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dc.contributor.authorSimões Nunes, Ângelo Dinis
dc.contributor.authorSierra-Pallaras, José
dc.contributor.authorTran, Quang Khanh
dc.contributor.authorHearst, Robert Jason
dc.date.accessioned2022-11-08T09:33:55Z
dc.date.available2022-11-08T09:33:55Z
dc.date.created2022-08-04T12:05:05Z
dc.date.issued2022
dc.identifier.issn0009-2509
dc.identifier.urihttps://hdl.handle.net/11250/3030581
dc.description.abstractA thermophysical model is developed that can predict the properties of two lignin mixtures, black liquor and lignosulfonates, up to 50% mass fractions, at hydrothermal conditions. An uncertainty quantification framework linked with classic thermodynamical modelling was included to account for the extreme variability of the raw material. An idealised flow simulation verified the model, where hot compressed water mixes with a cold, aqueous lignin stream in a T-piece reactor configuration. The uncertainty quantification procedure determined that density and heat capacity uncertainty significantly influence residence time, and viscosity uncertainty mainly affects mixing. Micromixing time is fivefold and ten-fold higher for black liquor and lignosulfonates mixtures, respectively, compared to pure water mixing. The uncertainty in all simulated quantities of interest caused by the thermophysical model is reduced by increasing flow rates. This study predicted chemical reactor behaviour under varying thermophysical conditions and their final effect in terms of confidence intervals.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleDevelopment of an aqueous lignin mixture thermophysical model for hydrothermal liquefaction applications using uncertainty quantification toolsen_US
dc.title.alternativeDevelopment of an aqueous lignin mixture thermophysical model for hydrothermal liquefaction applications using uncertainty quantification toolsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.volume261en_US
dc.source.journalChemical Engineering Science (CES)en_US
dc.identifier.doi10.1016/j.ces.2022.117944
dc.identifier.cristin2041140
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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