Affect Heat Transfer Research Articles

Wind Rose Analysis of Temperature Variation with Sensor Implantation Technique for Wind Turbine

This study focuses on analysing the impact of seasonal variations in heat on different parts of a "wind energy system," serving as a representative mechanical system. The proposed methodology utilizes wind rose analysis, offering a straightforward means to assess heat transfer effects, applicable to any mechanical system comprising numerous small heat-dissipating components. Furthermore, this work elucidates the correlation between mechanical component performance and heat dissipation impact, providing breakdown alerts for various wind turbine components. Additionally, it analyses the influence of mechanical part temperatures on energy generation, highlighting how high temperatures can indicate component deterioration, such as bearing damage. Notably, the study focuses on wind speeds ranging from 10 to 15 m/s, a typical operational range for wind turbines. By employing wind rose charts and real-time readings, the graded heat dissipating potential of mechanical parts under various wind velocities and weather conditions is determined. Moreover, the study emphasizes the significance of heat transfer analysis in optimizing wind turbine performance, demonstrating how temperature differentials between mechanical components and the environment, along with increased surface area, affect heat transfer. The proposed analysis underscores the importance of considering heat's impact on each mechanical component in tandem with seasonal environmental temperature fluctuations. The wind rose methodology, integrated with sensor implantation, emerges as a cost-effective tool for studying -level heat variances in mechanical systems, enabling the development of heat profiles for future turbine designs and computational fluid dynamics (CFD) analyses. As heat transfer coefficient increases the wind turbine performance decrease. The heat transfer coefficient decreases 14.28% from rainy to winter season and 42.85% from winter to summer season. The wind rose analysis provides valuable insights into wind patterns and characteristics at a specific location, which can inform decision-making in various fields such as energy, construction, environmental management, and safety planning. As the turbine temperature increases the wind velocity decreases. Here it decreases 28 % from rainy to winter season.

Temperature prediction of geothermal drilling considering the drilling fluid thermophysical parameters

An increasing number of geothermal wells are being drilled to meet the growing demand for geothermal energy. Given that the harsh environment of geothermal wells exposes drill-following tools to the risk of high-temperature failure, scholars have developed thermo-mathematical models to predict the temperature field distribution in wellbore. To the best of authors' knowledge, most models ignore the interaction between the fluid thermophysical parameters and its temperature. They also overlook the fact that the actual structure of the drilling column causes changes in the convective heat transfer coefficients between the fluid and the well wall, which subsequently affects heat transfer from the wellbore. In this study, we tested the changes of thermal property parameters of drilling fluid with density and temperature. Based on the actual drill string structure and considering the variation in thermophysical parameters during drilling fluids’ circulation, we innovatively established a transient heat transfer model for geothermal horizontal wells with heat–fluid–solid coupling. Subsequently, a drilled geothermal well was used to simulate the temperature during drilling. The effects of the drilling fluid system, density, and displacement, rotary speed, and WOB during drilling on the wellbore temperature distribution were analyzed. Furthermore, suggestions for the selection of drilling fluid and parameters during the drilling process were given. The results of this study can help accurately predict the wellbore temperature of geothermal wells and high-temperature wells, which provides guidance for the rational selection of drilling tools for drilling operations.

An experimental study on heat transfer using electrohydrodynamics (EHD) over a heated vertical plate.

The Corona effect offers significant potential for improving heat transfer efficiency in air. This study thoroughly examined how a single corona discharge affects heat transfer on a heated vertical flat plate. Key parameters tested included corona voltage, the aspect ratio of the vertical plate (y/L), and the inter-electrode discharge gap ratio (x/d). The findings revealed that increasing the corona voltage and decreasing the discharge gap enhanced heat transfer efficiency along the vertical surface. A predictive formula for the local Nusselt number was developed to characterize heat transfer on the plate. Additionally, Particle Image Velocimetry (PIV) was used to analyze the corona wind generated by the discharge. The study observed that the corona wind formed a vortex in the upstream region, which resulted in lower heat transfer rates upstream compared to the downstream region.

