Search Results (688)

Near-surface air temperature (Tair) is critical for addressing urban challenges in China, particularly in the context of rapid urbanization and climate change. While many studies estimate Tair at a national scale, they typically provide only daily data (e.g., maximum and minimum Tair), with few focusing on sub-daily urban Tair at high spatial resolution. In this study, we integrated MODIS-based land surface temperature (LST) data with 18 auxiliary data from 2013 to 2023 to develop a Tair estimation model for major Chinese cities, using random forest algorithms across four diurnal and seasonal conditions: warm daytime, warm nighttime, cold daytime, and cold nighttime. Four model schemes were constructed and compared by combining different auxiliary data (time-related and space-related) with LST. Cross-validation results were found to show that space-related and time-related variables significantly affected the model performance. When all auxiliary data were used, the model performed best, with an average RMSE of 1.6 °C (R² = 0.96). The best performance was observed on warm nights with an RMSE of 1.47 °C (R² = 0.97). The importance assessment indicated that LST was the most important variable across all conditions, followed by specific humidity, and convective available potential energy. Space-related variables were more important under cold conditions (or nighttime) compared with warm conditions (or daytime), while time-related variables exhibited the opposite trend and were key to improving model accuracy in summer. Finally, two samples of Tair patterns in Beijing and the Pearl River Delta region were effectively estimated. Our study offered a novel method for estimating sub-daily Tair patterns using open-source data and revealed the impacts of predictive variables on Tair estimation, which has important implications for urban thermal environment research. Full article

Optical remote sensing images have a wide range of applications but are often affected by cloud cover, which interferes with subsequent analysis. Therefore, cloud removal has become indispensable in remote sensing data processing. The Tibetan Plateau, as a sensitive region to climate change, plays a crucial role in the East Asian water cycle and regional climate due to its snow cover. However, the rich ice and snow resources, rapid snow condition changes, and active atmospheric convection in the plateau as well as its surrounding mountainous areas, make optical remote sensing prone to cloud interference. This is particularly significant when monitoring snow cover changes, where cloud removal becomes essential considering the complex terrain and unique snow characteristics of the Tibetan Plateau. This paper proposes a novel Multi-Scale Attention-based Cloud Removal Model (MATT). The model integrates global and local information by incorporating multi-scale attention mechanisms and local interaction modules, enhancing the contextual semantic relationships and improving the robustness of feature representation. To improve the segmentation accuracy of cloud- and snow-covered regions, a cloud mask is introduced in the local-attention module, combined with the local interaction module to modulate and reconstruct fine-grained details. This enables the simultaneous representation of both fine-grained and coarse-grained features at the same level. With the help of multi-scale fusion modules and selective attention modules, MATT demonstrates excellent performance on both the Sen2_MTC_New and XZ_Sen2_Dataset datasets. Particularly on the XZ_Sen2_Dataset, it achieves outstanding results: PSNR = 29.095, SSIM = 0.897, FID = 125.328, and LPIPS = 0.356. The model shows strong cloud removal capabilities in cloud- and snow-covered areas in mountainous regions while effectively preserving snow information, and providing significant support for snow cover change studies. Full article

Heat exchangers play essential roles in the oil and gas production process for convective heat transfer and heat conduction. The health management of heat exchangers stays in the direct monitoring of performance parameters. Aiming at the difficulty of precise fault identification and quantification for heat exchangers in multiple unknown failure modes, a data-model fusion-driven fault quantitative diagnosis method is proposed. Firstly, based on the monitoring data such as temperature, pressure and flow rate, the secondary parameters characterizing the heat exchanger running state are constructed combined with structural physical parameters. Then, by analyzing the correlation among parameter variation, failure modes and deterioration degree, a qualitative inference model of heat exchanger is formed for fault identification, where weights of parameters are introduced based on their sensitivity for different failure modes. After the fault mode is identified, to achieve quantitative analysis of the failure degree, an index-integrated mechanism equation is constructed using monitoring data and secondary parameters, where the index is dynamically modified by online data. Finally, a heat exchanger experiment is carried out to demonstrate the robustness and accuracy of the proposed method. Full article

