Computational Analysis of Factors Influencing Enhancement of Thermal Conductivity of Nanofluids

Abstract: Numerical investigations are conducted to study the effect of factors such as particle clustering and interfacial layer thickness on thermal conductivity of nanofluids. Based on this, parameters including Kapitza radius, and fractal and chemical dimension which have received little attention by previous research are rigorously investigated. The degree of thermal enhancement is analysed for increasing aggregate size, particle concentration, interfacial thermal resistance, and fractal and chemical dimensions. This analysis is conducted for water-based nanofluids of Alumina (Al2O3), CuO and Titania (TiO2) nanoparticles where the particle concentrations are varied up to 4vol%. Results from the numerical work are validated using available experimental data. For the case of aggregate size, particle concentration and interfacial thermal resistance; the aspect ratio (ratio of radius of gyration of aggregate to radius of primary particle, Rg/a) is varied between 2 to 60. It was found that the enhancement decreases with interfacial layer thickness. Also the rate of decrease is more significant after a given aggregate size. For a given interfacial resistance, the enhancement is mostly sensitive to Rg/a <20 indicated by the steep gradients of data plots. Predicted and experimental data for thermal conductivity enhancement are in good agreement.