Journal article
Prediction of higher heating values of biomass from proximate and ultimate analyses
Fuel, Vol.90(3), pp.1128-1132
2011
Abstract
Two new empirical correlations based on proximate and ultimate analyses of biomass used for prediction of higher heating value (HHV) are presented in this paper. The correlations have been developed via step-wise linear regression method by using data of biomass samples (from the open literature) of varied origin and obtained from different geographical locations. The correlations have been validated via incorporation of additional biomass data. The correlation based on ultimate analysis (HHV = 0.2949C + 0.8250H) has a mean absolute error (MAE) lower than 5% and marginal mean bias error (MBE) at just 0.57% which indicate that it has good HHV predictive capability. The other correlation which is based on proximate analysis (HHV = 0.1905VM + 0.2521FC) is a useful companion correlation with low absolute MBE (0.67%). The HHV prediction accuracies of 12 other correlations introduced by other researchers are also compared in this study.
Details
- Title
- Prediction of higher heating values of biomass from proximate and ultimate analyses
- Authors/Creators
- C-Y Yin (Author/Creator) - Murdoch University
- Publication Details
- Fuel, Vol.90(3), pp.1128-1132
- Publisher
- Elsevier BV
- Identifiers
- 991005544978507891
- Copyright
- 2011 Elsevier Ltd.
- Murdoch Affiliation
- School of Chemical and Mathematical Science
- Language
- English
- Resource Type
- Journal article
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites
Metrics
3693 File views/ downloads
280 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Citation topics
- 7 Engineering & Materials Science
- 7.139 Energy & Fuels
- 7.139.89 Gasification
- Web Of Science research areas
- Energy & Fuels
- Engineering, Chemical
- ESI research areas
- Engineering