An intelligent approach to predicting the effect of nanoparticle mixture ratio, concentration and temperature on thermal conductivity of hybrid nanofluids

Abstract

Hybrid nanofluids are better heat transfer fluids than conventional nanofluids because of the combined properties of two or more nanoparticles. In this study, the thermal conductivity of Al 2 O 3-ZnO nanoparticles suspended in a base fluid of distilled water is investigated. The experiments were conducted for three mixture ratios (1:2, 1:1 and 2:1) of Al 2 O 3-ZnO nanofluid at five different volume concentrations of 0.33%, 0.67%, 1.0%, 1.33% and 1.67%. X-ray diffractometric analysis, X-ray fluorescence spectrometry and scanning electron microscopy were used to characterise the nanoparticles. The highest thermal conductivity enhancement achieved for Al 2 O 3-ZnO hybrid nanofluids with 1:2, 1:1 and 2:1 (Al 2 O 3 :ZnO) mixture ratios was 36%, 35% and 40%, respectively, at volume concentration 1.67%. The study observed the highest thermal conductivity for Al 2 O 3-ZnO nanofluid was achieved at a mixture ratio of 2:1. A "deeping" effect was observed at a mixture ratio of 1:1 representing the lowest value of thermal conductivity within the considered range. The study proposed and compared three models for obtaining the thermal conductivity of Al 2 O 3-ZnO nanofluids based on temperature, volume concentration and nanoparticle mixture ratio. A polynomial correlation model, the adaptive neuro-fuzzy inference system model and an artificial neural network model optimised with three different learning algorithms. The adaptive neuro-fuzzy inference system model was most accurate in forecasting the thermal conductivity of the Al 2 O 3-ZnO hybrid nanofluid with an R 2 value of 0.9946.

Nanofluids in Solar Thermal Collectors: Review and Limitations

“…Early results from Said et al [92] experiment with Al 2 O 3 water nanofluid and Murshed et al [93] experiment with SiO 2 water nanofluid show that the classical models for predicting the thermal conductivity of nanofluids deviate significantly from experimental results. This deviation in prediction is increased in hybrid nanofluids as compared to conventional nanofluids [94,95]. The studies by Taherialekouhi et al [94] and Wole-Osho et al [95] also show that regression correlation models within the range of the experiments conducted have less deviation than the classical models.…”

“…This deviation in prediction is increased in hybrid nanofluids as compared to conventional nanofluids [94,95]. The studies by Taherialekouhi et al [94] and Wole-Osho et al [95] also show that regression correlation models within the range of the experiments conducted have less deviation than the classical models. The most accurate prediction models are correlation models…”

Advancement of Non-Newtonian Fluid with Hybrid Nanoparticles in a Convective Channel and Prabhakar’s Fractional Derivative—Analytical Solution

“…The impact of a nanoparticle's mixture ratio, as well as the temperature and concentration on the thermal conductivity Fractal Fract. 2021, 5, 99 2 of 17 of hybrid nanofluids, was established by Wole-Osho et al [7]. Haque et al [8] discussed the laminar nanoparticles having heat transfer, using convection force in the presence of noncircular ducts.…”

Nanofluid Development Using Silver Nanoparticles and Organic-Luminescent Molecules for Solar-Thermal and Hybrid Photovoltaic-Thermal Applications

“…Finally, it is the lack of diversity in the nanofluid filter designs in which the nanoparticles, typically, have a monomodal particle size-distribution or exhibit a single particle morphology [ 35 , 36 , 37 , 38 ]. This lack of diversity in the complexity of the nanoparticle population has now been widely recognised to constrain the enhancements reported in the thermal conductivity and the heat-transfer dynamics of the nanofluids currently implemented in PT and PVT devices [ 40 , 41 ]. Recently, the presence of a large ensemble of different particle-sizes and the inclusion of different anisotropic particle morphologies has shown to further promote the transport of thermal energy throughout the base fluid, yet the cross-application of this aspect to SBS-PVT systems remains largely unexploited [ 34 , 42 , 43 , 44 , 45 ].…”