fast growing conditions of the green areas, the diurnal latent energy flux corresponded with the area gained. This effect was supported by increasing evapotranspiration through the byproduct of canopy gas exchange. Consequently, the influence of green areas on lowering the average ambient temperature compared with the urban non-green surroundings was observed. In terms of CO₂ flux dynamics, the increasing efficacy of photosynthesis was parallel with the growing forest canopy. Changes in flux dynamics due to urban green areas show their potential as a mitigation tool for moderating ambient air temperatures. Moreover, they can serve as a carbon sink within tropical cities and provide a pivotal contribution in reaching carbon neutrality. Full article

Mesoscale eddies play a crucial role as primary transporters of heat, salinity, and freshwater in oceanic systems. Utilizing the latest Surface Water and Ocean Topography (SWOT) dataset, this study employed the py-eddy-tracker (PET) algorithm to identify and track mesoscale eddies in the North Atlantic (NA). Our investigation focused on evaluating the influence of applying varying filter wavelengths (800, 600, 400, and 200 km) for absolute dynamic topography (ADT) on the detection of spatiotemporal patterns and dynamic properties of mesoscale eddies, encompassing eddy kinetic energy (EKE), effective radius, rotational velocity, amplitude, lifespan, and propagation distance. The analysis reveals a cyclonic to anticyclonic eddy ratio of approximately 1.1:1 in the study region. The dynamic parameters of mesoscale eddies identified at filter wavelengths of 800 km and 600 km are similar, while a marked reduction in these parameters becomes evident at the 200 km wavelength. Parameter comparative analysis indicates that effective radius exhibits the highest sensitivity to wavelength reduction, followed by amplitude, whereas rotational velocity remains relatively unaffected by filtering variations. The lifespan distribution analysis shows that the majority of eddies persist for 7–21 days, with only a small number of robust mesoscale eddies maintaining activity beyond 45 days. These long-lived, strong mesoscale eddies are primarily generated in the high-energy current zones associated with the Gulf Stream (GS). Full article

This study establishes a standardized framework for thermal propagation test in nickel-7 lithium-ion battery systems through a high-frequency electromagnetic induction heating method. The non-intrusive triggering mechanism enables precise thermal runaway initiation within two seconds through localized eddy current heating (>1200 °C), validated through cell-level tests with 100% success rate across diverse trigger positions. System-level thermal propagation tests were conducted on two identical battery boxes. The parallel experiments revealed distinct propagation patterns influenced by system sealing quality. In the inadequately sealed system (Box 01), flame formation led to accelerated thermal propagation through enhanced convective and radiative heat transfer. In contrast, the well-sealed system (Box 02) maintained an oxygen-deficient environment, resulting in a controlled sequential propagation pattern. The testing methodology incorporating dummy modules proved efficient for validating thermal protection strategies while optimizing costs. This study contributes to a deeper understanding of thermal runaway propagation mechanisms and the development of standardized testing protocols for large-format battery systems. Full article