International Journal of Thermofluids最新文献

Liquid cooling using a mini-channel heat sink (MHS) has been highly efficient in cooling rectangular and cylindrical lithium batteries. This work proposed a new hexagonal MHS (HMHS) to cool a cylindrical heat source instead of the traditional cylindrical with smooth MHS (CSMHS). In addition to the smooth channels, four obstructed channels were proposed to further enhance the thermal performance of this HMHS. The obstructions used include: semicircular ribs–cavities, semicircular ribs–secondary flow, semicircular pin fins and semicircular pin fins–cavities. This study was numerically conducted using the finite volume method under water Reynolds number ranging from 100 to 800. CSMHS and HMHS with semicircular pin fins were manufactured and tested to verify the validity of the numerical results. Results showed that the HMHS exhibited superior hydro-thermal performance compared with the CSMHS. In addition, the HMHS with obstructed channels contributes to a significant improvement in thermal performance. The percentages of Nusselt number improvement with all channels were approximately: 12.3%, 60.5%, 71.5%, 104% and 112% for smooth, semicircular ribs–cavities, semicircular rib–secondary flow, semicircular pin fins and semicircular pin fins–cavities, respectively. Amongst all the channels, the channels with semicircular pin fins achieved the best performance with a hydro-thermal performance factor of 1.67.

Natural fiber-reinforced composites are increasingly recognized as sustainable alternatives in construction materials due to their environmentally friendly properties and ability to increase thermal insulation. This study conducts an in-depth comparative study between palm fiber (DPF) composites and other natural fiber-reinforced composites, including hemp and jute, with a focus on their application as insulation that provides insight into their thermal properties, performance, and mechanical properties to inform sustainable construction practices. The research methodology involves constructing and producing composite samples using date palm, hemp, and jute fibers, each combined into a common base material. Composites are mold-made, ensuring consistent and reproducible samples for testing. Through a systematic investigation, we explore these composites' thermal, and mechanical properties. Testing covers a specific range of fiber loadings, from 10 wt % – 30 wt %. Specific characterization techniques, including compression test, bending test, impact, FT-IR, and DSC, were used to evaluate the behavior of the composites under various conditions. Our results show that the thermal conductivity of the composites ranges from 0.0514 – 0.084 W/m. K for different fiber loading is affected by the fiber content.

Furthermore, at maximum fiber concentration (30 by weight), the highest heat capacity of the hemp composite was 1674 J/Kg.K. The 30 wt % of jute and date palm composites achieved a maximum compressive strength of (70 MPa) and (64 MPa) respectively.

In summary, this comprehensive study demonstrates the potential of natural fiber-reinforced composites as sustainable and fully bio-based alternatives for construction-related applications. Superior thermal properties and improved mechanical strength highlight their viability in thermal insulation applications.

Advancements in water electrolysis technologies are crucial for green hydrogen production. Proton exchange membrane water electrolysis (PEMWE) is characterized by its efficiency and environmental benefits. The prediction and optimization of hydrogen production rates (HPRs) in PEMWE systems is difficult and still challenging because of the complexity of the system as well as the operational parameters. The integration of artificial intelligence (AI) and machine learning (ML) appears to be effective in optimization within the energy sector. Hence, this work employs the artificial neural network (ANN) to develop a model that accurately predicts HPR in PEMWE setups. A novel approach is introduced by employing the Levenberg–Marquardt backpropagation (LMBP) algorithm for training the ANN. This model is designed to predict HPR based on critical operational parameters, including anode and cathode areas (mm²), cell voltage (V) and current (A), water flow rate (mL/min), power (W), and temperature (K). The optimized ANN configuration features an architecture with 7 input nodes, two hidden layers of 64 neurons each, and a single output node. The performance of the ANN model was evaluated against conventional regression models using key metrics: mean squared error (MSE), coefficient of determination (R²), and mean absolute error (MAE). The findings of this study reveal that the developed ANN model significantly outperforms traditional models, achieving an R² value of 0.9989 and an MAE of 0.012. In comparison, random forest (R² = 0.9795), linear regression (R² = 0.9697), and support vector machines (R² = − 0.4812) show lower predictive accuracy, underscoring the ANN model's superior performance. This work demonstrates the efficiency of the LMBP in enhancing hydrogen production forecasts and sets a foundation for future improvements in PEMWE efficiency. By enabling precise control and optimization of operational parameters, this study contributes to the broader goal of advancing green hydrogen production as a viable and scalable alternative to fossil fuels, offering both immediate and long-term benefits to sustainable energy initiatives.

