diffusion coefficient

In the present paper, using the non-equilibrium molecular dynamic (NEMD) method, thermal conductivity coefficient of water based nanofluids was calculated and the influence of the metal nanoparticles type with four particle types including copper, silver, platinum, and gold inside a cooper nanochannel was investigated. Also, Pcff force field was used for modeling of the bonded and unbonded interactions among the molecules of water, nanoparticles, and the walls. The results, show that the silver nanoparticle has the maximum effect on the increasing of the nanofluid thermal conductivity coefficient. The interaction and tendency between water and nanoparticles were investigated by using of the radial distribution function (RDF) analysis and the diffusion coefficient of the nanofluid inside the nanochannel was then evaluated. Moreover, the thermodynamic properties of nanofluids including Cv and Cp were studied by using equilibrium molecular dynamic (EMD) method. The studies indicate that by adding nanoparticles to water, the specific heat value is reduced in constant pressure and volume, of which the minimum and maximum specific heat reduction is related to copper and platinum nanoparticles. By investigating the diagram of atoms’ density distribution, it was found that the highest density is related to the silver nanoparticle and the maximum thickness of water layer is formed alongside with the gold nanoparticle. The viscosity of the nanofluids was also calculated by two methods of equilibrium and non-equilibrium dynamics and it was specified that the viscosities obtained for the nanofluids were increased by adding the nanoparticles to water fluid.

In this study, a fuzzy inference system based on look up table was used for modeling and predicting the diffusion coefficient of benzoic acid in the water based γ-Alumina and Silica nanofluids. Due to evaluate the designed fuzzy system, Nanofluids Diffusion coefficients of benzoic acid at constant temperature of 20 ◦C were measured with using a simple and inexpensive technique. The results revealed that the designed fuzzy system could accurately mimic the diffusional mass transfer in nanofluids. The deviation between fuzzy model and experiments for γ-Alumina and Silica nanofluids were about 0.939 and 0.997, respectively. The measurements showed that nanoparticles at low concentration did not have a significant effect on benzoic acid diffusion in nanofluids relative to that in pure water. But diffusion in silica nanofluids strongly reduced at high concentration of nanoparticles, as in volume fraction of 0.8% diffusion coefficient decreased up to 35% relative to that in base fluid. Such factors as the type of tests to determine the diffusion coefficient in nanofluids, nanoparticles concentration and type, could strongly influence of diffusional mass transfer in nanofluids.