Firefighters need personal protection equipment and protective clothing to be safe and protected when responding to fire incidents. At present, firefighters’ suits are developed by using inherently thermal-resistant fibers but pose serious problems related to comfort. In the present research, multilayered fire-fighting fabrics were developed with different fiber blends. Multilayer fire retardant (FR) fabrics with phase change materials (PCMs) inserts were developed and compared with reference multilayer fabrics without PCM. In this context, four fabric samples were chosen to fabricate the multilayer FR fabrics. Properties of multilayer fabrics were investigated, which include physical, thermo–physiological comfort, and flame-resistant performance. The heating process of the clothing was examined using infrared (IR) thermography, differential scanning calorimetry (DSC), thermal protective testing (TPP), and steady-state (Convective and Radiant) heat resistance tests. Areal density and thickness were measured as physical parameters, and air permeability (AP), overall moisture management capacity (OMMC), and thermal conductivity were measured as thermo–physiological comfort characteristics. The inclusion of PCM improved the thermal protection as well as flame resistance significantly. Sample S1 (Nomex + PTFE + Nomex with PCM) demonstrated superior fire resistance, air permeability, and thermal protection, with a 37.3% increase in air permeability as compared to the control sample (SC) by maintaining comfort while offering high thermal resilience. The inclusion of PCM enhanced its thermal regulation, moderating heat transfer. Flame resistance tests confirmed its excellent performance, while thermo–physiological assessments highlighted a well-balanced combination of thermal conductivity and air permeability. This study will help to improve the performance of firefighter protective fabrics and provide guidelines in terms of balancing comfort and performance while designing firefighter protective clothing for different climatic conditions. Full article

A numerical study was carried out to analyze the phenomenon of natural convection in a porous medium saturated with nanofluid. In the study, the boundary element method was used for computational modeling. The fluid flow through a porous matrix is described using the Darcy–Brinkman–Forchheimer momentum equation. In addition, a mathematical model for nanofluids was used, which follows a single-phase approach and assumes that the nanoparticles within a fluid can be treated as an independent fluid with effective properties. A combination of single- and sub-domain boundary element methods was used to solve the relevant set of partial differential equations. The method was originally developed for pure flow scenarios, but also proves to be effective in the context of fluid flow through porous media. The results are calculated for the case of two- and three-dimensional square cavities. In addition to various values of dimensionless control parameters, including the porous Rayleigh number (Ra_p), Darcy number (Da), porosity (ϕ) and nanoparticle volume fractions (φ), the effects of the inclination angle of the cavity on the overall heat transfer (expressed by the Nusselt number (Nu)) and fluid flow characteristics were investigated. The results indicate a pronounced dependence of the overall heat transfer on the introduction of nanoparticles and inclination angle. The heat transfer in a two-dimensional cavity is increased for higher values of Darcy number in the conduction flow regime, while it is suppressed for lower values of Darcy number in the Darcy flow regime. In the case of a three-dimensional cavity, increasing the volume fraction of nanoparticles leads to a decrease in heat transfer, and furthermore, increasing the inclination angle of the cavity considerably weakens the buoyancy flow. Full article

Due to its critical importance in engineering applications, this study is motivated by the essential need to understand natural convection over a vertical cylinder with combined heat and mass transfer. Lie group symmetry transformations are used to analyze the thermal and velocity boundary layers of steady, naturally convective laminar fluid flow over the surface of a vertical cylinder. The one-parameter Lie group symmetry technique converts the system of governing equations into ordinary differential equations, which are then solved numerically using the implicit Runge–Kutta method. The effect of the Prandtl number, Schmidt number, and combined buoyancy ratio parameter on axial velocity, temperature, and concentration profiles are illustrated graphically. A specific range of parameter values was chosen to compare the obtained results with previous studies, demonstrating the accuracy of this method relative to others. The average Nusselt number and average Sherwood number are computed for various values of the Prandtl number Pr and Schmidt number Sc and presented in tables. It was found that the time required to reach a steady state for velocity and concentration profiles decreases as the Schmidt number Sc increases. Additionally, both temperature and concentration profiles decrease with an increase in the combined buoyancy ratio parameter N. Flow reversal and temperature defect with varying Prandtl numbers are also shown and discussed in detail. Full article