Investigating forced convection in porous media-filled cavities for designing supplementary passive cooling systems

This study aims to propose innovative passive cooling methods within the reservoir section of a closed-loop liquid cooling system. The techniques employed in this study include using a cold wall, a porous medium, varying inlet positions, and nozzles of different sizes and shapes. The effects of parameters associated with these techniques on outlet temperature reduction, pressure drop, and average Nusselt number (Nu¯) have been analyzed in detail. The reservoir section has been numerically modeled as a two-dimensional (2D) and a three-dimensional (3D) cavity. The numerical model implements mass, momentum, energy, and conservation equations for the Darcy model in the porous region. A fluid flow with Re=50 with a laminar generalized porous media modeling approach employing Brinkman’s and Forchheimer’s terms has been used. The optimized inlet position with respect to maximum cooling (55.60 K) and moderate pressure drop (2.30kPa) for the 2D cavity has been identified in this work for a given Darcy number and porosity. Results show that decreasing porosity improves convective heat transfer efficiency and increases pressure drop. Similarly, varying Darcy’s number affects heat transfer, with lower Da values resulting in reduced outlet temperature reduction and lower Nu¯, with higher pressure drop. A similar analysis was conducted for the 3D reservoir. The use of a converging nozzle can lead to an increase in cooling by 61.61% and 3.44% for the 2D and 3D reservoirs, respectively.

Numerical Investigation of Shell-Nozzle Diameter Effect on Thermal Performance of Shell-and-Tube Heat-Exchanger

The shell nozzle diameter plays a crucial role in determining heat transfer efficiency and pressure characteristics in shell and tube heat exchangers. In this study, we have conducted a numerical simulation to explore the effects of varying shell nozzle diameters on heat transfer performance, flow behavior, and pressure drop within a shell and tube heat exchanger. Ranging from 10 to 110 mm, we assessed how altering the shell nozzle diameter affected heat transfer, flow patterns, and pressure drop. Employing the k-ω shear stress transport turbulence model, we compared numerical Nusselt numbers to experimental data, observing a correlation. As the shell nozzle diameter decreased, inlet velocity surged, generating a stronger vortex. Shrinking from 110 to 10 mm, this reduction amplified vorticity by an average of 169%, notably intensifying heat exchange by 35%. Evaluating the overall heat transfer coefficient against pressure drop, we used the thermal enhancement factor, reaching a peak of 4.39 at a 70 mm shell nozzle diameter. This exploration lays groundwork for optimizing shell nozzle diameters in these heat exchangers.

Turbulent pipe flow and heat transfer of a binary mixture at supercritical pressure: Influences of cross-diffusion effects

Cross-diffusion effects, including Soret and Dufour effects, are enhanced around the pseudo-critical temperature (Tpc) of a binary mixture. Their influences on heat transfer at supercritical pressure have been scarcely studied. To bridge this gap, large-eddy simulations (LES) are conducted to investigate forced convective heat transfer of a CO2–ethane mixture at supercritical pressures in a circular pipe subject to a uniform heat flux. Both heating and cooling conditions, along with varying initial concentrations and thermodynamic pressures, are included in the simulations. The LES results reveal that the Soret effect causes concentration separation, resulting in a concentration boundary layer. The magnitudes of the thermodiffusion factor (kT) and the radial temperature gradient control the intensity of separation, which is more pronounced at near-critical pressure and high heat flux. Since kT is significant only around Tpc, downstream decay of the concentration separation is observed as the loci of T=Tpc migrate away from the wall so that the local radial temperature gradient diminishes. The primary factors affecting heat transfer are the variations in thermal conductivity and isobaric specific heat resulting from concentration separation. In contrast, the Dufour effect and the accompanying inter-diffusion play negligible roles. In deterioration scenarios, the bulk Nusselt number (Nub) shows a maximum relative drop of 8%, whereas in enhancement scenarios, Nub shows a maximum relative increase in 10%, with both deterioration and enhancement decaying downstream. Cross-diffusion effects have negligible impacts on density and streamwise velocity, but noticeably alter streamwise velocity fluctuation and turbulent kinetic energy.

