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dc.contributor.authorNajm, Habib
dc.contributor.authorGalassi, R. Malpica
dc.contributor.authorValorani, M.
dc.date.accessioned2017-06-08T06:32:29Z
dc.date.available2017-06-08T06:32:29Z
dc.date.issued2016-01-05
dc.identifier.urihttp://hdl.handle.net/10754/624841
dc.description.abstractWe outline a strategy for chemical kinetic model reduction under uncertainty. We present highlights of our existing deterministic model reduction strategy, and describe the extension of the formulation to include parametric uncertainty in the detailed mechanism. We discuss the utility of this construction, as applied to hydrocarbon fuel-air kinetics, and the associated use of uncertainty-aware measures of error between predictions from detailed and simplified models.
dc.relation.urlhttp://mediasite.kaust.edu.sa/Mediasite/Play/cf64569c53d5426d8a37d2f4b9f054331d?catalog=ca65101c-a4eb-4057-9444-45f799bd9c52
dc.titleChemical model reduction under uncertainty
dc.typePresentation
dc.conference.dateJanuary 5-10, 2016
dc.conference.nameAdvances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2016)
dc.conference.locationKAUST
dc.contributor.institutionSandia National Laboratories California
refterms.dateFOA2018-06-13T14:49:34Z


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