Journal
COMBUSTION AND FLAME
Volume 245, Issue -, Pages -Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.combustflame.2022.112303
Keywords
Soot; Carbon black; Population balance; Particle size distribution; Aggregation
Categories
Funding
- Australian Research Council (ARC) [LP160100512]
- Synergen Met Pty Ltd
- Australian Research Council [LP160100512] Funding Source: Australian Research Council
Ask authors/readers for more resources
A 2-D population balance model with internal variables of carbon mass and surface sites was developed to study soot formation during hydrocarbon decomposition reactions. The model accurately predicts the size and composition distribution of soot particles under various conditions, which was confirmed by experimental data.
A 2-D population balance model utilizing carbon mass and surface sites as internal variables was de-veloped for soot formation during hydrocarbon decomposition reactions. The model provides particle properties such as composition and mean polyaromatic hydrocarbon size, enabling the incorporation of cyclization reactions, soot maturation, and a dynamic model of surface reactions. Accompanied by a re-duced kinetic model for gas-phase species, this population balance model was then discretized using the fixed-pivot method, to provide predictions of the soot distribution as a function of position within a plug flow reactor. The model predictions of the particle size distribution functions resulting from high -temperature hydrocarbon pyrolysis within a PFTR system provide good comparison with experimental measurements under a variety of conditions. In addition to this, by tracking the changes in particle com-position occurring through cyclization reactions, the point of carbon particle maturity could be deter-mined, allowing subsequent predictions of the size distributions of the primary particles comprising soot aggregates. Through comparison with TEM and SEM imaging, these primary particle distributions were found to be accurate for the experimental conditions examined. While the implementation of the second internal variable describing particle composition was not found to provide substantial improvements to the prediction of the overall aggregate distribution from existing models, the additional computational cost that accompanies additional variables is justified in applications where morphological predictions of particle aggregates are of interest, in addition to their size distribution.(c) 2022 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available