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dc.contributor.authorLu, Zhen
dc.contributor.authorRen, Zhuyin
dc.contributor.authorIm, Hong G.
dc.date.accessioned2021-04-20T10:01:25Z
dc.date.available2021-04-20T10:01:25Z
dc.date.issued2017-01-01
dc.identifier.urihttp://hdl.handle.net/10754/668869
dc.description.abstractTo separate the nonpremixed and premixed modes in partially premixed flame simulations with the transported PDF method, a flame index is proposed based on the subgrid mixing rate between Lagrangian particles. The mixing rate on local equivalence ratio and progress variable is compared to measure the combustion mode. With a renormalized progress variable, the proposed flame index is 0 for equilibrium solution of the nonpremixed flame, and 1 for the premixed flame with homogeneous cold flow. The index is validated on a series of constructed turbulent combustion subgrid particles and the partially stirred reactors with different mixing models. Tests demonstrate that the flame index for PDF method works well for nonpremixed flames with variant scalar dissipation rate. Furthermore, the index shows a consistent trend at different parameters. Results also confirms that the localness of the EMST model make it predict the physical process well.
dc.description.sponsorshipThis research work was sponsored by King Abdul-lah University of Science and Technology (KAUST). The simulations utilized the computing resources at KAUST Supercomputing Laboratory.
dc.publisherCombustion Institute
dc.relation.urlhttps://www.scopus.com/record/display.uri?eid=2-s2.0-85046546587&origin=inward&txGid=3e3efa1550eb613e5ae14ebcf5b90ef7
dc.rightsArchived with thanks to Combustion Institute
dc.titleA flame index for the lagrangian probability density function method
dc.typeConference Paper
dc.contributor.departmentClean Combustion Research Center
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.contributor.departmentMechanical Engineering Program
dc.conference.date2017-12-10 to 2017-12-14
dc.conference.name11th Asia-Pacific Conference on Combustion, ASPACC 2017
dc.conference.locationSydney, NSW, AUS
dc.eprint.versionPost-print
dc.contributor.institutionSchool of Aerospace Engineering, Tsinghua University, Beijing, 100084, China
dc.identifier.volume2017-December
kaust.personLu, Zhen
kaust.personIm, Hong G.
dc.identifier.eid2-s2.0-85046546587
kaust.acknowledged.supportUnitKAUST Supercomputing Laboratory
kaust.acknowledged.supportUnitSupercomputing Laboratory.


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