Understanding Soot Particle Growth Chemistry and Particle Sizing Using a Novel Soot Growth and Formation Model

Research efforts are focused on advancing soot modeling in laminar flames using a detailed sectional aerosol dynamic model, toward an end goal of developing a robust model applicable to a wide range of conditions.;The effects of the soot coalescence process on soot particle diameter predictions are studied. Two coalescence models based on different merging mechanisms are implemented into the soot model. The models are applied to a laminar ethylene/air diffusion flame, and comparisons are made with experimental data to validate the models. The implementation of coalescence models significantly improves the agreement of prediction of particle diameters with the experimental data.;A comprehensive study follows in which a function for surface reactivity of soot particles is developed to have a single model able to predict soot in many coflow ethylene/air flames. This study investigates how the surface reactivity of soot particles varies with particle thermal age. The surface reactivity function is applied to coflow diffusion flames with varying fuel/air ratios and fuel dilution, and to partially premixed coflow flames for a range of equivalence ratios. Comparisons are made with experimental data to validate the model. Good agreement is seen between numerical predictions and experimental measurements for soot volume fraction on the annular regions of the flames.;The final part of this thesis explores the role of PAH-soot modeling on burner stabilized stagnation premixed flames and a coflow diffusion flame. Two chemical mechanisms are employed to model both flames. It is found that one of the mechanisms gives more accurate description of the PAH chemistry in premixed flames while the other improves the agreement of soot predictions in diffusion flames and the results and conclusion are drastically effected by the choice of PAH mechanism. An equilibrium based condensation efficiency model is developed and combined with a reversible nucleation model to predict soot formation in both premixed and nonpremixed flames. Compared to the measured data, soot PSDs are reasonably well predicted. Effects of different soot formation processes on PSD predictions are characterized. In the diffusion flame, employing a reversible nucleation model leads to a shift in onset of soot formation.