Mixed convection convection is a vital subject and it is beneficial in many engineering applications. The current paper addresses this subject with a novel geometry and very vital variables including magnetohydrodynamic influences on the forced/free convection as well as the reproduction of irreversibilities in an enclosure filled with water/carbon nanotubes (CNT) and a nonadiabatic cylinder. The top wall is split from the middle and moves in different directions to drive the isotherms which are generated from the bottom wall and cold from the vertical surfaces. The numerical analysis was carried out using finite element method; the variables are Reynolds number (40–200), Richardson number (0.01–10), Hartmann number (0–62), inclined magnetohydrodynamic angle (0–60), volume concentration (0–0.08) while Prandtl number has kept constant at 6.2. The results show that the transformation of heat, as well as the fluid flow, are largely influenced by the change of variables, where increasing Reynolds number, Richardson number enhances heat and increases the flow circulation. Furthermore, heat transfer enhances by 57 % when increasing Ri from 0.1 to 10 at Re=41 and this enhancement increases to 62.5 % at Re = 200. Furthermore, increasing the concentration of the carbon nanotube can cause heat transfer but decrease the circulation of the fluid. In contrast, the transfer of heat as well as the flow streams are remarkably decreased with the increase of the Hartmann at zero inclination angle; however, the value of the Nusselt average increases with the increase of the inclination angle. Moreover, the value of Nusselt average decreses by 34.7 % when increasing Ha from 0 to 62 at Re = 200. Furthermore, the total entropy generation increases as Richardson number, Reynolds number, and volume concentration increase; in contrast, detraction with the rise of the MHD.

Numerous methods are conceived to pick up the heat from hot plats, where, amidst all, film cooling methods possess several benefits and have always been considered. However, increasing the cooling effectiveness of this method while reducing the coolant mass flow rate has always been considered one of the concerns, and much literature has yet to be presented to surmount this problem. In this study, three different novel jet configurations including simple, semi-mushroom, and semi-oval jet types are proposed to boost the effectiveness of the film cooling method while the mass rate is drastically lower compared to the traditional jet types. Instead of using the traditional film jet that usually blows the coolant flow at a 30-90-degree angle, it can be changed so that the coolant is wholly blown in the mainstream path, simultaneously reducing the mixing ratio and increasing the diffusion of coolant film. Meantime, the arc-shaped jet design can increase the surface coverage by the coolant fluid, especially in the transverse direction. This innovative concept is also reckoned for in this study by presenting computational simulation using the k − ω − SST turbulence model, which has some superiority for turbulent near wall flows. The results showed that at BR=0.5 and x/d=5, the proposed novel jet (simple type) achieved a 17.9% improvement in averaged cooling effectiveness compared to regular jets, while utilizing a coolant mass flow rate ten times lower. Also, it found that contrary to the results related to regular jets, the averaged cooling effectiveness increases with the increment of blowing ratio in innovative proposed jet types.

Background

The fluid flow and nanofluid heat transfer are studied in this research through porous microchannels with different flow path arrangements in single-phase and two-phase modes (Mode I and Mode II). In Mode I, the flow inlet is located in the longitudinal direction of the microchannel (single-way path), while in Mode II, the flow inlet is placed in the transverse direction of the microchannel (two-way path).

Methods

The finite volume method was utilized to simulate the flow and heat transfer. The porous medium is supposed homogeneous and isotropic with a porosity coefficient of 0.9 and it is assumed that the local thermal equilibrium is established between the fluid and the solid. The Eulerian-Eulerian mixture model is applied for modeling the two-phase flow. As demonstrated, mode II always has a higher heat transfer rate than mode I. However, in contrast, the pressure drop of mode I is lower than in mode II. Besides, using the two-phase model predicts a higher heat transfer rate than the single-phase model in all cases.

