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Research Papers: Multiphase Flows

Large Eddy Simulation of the Mixing of a Passive Scalar in a High-Schmidt Turbulent Jet

[+] Author and Article Information
Juan M. Mejía

Departamento de Procesos y Energía,
Universidad Nacional de Colombia,
Cr. 80, No. 65-223,
Medellín, Colombia
e-mail: jmmejiaca@unal.edu.co

Amsini Sadiki

Institute of Energy and Power Plant Technology,
Technischen Universität Darmstadt,
Petersenstr. 30,
Darmstadt D-64287, Germany
e-mail: sadiki@ekt.tu-darmstadt.de

Alejandro Molina

Departamento de Procesos y Energía,
Universidad Nacional de Colombia,
Cr. 80, No. 65-223,
Medellín, Colombia
e-mail: amolinao@unal.edu.co

Farid Chejne

Departamento de Procesos y Energía,
Universidad Nacional de Colombia,
Cr. 80, No. 65-223,
Medellín, Colombia
e-mail: fchejne@unal.edu.co

Pradeep Pantangi

Institute of Energy and Power Plant Technology,
Technischen Universität Darmstadt,
Petersenstr. 30,
Darmstadt D-64287, Germany
e-mail: pantangi@ekt.tu-darmstadt.de

1Corresponding author.

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received July 28, 2013; final manuscript received November 21, 2014; published online January 14, 2015. Assoc. Editor: Sharath S. Girimaji.

J. Fluids Eng 137(3), 031301 (Mar 01, 2015) (11 pages) Paper No: FE-13-1458; doi: 10.1115/1.4029224 History: Received July 28, 2013; Revised November 21, 2014; Online January 14, 2015

Accurate subgrid-scale (SGS) scalar flux models are essential when large eddy simulation (LES) is used to represent flow, mixing and transport of passive and active scalars in engineering, and environmental applications in turbulent regime. Many SGS scalar flux models have been developed for flows with low Schmidt numbers (Sc), but their application to high Sc flows has important limitations. In high Sc flows, the behavior of the scalar field becomes anisotropic because of intermittency effects, phenomenon that must be accounted for by SGS scalar flux models. The objective of this paper is to evaluate the ability of three SGS scalar flux models to predict the scalar behavior of a high Sc-number flow configuration, namely the anisotropy-resolved SGS scalar flux model: (1) appropriate for high Sc-number flow configurations, and two additional SGS models (linear eddy diffusivity based SGS models) with (2) constant, and (3) dynamically calculated turbulent Schmidt number. The LES simulation results accomplished by these models are compared to each other and to experimental data of a turbulent round jet discharging a diluted scalar into a low-velocity coflowing water stream. The comparison of simulation results and experimental observations shows that, in general, all SGS models reproduce the mean filtered concentration distribution in radial direction. The dynamic eddy diffusivity and anisotropy models reproduce the rms of the concentration and SGS scalar fluxes distribution. In particular, the anisotropy model improves the prediction reliability of LES. However, the three models evaluated in this study cannot accurately predict the scalar behavior at the superviscous layer. Finally, this work demonstrates that complex models can achieve reliable predictions on reasonable grids using less computational effort, while simple models require fine grids with increased computational costs.

Copyright © 2015 by ASME
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References

Figures

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Fig. 1

Scheme of the axis-symmetric jet [44]

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Fig. 2

Mesh details for the 1.2M case (plane xy, z = 0). To improve readability, the finite volumes have been scaled by a factor of 3.

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Fig. 3

Isosurfaces of the λ2-criterion. From left to right: −0.5, −1.0, and −5.0 A.U.

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Fig. 4

Instantaneous vorticity modulus (cut at z = 0) and velocity streamlines at the nozzle exit

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Fig. 5

Mean streamwise velocity distribution across the jet for different downstream positions. Solid line: x/D = 50; dashed line: x/D = 70; dotted line: x/D = 80; and dashed-dotted line: x/D = 90.

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Fig. 6

Streamwise (a) and radial (b) velocity fluctuations distribution across the jet for different downstream positions. Solid line: x/D = 50; dashed line: x/D = 70; dotted line: x/D = 80; and dashed-dotted line: x/D = 90.

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Fig. 7

Streamwise mean velocity distribution along the jet centerline. Experimental data [44] (symbol). Simulation results (lines): Solid line: 0.8M mesh; dashed line: 1.2M mesh; and dotted line: 1.6M mesh. Continuous lines denote linear regression.

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Fig. 8

Mean streamwise velocity distribution across the jet. Experimental data [44] (symbols): + x/D = 70; •x/D = 80; ×x/D = 90. Simulation results (lines): Solid: 0.8M mesh; dashed: 1.2M; and dotted: 1.6M.

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Fig. 9

Streamwise (a) and radial (b) velocity fluctuation distributions across the jet. Experimental data [44] (symbols): +x/D=70; •x/D=80; ×x/D=90. Simulation results (lines): Solid: 0.8M mesh; dashed: 1.2M; and dotted: 1.6M.

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Fig. 10

Power spectral density of axial velocity at r = 0 and x/D = 15. Solid line: 0.8M mesh; dashed line: 1.2M; and dotted line: 1.6M.

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Fig. 11

Instantaneous concentration of rhodamine B. Left: Isosurface plot (cut at z = 0); right: contour plot (plane xz, y = 0). Darkest denotes maximum concentration.

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Fig. 12

Instantaneous concentration of rhodamine B and velocity streamlines near the tube exit (plane xz,y = 0). The lines on the figure illustrate the direction of the counter-acting vortex. The color map of the Iso-concentration lines has been inverted for a better visualization.

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Fig. 13

Mean (a) and rms (b) concentration distribution across the jet for different downstream positions (EDM). Solid line: x/D = 50; dashed line: x/D = 70; dotted line: x/D = 80; and dashed-dotted line: x/D = 90.

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Fig. 14

Streamwise (a) and radial (b) velocity–concentration correlation across the jet for different downstream positions (dynamic model). Solid line: x/D = 50; dashed line: x/D = 70; dotted line: x/D = 80; and dashed-dotted line: x/D = 90.

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Fig. 15

Radial mean (a) and fluctuation (b) concentration distribution across the jet. Experimental data [44] (symbols): + x/D = 70; •x/D = 80; ×x/D = 90. Simulation results (lines): Solid line: eddy; dashed line: dynamic; dotted line: anisotropy; and dashed-dotted line: dynamic −1.6M mesh.

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Fig. 16

Streamwise (a) and radial (b) velocity–concentration correlation across the jet. Experimental data [44] (symbols): + x/D = 70; •x/D = 80; ×x/D = 90. Simulation results (lines): Solid line: eddy; dashed line: dynamic; dotted line: anisotropy; and dashed-dotted line: dynamic −1.6M mesh.

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Fig. 17

Power spectra density of the scalar field at r = 0 at x/D = 15. Solid line: eddy; dashed line: dynamic; and dotted line: anisotropy.

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