Title
Soot modeling in turbulent diffusion flames: review and prospects
Date Issued
01 April 2021
Access level
open access
Resource Type
editorial
Author(s)
Publisher(s)
Springer Science and Business Media Deutschland GmbH
Abstract
This work reviews the state of the art of the main soot modeling approaches used in turbulent diffusion flames. Accordingly, after a short introduction about the subject addressed here, the main soot formation mechanisms are described next. This description provides the basis for the discussions about the different soot modeling techniques employed nowadays for soot predictions. Since combustion and radiation models have a significant impact on soot predictions, as a consequence of the strong coupling between chemistry, turbulence and soot formation, a general overview about these models is also provided. For the sake of clarity, the main soot formation models reviewed in this work are classified as semiempirical soot precursor models and detailed ones. Both advantages and disadvantages of the referred soot modeling approaches are properly discussed. In the last part of this review, comparative results obtained using some of the main soot models currently available are presented along with a discussion about the prospects for soot modeling in turbulent flames. Finally, some conclusions and references are provided. Overall, based on the literature reviewed, it is concluded that there is yet a long path to be followed before understanding first and having then a soot model able to properly describe the formation of this critical pollutant for a variety of situations of industrial interest.
Volume
43
Issue
4
Language
English
OCDE Knowledge area
Ingeniería mecánica
Subjects
Scopus EID
2-s2.0-85103566863
Source
Journal of the Brazilian Society of Mechanical Sciences and Engineering
ISSN of the container
16785878
Sponsor(s)
This work has been supported by CONCYTEC-FONDECYT (Peru), Contract No. 415‐2019‐2019-FONDECYT, “Identification of soot precursors in turbulent combustion processes through numerical modeling to reduce the impact of soot on both health and environment.” During this work Luís Fernando Figueira da Silva was on leave from the Institut Pprime (CNRS—Centre National de la Recherche Scientifique, France). The authors also gratefully acknowledge the support provided by Brazil's Conselho Nacional de Desenvolvimento Cientifico e Tecnologico, CNPq, under the Research Grants No. 306069/2015-6 and 403904/2016-1.
Sources of information:
Directorio de Producción Científica
Scopus