Experimental Performance Evaluation and Artificial-Neural-Network Modeling of ZnO-CuO/EG-W Hybrid Nanofluids

作     者：Yuling Zhai Long Li Zihao Xuan Mingyan Ma Hua Wang 

作者机构：Engineering Research Center of Metallurgical Energy Conversion and Emission ReductionMinistry of EducationKunming University of Science and TechnologyYunnan650093China 

出 版 物：《Fluid Dynamics & Materials Processing》 (流体力学与材料加工（英文）)

年 卷 期：2022年第18卷第3期

页      面：629-646页

核心收录：

学科分类：08[工学] 0804[工学-仪器科学与技术] 0805[工学-材料科学与工程（可授工学、理学学位）] 0703[理学-化学] 0801[工学-力学（可授工学、理学学位）] 0702[理学-物理学] 

基　　金：This project is supported by Yulingn Zhai and the National Natural Science Foundation of China(No.51806090) the Basic Research Project of Yunnan Province(No.202001AT070081). 

主　　题：Hybrid nanofluids base fluid ratio viscosity thermal conductivity ANN model 

摘      要：The thermo-physical properties of nanofluids are highly dependent on the used base fluid.This study explores the influence of the mixing ratio on the thermal conductivity and viscosity of ZnO-CuO/EG(ethylene glycol)-W(water)hybrid nanofluids with mass concentration and temperatures in the ranges 1-5 wt.%and 25-60
C,respectively.The characteristics and stability of these mixtures were estimated by TEM(transmission electron microscopy),visual observation,and absorbance tests.The results show that 120 min of sonication and the addition of PVP(polyvinyl pyrrolidone)surfactant can prevent sedimentation for a period reaching up to 20 days.The increase of EG(ethylene glycol)in the base fluid leads to low thermal conductivity and high viscosity.Thermal conductivity enhancement(TCE)decreases from 21.52%to 11.7%when EG:W is changed from 20:80 to 80:20 at 1 wt.%and 60
C.A lower viscosity of the base fluid influences more significantly the TCE of the nanofluid.An Artificial Neural Network(ANN)has also been used to describe the effectiveness of these hybrid nanofluids as heat transfer fluids.The optimal number of layers and neurons in these models have been found to be 1 and 5 for viscosity,and 1 and 7 for thermal conductivity.The corresponding coefficient of determination(R^(2))was 0.9979 and 0.9989,respectively.