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dc.contributor.authorJakobsen, Krister
dc.contributor.authorJaiswal, Rajan
dc.contributor.authorFuruvik, Nora Cecilie Ivarsdatter
dc.contributor.authorMoldestad, Britt Margrethe Emilie
dc.date.accessioned2021-07-26T10:59:49Z
dc.date.available2021-07-26T10:59:49Z
dc.date.created2020-10-01T07:14:00Z
dc.date.issued2020
dc.identifier.citationJakobsen, K., Jaiswal, R., Furuvik, N. C. I. S., & Moldestad, B. M. E. (2020). Computational modeling of fluidized bed behavior with agglomerates. In Proceedings of The 61st SIMS Conference on Simulation and Modelling SIMS 2020 - Linköping Electronic Conference Proceedings, 176(60).en_US
dc.identifier.issn1650-3686
dc.identifier.urihttps://hdl.handle.net/11250/2765263
dc.description.abstractFluidized bed reactors can be used for biomass gasification. The product from biomass gasification is syngas, which can be used for production of bio oil. The main challenge when using fluidized bed for gasification is ash melting and agglomeration of the bed material. Agglomeration of the bed material influences on the flow behavior in the fluidized bed reactor and thus affects the gasification efficiency. A Computational Particle Fluid Dynamic (CPFD) model is developed to predict the flow behavior in a fluidized bed gasifier. The CPFD model was validated against experimental data from a cold fluidized bed. The model was then tested against the results from a biomass gasifier, and a few modifications were needed. Glickman’s scaling parameters were used to scale up from a lab-scale to a full-scale gasifier. Simulations using the modified model were performed to study the flow behavior in a full-scale gasifier with agglomerates. It was found that the CPFD model is capable of predicting the effect of agglomerates on flow behavior in a fluidized bed gasifier.en_US
dc.language.isoengen_US
dc.rightsNavngivelse-Ikkekommersiell 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/deed.no*
dc.titleComputational modeling of fluidized bed behavior with agglomeratesen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.rights.holder© The Author(s) 2020.en_US
dc.source.volume176en_US
dc.source.journalLinköping Electronic Conference Proceedingsen_US
dc.source.issue60en_US
dc.identifier.doihttps://doi.org/10.3384/ecp20176421
dc.identifier.cristin1835953
dc.relation.projectNorges forskningsråd: 280892en_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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Navngivelse-Ikkekommersiell 4.0 Internasjonal
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