Thermal conductivity of Cu/TiO2-water/EG hybrid nanofluid: Experimental data and modeling using artificial neural network and correlation

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Author list: Hemmat Esfe M., Wongwises S., Naderi A., Asadi A., Safaei M.R., Rostamian H., Dahari M., Karimipour A.

Publisher: Elsevier

Publication year: 2015

Journal: International Communications in Heat and Mass Transfer (0735-1933)

Volume number: 66

Start page: 100

End page: 104

Number of pages: 5

ISSN: 0735-1933

eISSN: 1879-0178

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84930640063&doi=10.1016%2fj.icheatmasstransfer.2015.05.014&partnerID=40&md5=ba1fdf4b90a0e4b18b4f03b8f5ff2df7

Languages: English-Great Britain (EN-GB)

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Abstract

In the present paper, the thermal conductivity of hybrid nanofluids is experimentally investigated. The studied nanofluid was produced using a two-step method by dispersing Cu and TiO2 nanoparticles with average diameter of 70 and 40 nm in a binary mixture of water/EG (60:40). The properties of this nanofluid were measured in various solid concentrations (0.1, 0.2, 0.4, 0.8, 1, 1.5, and 2%) and temperatures ranging from 30 to 60ฐC. Next, two new correlations for predicting the thermal conductivity of studied hybrid nanofluids, in terms of solid concentration and temperature, are proposed that use an artificial neural network (ANN) and are based on experimental data. The results indicate that these two new models have great ability to predict thermal conductivity and show excellent agreement with the experimental results. ฉ 2015 Elsevier Ltd.

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Experimental data