Properties of water-based fly ash-copper hybrid nanofluid for solar energy applications: Application of RBF model

Abstract

The hybrid nanofluids were used as absorber fluids in solar energy applications, which could further increase the efficiency of solar devices. The use of nanofluids in solar devices with the laminar and turbulent flow has received much attention. Presently, the effect of temperature and concentration on thermal conductivity and viscosity of fly ash-copper (80:20% by volume) hybrid nanofluid is investigated. The thermal conductivity and viscosity measurements were carried in the temperature range of 30–60 °C for a concentration range of 0–4.0 vol%. The nanoparticles and nanofluids were characterized by XRF, XRD, SEM, TEM, zeta potential, and DLS techniques. The maximum augmentation in the hybrid nanofluid's dynamic viscosity and thermal conductivity at a concentration of 4 vol% is 45.18% and 49.8%, respectively, at 30 and 60 °C. Correlations to estimate the hybrid nanofluid's dynamic viscosity and thermal conductivity have been proposed considering the results obtained from the present study. A radial basis function-based neural network is used to model nanofluids' effective thermal conductivity and relative viscosity. The outcomes of the experiments were used to calculate the Mouromtseff number and heat transfer efficiency for solar energy applications. • HyNF shows Newtonian behavior in the studied range. • The maximum augmentation in viscosity is 45.2%. • The highest amplification in thermal conductivity is 49.8%. • Radial basis function based neural network was used.