Computational analysis of factors influencing thermal conductivity of nanofluids |
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Authors: | G Okeke S Witharana S J Antony Y Ding |
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Institution: | (1) Institute of Particle Science and Engineering, School of Process, Environmental and Materials Engineering, University of Leeds, Leeds, LS2 9JT, UK; |
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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
analyzed 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 4 vol%. 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, R
g/a) is varied from 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 R
g/a < 20 indicated by the steep gradients of data plots. Predicted and experimental data for thermal conductivity enhancement
are in good agreement. On the influence of fractal and chemical dimensions (d
l
and d
f) of Alumina–water nanofluid, the R
g/a was varied from 2 to 8, d
l from 1.2 to 1.8, and d
f from 1.75 to 2.5. For a given concentration, the enhancement increased with the reduction of d
l or d
f. It appears a distinctive sensitivity of the enhancement to d
f, in particular, in the range 2–2.25, for all values of R
g/a. However, the sensitivity of d
l was largely depended on the value of R
g/a. The information gathered from this study on the sensitivity of thermal conductivity enhancement to aggregate size, particle
concentration, interfacial resistance, and fractal and chemical dimensions will be useful in manufacturing highly thermally
conductive nanofluids. Further research on the refine cluster evolution dynamics as a function of particle-scale properties
is underway. |
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Keywords: | |
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