Click on “Download PDF” for the PDF version or on the title for the HTML version.

If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options.

A Technical Review on Biomass Processing: Densification, Preprocessing, Modeling and Optimization

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2010 Pittsburgh, Pennsylvania, June 20 - June 23, 2010  1009401.(doi:10.13031/2013.29874)
Authors:   Jaya Shankar Tumuluru, Christopher T Wright, Kevin L Kenney, Richard J Hess
Keywords:   Biomass, densification, pelleting, briquetting, extrusion process, densification process variables, modeling, optimization.

Biomass from plants can serve as an alternative renewable and carbon-neutral raw material for the production of bioenergy. Low densities of 4060 kg/m3 for lignocellulosic and 200400 kg/m3 for woody biomass limits their application for energy purposes. Prior to use in energy applications these materials need to be densified. The densified biomass can have bulk densities over 10 times the raw material helping to significantly reduce technical limitations associated with storage, handling and transportation. Pelleting, briquetting, and other extrusion processes are commonly used methods for densification. The aim of the present research is to develop a comprehensive review of biomass processes including densification, preprocessing, modeling and optimization. Specific objectives include performing a technical review on (a) mechanisms of particle bonding during densification; (b) methods of densification including extrusion, briquetting, pelleting, and agglomeration; (c) effects of process and feedstock variables on biomass chemical composition and densification (d) effects of preprocessing (e.g., grinding, preheating, steam explosion, and torrefaction) on biomass quality and binding characteristics; (e) models for understanding compression characteristics; and (f) procedures for response surface modeling and optimization.

(Download PDF)    (Export to EndNotes)