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Research Papers

Effects of Preferential Concentration on Heat Transfer in Particle-Based Solar Receivers

[+] Author and Article Information
Hadi Pouransari

Center for Turbulence Research,
Department of Mechanical Engineering,
Stanford University,
Stanford, CA 94305
e-mail: hadip@stanford.edu

Ali Mani

Center for Turbulence Research,
Department of Mechanical Engineering,
Stanford University,
Stanford, CA 94305
e-mail: alimani@stanford.edu

Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received July 21, 2016; final manuscript received November 2, 2016; published online November 29, 2016. Assoc. Editor: Nesrin Ozalp.

J. Sol. Energy Eng 139(2), 021008 (Nov 29, 2016) (11 pages) Paper No: SOL-16-1335; doi: 10.1115/1.4035163 History: Received July 21, 2016; Revised November 02, 2016

The working principle of particle-based solar receivers is to utilize the absorptivity of a dispersed particle phase in an otherwise optically transparent carrier fluid. In comparison to their traditional counterparts, which use a solid surface for radiation absorption, particle-based receivers offer a number of opportunities for improved efficiency and heat transfer uniformity. The physical phenomena at the core of such receivers involve coupling between particle transport, fluid turbulence, and radiative heat transfer. Previous analyses of particle-based solar receivers ignored delicate aspects associated with this three-way coupling. Namely, these investigations considered the flow fields only in the mean sense and ignored turbulent fluctuations and the consequent particle preferential concentration. In the present work, we have performed three-dimensional direct numerical simulations of turbulent flows coupled with radiative heating and particle transport over a range of particle Stokes numbers. Our study demonstrates that the particle preferential concentration has strong implications on the heat transfer statistics. We demonstrate that “for a typical setting” the preferential concentration of particles reduces the effective heat transfer between particles and the gas by as much as 25%. Therefore, we conclude that a regime with Stokes number of order unity is the least preferred for heat transfer to the carrier fluid. We also provide a 1D model to capture the effect of particle spatial distribution in heat transfer.

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Figures

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Fig. 1

Schematics of a particle-based solar receiver (a) in contrast to a conventional receiver (b)

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Fig. 2

Approximate range of particle volume fraction versus particle relaxation time in some of the recent studies of particle-based solar receivers

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Fig. 3

Computational domain. The side and bottom walls of the channel are colored by gas temperature and particle concentration, respectively.

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Fig. 4

Results of the 1D model as functions of streamwise location for different particle relaxation times. Arrows show increasing particle relaxation time. (a) nondimensionalized mean gas (solid) and particle (dashed) temperatures; (b) nondimensionalized particle-gas temperature difference; (c) nondimensionalized radiative heat absorption by particles, Ha; (d) heat transfer from the dispersed phase to the gas phase, Ht. Heat absorption and heat transfer are nondimensionalized by nominal radiative heat absorption per unit volume 1/4πDp2ϵpIn0.

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Fig. 5

Snapshots of the simulations for different Stokes numbers (from 0.04 at the bottom to 9.2 at the top). Left: particle concentration contours in the inlet yz plane, middle: gas temperature contours in the mid xy plane, right: gas temperature contours in the exit yz plane.

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Fig. 6

Normalized temperature PDFs at the domain outlet: (a) gas; (b) particles; (c) normalized standard deviation of particle and gas temperature at the domain outlet for different Stokes numbers

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Fig. 7

Two-dimensional radial distribution function at the outlet of the domain for different cases. Radial distance is nondimensionalized by the inlet Kolmogorov length.

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Fig. 8

Spatial autocovariance of the gas temperature at the outlet of the domain for different Stokes numbers

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Fig. 9

Gas and particle temperatures at the outlet: (a) mean; (b) particle-gas temperature difference

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Fig. 13

Dimensional mean gas and particle temperatures for the parameter set given in Table 2

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Fig. 10

Voronoi tessellation of particles at the exit of the domain for: (a) case 1 colored by the normalized particle temperature; (b) case 1 colored by the normalized gas temperature at the location particle; (c) case 4 colored by the normalized particle temperature; (d) case 4 colored by the normalized gas temperature at the location particle. The same color map is used for all figures.

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Fig. 14

Averaged standard deviation of the normalized Voronoi cell volumes as in Ref. [47] at the domain outlet

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Fig. 11

(a) Correction factor as a function of Stokes number; (b) correction factor versus St*, the amount of particle clustering. Points' colors are the same in two figures.

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Fig. 12

(a) Averaged particle temperature at the exit of the domain as a function of particle Stokes number; (b) averaged particle-gas temperature difference at the exit of the domain as a function particle Stokes number

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