Ezekiel Egbert ChandraProf. Evatt Hawkes, Dr. Armin Wehrfritz, Dr. Bruno Savard, Zisan Li

Fluid Dynamics and Thermal Engineering

Background

Aims

Our society is highly dependent on finite energy such as fossil fuels and the consumption

trend is expected to grow over the upcoming decades due to rapid development.

Fossil fuel combustion produces emissions that cause detrimental effects on the

environment and the regulations for this matter progressively becoming more prominent

and stern.

Simulation using the DNS method consumes a substantial amount of resources primarily

the cost to run due to its nature that require substantial energy and computational power.

A thorough evaluation of the mixing models needs to be performed and temporal evolution of

the combustion should be investigated to understand the underlying concept of compression

ignition engine process. The mixing models that will be simulated are Interaction by

Exchange (IEM), Modified Curl (MC) and Euclidean Minimum Spanning Tree (EMST).

The validation will involve characterization and comparison of different profiles at different

time step for each mixing model in reference to the DNS using a cost-effective method. This

investigation will improve our understanding of the process and enables our research to

improve the efficiency of a combustion engine with minimum cost and time

One-dimensional Spatial Profile Progression Figures above show the flame key profiles progression as indicated by the colormaps. IEM

and EMST over-predicted opposite to MC at predicting the tempertur, but the ignition time

was predicted at earlier time by MC and EMST.

The YI was only predicted accurately by the EMST at the early stage of ignition while the rest

failed to reach similarities. The temperature was reflected by the formation of YX which

contributes significantly to the increasing temperature because of the high energy dissipation

and as such, the similar trends were observed.

Conclusions The models shows great potential and capabilities of producing a notable prediction of the flame using the T-

PDF method in a shorter time and less computational resources.

The flame propagation was predicted accurately in the early combustion stage, albeit this was reduced to a

different level for each model as the combustion develops to higher temperature region. The errors can be

attributed to mixing frequency, turbulent diffusivity and core of the model. The statistical noise in the graph can

be reduced with more particles to increase accuracy in the expense of computation power.

The research can be improved by proposing a better method of modelling the mixing models between the

fuels and the oxidiser and improving the mixing frequency and turbulent diffusivity.

MethodologyThe T-PDF method uses an ensemble of stochastic notional particles that is

distributed evenly in a finite difference grid as seen on the right. these

particles when used in great numbers represent the flow properties itself at

this particular location and time and solved using the join T-PDF equation

which requires less computation power compared to the DNS method. Each

of these particles are solved by advancing their properties using numerical

methods. The cases that were simulated uses the configuration illustrated in

were the figure below. The fuel (heptane) and the oxidiser were separated and

allowed to mixed in a diffusive manner resembling the actual condition in a

compression ignition engine.

Mean and RMS Spatial Profiles The temporal timestep of mean and RMS profiles were compared in the figures below to

quantify the performance. The mixing models were observed to reach a reasonable

agreement for the temperature at the early timestep when the flow field was less turbulent.

On the contrary, the YI formation was predicted under-predicted at mixed accuracy by different

models. The models failed to predict the rms and temperature profiles at 17 and 27tj and the

ignition times. However, all current models managed to predict the profile better at 37tj but it

was notable that EMST managed to predict the ignition time better than the other models.

Results and Discussions

AcknowledgementsI would extend my gratitude towards the name I have mentioned above especially

Prof. Evatt Hawkes for the guidance and resources provided and at utmost, thechance for me to see the bigger picture of the my research for the industry.

References A. Krisman, E. Hawkes and J. Chen, "Two-stage autoignition and edge flames in a

high pressure turbulent jet", Journal of Fluid Mechanics, vol. 824, pp. 5-41, 2017.

A. Krisman, "Direct numerical simulation of diesel-relevant combustion", Doctor of

Philosophy, UNSW, 2016.

The combustion of heptane occurs in a two-stage process.

The I and X corresponds to low and high intermediate

species. The low temperature chemistry (LTC) develops a

rich mixture fraction region to improve the fuel distribution

pre-ignition.

The high temperature chemistry then

occurs at the later stage, fuel-rich

mixture allowing the gas to exert the

stored energy for power generation.