Numerical modeling of alkali metal heat pipes

Heat pipe cooled reactors passively transfer heat from the core to the energy conversion system through alkali metal heat pipes. Further studies of the heat transfer characteristics of alkali metal heat pipes are needed to develop heat pipe cooled reactors. This work used a two-dimensional heat and mass transfer model of an alkali metal heat pipe. The flow field was validated against CFD predictions which showed that the model has less than 10 % errors in the velocity distribution and less than 5 % errors in the pressure distribution. A comparison of the predictions with experimental data in the literature indicated that the predicted wall temperature error was within 30 °C. This model was then used to analyze four factors that affect heat transfer in sodium heat pipes. The simulations show that higher heat fluxes shorten the startup time by approximately 70 % but significantly increase the operating temperature. The heat flux distribution significantly affects the evaporator temperature distribution. The heat transfer boundary condition on the condenser’s outer surface mainly affects the operating temperature and startup time. Increasing the heat pipe length-to-diameter ratio with a fixed heat flux increases the operating temperature with the increase proportional to the heat flux. This model provides accurate simulations of sodium heat pipes for various heat transfer boundary conditions. The simulations provide a reference for the selection of working conditions for heat pipe operation instability experiments.

Bubble behavior parameters extraction and analysis during pool boiling based on deep-learning method

The nucleate pool boiling plays an important role in thermal and chemical engineering applications. Analyzing bubble dynamics at nucleation site is crucial to improve the understanding of boiling heat transfer mechanism. Quantitative extraction of bubble parameters from high-speed visualized images is a labor-intensitive and time-consuming task making it necessary for automatically detect single bubble growth and measure boiling characteristic parameters.In the present work, we proposed a deep learning based self-adaptive statistical algorithm for extraction of bubble behavior parameters quickly and automatically from numerous high-speed visualization images looking from the side view of a boiling chamber. A dataset was constructed for training and performance evaluation based on experimental data of saline solution pool boiling. The StarDist and U-Net convolutional neural network were combined in the algorithm so that more exact segmentation of the bubbles can be identified. Based on the segmentation results, a post-processing program was developed to extract the sequential variation of bubbles during consecutive cycles at nucleation sites. The dynamic characteristic parameters that affect heat transfer, such as nucleation density, bubble departure diameter, departure frequency, and wait time under different heat flux were obtained quantitatively. The comparison of automatic extraction algorithm and manual processing proves the reliability and superiority of our method. This work indicates that the proposed method has great potential to be widely applied as an efficient and universal tool for processing different types of bubble shadowgraph images.

Modeling polydispersed droplets in non-equilibrium condensing CO2 flows through turbine cascades using moment-based methods for efficient energy utilization

The efficiency of a power cycle is significantly influenced by the condensation process and the size distribution of the droplets, as these factors directly affect heat transfer rates and overall energy conversion efficiency. Accurate numerical modeling of thermodynamic non-equilibrium condensation is crucial for predicting droplet nucleation and growth in carbon dioxide flows. This study applies moment-based polydispersed droplet models, such as the quadrature method of moments, to account for the droplet size spectrum. Additionally, discrete methods based on a predefined shape of the polydispersed droplet size spectrum are utilized and evaluated to reduce numerical complexity. Our results demonstrate that polydispersed models provide higher accuracy compared to monodispersed models when simulating steam and supercritical carbon dioxide flows in converging–diverging nozzles. In turbine cascades, the choice of model significantly influences the predicted mean droplet size and efficiency. Isentropic efficiency evaluations reveal higher values for carbon dioxide compared to steam, with efficiencies of 94.6–95.8% versus 91.8–92.9% for wet cases and 96.5–97.2% versus 95.8–96.5% for dry cases. Notably, spontaneous droplet nucleation slightly affects the efficiency of the blade cascade in carbon dioxide flows, whereas steam flows experience efficiency reductions between 3.58% and 4.01%. This work advances the understanding of droplet condensation processes in turbine cascades, highlighting the superior performance of polydispersed models and providing quantitative insights into their impact on efficiency.

