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Two-phase numerical model for thermal conductivity and convective heat transfer in nanofluids.

Kondaraju S, Lee JS - Nanoscale Res Lett (2011)

Bottom Line: Due to the numerous applications of nanofluids, investigating and understanding of thermophysical properties of nanofluids has currently become one of the core issues.Although numerous theoretical and numerical models have been developed by previous researchers to understand the mechanism of enhanced heat transfer in nanofluids; to the best of our knowledge these models were limited to the study of either thermal conductivity or convective heat transfer of nanofluids.Ability of this model to be able to understand the mechanism of convective heat transfer enhancement distinguishes the model from rest of the available numerical models.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Mechanical Engineering, Yonsei University, Seoul, Korea. joonlee@yonsei.ac.kr.

ABSTRACT
Due to the numerous applications of nanofluids, investigating and understanding of thermophysical properties of nanofluids has currently become one of the core issues. Although numerous theoretical and numerical models have been developed by previous researchers to understand the mechanism of enhanced heat transfer in nanofluids; to the best of our knowledge these models were limited to the study of either thermal conductivity or convective heat transfer of nanofluids. We have developed a numerical model which can estimate the enhancement in both the thermal conductivity and convective heat transfer in nanofluids. It also aids in understanding the mechanism of heat transfer enhancement. The study reveals that the nanoparticle dispersion in fluid medium and nanoparticle heat transport phenomenon are equally important in enhancement of thermal conductivity. However, the enhancement in convective heat transfer was caused mainly due to the nanoparticle heat transport mechanism. Ability of this model to be able to understand the mechanism of convective heat transfer enhancement distinguishes the model from rest of the available numerical models.

No MeSH data available.


Related in: MedlinePlus

Distribution of terms in square temperature gradient. Distribution of , Pc2 and negative and positive terms of Pc3 are shown for Cu(100 nm)/DIW nanofluids at (a) Φ = 0.001, (b) Φ = 0.005 and (c) Φ = 0.01. Reprint from S. Kondaraju, E. K. Jin and J. S. Lee, Investigation of heat transfer in turbulent nanofluids using direct numerical simulations, 81, 016304, 2010. "Copyright 2010 by the American Physical Society."
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Figure 3: Distribution of terms in square temperature gradient. Distribution of , Pc2 and negative and positive terms of Pc3 are shown for Cu(100 nm)/DIW nanofluids at (a) Φ = 0.001, (b) Φ = 0.005 and (c) Φ = 0.01. Reprint from S. Kondaraju, E. K. Jin and J. S. Lee, Investigation of heat transfer in turbulent nanofluids using direct numerical simulations, 81, 016304, 2010. "Copyright 2010 by the American Physical Society."

Mentions: To understand the mechanism of convective heat transfer in turbulent nanofluids, distribution of the production terms (Pc2 and Pc3) in transport equation of square temperature gradient () (Equation 7) and are plotted for Cu(100 nm)/DIW nanofluids at 0.001, 0.005 and 0.01 volume fractions (Figure 3). Pc1, which is production caused by the mean temperature gradient in fluid temperature equation (Equation 6) was found to be 70 times smaller compared to Pc2, which is production caused by the deformation of velocity field. Thus, it was assumed that the effect of Pc1 on convective heat transfer is negligible and was not considered in further analysis. Pc3 in Equation 7 is production caused by the particle heat transport effect on fluid medium, which is represented as q2w in Equation 6. Distribution of shows an increase in the temperature gradients with an increase of particle volume fraction. However, the change in distribution of Pc2 with change in particle volume fraction is found to be negligible. It suggests that the particle dispersions, which deform the fluid velocity, do not significantly affect the convective heat transfer rate in nanofluids. On the other hand, distribution of Pc3 shows a significant difference at different particle volume fractions. Moreover, the high temperature gradients are found to be distributed in the regions of high magnitudes of Pc3. It suggests a significant influence of particle heat transport on convective heat transfer of nanofluids.(7)


Two-phase numerical model for thermal conductivity and convective heat transfer in nanofluids.

