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Author: Joshua Tang Supervisor: A/Professor Evatt Hawkes

Research Theme: Fundamental and Enabling research

Non Premixed Combustion: Modelling Gas

Turbine Flames using TPDF methods

Research Theme: Fundamental and Enabling research

Motivation and Background

Non premixed combustion occurs in devices like gasturbines for power generation and aviation. These flamesexperience extinction if local mixing rates exceedcombustion rates. Aviation devices demand smallercombustors which can increase mixing rates creating extinctregions. Power generation applications require lower

Pre-processing involved extracting and smoothing of velocity data from the DNS using Matlab. TheComposition-TPDF (C-TPDF) method requires velocity flow field information, a 2 equation model such as the k –ε model can be used, however, to reduce modelling errors DNS data was used for the simulation.

Simulation Methodology:

regions. Power generation applications require lowertemperatures to reduce production of NOx, this results inlower combustion rates which can also lead to extinction.

.

The simulation was run using a Fortran 90 code whichsimulated the mixing and chemistry of the flame usingthe C-TPDF method and one of 3 mixing models, IEM,MC or EMST. The chemistry simulation method wasidentical to the DNS.

Output from this program was processed using aspecifically designed Matlab script. Results for eachmodel were compared against the DNS

In both devices extinction isa problem that can result inflame instability andincreased pollutantformation. Extinguishedregions can re-ignite, whichcan help to mitigate these model were compared against the DNS

Results:

Transported Probability Density Function (TPDF) methods

can help to mitigate theseeffects. Modelling flameextinction and re-ignition isdifficult due the randomnature of turbulence andthe complex interactionbetween the fluid flow and

the underlying chemistry

Figure 1: Visualisation of non

premixed flames. Note the

random nature of flame

structures*

Aim and Objectives

• To develop computationally efficient methods to Figure 3: Temperature (Kelvin) colour maps

for DNS and model simulations.

Transported Probability Density Function (TPDF) methodsoffer compelling advantages, in particular, they treat thechemical reaction of the flow without approximation.However, a mixing model is needed to account for the effectof molecular diffusion. The effectiveness of TPDF methodsrelies heavily on the performance of the mixing model.

Methodology:Simulation Scenario:

simulate turbulent combustion

• To assess the performance of Interaction with themean (IEM), Modified Curl (MC) and EuclideanMinimum Spanning Tree (EMST) mixing models foruse in TPDF methods.

for DNS and model simulations.

Figure 3 shows that the models can qualitatively predictthe extinction and re-ignition events as there is littlevariance between the DNS and the model maps. A morequantitative measure of performance is given in Figure 3,the spatial temperature and mixture fraction distributions

The simulation is based on a Direct numerical simulation(DNS) run by Hawkes, modelling a diffusion flame atReynolds number (Re) = 2510, using Syn-gas (CO and H2)as fuel. Figure 2 shows simulation configuration, there isone planar slab of fuel in counter flow with 2 slabs of oxidanton either side. Data from this simulation was provided as avalidation data set.

Figure 4: Temperature (left) and mixture fraction

Conclusions:

From Figure 4 it can be seen that all models underpredict the peak temperature at the jet core (Y=0), withgood agreement elsewhere in the simulation. Themixture fraction is over predicted at the jet core howevershows almost perfect agreement in other regions for allmodels.

Figure 4: Temperature (left) and mixture fraction

(right) distributions at the final time-step

Conclusions:

The mixing models are all capable of qualitativelypredicting the extinction and re-ignition as well asquantitatively predicting the spatial temperature andmixture fraction distributions for the given test case.

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Figure 2: Simulation configuration.**

•J. Jarosinski and B. Veyssiere. Combustion Phenomena: selected mechanisms of flame

formation, propagation, and extinction. Taylor and Francis Group, 1st edition, 2009.** D. Lignell, J. Chen, H . Schmultz (2010). Effects of Damköhler number on flame extinction and reignition in turbulent non-premixed flames using DNS. Combustion and Flame, Vol.

158, pp 949 – 963.