Convective drying is one of the most commonly employed preservation techniques for food. However, the use of high temperatures and extended drying times often leads to a reduction in product quality and increased energy consumption. To address these issues, hybrid processes combining convective drying with more efficient methods are frequently employed. This study investigates the convective rotary drying of carrot (cv. Nantes), assisted by microwaves and ultrasound, using a hybrid rotary dryer. In total, four distinct drying programs—comprising one convective and three hybrid approaches—were evaluated. The study assessed drying kinetics, energy consumption, and product quality. The use of ultrasound increased the drying rate by 13%, microwaves by 112%, and microwaves and ultrasound together by 140%. The use of microwaves reduced energy consumption by 30%, whereas ultrasound resulted in a slight increase. All processes resulted in a significant reduction in water activity. Ultrasound decreased the color difference index, while microwaves increased it compared to convective drying. Full article

The present paper reports the theoretical results on the thermal performance of proposed Integrated Hybrid Nanofluid Hemi-Spherical Fin Model assuming a combination of Fe₃O₄-Ni/C₆H₁₈OSi₂ hybrid nanofluid. The model leverages the concept of symmetrical geometries and optimized nanoparticle shapes to enhance the heat flux, with a focus on symmetrical design applications in thermal engineering. The simulations are carried out by assuming a silicone oil as a base fluid, due to its exceptional stability in hot and humid conditions, enriched with superparamagnetic Fe₃O₄ and Ni nanoparticles to enhance the heat transfer capabilities, with the aim of contributing to the field of nanotechnology, electronics and thermal engineering, The focus of this work is to optimize the heat dissipation in systems that require high thermal efficiency and stability such as automotive cooling systems, aerospace components and power electronics. In addition, the study explores the influence of key parameters such as heat transfer coefficients and thermal conductivity that play an important role in improving the thermal performance of cooling systems. The overall thermal performance of the model is evaluated based on its heat flux and thermal efficiency. The study also examines the impact of the shape optimized nanoparticles in silicone oil by incorporating shape-factor in its modelling equations and proposes optimization of parameters to enhance the overall thermal performance of the system. Darcy’s flow model is used to analyse the key parameters in the system and study the thermal behaviour of the hybrid nanofluid within the fin by incorporating natural convection, temperature-dependent internal heat generation, and radiation effects. By using the similarity approach, the governing equations were reduced to non-linear ordinary differential equations and numerical solutions were obtained by using four-stage Lobatto-IIIA numerical technique due to its robust stability and convergence properties. This enables a systematic investigation of various influential parameters, including thermal conductivity, emissivity and heat transfer coefficients. Additionally, it stimulates interest among researchers in applying mathematical techniques to complex heat transfer systems, thereby contributing towards the development of highly efficient cooling system. Our findings indicate that there is a significant enhancement in the heat flux as well as improvement in the thermal efficiency due to the mixture of silicone oil and shape optimized nanoparticles, that was visualized through comprehensive graphical analysis. Quantitatively, the proposed model displays a maximum thermal efficiency of 57.5% for lamina shaped nanoparticles at $N_c$ = 0.5, $N_r$ = 0.2, $N_g$ = 0.2 and ${\Theta }_a$ = 0.4. The maximum enhancement in the heat flux occurs when $N_c$ doubles from 5 to 10 for $m_2$ = 0.2 and $N_r$ = 0.1. Optimal thermal performance is found for $N_c$, $N_r$ and $m_2$ values in the range 5 to 10, 0.2 to 0.4 and 0.4 to 0.8 respectively. Full article

Quasi-Linear Convective Systems (QLCSs) are a type of Mesoscale Convective System characterised by their linear shape and association with severe weather phenomena (such as hail, tornadoes, or wind gusts). This study deals with the application of a technique that consists of combinations of radar and lightning data to identify QLCS in Catalonia (the northeast region of the Iberian Peninsula) and the surrounding areas. Even with the limitation of reduced coverage, the technique has revealed efficiency in identifying the systems affecting the region of interest. Concretely, we have detected twenty cases for 2013–2023, significantly less than for other parts of Central Europe but similar to the global values for the whole continent and the United States of America. All cases occurred during the warm season and are divided into diurnal and nocturnal cases with different behaviours. Full article

