Abstract
In this study, thermal conductivity of graphene nano-sheets (GNs)/ethylene glycol (EG) nanofluid was compared with EG thermal conductivity at 25–70°C and 0.005–0.5 wt% to examine the effects of GNs nanoparticles. For all samples, presence of nanoparticles intensifies EG thermal conductivity up to 54.6%. Moreover, loading GNs into EG inverts the dependency of the thermal conductivity to temperature. As the temperature rises, the thermal conductivity of the base fluid decreases, while for nanofluid, thermal conductivity increases. Based on the results, by incorporating more nanoparticles, the positive effects of nanoparticles on thermal conductivity s reduced. It was concluded that with increasing temperature, the effect of adding GNs on the thermal conductivity is strengthened. Neural network implementation showed that this method can forecast kGNs/EGkEG with maximum error of less than 3%.
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•If the amount of nanoparticles doubles, the rate of improvement will not double•The best thermal conductivity enhancement was 54.6%.•At higher mass fractions, conductivity is more sensitive to temperature•ANN consisting 9 neurons forecasted kGr/EGkEG with error of less than 3%.