Significant Findings

The percent increase of pressure in mode II compared to mode I in Re= 100 and 400 is obtained as 11.5 % and 20.8 %, respectively. At Re= 100 in mode I, the heat transfer percentage increases by 52.6 % from Da=1 compared to a case without the porous foam. Whilst, at Re= 400, the rise is found to be 45.5 %. In mode II, at Re=100, the heat transfer percentage increases by 63.9 % from Da= 1 compared to a case without the porous foam. Whilst, at Re= 400, the rise is found to be 43.3 %. Finally, Mode II microchannel has more heat transfer rate and pressure drop than Mode I.

This study introduces a unique coaxial cylindrical electrode design for Alkaline Water Electrolysers (AWEs) that is analyzed to show possible enhancements over the traditional stacked plate design. It investigates the performance of the proposed coaxial AWE for enhanced hydrogen production. Through comprehensive computational simulations, key performance indicators, such as current density and hydrogen volume fraction, are analyzed across various operating parameters. The results of this study indicate that the production rate of hydrogen achieves its highest level at a volume percentage of 3.4 %. This rate is significantly influenced by the concentration of the electrolyte, the distance between the cathode and anode rings, and, to a lesser degree, the porosity of the separator. Consequently, the optimized conditions demonstrate a promising increase in current densities, reaching 1000 mA/cm² at an operating voltage of 2 V, showcasing the potential for developing more efficient and cost-effective AWE systems. This study further contributes valuable insights into the design and operational improvements needed for the advancement of large-scale hydrogen production technologies.

Addressing the critical issue of heat generation in electronic devices due to miniaturization and higher power density is essential. As electronic components become more compact, they generate more heat flux, necessitating efficient thermal management solutions. Traditional methods and fluids, such as water, struggle to meet the demand for efficient heat dissipation. To address this challenge, the utilization of nanofluids presents a promising solution. The objective of this study is to use CFD methods to examine how a nanofluid can improve heat transmission and lower the maximum temperature in a microchannel heatsink. This article presents the study of microchannel heatsinks with two distinct channel counts (five and eight). A constant flow, incompressible, laminar model was used to verify the findings. The working fluids used in the study were water in various concentrations, water-based nanofluids of Fe₃O₄-water and MWCNTs. CFD simulations revealed that a MWCNT-water nanofluid at 0.2 % concentration significantly improved cooling performance compared to water, demonstrating the potential of nanofluids for efficient thermal management in electronic devices.

The research examines the intricate between Eyring-Powell microfluidic heat transfer, electromagnetic radiation and viscous heating in a Riga slippery device as applied in heat exchangers, cooling systems, biomedical devices, energy generation, polymer processing, and others. The viscoelastic property of the fluid is characterized by the Eyring-Powell Cauchy fluid model with shear-thickening and shear-thinning phenomena that are useful in several heat transport processes and thermal management. The developed governing model is taken from the constitutive relations and conservation principles and solved via an adaptive partition weighted residual method. The essential fluid term sensitivities are systematically investigated on the flow and thermal distribution characteristics. An appropriate validation and comparison of results is done and found to agree quantitatively, this confirmed the correctness of the presented outcomes. The results reveal the significant impact of the thermofluidic terms interaction on the viscous flowing fluid and thermal behaviour. As seen, slip conditions momentously increase the flow rate gradients for about 1.7% to 2.4% close to the boundary wall and consequently raise the microfluidic thermal propagation rates with 3.7% non-Newtonian fluid and thickness of the boundary layer. Moreover, the thermal gradient and distribution complexities are modulated within the fluid regime due to radiation and Lorentz force.

This paper explores the magnetohydrodynamic (MHD) squeeze flow of an electrically conducting fluid between two infinite parallel disks with a perpendicular magnetic field. The study focuses on the case where the upper disk moves towards a stationary lower disk. By employing similarity variables, we reduce the MHD momentum and continuity equations into a fourth-order linear boundary value problem, solved using a modified operational matrix method. The numerical approach is validated through $L_2$-truncation error analysis, boundary condition comparisons, and by comparing results with other methods like HAM, HPM, and bvp4c that produce analytical and numerical solutions. Graphical analyses reveal the effects of the squeeze number, Hartman number, and the boundary parameter on velocity and flow profile. Results indicate that the Hartman number significantly affects the velocity due to the Lorentz force, while the squeeze number and boundary parameter influence the velocity and flow profile differently in suction and injection cases. The numerical solution demonstrates high accuracy and convergence compared to previous methods in terms of absolute error.