Research Papers

Effect of Diamond Nanolubricant on R134a Pool Boiling Heat Transfer

[+] Author and Article Information
M. A. Kedzierski

 Fellow ASMENational Institute of Standards and Technology, Building 226, Room B114, Gaithersburg, MD 20899

Certain commercial equipment, instruments, or materials are identified in this paper in order to specify the experimental procedure adequately. Such identification is not intended to imply recommendation or endorsement by the National Institute of Standards and Technology, nor is it intended to imply that the materials or equipment identified are necessarily the best available for the purpose.

The equivalent mixture is RL68H/diamond (91.3/8.7) in terms of mass.

For the record, Table 1 provides functional forms of the Laplace equation that were used in this study in the same way as was done in Kedzierski [15] and in similar studies by this author.

Because of the consistent trend of the stratified data, it is likely that a larger degradation would have been exhibited by the worst performing mixtures had more data runs been taken.

The 10 nm particle diameter was specified by the manufacturer of the nanopowder that was used to make the nanolubricant.

As shown in Ref. [14], the nanoparticles resulted in an approximate 7% increase in the thermal conductivity of that of the pure lubricant.

J. Heat Transfer 134(5), 051001 (Apr 13, 2012) (8 pages) doi:10.1115/1.4005631 History: Received March 16, 2010; Revised April 19, 2010; Published April 11, 2012; Online April 13, 2012

This paper quantifies the influence of diamond nanoparticles on the pool boiling performance of R134a/polyolester mixtures on a roughened, horizontal, and flat surface. Nanofluids are liquids that contain dispersed nanosize particles. A lubricant based nanofluid (nanolubricant) was made by suspending 10 nm diameter diamond particles in a synthetic ester to roughly a 2.6% volume fraction. For the 0.5% nanolubricant mass fraction, the nanoparticles caused a heat transfer enhancement relative to the heat transfer of pure R134a/polyolester (99.5/0.5) up to 129%. A similar enhancement was observed for the R134a/nanolubricant (99/1) mixture, which had a heat flux that was on average 91% larger than that of the R134a/polyolester (99/1) mixture. Further increase in the nanolubricant mass fraction to 2% resulted in boiling heat transfer degradation of approximately 19% for the best performing tests. It was speculated that the poor quality of the nanolubricant suspension caused the performance of the (99.5/0.5), and the (98/2) nanolubricant mixtures to decay over time to, on average, 36% and 76% of the of pure R134a/polyolester performance, respectively. Thermal conductivity and viscosity measurements and a refrigerant\lubricant mixture pool-boiling model were used to suggest that increases in thermal conductivity and lubricant viscosity are mainly responsible for the heat transfer enhancement due to nanoparticles. Particle size measurements were used to suggest that particle agglomeration induced a lack of performance repeatability for the (99.5/0.5) and the (98/2) mixtures. From the results of the present study, it is speculated that if a good dispersion of nanoparticles in the lubricant is not obtained, then the agglomerated nanoparticles will not provide interaction with bubbles, which is favorable for heat transfer. Further research with nanolubricants and refrigerants are required to establish a fundamental understanding of the mechanisms that control nanofluid heat transfer.

Copyright © 2012 by American Society of Mechanical Engineers
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Figure 3

R134a/RL68H mixtures boiling curves

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Figure 1

Schematic of test apparatus

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Figure 2

OFHC copper flat test plate with cross-hatched surface and thermocouple coordinate system

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Figure 4

R134a/RL68H2C (99.5/0.5) mixture boiling curves

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Figure 5

R134a/RL68H2C (99/1) mixture boiling curves

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Figure 6

R134a/RL68H2C (98/2) mixture boiling curves

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Figure 7

Boiling heat flux of R134a/RL68H mixture relative to that of pure R134a

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Figure 8

Boiling heat flux of R134a/RL68H2C mixtures relative to that of R134a/RL68H without nanoparticles for best performance data runs

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Figure 9

Boiling heat flux of R134a/RL68H2C mixtures relative to that of R134a/RL68H without nanoparticles for worst performance data runs

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Figure 10

Agglomerated diamond nanoparticles in syringe filter material

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Figure 11

Predicted heat flux ratio for RL68H2C (99.5/0.5) mixture using Kedzierski [22] model compared with measurement means



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