An experimental investigation of thermal conductivity and dynamic viscosity of Al2O3-ZnO-Fe3O4 ternary hybrid nanofluid and development of machine learning model

Abstract The growing interest in hybrid nanofluids is due to the synergistic effects of nanoparticles, which could give them better heat transfer properties as compared to base fluids, and conventional nanofluids. Several factors like temperature and volume fraction have been used in explaining the behaviours of hybrid nanofluids, however, the need to investigate comprehensively, the mixing ratios of hybrid nanofluids, remains a critical research area in the development of efficient nanofluids as heat transfer fluids. In this study, three mixture ratios of 1:1:1 (33.3% Al2O3, 33.3% ZnO, 33.3% Fe3O4), 1:2:1 (25% Al2O3, 50% ZnO, 25% Fe3O4), and 1:1:2 (25% Al2O3, 25% ZnO,50% Fe3O4) ternary hybrid nanofluid (THNF) are synthesized at volume concentrations of 0.5%, 0.75%, 1%, and 1.25%. All experiments were carried out at a temperature range between 25 °C-65 °C. The effect of temperature, volume concentration, mixture ratio, are examined, as well as the development of a machine learning model for accurate prediction. The thermal conductivity and dynamic viscosity behaviour of the THNF were investigated. The result showed that temperature and volume concentration significantly affected the thermophysical properties of the fluid. The optimum Thermal Conductivity enhancement (TCE) was retrieved for the 1:1:1 THNF, at 36.018%. The 2:1:1, and 1:2:1 mixture ratios had a 32.92%, and 31.68% TCE respectively. At 1% volume concentration, the optimum TCE (as compared with water) for the mono, hybrid, and THNF measured are 18.98%, 28.58%, and 32.45% respectively. It is seen that the least viscosity was recorded for the 1:1:1 mixture ratio (0.001 Pa.s), while the highest viscosity was measured for the 2:1:1 THNF mixture ratio (0.021 Pa. s). The Gaussian process regression (GPR) gave an excellent prediction showing an R2 value of 0.9656, and 0.934 for the thermal conductivity and dynamic viscosity prediction respectively. In terms of application to solar thermal systems, the low viscosity of 1:1:1 Al2O3–ZnO-Fe3O4 THNF makes that a low-pressure drop and pump work is required in practical applications of the 1:1:1 Al2O3–ZnO-Fe3O4 THNF.