Articles | Volume 4, issue 2
https://doi.org/10.5194/ar-4-279-2026
https://doi.org/10.5194/ar-4-279-2026
Research article
 | 
06 Jul 2026
Research article |  | 06 Jul 2026

Soot growth by monodisperse particle dynamics coupled with computational fluid dynamics

Arash Fakharnezhad, Joseph D. Berry, and Eirini Goudeli

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Cited articles

Appel, J., Bockhorn, H., and Frenklach, M.: Kinetic modeling of soot formation with detailed chemistry and physics: laminar premixed flames of C2 hydrocarbons, Combust. Flame, 121, 122–136, https://doi.org/10.1016/S0010-2180(99)00135-2, 2000. 
arashfakharnezhad: arashfakharnezhad/soot-udf-fluent: soot-udf-fluent (soot-udf-fluent), Zenodo [code], https://doi.org/10.5281/zenodo.21102904, 2026. 
Batchelor, G. K.: An introduction to fluid dynamics, Cambridge university press, https://doi.org/10.1017/CBO9780511800955, 2000. 
Brookes, S. J. and Moss, J. B.: Predictions of soot and thermal radiation properties in confined turbulent jet diffusion flames, Combust. Flame, 116, 486–503, https://doi.org/10.1016/S0010-2180(98)00056-X, 1999. 
Buesser, B., Grohn, A. J., and Pratsinis, S. E.: Sintering Rate and Mechanism of TiO(2) Nanoparticles by Molecular Dynamics, J. Phys. Chem. C Nanomater Interfaces, 115, 11030–11035, https://doi.org/10.1021/jp2032302, 2011. 
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Short summary
A computationally efficient monodisperse particle dynamics–computational fluid dynamics simulation is developed to predict soot particle growth in flames without use of reaction kinetic models. The proposed model is in good agreement with soot volume fraction and mobility size measurements, demonstrating a level of accuracy comparable to that of sectional models. This model can be readily used for design applications of engines and industrial burners.
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