Combustion and Flame, Vol.156, No.4, 896-913, 2009
A statistical approach to develop a detailed soot growth model using PAH characteristics
A detailed PAH growth model is developed, which is solved using a kinetic Monte Carlo algorithm. The model describes the structure and growth of planar PAH molecules, and is referred to as the kinetic Monte Carlo-aromatic site (KMC-ARS) model. A detailed PAH growth mechanism based on reactions at radical sites available in the literature, and additional reactions obtained from quantum chemistry Calculations are used to model the PAH growth processes. New rates for the reactions involved in the cyclodehydrogenation process for the formation of 6-member rings on PAHs are Calculated in this work based on density functional theory simulations. The KMC-ARS model is validated by comparing experimentally observed ensembles on PAHs with the Computed ensembles for a C2H2 and a C6H6 flame at different heights above the burner. The motivation for this model is the development of a detailed soot particle Population balance model which describes the evolution of an ensemble of soot particles based on their PAH Structure. However, at Present incorporating such a detailed model into a population balance is computationally unfeasible. Therefore, a simpler model referred to as file site-counting model has been developed, which replaces the Structural information of the PAH molecules by their functional groups augmented with statistical closure expressions. This Closure is obtained from the KMC-ARS model, which is used to develop correlations and statistics in different flame environments which describe such PAH structural information. These Correlations and statistics are implemented in the site-counting model, and results from the site-counting model and the KMC-ARS model are in good agreement. Additionally the effect of steric hindrance in large PAH structures is investigated and Correlations for sites unavailable for reaction are presented. (c) 2009 The Combustion Institute. Published by Elsevier Inc. All rights reserved.