Simulation of Soot Formation in Turbulent Diffusion Flames Using Conditional Source-term Estimation
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Conditional Source-term Estimation (CSE) is a turbulent combustion model which uses the conditional averages of scalars for calculating the mean reaction source term in the species transport equation. CSE has been shown to be a very efficient and accurate method for simulating turbulent flames without being limited to certain conditions and regimes. In this study, for the first time, CSE is used for the simulation of soot formation in turbulent diffusion flames. The objective of the present research is to develop a CSE code for simulating soot formation in turbulent diffusion flames. The modeling of soot formation is investigated for two turbulent flames, at atmospheric and 3 atm pressure conditions. A semi-empirical soot formulation that accounts for soot inception, coagulation, surface growth, and oxidation processes is coupled with the CSE turbulent combustion model using Reynolds Averaged Navier Stokes equations. Detailed chemistry is included and an optically thin radiation model is considered. Good agreement with the experiments is found for turbulent mixing and temperature fields in both flames, with some discrepancies believed to be due to the turbulence model. The predicted soot volume fraction values match the experimental data well at 1 atm with some under prediction in the range of experimental uncertainty. At higher pressure, the predicted level of soot increases, as expected. At 3 atm, underpredictions can be noticed in the predicted soot volume fraction. In the current work, the CSE framework is extended to include the effect of radiation in the chemistry tables and to have better predictions for species mass fractions and reaction rates. This is applied to the turbulent methane-air flame at 3 atm pressure and significant improvements are observed for the temperature and soot predictions. A detailed soot model that takes into account the soot aerosol dynamics, the Quadrature based Method of Moments (QMOM) is added to the CSE code as an advanced model after promising results were observed from the semi-empirical soot model. The CSE-QMOM method is applied to an ethylene turbulent flame. The results show very good predictions of soot volume fraction. Finally, a Poly cyclic Aromatic Hydrocarbon (PAH) based model is implemented into the CSE-soot framework. PAH based inception models are known to provide more accurate predictions compared to the conventional acetylene based models. The CSE-soot model is capable of providing good predictions for soot volume fraction. Possible sources of discrepancies and limitations of the model are discussed and future improvements are explained.
Cite this version of the work
Seyed Mehdi Ashrafizadeh (2022). Simulation of Soot Formation in Turbulent Diffusion Flames Using Conditional Source-term Estimation. UWSpace. http://hdl.handle.net/10012/18298