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Using Perceptron Feed-Forward Artificial Neural Network (ANN) for Predicting the Thermal Conductivity of Graphene oxide-Al2O3/Water-Ethylene Glycol Hybrid Nanofluid
2021
Case Studies in Thermal Engineering
A B S T R A C T In this paper, Artificial Neural Network (ANN) was used to investigate the influence of temperature and volume fraction of nanoparticles on the thermal conductivity of Graphene oxide-Al 2 O 3 / Water-Ethylene glycol hybrid nanofluid. Nanofluids were prepared with the volume fraction of nanoparticles 0.1, 0.2, 0.4, 0.8, and 1.6% in the temperature range of 25-55 • C. The nanofluid's thermal conductivity results were extracted from six different volume fractions of nanoparticles
doi:10.1016/j.csite.2021.101055
fatcat:v3cl3hrksbecjc4y2xda4ebubq