Effects of dissipation and radiation on the Jeffrey fluid flow in between nano and hybrid nanofluid subject to porous medium

AbstractThe magnetohydrodynamic (MHD) movement of fluids through a porous material has a variety of uses such as distillation towers, heat exchangers, catalytic processes, magnetic field‐based wound treatments, cancer therapy and hyperthermia. This paper explores the complex dynamics of a three‐phase flow utilizing MHD Jeffrey fluid, which sits in between nano and hybrid (molybdenum disulphide [MoS2] and multi‐walled carbon nanotubes [MWCNTs]) nanofluids. The governing differential equations are derived for the physical flow model. The equations are reduced to dimensionless equations by using dimensionless parameters. The resultant equations are solved by using the regular perturbation technique. The results are analysed for various physical pertinent parameters through 2D/3D graphs. The heat transfer rate and volume flow rate are calculated for the left and right plates. This analysis also considers how the system's overall behaviour would be affected by radiation and dissipation effects. The results indicate that the magnetic parameter, electric parameter, quadratic convective parameter, Brinkman number and Grashof number significantly affect heat transfer enhancement. Fluid velocity can be reduced using radiation parameters, porosity, electric and magnetic parameters and velocity declines by Jeffrey parameters.

Numerical Simulation of Effects of Catalyst Layer Parameters on Heat Transfer in Proton Exchange Membrane Fuel Cells

A non-isothermal, two-dimensional, two-phase fuel cell agglomerate model is used, and studies are done on how platinum loading and catalyst layer thickness affect heat transfer in fuel cells. Results indicate that as the cathode platinum content and catalyst layer (CL) thickness rise, the electrical property is improved. The maximum power density corresponding to the platinum loading of 0.40 mg/cm2 increases by 8.92% compared with 0.20 mg/cm2, and the maximum power density corresponding to the CL thickness of 17.5 µm increases by 4.63% compared with 10.0 µm. Temperature variation trends in CLs from entry to exit and inside the cell along the thickness direction do not change. Furthermore, with the CL thickness as well as platinum content increasing, the temperature increment inside cathode gas diffusion layer as well as CL is more obvious, and temperature distribution uniformity within the cell deteriorates. The impact of platinum loading on the temperature in the cell is more obvious than that of CL thickness. In the selection about platinum content and thickness of CL, temperature distribution uniformity and electrical property should be weighed.

Modelling of evaporative falling-film heat transfer over a horizontal tube

This article focuses on evaporative falling film heat transfer through numerical simulations. A two-dimensional symmetric liquid film flowing outside a single horizontal tube was simulated using the open-source CFD software OpenFOAM. The Tanasawa model was employed to consider mass transfer at the liquid–vapour interface, and the isoAdvector VOF method was used for interface tracking. The simulations explored the impact of film flow rate, tube surface heat flux, and tube diameter on the liquid film thickness and surface heat transfer coefficient. Additionally, the critical heat flux and operational limits were considered. The results demonstrate the accurate reproduction of evaporative falling film heat transfer performance by the present model. The film thickness exhibits a similar profile to adiabatic and sensible falling film heat transfer but provides smaller values. Similarly, the evaporative heat transfer coefficient exhibits significantly higher values and a gentle peripheral variation. The influence of heat flux on evaporative falling film heat transfer is contingent on the film flow rate; it can either enhance or weaken the process. Notably, a larger tube diameter negatively affects heat transfer, suppressing the impact of heat flux, and also increases the risk of liquid film dryout. For a given film flow rate, the average heat transfer coefficient increases initially, reaches a maximum value, and then decreases as the wall heat flux is increased. The peak heat flux, termed critical heat flux, increases with film flow rate but decreases with tube diameter. An operational limit exists where the heat flux is lower than the critical heat flux and the film flow rate is higher than the critical film flow rate; under these conditions, evaporative falling film heat transfer operates in a fully wetting status.

