Enhanced entropy generation and heat transfer characteristics of magnetic nano-encapsulated phase change materials in latent heat thermal energy storage systems

The objective of the current study is to investigate the importance of entropy generation and thermal radiation on the patterns of velocity,isentropic lines,and temperature contours within a thermal energy storage device filled with magnetic nanoencapsulated phase change materials(NEPCMs).The versatile finite element method(FEM)is implemented to numerically solve the governing equations.The effects of various parameters,including the viscosity parameter,ranging from 1 to 3,the thermal conductivity parameter,ranging from 1 to 3,the Rayleigh parameter,ranging from 102 to 3×10^(2),the radiation number,ranging from 0.1 to 0.5,the fusion temperature,ranging from 1.0 to 1.2,the volume fraction of NEPCMs,ranging from 2%to 6%,the Stefan number,ranging from 1 to 5,the magnetic number,ranging from 0.1 to 0.5,and the irreversibility parameter,ranging from 0.1 to 0.5,are examined in detail on the temperature contours,isentropic lines,heat capacity ratio,and velocity fields.Furthermore,the heat transfer rates at both the cold and hot walls are analyzed,and the findings are presented graphically.The results indicate that the time taken by the NEPCMs to transition from solid to liquid is prolonged inside the chamber region as the fusion temperatureθf increases.Additionally,the contours of the heat capacity ratio Cr decrease with the increase in the Stefan number Ste.

Latent Heat Prediction of Nano Enhanced Phase Change Material by ANN Method

Thermal characteristics of phase change material(PCM)are important in design and utilization of thermal energy storage or other applications.PCMs have great latent heat but suffer from low thermal conductivity.Then,in recent years,nano particles have been added to PCM to improve their thermophysical properties such as thermal conductivity.Effect of this nano particles on thermophysical properties of PCM has been a question and many experimental and numerical studies have been done to investigate them.Artificial intelligence-based approach can be a good candidate to predict thermophysical properties of nano enhance PCM(NEPCM).Then,in this study an artificial neural network(ANN)has been developed to predict the latent heat of the NEPCM.A comprehensive literature search was conducted to acquire thermal characteristics data from various NEPCM to train and test this artificial neural network model.Twenty different types of Nano particle and paraffin based PCMs were used in ANN development.The most important properties which are used as the input for the developed ANN model are NP size,density of NP,latent heat of PCM,density of PCM,concentration and latent heat of NEPCM in the range of 1-60 nm,100-8960 kg/m^(3),89.69-311 kJ/kg,760 to 1520 kg/m^(3),0.02-20 wt%and 60.72-338.6 kJ/kg,respectively.The output variable was latent heat of NEPCM.The result indicates that the ANN model can be applied to predict the latent heat of nano enhanced PCM satisfactory.The correlation coefficient of the created model was 0.97.This result shows ability of ANN to predict the latent heat of NEPCM.

纳米增强型复合相变材料的传热特性

高导热颗粒常被用来增强相变材料(phase change materials,PCMs)的固有导热性能。为研究纳米颗粒种类、含量和分散剂对纳米增强型复合相变材料(nano-enhanced PCMs, NePCMs)传热过程的影响,本文采用纳米石墨(nano graphite,NG)和纳米椰壳炭(nano coconut shell based-carbon,NC)来提高石蜡的导热性能,使用T型热电偶监测不同边界温度下各复合相变材料熔化过程的温度变化,并用红外热像仪观察整体的温度分布。实验结果表明:纳米颗粒能够增强PCMs的热传递性能,且相同浓度下添加纳米石墨的石蜡传热速率更快,但纳米颗粒在相变过程中易分散不均匀;分散剂能够改善纳米颗粒在PCMs中的分散性能从而增强NePCMs的传热速率,其中用油酸作分散剂时能最大程度促进NePCMs的传热;分散良好的情况下,NePCMs的传热性能随其浓度的增大而增强。

纳米胶囊潜热型功能流体制备及强化沸腾换热的实验研究

采用溶胶凝胶法制备了以软脂酸为芯材,二氧化硅为壳材的纳米相变胶囊,分析测试表明所合成的胶囊呈现为核壳结构分明的规则球形结构,且具有良好的储热能力。选用聚二甲基硅氧烷疏水改性,制备了稳定分散的丙酮基纳米胶囊潜热型功能流体,热导率及粘度测试表明其可以应用于强化换热。微小通道过冷流动沸腾实验研究发现,纳米相变胶囊的加入不但可以阻止气泡的合并,而且可以加速沸腾气泡的破裂,揭示了除提升热导率及提供潜热之外的另一强化沸腾换热的原因。