Soot modeling in turbulent diffusion flames: review and prospects

dc.contributor.affiliationPontificia Universidad Católica del Perú. Sección de Ingeniería Mecánica
dc.contributor.authorValencia, S.
dc.contributor.authorRuiz, S.
dc.contributor.authorManrique, J.
dc.contributor.authorCelis, C.
dc.contributor.authorFigueira da Silva, L.F.
dc.date.accessioned2026-03-13T16:59:55Z
dc.date.issued2021
dc.description.abstractThis 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.
dc.description.sponsorshipFunding: This work has been supported by CONCYTEC-FONDECYT (Peru), Contract No. 415‐2019‐2019-FONDECYT, “Identificatión of soot precursors in turbulent combustión processes through numerical modeling to reduce the impact of soot on both health and environment.” During this work Luis Fernando Figueira da Silva was on leave from the Institut Pprime (CNRS—Centre National de la Recherche Scióntifique, France). The authors also gratefully acknowledge the support provided by Brazil's Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq, under the Research Grants No. 306069/2015-6 and 403904/2016-1.; Funding text 2: This work has been supported by CONCYTEC-FONDECYT (Peru), Contract No. 415-2019-2019-FONDECYT, Identificatión of soot precursors in turbulent combustión processes through numerical modeling to reduce the impact of soot on both health and environment.? During this work Luis Fernando Figueira da Silva was on leave from the Institut Pprime (CNRS?Centre National de la Recherche Scióntifique, France). The authors also gratefully acknowledge the support provided by Brazil's Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq, under the Research Grants No. 306069/2015-6 and 403904/2016-1.
dc.identifier.doihttps://doi.org/10.1007/s40430-021-02876-y
dc.identifier.urihttp://hdl.handle.net/20.500.14657/206479
dc.language.isoeng
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.relation.ispartofurn:issn:1678-5878
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.sourceJournal of the Brazilion Society of Mechanical Sciences and Engineering; Vol. 43, Núm. 4 (2021)
dc.subjectSoot modeling
dc.subjectTurbulent diffusion flames
dc.subjectPollutant formation
dc.subjectComputational fluid dynamics
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.01.02
dc.titleSoot modeling in turbulent diffusion flames: review and prospects
dc.typehttp://purl.org/coar/resource_type/c_dcae04bc
dc.type.otherArtículo de revisión
dc.type.versionhttps://vocabularies.coar-repositories.org/version_types/c_970fb48d4fbd8a85/

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