Uddin Ziya, Hassan Hamdy, Harmand Souad, Ibrahim Wubshet
Department of Applied Sciences, SoET, BML Munjal University, Gurgaon, Haryana, India.
Energy Resources Engineering Department, Egypt-Japan University of Science and Technology (E-JUST), Alexandria, Egypt.
Sci Rep. 2022 Sep 2;12(1):14983. doi: 10.1038/s41598-022-18736-1.
In this paper, the numerical solution for heat transfer through a rotating heat pipe is studied and a sensitivity analysis is presented by using statistical experimental design technique. Graphene oxide-molybdenum disulfide (GO-MoS) hybrid nanofluid is taken as working fluid inside the pipe. The impact of the heat pipe parameters (rotation speed, initial mass, temperature difference) on the heat transfer and liquid film thickness is investigated. The mathematical model coupling the fluid mass flow rate and liquid film evolution equations in evaporator, adiabatic, and condenser zones of the heat pipe is constructed. The mathematical model is solved by implementation of "Particle Swarm Optimization" along with the finite difference method. The outcomes demonstrate that hybrid nanoparticles help to improve the heat transfer through the heat pipe and reduce liquid film thickness. The heat transfer rises with increasing temperature difference and reducing inlet mass, and it reduces slightly with rising rotation speed. The difference in liquid film thickness between the evaporator and condenser zones increases with increasing temperature difference and decreasing rotation speed. The impact of increasing the volume fraction of GO on the liquid film thickness is higher than that in the case of the MoS nanoparticles. However, an increase of the heat transfer is noticed in case of increasing the volume fraction of GO relative to increasing MoS concentration. Statistical analysis of the computed numerical data and the identification of significant parameters for total heat transfer are found using the response surface method. At 95% level of significance, the GO concentration in the hybrid nanofluid, inlet mass of the hybrid nanofluid and the temperature difference inside the evaporator zone of the pipe are found to be significant linear parameters for increasing heat transfer.
本文研究了旋转热管内传热的数值解，并采用统计实验设计技术进行了敏感性分析。以氧化石墨烯-二硫化钼（GO-MoS）混合纳米流体作为管内工作流体。研究了热管参数（转速、初始质量、温差）对传热和液膜厚度的影响。建立了耦合热管蒸发器、绝热段和冷凝器段流体质量流量和液膜演化方程的数学模型。采用粒子群优化算法结合有限差分法求解该数学模型。结果表明，混合纳米颗粒有助于提高热管的传热性能并减小液膜厚度。传热随温差增大和入口质量减小而增加，随转速升高略有降低。蒸发器和冷凝器段液膜厚度的差异随温差增大和转速降低而增大。增加GO体积分数对液膜厚度的影响高于MoS纳米颗粒的情况。然而，相对于增加MoS浓度，增加GO体积分数时传热增加。使用响应面法对计算得到的数值数据进行统计分析，并确定总传热的显著参数。在95%的显著性水平下，发现混合纳米流体中GO的浓度、混合纳米流体的入口质量以及管蒸发器段内的温差是增加传热的显著线性参数。
