Heat Transfer最新文献

This research work investigates how different dimple designs affect the flow field and thermal performance of three-dimensional pipes. The study focuses on the effect of the number of improved dimples NOD (3, 4, and 5), different groups numbers DGNs (1, 2, and 3 groups), arranged around the pipe, and different distances between dimples (DBDs). Dimple geometry affects flow: Changing dimple parameters alters the velocity and pressure distribution within the pipe. Performance evaluation factor (PEF) varies with dimple configuration: The PEF, which balances heat transfer enhancement and pressure drop penalty, ranges from 1.187 to 1.23 for NOD and from 1.292 to 1.31 for DGN, and also from 1.26 to 1.302 for DBD. Reynolds number range, Re = 4000–15,000; turbulence model, standard k–ε model; numerical scheme, second-order upwind scheme; test tube conditions, inlet temperature (T_in) = 25°C; pipe diameter D = 23 mm; thickness = 2 mm; heat flux q = 25,500 W/m²; and material (Cu). This research focuses on improving heat transfer efficiency in pipes using dimples. Dimple size and arrangement significantly impact flow dynamics and heat transfer. PEF is used to evaluate the overall performance considering both heat transfer improvement and pressure drop penalty. The study found a specific range for PEF under various conditions for different dimple configurations. The average enhancement in Nusselt number for model 2 was 15.16% compared with a smooth pipe and the heat transfer performance by 10.028%–28.963% at the effect of NOD, the DGN has slightly higher Nu values than smooth pipes, indicating improved heat transfer due to the dimples (around 7%–58% at Re 4000–15,000 and 9%–13% at Re 12,000), and at DBD (13.5%) at a Reynolds number of 12,000 and 4.6%–59% at Re 4000–15,000.

There are still significant technical challenges associated with thermal management of electronic devices such as microprocessors. To improve heat dissipation performance of integrated circuits, a new Fibonacci phyllotaxis design of circular micropin fin heat sinks has been developed. To minimize both chip temperature and pumping power, a multi-objective optimization technique was employed. The effect of design parameters such as phyllotaxis coefficient, pin fin diameter, and pin fin height on response parameters was numerically investigated using the full factorial design of the experiment. Artificial neural network was coupled with MO-Jaya, to arrive at a Pareto frontier of optimal compromise solutions. The optimal set of design variables were found to be a height of 300 μm, a diameter of 122.6 μm, and a phyllotaxis coefficient of 130 μm with an inlet velocity of coolant 2.263 m/s. The selected optimum design was then investigated numerically, and the outcomes were compared to those predicted by the MO-Jaya algorithm. The final confirmed response variables were a maximum temperature of 51.6°C and a pumping power of 0.191 W. The results show that the Fibonacci phyllotaxis structure of the micro pin fin heat sink has better heat-dissipating performance.

Free convective heat transfer created from two aligned cylinders immersed inside a vented air duct is experimentally investigated. The experiments include the measurements of cylinders temperature and the air temperature inside the enclosure under steady, turbulent, and incompressible flow properties by using steady-state heat equations. The studied parameters include Rayleigh number ($��{10}^5�\; �\le �\; �\mathrm{Ra}�\; �\le �\; �{�3.4�\; �\times �\; �10�}^6�$), opening sizes at lower and upper enclosure surfaces ($��0.146�\; �\le �\; �O�\; �\le �\; �1�$), and space size between cylinders ($��0.35�\; �\le �\; �S�\; �\le �\; �0.532�$) with the constant ratio of enclosure width to cylinder diameter equal to 6. The findings displayed that the average air temperature inside the enclosure for the low values of S and O is low, and it rises as S is raised. The behaviors of Nu differ with changing Ra values. An interaction between hot cylinder and cold cylinder inside the enclosure is observed that depends on O and S values, and hence, they have a large impact on fluid temperature. The data indicated that $��\mathrm{Nu}�$ rises with the $��\mathrm{Ra}�$