Journal
BIORESOURCE TECHNOLOGY
Volume 187, Issue -, Pages 263-274Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.biortech.2015.03.054
Keywords
Hydrochar; Process conditions; Feedstock properties; Linear regression; Regression tree
Funding
- National Science Foundation [1055327]
- Directorate For Engineering
- Div Of Chem, Bioeng, Env, & Transp Sys [1055327] Funding Source: National Science Foundation
Ask authors/readers for more resources
The purpose of this study is to develop regression models that describe the role of process conditions and feedstock chemical properties on carbonization product characteristics. Experimental data were collected and compiled from literature-reported carbonization studies and subsequently analyzed using two statistical approaches: multiple linear regression and regression trees. Results from these analyses indicate that both the multiple linear regression and regression tree models fit the product characteristics data well. The regression tree models provide valuable insight into parameter relationships. Relative weight analyses indicate that process conditions are more influential to the solid yields and liquid and gas-phase carbon contents, while feedstock properties are more influential on the hydrochar carbon content, energy content, and the normalized carbon content of the solid. (C) 2015 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available