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Higher heating value prediction of torrefaction char produced from non-woody biomass

Higher heating value prediction of torrefaction char produced from non-woody biomass Abstract The higher heating value of five types of nonwoody biomass and their torrefaction char was predicted and compared with the experimental data obtained in this paper. The correlation proposed in this paper and the ones suggested by previous researches were used for prediction. For prediction using proximate analysis data, the mass fraction of fixed carbon and volatile matter had a strong effect on the higher heating value prediction of torrefaction char of non-woody biomass. The high ash fraction found in torrefied char resulted in a decrease in prediction accuracy. However, the prediction could be improved by taking into account the effect of ash fraction. The correlation developed in this paper gave a better prediction than the ones suggested by previous researches, and had an absolute average error (AAE) of 2.74% and an absolute bias error (ABE) of 0.52%. For prediction using elemental analysis data, the mass fraction of carbon, hydrogen, and oxygen had a strong effect on the higher heating value, while no relationship between the higher heating value and mass fractions of nitrogen and sulfur was discovered. The best correlation gave an AAE of 2.28% and an ABE of 1.36%. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png "Frontiers in Energy" Springer Journals

Higher heating value prediction of torrefaction char produced from non-woody biomass

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References (24)

Publisher
Springer Journals
Copyright
2015 Higher Education Press and Springer-Verlag Berlin Heidelberg
ISSN
2095-1701
eISSN
2095-1698
DOI
10.1007/s11708-015-0377-3
Publisher site
See Article on Publisher Site

Abstract

Abstract The higher heating value of five types of nonwoody biomass and their torrefaction char was predicted and compared with the experimental data obtained in this paper. The correlation proposed in this paper and the ones suggested by previous researches were used for prediction. For prediction using proximate analysis data, the mass fraction of fixed carbon and volatile matter had a strong effect on the higher heating value prediction of torrefaction char of non-woody biomass. The high ash fraction found in torrefied char resulted in a decrease in prediction accuracy. However, the prediction could be improved by taking into account the effect of ash fraction. The correlation developed in this paper gave a better prediction than the ones suggested by previous researches, and had an absolute average error (AAE) of 2.74% and an absolute bias error (ABE) of 0.52%. For prediction using elemental analysis data, the mass fraction of carbon, hydrogen, and oxygen had a strong effect on the higher heating value, while no relationship between the higher heating value and mass fractions of nitrogen and sulfur was discovered. The best correlation gave an AAE of 2.28% and an ABE of 1.36%.

Journal

"Frontiers in Energy"Springer Journals

Published: Dec 1, 2015

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