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

Large-Eddy Simulation of Soot Formation in a Model Gas Turbine Combustor

[+] Author and Article Information
Heeseok Koo

Department of Aerospace Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: heeseokkoo@gmail.com

Malik Hassanaly

Department of Aerospace Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: malik.hassanaly@gmail.com

Venkat Raman

Associate Professor
Mem. ASME
Department of Aerospace Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: ramanvr@umich.edu

Michael E. Mueller

Assistant Professor
Mem. ASME
Department of Mechanical and
Aerospace Engineering,
Princeton University,
Princeton, NJ 08544
e-mail: muellerm@princeton.edu

Klaus Peter Geigle

Mem. ASME
German Aerospace Center (DLR),
Institution of Combustion Technology,
Pfaffenwaldring 38-40,
Stuttgart D-70569, Germany
e-mail: klauspeter.geigle@dlr.de

1Corresponding author.

Contributed by the Combustion and Fuels Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received June 26, 2016; final manuscript received July 10, 2016; published online September 27, 2016. Editor: David Wisler.

J. Eng. Gas Turbines Power 139(3), 031503 (Sep 27, 2016) (9 pages) Paper No: GTP-16-1277; doi: 10.1115/1.4034448 History: Received June 26, 2016; Revised July 10, 2016

The computational modeling of soot in aircraft engines is a formidable challenge, not only due to the multiscale interactions with the turbulent combustion process but the equally complex physical and chemical processes that drive the conversion of gas-phase fuel molecules into solid-phase particles. In particular, soot formation is highly sensitive to the gas-phase composition and temporal fluctuations in a turbulent background flow. In this work, a large-eddy simulation (LES) framework is used to study the soot formation in a model aircraft combustor with swirl-based fuel and air injection. Two different configurations are simulated: one with and one without secondary oxidation jets. Specific attention is paid to the LES numerical implementation such that the discrete solver minimizes the dissipation of kinetic energy. Simulation of the model combustor shows that the LES approach captures the two recirculation zones necessary for flame stabilization very accurately. Further, the model reasonably predicts the temperature profiles inside the combustor. The model also captures variation in soot volume fraction with global equivalence ratio. The structure of the soot field suggests that when secondary oxidation jets are present, the inner recirculation region becomes fuel lean, and soot generation is completely suppressed. Further, the soot field is highly intermittent suggesting that a very restrictive set of gas-phase conditions promotes soot generation.

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References

Figures

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Fig. 1

Velocity magnitude contours after 1 s for orthogonal and skewed meshes

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Fig. 2

Temporal kinetic energy decay between different numerical approaches for orthogonal and skewed meshes, for two different time-step sizes. Ham and Iaccarino results (solid lines [14]) correspond to both orthogonal and skewed mesh cases.

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Fig. 3

(a) Full three-dimensional grid with secondary inlets marked. (b) The center plane mesh with the Pope's criterion. M = 0.2 along the solid lines.

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Fig. 4

Flamelet solutions showing (a) progress variable source term, SC in Eq.(3), and (b) key soot chemistry source terms

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Fig. 5

Mean (a) axial (Uy) and (b) tangential (Ux) velocity contours from LES. Axial velocity is zero along the solid lines.

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Fig. 6

Mean (a) axial and (b) tangential velocities from LES (solid lines) compared to experimental data (circles) at different axial locations

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Fig. 7

Mean axial velocities for the case with and without secondary injections, compared to the experimental PIV data [16]. Axial velocity is zero along the solid lines: (a) no secondary flow and (b) with secondary flow.

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Fig. 8

Mean mixture fraction and temperature fields: (a) no secondary flow and (b) with secondary flow

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Fig. 9

Mean and RMS temperature profiles along the centerline and two off-center axial lines for the case with secondary air injection. Solid lines and filled circles are mean temperature profiles while dashes and empty circles are RMS values.

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Fig. 10

Instantaneous soot volume fraction snapshots at thecenter plane every 8 ms for the case without secondary injection

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Fig. 11

Instantaneous soot volume fraction snapshots at thecenter plane every 8 ms for the case with the secondary injection

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Fig. 12

Soot volume fraction statistics for the case without secondary air injection compared to the experiment: (a) mean soot volume fraction and (b) RMS volume fraction

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Fig. 13

Soot volume fraction statistics for the case with the secondary air injection compared to the experiment: (a) mean soot volume fraction and (b) RMS volume fraction

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