Prediction of stability and thermal conductivity of nanofluids for thermal energy storage applications

This study assesses the stability of nanofluids using a computational modelling technique based on Lagrangian particle tracking. A multiphase liquid-solid model is used where the motion of embedded nanoparticles in the suspended fluid is treated by an Eulerian-Lagrangian hybrid scheme with fixed time stepping. This technique enables various multiscale forces, whose characteristics (length and timescales) are quite different, to be established. The system under consideration consists of 50 nm Al2O3 ceramic nanoparticles at various volume fractions ranging between 1.0 and 5.0% suspended in fluids of different density ratios, including water with homogeneous temperature distributions from 5 to 95 degrees C. The simulation results demonstrate the effectiveness of the technique, with predictions elucidating the role of Brownian motion, particle collision and DLVO forces, and their influence on the level of nanoparticle agglomeration. The nano-aggregates formed are found to play a key role in the thermal behaviour of the nanofluid at various particle concentrations, with predictions in agreement with theoretical and experimental results obtained in similar studies. The results of the work are used to consider the heat transfer characteristics of nanofluids and their potential applications.