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Research Papers: Energy Systems Analysis

Large Eddy Simulation for Prediction of Entropy Generation in a Nonpremixed Turbulent Jet Flame

[+] Author and Article Information
Mehdi Safari

Graduate Research Assistant
Mem. ASME
Department of Mechanical and
Industrial Engineering,
Northeastern University,
Boston, MA 02115
e-mail: safariqariq.m@husky.neu.edu

M. Reza H. Sheikhi

Assistant Professor
Mem. ASME
Department of Mechanical and
Industrial Engineering,
Northeastern University,
Boston, MA 02115

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received August 6, 2013; final manuscript received November 5, 2013; published online January 15, 2014. Editor: Hameed Metghalchi.

J. Energy Resour. Technol 136(2), 022002 (Jan 15, 2014) (6 pages) Paper No: JERT-13-1230; doi: 10.1115/1.4025974 History: Received August 06, 2013; Revised November 05, 2013

Local entropy generation in a turbulent nonpremixed jet flame (Sandia Flame D) is predicted using large eddy simulation (LES) with inclusion of entropy transport. The filtered form of entropy transport equation contains several unclosed source terms which represent irreversibilities due to viscous dissipation, heat conduction, mass diffusion, and chemical reaction. The subgrid scale (SGS) closure is accounted for by the entropy filtered density function (En-FDF) methodology to include complete statistical information about SGS variation of scalars and entropy. The En-FDF provides closed forms for the chemical reaction effects. The methodology is applied for LES of Sandia Flame D and predictions are validated against experimental data. Entropy statistics are shown to compare favorably with the data. All individual irreversible processes in this flame are predicted and analyzed. It is shown that heat conduction and chemical reaction are the main sources of entropy generation in this flame.

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Figures

Grahic Jump Location
Fig. 1

Instantaneous contours of entropy (kJ/kg · K) predicted by the En-FDF

Grahic Jump Location
Fig. 2

Radial variation of (a) mean temperature (K) and (b) mixture fraction at x/D = 15. The circles denote the experimental data.

Grahic Jump Location
Fig. 3

Radial variation of entropy (kJ/kg · K) statistics: (a) mean and (b) resolved (solid line) and total (dashed line) RMS fields at x/D = 15. The circles denote the experimental data.

Grahic Jump Location
Fig. 4

Instantaneous contours of (a) temperature (K) and (b) mixture fraction at z = 0 plane

Grahic Jump Location
Fig. 5

Instantaneous contours of entropy generation (J/K.m3 · s) contributions due to (a) heat conduction, (b) chemical reaction, (c) mass diffusion, and (d) viscous dissipation at z = 0 plane

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