Prediction of Thermal Conductivity and Shear Viscosity of Water-Cu Nanofluids Using Equilibrium Molecular Dynamics

Nanofluids are new class of fluids which can be used for many engineering applications due to their enhanced thermal properties. The macroscopic modeling tools used for flow simulations usually rely on effective thermal and rheological properties of the nanofluids that can be predicted through various effective medium theories. As these theories significantly under-predict, using correlations based on experimental data is considered as the only reliable means for prediction of these effective properties. However, the behavior might change significantly once the particle material or base fluid change due to different particle fluid interactions in the molecular level. One of the most promising means of modeling effective properties of the nanofluids is the molecular dynamics simulations where all the intermolecular effects can be modeled. This study investigates equilibrium molecular dynamics simulation of the water-Cu nanofluids to predict the thermal and rheological properties. The molecular dynamics simulation is carried out to achieve a thermodynamic equilibrium, based on a state that is defined by targeted thermodynamic properties of the system. The Green-Kubo method is used to predict the thermal conductivity and viscosity of the system. The study considers the use of different combining rules such as Lorentz-Berthelot and sixth-power rules for defining the inter-atomic potentials for water modeled by SPC/E and nanoparticles modeled by Lennard-Jones potential. The predicted effective properties that are thermal conductivity and shear viscosity are then compared with experimental data from literature. The predicted transport properties at different temperatures and particle concentrations are compared to experimental data from literature for model validation.