Computational Analysis of Factors Influencing Enhancement of Thermal Conductivity of Nanofluids
George Okeke, Sanjeeva Witharana, Joseph Antony, Yulong Ding

TL;DR
This study numerically investigates how factors like particle clustering, interfacial layer thickness, and fractal dimensions influence the thermal conductivity of nanofluids, validated by experimental data.
Contribution
It introduces a comprehensive numerical analysis of previously overlooked parameters such as Kapitza radius and fractal dimensions affecting nanofluid thermal conductivity.
Findings
Thermal enhancement decreases with increasing interfacial layer thickness.
Enhancement is most sensitive to aspect ratio Rg/a <20.
Numerical results agree well with experimental data.
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…
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