Nanofluid has attracted a large number of researchers in recent decades due to its exceptional heat transfer properties. In this study, a ZnO–H2O nanofluid with surfactant sodium dodecyl benzene sulphonate has been investigated to quantify heat transfer and frictional loss in a double-pipe heat exchanger. The turbulent zone was studied, with Reynolds numbers ranging from 5500 to 16,000 for fully developed flow. Volume fractions employed were 0.005%, 0.01%, 0.03% and 0.06%. Brownian motion and the interfacial layer, in addition to thermal conductivity, are the primary factor to influence heat transfer in heat exchangers. The maximum enhancement in Nusselt number and thermal performance achieved for a volume fraction of 0.06% at Reynolds number 5500 is 35% and 1.15, respectively.
Heat transfer is a desirable phenomenon in many industries such as in
refrigeration, transportation, power generation, cell preservation,
incubator, metallurgy and material processing, health services, etc.
Different types of fluids like water, oil, ethylene glycol etc are being
used as a heat transfer medium. Water is a commonly used as working fluid
for transfer of heat. Nanofluids are developed by adding nano sized
particle(s) in existing fluid to improve the heat transfer rate. Thermal
conductivity of the nanofluid is an important parameter in estimation of
heat transfer rate. Different types of mathematical models were developed by
various investigators to predict the thermal conductivity of the nanofluids.
In this review paper,the theoretical and mathematical model(s) have been
compared to predict the thermal conductivity of nanofluids. The experimental
data have been collected from literature and compared with Maxwell model,
Hamilton and crosser(H-C) model, Maxwell-Garnetts(MG) model, Pak cho model,
Timofeeva et al. model, Li and Peterson model, Bhattacharya et al. model
respectively in detail. It has been observed that the prediction wih the
help of the mathematical models is good when the value of volume fraction
was less than 0.01.
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