Swirling Flame Analysis
Dustin Cook
Final Project
Applied Combustion
Abstract
A swirl burner produces a swirling flame through the combustion of methane. The complex
swirling flow considered is a round reacting turbulent jet surrounded by an annular shroud of swirling air.
The annular shroud is also surrounded by an air co-flow. The combustion process of a swirling flame
burner was analyzed by using the turbulence model k-epsilon (2 equations) and two solution methods.
The predictions shown in the results compared very well to the theoretical data from the University of
Sidney. The improvements discovered over the initial problem statement were the addition of radiation
and a third order solution method.
Introduction
A swirl burner produces a swirling flame through the combustion of methane. The complex swirling flow
considered is a round reacting turbulent jet surrounded by an annular shroud of swirling air. The annular
shroud is also surrounded by an air co-flow. The fuel inlet has a diameter of 3.6mm and bulk velocity of
32.7 m/s. The air inlet for the annular shroud has an inner diameter of 50mm and an outer diameter of
60mm with a bulk axial velocity of 38.2 m/s and an average swirl velocity of 19.1 m/s. The annular
shroud enters free of methane. The air co-flow is also free of methane, has an average velocity of 20
m/s, and has an outer diameter of 310mm.
Procedure
1. Load mesh and data
2.
3.
4.
5.
6.
Check mesh
Set the solver to Axisymmetric Swirl
Set the energy equation to enable heat transfer
Set the model to turbulent k-epsilon (2 eqn), Realizable
Set the species model to: Species transport , volumetric reactions, eddy-dissipation, add
the suggested reactions
7. Upload methane-air 2 step mixture data from fluent database, add o2,co,co2,n2,
ch4,h20
8. Set air inlet conditions :Ux=38.2 m/s, T=300K ,swirl-velocity=19.1m/s, XO2 =0.21
9. Set air inlet-top conditions :Ux=38.2 m/s, T=300K ,swirl-velocity=19.1m/s, X O2 =0.21
10. Set fuel-inlet conditions: Ux=32.7 m/s, T=300K, XCH4 =1
11. Set top conditions: Ux=20 m/s, T=300K
12. Make sure all walls are adiabatic
13. Create vertical lines at: 6.8mm, 10mm, 20mm, 40mm, 60mm, 75mm
14. Set Residual Monitors: check Plot, Iterations to plot 1000, Iterations to store 1000
15. Create a surface monitor to check for convergence, Mass weighted average-Static
temperature
16. Set Solution initialization to compute from the fuel inlet
17. Initialize
18. Set Run calculation: number of iterations 50000
19. Allow to run for 9541 iterations
20. Create a XY plot for static temperature for the outlet
21. Allow to run another 2100 iterations
22. Create a XY plot for static temperature for the outlet
23. Compare the two to see if the residuals have converged
24. Check the flux reports for convergence
25. Once converged create contours and vectors plots
Results: Convergence Test
Convergence was tested by comparing the static temperature XY plot at two different interations
and by comparing the heat fluxes at the inlets and outlets.
Convergence test: Iteration 9541 compared to iteration 12000
Convergence can be seen in figure 1 which is a comparison of iteration 9541 and 12000. They
are nearly identical which suggest s that the analysis has converged since the solution no longer
changes with more iterations.
Convergence can also be determined by examining the flux reports in figure 2. The flux reports
shows that the net in is extremely close the net out. The standard acceptance for convergence is
.02% the results were actually 0.0000237% which suggests convergence.
Convergence Test: Convergence history of static temperature on the outlet
The last convergence test conducted was to observe the mass weighted average of the static
temperature at the outlet. Convergence can be seen between iterations 6000-10000. The stabilizing of
the graph show that the data has converged on a particular value.
Results: Contours
Figure 2: The highest pressure points can be seen above the flame and combustion area.
Results: Contours
Figure 3: The highest temperature points are located within the flame and combustion area.
2410K
Figure 4: magnification of the static temperature contours. The highest temperature achieved by the combustion process
was 2410(K⁰)
Figure 5: The highest velocities can be seen at the combustion area.
Figure 7: Magnification of the velocity vectors. The swirl in the flame can be seen by flow of the plot. The highest velocity
achieved by the combustion process was 45.9 m/s
Results: Comparison of experimental data and theoretical data
Model: k-epsilon (2 eqn) Solution Method: Second order upwind
Static Temperature: Second Order solution
Static Temperature: First Order solution
Static Temperature: Second Order solution
Static Temperature: First Order solution
Discussion and Conclusion
The combustion process of a swirling flame burner was analyzed by using the turbulence model
k-epsilon (2 equations) and a second order upwind solution method. The predictions shown in the
results compared very well to the theoretical data from the University of Sidney. In fact the swirl and
axial velocity profiles were fairly close showing very few outliers. However there was one exception, the
experimental static temperature profile, when compared to the theoretical data showed a peak
temperature that was a 1000 degrees higher. The possible causes for the temperature increase could
have been the simple reaction scheme. The combustion process for methane has many more reaction to
consider than the two reactions supplied.
One other possible cause could be the solution method used. The third order solution method could be
used instead of the second order which could produce better results. The last possible cause could have
been the absence of radiation in the model setup. One interesting finding was that the first order
solution for the static temperatures was closer to the theoretical data supplied from the University of
Sydney. The When analyzing combustion processes with fluent the solution method and model setup
are extremely important. Time and complexity of the problem should be considered when initializing a
problem.
References

Barlow, Rob, and Peter Kalt. "Aerospace, Mechanical and Mechatronic Engineering - The
University of Sydney." The University of Sydney. N.p., n.d. Web. 1 May 2012.
<http://sydney.edu.au/engineering/aeromech

Barlow, Rob. "Boundry Conditions." Aerospace, Mechanical and Mechatronic
Engineering 1 (2002): n. pag. The University Of Sydney. Web. 1 May 2012.

Barlow, Rob. “Flow field Measurements" Aerospace, Mechanical and Mechatronic
Engineering 1 (2002): n. pag. The University Of Sydney. Web. 1 May 2012.