Thermal conductivity of non-Newtonian nanofluids: Experimental data and modeling using neural network

被引:187
|
作者
Hojjat, M. [1 ]
Etemad, S. Gh. [1 ]
Bagheri, R. [1 ]
Thibault, J. [2 ]
机构
[1] Isfahan Univ Technol, Dept Chem Engn, Esfahan 8415683111, Iran
[2] Univ Ottawa, Dept Chem & Biol Engn, Ottawa, ON K1N 6N5, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Nanofluid; Non-Newtonian fluid; Thermal conductivity; Nanoparticle; Neural network; HEAT-TRANSFER; PARTICLE-SIZE; CARBON NANOTUBE; ETHYLENE-GLYCOL; ENHANCEMENT; TEMPERATURE; SUSPENSIONS; VISCOSITY; WATER; NANOPARTICLES;
D O I
10.1016/j.ijheatmasstransfer.2010.11.039
中图分类号
O414.1 [热力学];
学科分类号
摘要
Three different types of nanofluids were prepared by dispersing gamma-Al2O3, TiO2 and CuO nanoparticles in a 0.5 wt% of carboxymethyl cellulose (CMC) aqueous solution. Thermal conductivity of the base fluid and nanofluids with various nanoparticle loadings at different temperatures were measured experimentally. Results show that the thermal conductivity of nanofluids is higher than the one of the base fluid and the increase in the thermal conductivity varies exponentially with the nanoparticle concentration. In addition to increase with the nanoparticle concentration, the thermal conductivity of nanofluids increases with the temperature. Neural network models were proposed to represent the thermal conductivity as a function of the temperature, nanoparticle concentration and the thermal conductivity of the nanoparticles. These models were in good agreement with the experimental data. On the other hand, the Hamilton Crosser model was only satisfactory for low nanoparticle concentrations. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1017 / 1023
页数:7
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