umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Predicting fuel properties of biomass using thermogravimetry and multivariate data analysis
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
2017 (English)In: Fuel processing technology, ISSN 0378-3820, E-ISSN 1873-7188, Vol. 156, 107-112 p.Article in journal (Refereed) Published
Abstract [en]

Simple and reliable characterization methods for determining fuel properties of biomass are needed for several different applications. This paper describes and demonstrates such a method combining thermogravimetric analysis with multivariate data analysis, based on the thermal decomposition behavior of the fuel. Materials used for the tests were milled samples of wood chips thermally pretreated under different conditions in a torrefaction pilot plant. The predictions using the multivariate model were compared to those from a conventional curve deconvolution approach. The multivariate approach showed better and more flexible performance, with error of prediction of 2.7% for Mass Yield prediction, compared to the reference method that resulted in 29.4% error. This multivariate method could handle samples pretreated under more severe conditions compared to the curve deconvolution methods. Elemental composition, heating value and volatile content were also predicted with even higher accuracies. The results highlight the usefulness of the method and also the importance of using calibration data of good quality. (C) 2016 Elsevier B.V. All rights reserved.

Place, publisher, year, edition, pages
2017. Vol. 156, 107-112 p.
Keyword [en]
Thermogravimetric analysis, Multivariate data analysis, Fuel characterization, Fuel composition, Torrefaction
National Category
Bioenergy Chemical Engineering
Identifiers
URN: urn:nbn:se:umu:diva-130216DOI: 10.1016/j.fuproc.2016.10.021ISI: 000390078200014OAI: oai:DiVA.org:umu-130216DiVA: diva2:1070986
Available from: 2017-02-02 Created: 2017-01-14 Last updated: 2017-03-20Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Strandberg, AnnaHolmgren, PerBroström, Markus
By organisation
Department of Applied Physics and Electronics
In the same journal
Fuel processing technology
BioenergyChemical Engineering

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 70 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf