An inspection of thermal conductivity of CuO-SWCNTs hybrid nanofluid versus temperature and concentration using experimental data, ANN modeling and new correlation

The aim of this paper is to study the variations of thermal conductivity of CuO-SWCNTs/EG water (40:60) against temperature and solid volume fraction by experimental data, ANN modeling and proposing correlation. In the present study, the SWCNT is mixed with CuO nanoparticles (40 nm) with equal volume (50:50) and the temperature of nanofluid ranging from 20 to 50 °C while solid volume fraction ranging between 0.02% and 0.75%. Due to lacking of investigation about CuO-SWCNTs/EG water (40:60) and the absence of predicted model for estimation of thermal conductivity of this nanofluid, a new correlation based on experimental results is proposed. Then, modeling of thermal conductivity of nanofluids has been executed using artificial neural network by using experimental data. For this purpose, multilayer perception of neural network is employed. Both proposed correlation and ANN method can well predict the thermal conductivity of nanofluid but the precision and accuracy of ANN method is better.