Coproduction of metal oxide and CO2 through decomposition of carbonate in a moving bed with a central gas-flow channel

During carbonate calcination process, the block ores are often directly heated by high-temperature flue gas, which inevitably dilutes the potentially high-concentration CO2 from carbonate decomposition. In this study, we well implemented the coproduction of lightly burned magnesia (LBM) and high-concentration CO2 through decomposition of small-size magnesite in a devised novel moving bed reactor. The reactor is installed with a central gas-flow channel as internals to convert the moving bed into a radially flowing reactor, making it can process small-size particles. Verification of this design was implemented in an electrically heated pilot-scale facility processing about 10 kg h−1 magnesite (0–6 mm), and gaseous product contains about 99% CO2. Systematic tests employing laboratory fixed bed reactors with and without internals further showed that the thickness of particle layer between the heating wall and the central internals substantially affects heat transfer from outside to the inside, thus influencing the decomposition. It is particularly for magnesite because the formed LBM is both heat-resistant and flame-retardant. Therefore, an updated reactor for small-size carbonates decomposition and coproduction of CO2 is proposed.

Modelling the Relationship between Water Jetting Parameters and Material Failure in Heat Exchanger Tubes

The Zeeland-Flemish region has a robust process industry where heat exchangers (HEX) are essential for managing heat transfer. However, Fouling in HEX occurs when deposits of contaminants form on surfaces affecting heat transfer. HEX maintenance/cleaning can harm the material of construction (MoC). This study explores how altering Water Jetting (WJ) parameters affects MoC failure mechanisms. This knowledge can optimize processes to prevent unwanted MoC failure while achieving desired fouling control. In this study, a three-factorial experiment was designed to investigate how increased water pressure and flow rates impact the structural health of copper used in HEX tubes during WJ cleaning. Then, we compared these results with experiments using steel as the MoC. Statistical and mathematical analysis were employed to understand the effect of process parameters on damage mechanisms and identify the most influential parameter. For copper samples, we observed that higher water pressure consistently increased damage across all flow rates, following a linear trend of α_p =0.001(gm loss/gm sample. Kpsi). Flow rate's impact on damage exhibited logarithmic behavior, which can be split into two ranges. At low to medium flow levels, increased flow rates raised damage at a rate of α_f =0.007(gm loss/gm sample. gpm). However, at high flow rates, the increase in flow had no effect on the damage as it was attributed solely to pressure. Comparing steel and copper at high pressure levels, it was found that steel experienced a lower linear increase in damage, β_f =0.0036(gm loss/gm sample. gpm), compared to α_f for copper. These results offer insights for optimizing water jetting cleaning processes to minimize material damage during HEX maintenance, enhancing overall efficiency.

Bubble evolution due to super-saturation in the cooling circuit of the PEM-electrolysis

The formation of oxygen bubbles in the anodic circuit of a polymer electrolyte membrane (PEM) electrolyser is a major technological problem as it greatly affects heat transfer, process performance and safety. Overall, bubbles evolve in the pipe flow upstream of the gas separator due to oxygen super-saturation created by the chemical reaction at the anode. The accurate prediction of bubble formation in the pipes is important for the correct positioning and design of the gas separator. This paper therefore presents a cell-based one-dimensional numerical model that estimates bubble evolution in a horizontal pipe-flow. For this purpose, the model considers bubble growth at nucleation sites and in the flow, enabling the prediction of the corresponding gas fraction at different locations within the cooling circuit. Furthermore, a sensitivity analysis was conducted based on the derived model to evaluate the impact of various parameters on the degassing rate. It was found that the smaller the pipe diameter, the greater the initial gas content and the greater the number of nucleation sites, the shorter the pipe length required to achieve solubility.

