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Research Papers: Nuclear Power

Computational Fluid Dynamics Application of the Diffusion-Inertia Model to Bubble Flows and Boiling Water Problems

[+] Author and Article Information
Alexander S. Filippov1

Nuclear Safety Institute, Russian Academy of Sciences, Moscow 113191, Russiaphil@ibrae.ac.ru

Vladimir M. Alipchenkov

Institute for High Temperatures, Russian Academy of Sciences, Moscow 113191, Russia

Nickolay I. Drobyshevsky, Roman V. Mukin, Valeri F. Strizhov, Leonid I. Zaichik

Nuclear Safety Institute, Russian Academy of Sciences, Moscow 113191, Russia

1

Corresponding author.

J. Eng. Gas Turbines Power 132(12), 122901 (Aug 20, 2010) (7 pages) doi:10.1115/1.4000890 History: Received July 31, 2009; Revised August 09, 2009; Published August 20, 2010; Online August 20, 2010

This paper is aimed at the application of a model for simulating the dispersed turbulent flows. The presented model proceeds from a kinetic equation for the probability density function of the particle velocity distribution in turbulent flow. This approach is called the diffusion-inertia model (DIM). Applications of the model to droplet and bubble flows are presented. In the case of vaporized liquid, the interphase heat and mass transfer is introduced by adding the corresponding governing equations. This extended version of the DIM was applied to simulating the boiling water flow in a heated pipe.

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Copyright © 2010 by American Society of Mechanical Engineers
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Figures

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Figure 1

The deposition coefficient in vertical duct flows. (1–3) DIM: (1) Re=10,000, (2) Re=20,000, (3) Re=50,000, (4) experiment by Liu and Agarwal (6), (5) DNS by McLaughlin (7), (6) LES by Wang (8), (7) DNS by Marchioli (9), (8) DNS by Marchioli (10).

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Figure 2

Particles concentration distribution along the pipe and at some pipe sections

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Figure 3

The effect of Stokes number on the deposition efficiency in the 90 deg bend. (1) DIM, (2) experiment by Pui (11), (3) LES by Breuer (12), and (4) LES by Berrouk and Laurence (13)

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Figure 4

Radial profiles of (a) liquid and bubble velocities and (b) void fraction. Experimental data under microgravity conditions (16): jL=1 m/s and jG=0.025 m/s. 1 and 2: numerical; 3 and 4: experimental; 1 and 3: bubbles; 2 and 4: liquid.

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Figure 5

Radial profiles of (a) liquid and bubble velocities and (b) void fraction. Experimental data for upward flow (16): jL=1 m/s and jG=0.023 m/s. 1 and 2: numerical; 3 and 4: experimental; 1 and 3: bubbles; 2 and 4: liquid.

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Figure 6

Radial profiles of (a) liquid and bubble velocities and (b) void fraction. Experimental data for downward flow (16): jL=1 m/s and jG=0.024 m/s: 1 and 2: numerical; 3 and 4: experimental; 1 and 3: bubbles; 2 and 4: liquid

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Figure 7

(a) Near-wall bubble plum. (b) The calculation domain and the heights of taking volume fraction profiles.

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Figure 8

Bubble volume fraction at different heights. (a) Full approach and (b) DIM approach.

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Figure 9

Stream function (picture is compressed along vertical)

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Figure 10

Temperature distributions along the pipe: 1 and 3—bulk flow temperature; 2 and 4—wall temperature; 1 and 2—simulations; 3 and 4—experiments (22)

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Figure 11

Distribution of bulk void fraction along the pipe: 1—simulation; 2—experiment by Bartolomei and Chanturia (22)

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Figure 12

Bulk void fraction profile along the pipe: 1 and 2—simulations; 3 and 4—experiments by Bartolomei and Gorbunov (23); 1 and 3—p=2 MPa, G=250 kg/m2 s, and ΔTS=15°C; 2 and 4—p=3 MPa, G=420 kg/m2 s, and ΔTS=35°C

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Figure 13

Pressure drop against the boiling length for p=2.45 MPa, G=2000 kg/m2 s, and q=0.625 MW/m2. 1 and 2—with boiling; 3—without boiling; 1 and 3—simulations; 2—experiments by Tarasova (24).

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