In metal cutting, a large amount of mechanical energy converts into heat, leading to a rapid temperature rise. Excessive heat accelerates tool wear, shortens tool life, and hinders chip breakage. Most existing thermal studies have focused on dry machining, with limited research on the effects of cutting fluids. This study addresses that gap by investigating the thermal behavior of cutting tools during continuous and interrupted turning with cutting fluid. Tool temperatures were first measured experimentally by embedding a thermocouple in a defined position within the tool. These experimental results were then combined with simulations to evaluate temperature changes, heat partition, and cooling efficiency under various cutting conditions. This work presents novel analytical and numerical models. Both models accurately predicted the temperature distribution, with the analytical model offering a computationally more efficient solution for industrial use. Experimental results showed that tool temperature increased with cutting speed, feed, and cutting depth, but the heat partition into the tool decreased. In continuous cutting, cooling efficiency was mainly influenced by feed rate and cutting depth, while cutting speed had minimal impact. Interrupted cutting improved cooling efficiency, as the absence of chips and workpieces during non-cutting phases allowed the cutting fluid to flow over the tool surface at higher speeds. The convective cooling coefficient was determined through inverse calibration. A comparative analysis of the analytical and numerical simulations revealed that the analytical model can underestimate the temperature distribution for complex tool structures, particularly non-orthogonal hexahedral geometries. However, the relative error remained consistent across different cutting conditions, with less error observed in interrupted cutting compared to continuous cutting. These findings highlight the potential of analytical models for optimizing thermal management in metal turning processes. Full article

Mediterranean tropical-like cyclones, or Medicanes, present unique challenges for precipitation estimations due to their rapid development and localized impacts. This study evaluates the performance of satellite precipitation products in capturing the precipitation associated with Medicane Daniel that struck Greece in early September 2023. Utilizing a combination of ground-based observations, reanalysis, and satellite-derived precipitation data, we assess the accuracy and spatial distribution of the satellite precipitation products GPM IMERG, GSMaP, and CMOPRH during the cyclone event, which formed in the Eastern Mediterranean from 4 to 7 September 2023, hitting with unprecedented, enormous amounts of rainfall, especially in the region of Thessaly in central Greece. The results indicate that, while satellite precipitation products demonstrate overall skill in capturing the broad-scale precipitation patterns associated with Medicane Daniel, discrepancies exist in estimating localized intense rainfall rates, particularly in convective cells within the cyclone’s core. Indeed, most of the satellite precipitation products studied in this work showed a misplacement of the highest amounts of associated rainfall, a significant underestimation of the event, and large unbiased root mean square error in the areas of heavy precipitation. The total precipitation field from IMERG Late Run and CMORPH showed the smallest bias (but significant) and good temporal correlation against rain gauges and ERA5-Land reanalysis data as a reference, while IMERG Final Run and GSMaP showed the largest underestimation and overestimation, respectively. Further investigation is needed to improve the representation of extreme precipitation events associated with tropical-like cyclones in satellite precipitation products. Full article

With the advancement of high-integration and high-density interconnection in chip manufacturing and packaging, Cu bumping technology in wafer- and panel- level packaging is developed to micrometer-sized structures and pitches to accommodate increased I/O numbers on high-end integrated circuits. Driven by this industrial demand, significant efforts have been dedicated to Cu electroplating techniques for improved pillar shape control and solder joint reliability, which substantially depend on additive formulations and electroplating parameters that regulate the growth morphology, crystal structure, and impurity incorporation in the process of electrodeposition. It is necessary to investigate the effect of an additive on Cu pillar electrodeposition, and to explore the Kirkendall voids formed during the reflowing process, which may result from the additive-induced impurity in the electrodeposited Cu pillars. In this work, a self-synthesized polyquaterntum (PQ) was made out with dual suppressor and leveler effects, and was combined with prototypical accelerator bis- (sodium sulfopropyl)-disulfide (SPS) for patterned Cu pillar electroplating. Then, Sn96.5/Ag3.0/Cu0.5 (SAC305) solder paste were screen printed on electroplated Cu pillars and undergo reflow soldering. Kirkendall voids formed at the joint interfaces were observed and quantified by SEM. Finally, XRD, and EBSD were employed to characterize the microstructure under varying conditions. The results indicate that PQ exhibits significant suppressive and levelled properties with the new structure of both leveler and suppressor. However, its effectiveness is dependent on liquid convection. PQ and SPS work synergistically, influencing the polarization effect in various convective environments. Consequently, uneven adsorption occurs on the surface of the Cu pillars, which results in more Kirkendall voids at the corners than at the center along the Cu pillar surface. Full article

