Nanoscale solid particles dispersed in a host fluid are called nanofluids, which have attracted a vast attention in recent decades. Despite the diverse range of studies accomplished on nanofluids, there are still some secrets about them, which should be revealed by further in-depth studies. Hence, the present dissertation focuses on some important parameters that can affect the thermal performance of the nanofluids.
Initially, this thesis presents a new data processing method for calculating more reliable thermophysical properties of liquids using Green-Kubo Method based molecular dynamics (MD) simulation. Equilibrium molecular dynamics simulation of water is first performed using three common water models. A new approach for analysing the simulation data is then developed to obtain statistically meaningful thermophysical properties such as thermal conductivity and viscosity. The proposed approach can ensure the repeatability and reliability of the calculated thermophysical properties of the liquid. Then, a guideline is developed that can suggest an appropriate simulation box size for a target standard deviation at different temperatures and water models.
Several numerical and theoretical models have been proposed to predict the thermophysical behaviour of the nanofluids. However, most of these models were not able to predict accurately the thermal conductivity and viscosity for a variety of particle shapes or sizes. In the present paper, using the Green-Kubo Method based molecular dynamics simulations, new correlations for predicting the thermophysical properties of nanofluids are developed based on the particle shape, concentration, and fluid temperature. Silver nanofluids with various nanoparticle shapes including sphere, cube, cylinder and rectangular prisms were under investigation. The relative thermal conductivity and relative viscosity predicted by the proposed correlations are within a mean deviation of 2% and 5%, respectively, as compared with the experimental results from this study and available literature. The proposed correlations will be useful tools for engineers in designing the nanofluid for different applications.
Hydraulic and thermal (hydrothermal) analysis of the silver nanofluid has been also investigated in this study. This is an important matter in thermal applications where working fluid is in motion. Two main parameters of the nanofluid flow, namely heat transfer coefficient and pressure drop in a double pipe heat exchanger are investigated using computational fluid dynamics (CFD). The results are validated against available experimental data in the literature. Finally, two correlations are developed for Nu number and friction factor of the nanofluids with different particle shapes, volume concentrations, Prandtl numbers, and flow rates in laminar regime.