Stability, thermal performance and artificial neural network modeling of viscosity and thermal conductivity of Al2O3-ethylene glycol nanofluids

The aim is to estimate the stability of Al2O3-ethylene glycol (EG) nanofluids using the particle size distribution and velocity ratio. The thermal conductivity and viscosityweremeasured under ultrasonic conditions for various time intervals, mass fraction (from 0 to 2.0 wt%), and temperature range (from 25 to 60 degrees C). Moreover, various criteria were presented to estimate the thermal performance in the convective heat transfer. Based on different sets of experimental data, new correlations and optimal artificial neural network models (ANN) were proposed. The results showed that Al2O3-EG nanofluids obtained by ultrasonation for 60 min exhibits the most encouraging properties. Moreover, the correlations for the experiment and ANN models can predict these two parameters. However, the ANN model ismore precise. It is expected that the results to be useful for other studies of nanofluids stability especially since it recommends suitable selecting criteria based on heat transfer behavior before real applications. (c) 2020 Elsevier B.V. All rights reserved.