An aerosol model to predict size and structure of soot particles

An aerosol model to simulate soot formation and growth was developed using moving- and fixed-sectional methods. The new model is composed of a set of subroutines that can be easily combined with the Chemkin package. Using the model, we have simulated soot formation and growth in plug flow reactors.

Our model was compared with a previously published method of moments model for a simulation of the plasma pyrolysis of methane in a plug flow reactor. Inclusion of the transition correction factor for the condensation coefficient led to the prediction of a smaller condensation rate compared with the method of moments model. The average coagulation rate calculated by the sectional model was much higher than that by the method of moments model for a broad particle size distribution. The two models predicted significantly different soot precursor concentration and rates of aerosol processes, but substantially similar particle mass and number for the pyrolysis process.

We have also simulated soot formation and growth in a jet-stirred/plug flow reactor (JSR/PFR) system for which soot size distribution measurements are available in the literature. It is shown that the adjusted-point fixed-sectional method can provide comparable accuracy to the moving-sectional model in a simulation of soot formation and growth. It is also shown that the measured surface growth rate could be much higher than the value used in this study. Soot mass concentrations and size distributions for particles larger than 10 nm were well predicted with a surface reaction enhancement. The primary particle size was underpredicted by only about 30% compared with the measurements, without any model adjustments. As the new model can predict both the particle size distribution and structure, and is suitable for application in complex flows, its application to diverse soot formation conditions will enhance our knowledge on the evolution of soot structures.

Acknowledgements

This work was supported by the Auto21 Network of Centres of Excellence (SNR and WKB) and by the Brain Korea 21 program from the Ministry of Education through the Graduate Program for Chemical and Environmental Engineering at Gwangju Institute of Science and Technology (SHP).