Prediction of effective thermal conductivity of nanofluids by modifying renovated Maxwell model

Abstract

Nanofluids, which are formed by suspending nanoparticles into conventional fluids, exhibit anomalously high thermal conductivity. Renovated Maxwell model was developed by Choi in which the presence of very thin nanolayer surrounding the solid particles was considered, which can measurably increase the effective thermal conductivity of nanofluids. A new model is proposed by introducing a fitting parameter χ in the renovated Maxwell model, which accounts for nanolayer, nonuniform sizes of filler nanoparticles together with aggregation. The model shows that the effective thermal conductivity of nanofluids is a function of the thickness of the nanolayer, the nanoparticle size, the nanoparticle volume fraction and the thermal conductivities of suspended nanoparticles, nanolayer and base fluid. The validation of the model is done by applying the results obtained by the experiments on nanofluids, other theoretical models, and artificial neural network technique. The uncertainty of the present measurements is estimated to be within 5% for the effective thermal conductivity.