Heat Exchangers

Supercritical Carbon Dioxide Heat Transfer in Horizontal Semicircular Channels

[+] Author and Article Information
Alan Kruizenga

 Sandia National Laboratories, P.O. Box 0969, Livermore, CA 94551;  Nuclear Engineering and Engineering Physics, University of Wisconsin Madison, 1500 Engineering Drive, Madison, WI 53711amkruiz@sandia.gov

Hongzhi Li, Mark Anderson, Michael Corradini

 Nuclear Engineering and Engineering Physics, University of Wisconsin Madison, 1500 Engineering Drive, Madison, WI 53711

J. Heat Transfer 134(8), 081802 (Jun 08, 2012) (10 pages) doi:10.1115/1.4006108 History: Received May 06, 2011; Revised December 02, 2011; Published June 07, 2012; Online June 08, 2012

Competitive cycles must have a minimal initial cost and be inherently efficient. Currently, the supercritical carbon dioxide (S-CO2 ) Brayton cycle is under consideration for these very reasons. This paper examines one major challenge of the S-CO2 Brayton cycle: the complexity of heat exchanger design due to the vast change in thermophysical properties near a fluid’s critical point. Turbulent heat transfer experiments using carbon dioxide, with Reynolds numbers up to 100 K, were performed at pressures of 7.5–10.1 MPa, at temperatures spanning the pseudocritical temperature. The geometry employed nine semicircular, parallel channels to aide in the understanding of current printed circuit heat exchanger designs. Computational fluid dynamics was performed using FLUENT and compared to the experimental results. Existing correlations were compared, and predicted the data within 20% for pressures of 8.1 MPa and 10.2 MPa. However, near the critical pressure and temperature, heat transfer correlations tended to over predict the heat transfer behavior. It was found that FLUENT gave the best prediction of heat transfer results, provided meshing was at a y+  ∼ 1.

Copyright © 2012 by American Society of Mechanical Engineers
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Figure 1

Tpc is marked by the local maximum in specific heat at a constant pressure. This peak also corresponds to a large gradient in other thermophysical properties of interest.

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Figure 2

Schematic of experimental facility at the University of Wisconsin

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Figure 3

Top and Bottom of heat transfer test section (dimensions in brackets millimeters, else inches)

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Figure 4

Mixing manifold on test section. Also shown is the wall thermocouple implanted into the stainless steel.

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Figure 5

Test section assembled with water cooling block

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Figure 6

One of ten subsections used to determine experimental heat transfer coefficient

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Figure 7

Schematic of the computational model, showing adiabatic entrance and exit length, in addition to heating test section, which has measured thermocouple data as temperature boundary conditions

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Figure 8

Cross section mesh scheme

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Figure 9

Wall temperatures predicted by different models with different mesh cells

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Figure 10

Comparison of k-ω SST, k-ɛ, and experiments versus bulk temperature

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Figure 11

Nusselt number is maximized by reduction of pressure, proximately of bulk temperature to Tpc and an increase in mass flux

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Figure 12

FLUENT calculations are able to capture both an increase and decrease in the normalized Nusselt number, which matches well to experimentally observed data in the cooling mode

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Figure 13

Specific heat ratio versus normalized temperature indicating that the shape of the normalized Nusselt plots is due to the changing specific heat in the radial direction

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Figure 14

FLUENT calculations show very similar trends to experimental values, which are both normalized to Jackson’s correlation

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Figure 15

The characterisic over-prediction of the experimental and FLUENT ’s Nusselt number is observed in the heating mode when using the Dittus-Boelter correlation

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Figure 16

Jackson’s correlation predicts heat transfer behavior better than the Dittus-Boelter correlation, however, this correlation still exhibits the over-prediction of data in the heating mode

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Figure 17

Developed correlation as a modifier to the Jackson correlation near Tpc for low reduced pressures

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Figure 18

Specific heat weighted fit describes experimental data within 30%

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Figure 19

Experimental data compared to Dittus-Boelter evaluated at the film temperature (open symbols), and to Dittus-Boelter with integrated properties (Eq. 17)




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