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Defluidisation of fluidised beds during gasification of biomass
KTH, School of Chemical Science and Engineering (CHE), Chemical Engineering and Technology, Chemical Technology.
KTH, School of Chemical Science and Engineering (CHE), Chemical Engineering and Technology, Chemical Technology.
KTH, School of Chemical Science and Engineering (CHE), Chemical Engineering and Technology, Chemical Technology.ORCID iD: 0000-0002-6326-4084
KTH, School of Chemical Science and Engineering (CHE), Chemical Engineering and Technology, Chemical Technology.ORCID iD: 0000-0002-2460-914X
2011 (English)In: Biomass and Bioenergy, ISSN 0961-9534, E-ISSN 1873-2909, Vol. 35, no SUPPL. 1, S63-S70 p.Article in journal (Refereed) Published
Abstract [en]

Defluidisation and agglomeration during fluidised bed gasification of biomass is analysed and discussed. It is argued that the agglomeration and defluidisation processes, in principle, closely resemble those that determine the behaviour of glass during glass processing. Crucial properties for working with glass melts are the viscosity, stickiness, surface tension, etc. It is, however, (very) difficult to theoretically quantify these properties through thermodynamics or other theoretical means. Hence it will be problematic to theoretically predict agglomeration and defluidisation. Models for predicting defluidisation must therefore probably be of an empirical nature. As a consequence of this, a number of fluidised bed gasification tests were empirically analysed with respect to defluidisation. In total 145 tests were evaluated; of these 51 defluidised or exhibited some kind of bed disturbance. A number of fuels and bed materials were included in the analysis using a multivariate statistical approach.Based on the analysis an empirical regression equation for predicting the defluidisation temperature during fluidised bed gasification is suggested.

Place, publisher, year, edition, pages
2011. Vol. 35, no SUPPL. 1, S63-S70 p.
Keyword [en]
Biomass, Defluidisation, Fluidised bed gasification, Multivariate analysis, Prediction
National Category
Energy Systems Chemical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-48152DOI: 10.1016/j.biombioe.2011.05.006ISI: 000297610300008Scopus ID: 2-s2.0-80054839207OAI: oai:DiVA.org:kth-48152DiVA: diva2:456884
Funder
EU, European Research Council, SES6-CT-2004-502587
Note
QC 20111116Available from: 2011-11-16 Created: 2011-11-16 Last updated: 2017-12-08Bibliographically approved

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Engvall, KlasRosén, Christer

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