Brownian dynamic simulation for the prediction of effective thermal conductivity of nanofluid

被引:0
作者
Shashi Jain
Hrishikesh E. Patel
Sarit Kumar Das
机构
[1] Indian Institute of Technology Madras,Department of Mechanical Engineering
[2] Massachusetts Institute of Technology (MIT),Department of Mechanical Engineering
来源
Journal of Nanoparticle Research | 2009年 / 11卷
关键词
Nanofluids; Suspensions; Thermal conduction; Brownian dynamic simulation; Effective conductivity; Nanoparticles; Modeling;
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摘要
Nanofluid is a colloidal solution of nanosized solid particles in liquids. Nanofluids show anomalously high thermal conductivity in comparison to the base fluid, a fact that has drawn the interest of lots of research groups. Thermal conductivity of nanofluids depends on factors such as the nature of base fluid and nanoparticle, particle concentration, temperature of the fluid and size of the particles. Also, the nanofluids show significant change in properties such as viscosity and specific heat in comparison to the base fluid. Hence, a theoretical model becomes important in order to optimize the nanofluid dispersion (with respect to particle size, volume fraction, temperature, etc.) for its performance. As molecular dynamic simulation is computationally expensive, here the technique of Brownian dynamic simulation coupled with the Green Kubo model has been used in order to compute the thermal conductivity of nanofluids. The simulations were performed for different concentration ranging from 0.5 to 3 vol%, particle size ranging from 15 to 150 nm and temperature ranging from 290 to 320 K. The results were compared with the available experimental data, and they were found to be in close agreement. The model also brings to light important physical aspect like the role of Brownian motion in the thermal conductivity enhancement of nanofluids.
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