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Turbulence Modeling Insights into Supercritical Nitrogen Mixing Layers

2020-04-01Journal article Open access
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dc.contributor.authorMagalhães, Leandro
dc.contributor.authorCarvalho, Francisco
dc.contributor.authorSilva, A. R. R.
dc.contributor.authorBarata, Jorge M M
dc.date.accessioned2020-04-07T08:40:41Z
dc.date.available2020-04-07T08:40:41Z
dc.date.issued2020-04-01
dc.description.abstractIn Liquid Rocket Engines, higher combustion efficiencies come at the cost of the propellants exceeding their critical point conditions and entering the supercritical domain. The term fluid is used because, under these conditions, there is no longer a clear distinction between a liquid and a gas phase. The non-conventional behavior of thermophysical properties makes the modeling of supercritical fluid flows a most challenging task. In the present work, a Reynolds Averaged Navier Stokes (RANS) computational method following an incompressible but variable density approach is devised on which the performance of several turbulence models is compared in conjunction with a high accuracy multi-parameter equation of state. In addition, a suitable methodology to describe transport properties accounting for dense fluid corrections is applied. The results are validated against experimental data, making it clear that there is no trend between turbulence model complexity and the quality of the produced results. For several instances, one- and two-equation turbulence models produce similar results. Finally, considerations about the applicability of the tested turbulence models in supercritical simulations are given based on the results and the structural nature of each model.pt_PT
dc.description.sponsorshipAeronautics and Astronautics Research Center (AEROG), Laboratório Associado em Energia, Transportes e Aeronáutica (LAETA) e Fundação para a Ciência e Tecnologia (FCT)pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationMagalhães, L.; Carvalho, F.; Silva, A.; Barata, J. Turbulence Modeling Insights into Supercritical Nitrogen Mixing Layers. Energies 2020, 13, 1586.pt_PT
dc.identifier.doi10.3390/en13071586pt_PT
dc.identifier.issn1996-1073
dc.identifier.urihttp://hdl.handle.net/10400.6/10256
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationalterado para: “Contribution to the Physical Understanding of Supercritical Fluid Flows: a Computational Perspective”. Computational methods for jet/spray characterization: transcritical and supercritical conditions
dc.relationAssociate Laboratory of Energy, Transports and Aeronautics
dc.relationAssociate Laboratory of Energy, Transports and Aeronautics
dc.relation.publisherversionhttps://www.mdpi.com/1996-1073/13/7/1586pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectTurbulence modelingpt_PT
dc.subjectSupercritical injectionpt_PT
dc.subjectLiquid Rocket Enginespt_PT
dc.titleTurbulence Modeling Insights into Supercritical Nitrogen Mixing Layerspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitlealterado para: “Contribution to the Physical Understanding of Supercritical Fluid Flows: a Computational Perspective”. Computational methods for jet/spray characterization: transcritical and supercritical conditions
oaire.awardTitleAssociate Laboratory of Energy, Transports and Aeronautics
oaire.awardTitleAssociate Laboratory of Energy, Transports and Aeronautics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBD%2F136381%2F2018/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FEMS%2F50022%2F2019/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50022%2F2020/PT
oaire.citation.issue7pt_PT
oaire.citation.startPage1586pt_PT
oaire.citation.titleEnergiespt_PT
oaire.citation.volume13pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameMagalhães
person.familyNameCarvalho
person.familyNameResende Rodrigues da Silva
person.familyNameMartins Barata
person.givenNameLeandro
person.givenNameFrancisco
person.givenNameAndré
person.givenNameJorge Manuel
person.identifier2611303
person.identifierJ-4185-2012
person.identifierhFY_5JYAAAAJ&hl
person.identifier.ciencia-id571C-5641-9D78
person.identifier.ciencia-id8219-4B2B-E1C7
person.identifier.ciencia-idF611-BBCC-DAA8
person.identifier.orcid0000-0002-1256-9689
person.identifier.orcid0000-0002-3069-8345
person.identifier.orcid0000-0002-4901-7140
person.identifier.orcid0000-0001-9014-5008
person.identifier.scopus-author-id11440407500
person.identifier.scopus-author-id11439470600
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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