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

# Comparison of Unsteady Reynolds Averaged Navier–Stokes and Large Eddy Simulation Computational Fluid Dynamics Methodologies for Air Swirl Fuel Injectors

[+] Author and Article Information
David Dunham, James J. McGuirk, Mehriar Dianat

Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough LE11 3TU, UK

Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough LE11 3TU, UKa.spencer@lboro.ac.uk

J. Eng. Gas Turbines Power 131(1), 011502 (Nov 20, 2008) (8 pages) doi:10.1115/1.2969096 History: Received April 11, 2008; Revised April 11, 2008; Published November 20, 2008

## Abstract

It is well documented that various large-scale quasiperiodic flow structures, such as a precessing vortex core (PVC) and multiple vortex helical instabilities, are present in the swirling flows typical of air swirl fuel injectors. Prediction of these phenomena requires time-resolved computational methods. The focus of the present work was to compare the performance and cost implications of two computational fluid dynamics (CFD) methodologies—unsteady Reynolds averaged Navier–Stokes (URANS) using a $k-ε$ model and large eddy simulation (LES) for such flows. The test case was a single stream radial swirler geometry, which has been the subject of extensive experimental investigation. Both approaches captured the gross (time-mean) features of strongly swirling confined flows in reasonable agreement with experiment. The temporal dynamics of the quadruple vortex pattern emanating from within the swirler and observed experimentally were successfully predicted by LES, but not by URANS. Spectral analysis of two flow configurations (with and without a central jet) revealed various coherent frequencies embedded within the broadband turbulent frequency range. LES reproduced these characteristics, in excellent agreement with experimental data, whereas URANS predicted the presence of coherent motions but at incorrect amplitudes and frequencies. For the no-jet case, LES-predicted spectral data indicated the occurrence of a PVC, which was also observed experimentally for this flow condition; the URANS solution failed to reproduce this measured trend. On the evidence of this study, although $k-ε$ based URANS offers considerable computational savings, its inability to capture the temporal characteristics of the flows studied here sufficiently accurately suggests that only LES-based CFD, which captures the stochastic nature of the turbulence much more faithfully, is to be recommended for fuel injector flows.

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## Figures

Figure 1

Datum fuel injector geometry (6)

Figure 2

x-r plane Reynolds-decomposed vectors and swirl strength contours (6)

Figure 3

Computational mesh

Figure 4

Mean streamlines and mean axial velocity contours—with jet condition

Figure 5

Mean streamlines and mean axial velocity contours—no-jet condition

Figure 6

Time-averaged axial (left) and tangential (right) velocity profiles for with jet condition: top x/Ds=0.02, middle x/Ds=1.06, and bottom x/Ds=2.66

Figure 7

Time-averaged axial (left) and tangential (right) velocity profiles for no-jet condition: top x/Ds=0.02, middle x/Ds=1.06, and bottom x/Ds=2.66

Figure 8

Reynolds decomposed instantaneous streamlines at x/Ds=0.02 with jet (left) and no-jet (right) conditions

Figure 9

Time history of instantaneous velocities at x/Ds=0.27 and r/Ds=0.27 for with jet condition LES (left) and URANS (right)

Figure 10

PSD of axial velocity x/Ds=0.27 and r/Ds=0.27 with jet condition

Figure 11

PSD of axial velocity x/Ds=0.27 and r/Ds=0.27 no-jet condition

Figure 12

Spatial correlations of the radial velocity swirler exit with jet (left) and no-jet (right) conditions.

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