Kondaraju S, Lee JS - Nanoscale Res Lett (2011)

Distribution of terms in square temperature gradient. Distribution of , Pc2 and negative and positive terms of Pc3 are shown for Cu(100 nm)/DIW nanofluids at (a) Φ = 0.001, (b) Φ = 0.005 and (c) Φ = 0.01. Reprint from S. Kondaraju, E. K. Jin and J. S. Lee, Investigation of heat transfer in turbulent nanofluids using direct numerical simulations, 81, 016304, 2010. "Copyright 2010 by the American Physical Society."
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3211299&req=5

Figure 3: Distribution of terms in square temperature gradient. Distribution of , Pc2 and negative and positive terms of Pc3 are shown for Cu(100 nm)/DIW nanofluids at (a) Φ = 0.001, (b) Φ = 0.005 and (c) Φ = 0.01. Reprint from S. Kondaraju, E. K. Jin and J. S. Lee, Investigation of heat transfer in turbulent nanofluids using direct numerical simulations, 81, 016304, 2010. "Copyright 2010 by the American Physical Society."
Mentions: To understand the mechanism of convective heat transfer in turbulent nanofluids, distribution of the production terms (Pc2 and Pc3) in transport equation of square temperature gradient () (Equation 7) and are plotted for Cu(100 nm)/DIW nanofluids at 0.001, 0.005 and 0.01 volume fractions (Figure 3). Pc1, which is production caused by the mean temperature gradient in fluid temperature equation (Equation 6) was found to be 70 times smaller compared to Pc2, which is production caused by the deformation of velocity field. Thus, it was assumed that the effect of Pc1 on convective heat transfer is negligible and was not considered in further analysis. Pc3 in Equation 7 is production caused by the particle heat transport effect on fluid medium, which is represented as q2w in Equation 6. Distribution of shows an increase in the temperature gradients with an increase of particle volume fraction. However, the change in distribution of Pc2 with change in particle volume fraction is found to be negligible. It suggests that the particle dispersions, which deform the fluid velocity, do not significantly affect the convective heat transfer rate in nanofluids. On the other hand, distribution of Pc3 shows a significant difference at different particle volume fractions. Moreover, the high temperature gradients are found to be distributed in the regions of high magnitudes of Pc3. It suggests a significant influence of particle heat transport on convective heat transfer of nanofluids.(7)

Bottom Line: Due to the numerous applications of nanofluids, investigating and understanding of thermophysical properties of nanofluids has currently become one of the core issues.Although numerous theoretical and numerical models have been developed by previous researchers to understand the mechanism of enhanced heat transfer in nanofluids; to the best of our knowledge these models were limited to the study of either thermal conductivity or convective heat transfer of nanofluids.Ability of this model to be able to understand the mechanism of convective heat transfer enhancement distinguishes the model from rest of the available numerical models.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Mechanical Engineering, Yonsei University, Seoul, Korea. joonlee@yonsei.ac.kr.

ABSTRACT
Due to the numerous applications of nanofluids, investigating and understanding of thermophysical properties of nanofluids has currently become one of the core issues. Although numerous theoretical and numerical models have been developed by previous researchers to understand the mechanism of enhanced heat transfer in nanofluids; to the best of our knowledge these models were limited to the study of either thermal conductivity or convective heat transfer of nanofluids. We have developed a numerical model which can estimate the enhancement in both the thermal conductivity and convective heat transfer in nanofluids. It also aids in understanding the mechanism of heat transfer enhancement. The study reveals that the nanoparticle dispersion in fluid medium and nanoparticle heat transport phenomenon are equally important in enhancement of thermal conductivity. However, the enhancement in convective heat transfer was caused mainly due to the nanoparticle heat transport mechanism. Ability of this model to be able to understand the mechanism of convective heat transfer enhancement distinguishes the model from rest of the available numerical models.

No MeSH data available.


Related in: MedlinePlus