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Research Papers: Gas Turbines: Combustion, Fuels, and Emissions

Large Eddy Simulation of an Enclosed Turbulent Reacting Methane Jet With the Tabulated Premixed Conditional Moment Closure Method

[+] Author and Article Information
Carlos Velez

Center for Advanced Turbomachinery and
Energy Research,
University of Central Florida,
Orlando, FL 32816
e-mail: velezcar@yahoo.com

Scott Martin

Eagle Flight Research Center,
Embry-Riddle Aeronautical University,
Daytona Beach, FL 32114
e-mail: martis38@erau.edu

Aleksander Jemcov

Institute for Flow Physics and Control,
University of Notre Dame,
South Bend, IN 46556
e-mail: ajemcov@nd.edu

Subith Vasu

Center for Advanced Turbomachinery and
Energy Research,
University of Central Florida,
Orlando, FL 32816
e-mail: subith@ucf.edu

Contributed by the Combustion and Fuels Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received July 21, 2015; final manuscript received January 28, 2016; published online April 12, 2016. Assoc. Editor: Song-Charng Kong.

J. Eng. Gas Turbines Power 138(10), 101501 (Apr 12, 2016) (9 pages) Paper No: GTP-15-1357; doi: 10.1115/1.4032846 History: Received July 21, 2015; Revised January 28, 2016

The tabulated premixed conditional moment closure (T-PCMC) method has been shown to provide the capability to model turbulent, premixed methane flames with detailed chemistry and reasonable runtimes in Reynolds-averaged Navier–Stokes (RANS) environment by Martin et al. (2013, “Modeling an Enclosed, Turbulent Reacting Methane Jet With the Premixed Conditional Moment Closure Method,” ASME Paper No. GT2013-95092). Here, the premixed conditional moment closure (PCMC) method is extended to large eddy simulation (LES). The new model is validated with the turbulent, enclosed reacting methane backward facing step data from El Banhawy et al. (1983, “Premixed, Turbulent Combustion of a Sudden-Expansion Flow,” Combust. Flame, 50, pp. 153–165). The experimental data have a rectangular test section at atmospheric pressure and temperature with an inlet velocity of 10.5 m/s and an equivalence ratio of 0.9 for two different step heights. Contours of major species, velocity, and temperature are provided. The T-PCMC model falls into the class of table lookup turbulent combustion models in which the combustion model is solved offline over a range of conditions and stored in a table that is accessed by the computational fluid dynamic (CFD) code using three controlling variables: the reaction progress variable (RPV), variance, and local scalar dissipation rate. The local scalar dissipation rate is used to account for the affects of the small-scale mixing on the reaction rates. A presumed shape beta function probability density function (PDF) is used to account for the effects of subgrid scale (SGS) turbulence on the reactions. SGS models are incorporated for the scalar dissipation and variance. The open source CFD code OpenFOAM is used with the compressible Smagorinsky LES model. Velocity, temperature, and major species are compared to the experimental data. Once validated, this low “runtime” CFD turbulent combustion model will have great utility for designing the next generation of lean premixed (LPM) gas turbine combustors.

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References

Figures

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Fig. 1

Flow chart of the T-PCMC CFD model

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Fig. 4

Borghi diagram: computed from CFD in flame zone (c = 0.05–0.95)

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Fig. 8

T-PCMC (top) and experimental (bottom) mean CO2 % volume concentrations

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Fig. 9

Experimental (top) and T-PCMC (bottom) mean CO% volume concentrations

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Fig. 10

Experimental (top) and T-PCMC (bottom) mean UHC% volume concentrations

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Fig. 11

Experimental versus T-PCMC profiles for mean CO2 % volume concentrations. Lines—CFD and symbols—experiment.

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Fig. 12

Experimental versus T-PCMC profiles for mean UHC% volume concentrations. Lines—CFD and symbols—experiment.

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Fig. 2

Density as a function of RPV and variance for a scalar dissipation rate of 200

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Fig. 3

RPV source term as a function of RPV and scalar dissipation rate at a variance equal to 1/3Cvar,Max

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Fig. 5

Experimental (bottom) and T-PCMC (top) temperature contours

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Fig. 6

Compares the contours of the measured and predicted mean axial velocity

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Fig. 7

T-PCMC (top) and experimental (bottom) RMS of axial velocity contours

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