Effect of using a ZnO-TiO2/water hybrid nanofluid on heat transfer performance and pressure drop in a flat tube with louvered finned heat exchanger

This study used an experimental setup consisting of a flat tube with a louvered finned crossflow configuration to examine the effects of utilizing a ZnO-TiO2-water hybrid nanofluid on heat transfer rate, heat transfer coefficient, Nusselt number, and pressure drop. The studies were carried out under laminar flow conditions (200 < Re < 800), at four different temperatures (50, 60, 70, 80 °C), four different volume concentrations of nanoparticles (0.025, 0.05, 0.1, 0.2%), and three different volume flow rates (4, 6, 8 LPM). The findings were compared with pure water (0%). The results indicate that using hybrid nanofluid improves the heat transfer performance and increases pressure loss in comparison with pure water. When comparing hybrid nanofluid to pure water, the largest increases in heat transfer rate, heat transfer coefficient, Nusselt number, and pressure drop were 87.8%, 21.7%, 26.4%, and 10%, respectively. In addition, it was found that, up to a specific value (0.05%), increasing the nanoparticle volume concentration enhanced the heat transfer rate, heat transfer coefficient and Nusselt number, but which began to decrease on increasing the concentration past this value. Therefore, it was concluded that nanoparticle volume concentrations greater than 0.05% negatively affect heat transfer under the current operating conditions. The maximum heat transfer rate, heat transfer coefficient, and Nusselt number were obtained under the conditions of an 8 LPM volume flow rate, 80 °C inlet temperature, and 0.05% volume concentration.

Investigation of the effect of geometric configurations on natural convection heat transfer in external flow

AbstractThe complexities of natural convection heat transfer are investigated through experimentation, focusing on the influence of geometric configurations such as spheres, cylinders, and cubes in external flows. The study aims to understand how different geometries affect heat transfer coefficients, providing insights for architectural and engineering applications. Experimental results revealed significant variations in heat transfer efficiency among geometric models, with cubic configurations exhibiting the lowest heat transfer rates compared with spherical and cylindrical counterparts. This underscores the critical impact of geometric configuration on thermal performance and heat dissipation characteristics. The findings highlight the necessity of considering geometric factors in design processes to optimize thermal management strategies. The study contributes to a deeper understanding of convective heat transfer mechanisms, emphasizing the importance of precise geometric modeling in enhancing energy efficiency and sustainability in built environments

An assessment of the performance of heat transfer enhancement for optimizing high-temperature thermal energy storage

Background: High-temperature phase change materials (PCMs) are increasingly recognized for their potential in applications such as solar energy utilization, industrial waste heat recovery, and power load regulation. These materials can store and release significant amounts of latent heat, making them highly efficient for thermal energy storage. Purpose: This study aims to propose and analyze a novel structure to enhance latent heat energy storage using a graphite sheet combined with a PCM (KNO3-NaNO3) with a melting point of 220 K. The focus is on improving heat transfer efficiency and understanding the parameters affecting the exothermic process. Research Design: A numerical simulation approach was employed, using Fluent 7.1 software to analyze the exothermic process. The simulation method was validated with two examples before being applied to study the energy storage system incorporating graphite sheets. Study Sample: The study analyzed the performance of a high-temperature thermtotal energy storage (HTTES) system using graphite sheets of varying thicknesses, tube spacing, tube temperatures, and PCM thermal conductivities. Data Collection and/or Analysis: The study utilized numerical simulations to examine how different parameters i.e. thickness of graphite sheets, spacing between tubes, tube temperatures, and the thermal conductivity of PCM—affect heat transfer efficiency and exothermic time. Results: The integration of graphite sheets with a thickness of 2 mm was found to significantly improve heat transfer efficiency. The results indicated that increasing the spacing between graphite sheets and tube diameter influenced the total exothermic time. A logarithmic relationship was observed between the thermal conductivity coefficient and exothermic time, suggesting diminishing returns beyond 3.5 W/(m·K). Additionally, increasing the quantity of graphite sheets enhanced heat transmission and overall system efficiency. Conclusions: The study provides valuable insights into the performance of HTTES systems, demonstrating that incorporating graphite sheets can significantly enhance heat transfer and system efficiency. These findings guide the design of more effective thermal energy storage systems, supporting the broader adoption of HTTES technologies and contributing to the transition toward sustainable energy solutions. Further research and development in this field are essential to drive advancements and promote the widespread implementation of high-temperature thermal energy storage systems. Practical applications The enhanced heat transfer techniques developed in this research offer practical applications across various sectors. These techniques, utilizing PCMs and innovative graphite structures, enhance the efficiency and reliability of high-temperature thermal energy storage systems. This advancement enables continuous power generation in concentrated solar power (CSP) plants, optimizes energy utilization in district heating and cooling systems, and improves industrial waste heat recovery. By implementing these techniques, energy costs can be reduced, system performance can be optimized, and greenhouse gas emissions can be lowered, contributing to a more sustainable energy future.

