Title

Investigation Of Natural Convection In Nanofluids By Lattice Boltzmann Method

Abstract

Introduction of suspended nanoparticles into a base liquid will remarkably enhance energy transport process of the original liquid, which has been proved by a few experiments carried out by many authors. Irregular displacement and random distribution of the suspended nanoparticles as well as the interaction between nanoparticles and the adjacent liquid molecules make the modeling of flow and heat transfer in nanofluids very difficult. In this paper, a Lattice Boltzmann (LB) model for nanofluids has been developed. The external and internal forces, such as buoyancy, gravity, drag and Brownian force, and the mechanical and thermal interactions among the nanoparticles and their impact on the equilibrium velocity have been introduced. Along with a Gauss white noise model for Brownian motion, the double-distribution-function (DDF) approach, which treats temperature as a passive diffusing scalar and simulates it by a density-independent distribution function, was used to simulate free convection in nanofluids. By this model, the possible sedimentation and fluctuation of nanoparticles, and their impacts on the free convection in nanofluids have been observed and studied. A correlation formula for Nusselt number which characterized by properties of nanofluids has been obtained. The comparison of characteristics of natural convections between the nanofluids and its corresponding pure liquid has been done, and the possible mechanisms which enhance the heat transfer of natural convection in nanofluids have been discussed and revealed. Copyright © 2005 by ASME.

Publication Date

2-23-2006

Publication Title

Proceedings of the ASME/Pacific Rim Technical Conference and Exhibition on Integration and Packaging of MEMS, NEMS, and Electronic Systems: Advances in Electronic Packaging 2005

Volume

PART C

Number of Pages

2319-2326

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

32844457269 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/32844457269

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