Accurate temperature prediction of the operating tunnel cable is crucial for its safe and efficient function. To achieve a rapid and accurate prediction of the steady-state temperature of the tunnel cable, the self-modeling pattern in natural convection on the cable surface in the rectangular tunnel is investigated, and the self-modeling method for the convective heat transfer coefficient calculation is proposed. A thermal circuit model for single cables is further established to predict the cable core temperature, and the model is extended to predict the cluster-laid cable core temperature based on the combined method. The results show that when the tunnel size is neglected, the maximum relative deviation of the convective heat transfer coefficient between the self-modeling method and the finite element simulation is only 1.78% in the studied cases, indicating that the natural convection on the cable surface approximately satisfies the self-modeling method. Additionally, applying the self-modeling method to the thermal circuit can accurately predict the temperature of the single cable core. Furthermore, for the three-phase four-circuit cable, the maximum deviation between the temperature prediction results and the finite element results is within 2 K in the studied cases, which verifies the predictive accuracy of the combined method for the cluster-laid tunnel cable. Full article

Convection monitoring and forecasting are crucial for air traffic management as they can lead to the development of intense thunderstorms and hazards such as severe turbulence and icing, lightning activity, microbursts and hail that affect aviation safety. The airport of Burgas is located in southeast Bulgaria on the Black Sea coast and occurrences of intense thunderstorms are mainly observed in the warm season between May and September. This work presents an analysis of severe convection over southeast Bulgaria on 17 September 2022. In the late afternoon, a gust front was formed that reached the Burgas airport with a wind speed exceeding 45 m/s, the record for the past 50 years, damaging the instrument landing system of the airport. To analyse the severe weather conditions, we combine state-of-the-art observations from satellite and radar with the upper-air sounding and surface. The studied period was dominated by the presence of a very unstable air mass over southeast Bulgaria ahead of the atmospheric front. As convection developed and moved east towards Burgas, it had four characteristics of severe deep convection, including gravitational waves at the overshooting cloud top, a cold U-shape, a flanking line and a cloud top temperature below −70 °C. The positive integrated water vapour (IWV) rate of change preceded the lightning activity peak by 30 min. Analysis of integrated vapour transport (IVT) gives higher values by a factor of two compared to climatology associated with the atmospheric river covering the eastern Mediterranean sea. Full article

Variable-temperature convective drying (VTCD) is a promising technology for obtaining high-quality dried mushrooms, particularly when considering rehydration capacity. However, accurate numerical models for variable-temperature convective drying and rehydration of shiitake mushrooms are lacking. This study addresses this gap by employing a model with thermo–hydro and mechanical bidirectional coupling to investigate five dehydration characteristics (moisture ratio, drying rate, temperature, evaporation rate, and volume shrinkage ratio) and a drying load characteristic (enthalpy difference) during VTCD. Additionally, a mathematical model combining drying and rehydration is proposed to analyze the effect of VTCD processes on the rehydration performance of shiitake mushrooms. The results demonstrate that, compared to constant-temperature drying, VTCD-dried mushrooms exhibit moderate shrinkage rates and drying time (16.89 h), along with reduced temperature variation and evaporation rate gradient (Max. 1.50 mol/(m³·s)). VTCD also improves enthalpy stability, reducing the maximum drying load by 58.84% compared to 338.15 K constant-temperature drying. Furthermore, drying time at medium temperatures (318.15–328.15 K) greatly influences rehydration performance. This study quantitatively highlights the superiority of variable-temperature convective drying, offering valuable insights for optimizing the shiitake mushroom drying processes. Full article