Two-temperature modeling of lamellar cathode arc

A three-dimensional, two-temperature (2T) model of a lamellar cathode arc is constructed, drawing upon the conservation equations for mass, momentum, electron energy, and heavy particle energy, in addition to Maxwell’s equations. The model aims to elucidate how the physical properties of electrons and heavy particles affect heat transfer and fluid flow in a lamellar cathode arc. This is achieved by solving and comparing the fields of electron temperature, heavy particle temperature, fluid flow, current density, and Lorentz force distribution under varying welding currents. The results show that the guiding effect of the lamellar cathode on current density, the inertial drag effect of moving arc, and the attraction effect of Lorentz force at the lamellar cathode tip primarily govern the distribution of the arc’s physical fields. The guiding effect localizes the current density to the front end of the lamellar cathode, particularly where the discharge gap is minimal. Both the inertial drag effect and the attraction effect of Lorentz force direct arc flow toward its periphery. Under the influence of the aforementioned factors, the physical fields of the lamellar cathode arc undergo expansion and shift counter to the arc’s direction of motion. A reduction in welding current substantially weakens the guiding effect, causing the arc’s physical fields to deviate further in the direction opposite to the arc motion. In comparison with a cylindrical cathode arc, the physical fields of the lamellar cathode arc are markedly expanded, leading to a reduction in current density, electron temperature, heavy particle temperature, cathode jet flow velocity, and Lorentz force.

Thermal analysis of natural convection in rectangular porous fin wetted with CNTs nanoparticles and thermal radiation

AbstractIn the present investigation, the phenomenon of heat conduction in rectangular shaped porous fin wetted with nanofluid (a mixture of carbon nanotube [CNT] with water as base liquid) is examined using the local thermal non‐equilibrium (LTNE) paradigm. The heat transport mechanism involving the nanofluid and solid phases is represented by the dimensional thermal governing ordinary differential equations (TGODEs). These equations are transformed into nonlinear ordinary differential equations (ODEs) using relevant non‐dimensional variables. To solve the resultant dimensionless TGODEs, probabilists collocation method with Hermite polynomials (PCMHPs) is utilized. This study of temperature analysis has examined the characteristics of internal and exterior radiation, convection, and thermal conductivity to determine the attributes affecting heat transfer. For both the nanofluid and solid phase aspects, temperature distribution characteristics are revealed in tables and graphs. Subsequently, it is determined that as surface‐ambient radiation parameter levels decreased, the temperature profile of both solid and nanofluid phase augmented. The temperature variance among the solid and nanofluid phases decreased with an escalation in the wet porous parameter. The numerical outcomes illustrate that the presented PCMHP approach is not only convenient to execute but also provides accurate results.