Analysis of standard sieving method for milled biomass through image processing. Effects of particle shape and size for poplar and corn stover

Published Date
Fuel
15 January 2014, Vol.116:328–340, doi:10.1016/j.fuel.2013.08.011

Author 

Miguel Gil ^a,,

Enrique Teruel ^b,

Inmaculada Arauzo ^a,

• aCentre of Research for Energy Resources and Consumptions, University of Zaragoza, Mariano Esquillor 15, E-50018 Zaragoza, Spain
• bDep. Informática e Ingeniería de Sistemas, University of Zaragoza, María de Luna, E-50018 Zaragoza, Spain

Received 8 October 2012. Revised 2 August 2013. Accepted 5 August 2013. Available online 22 August 2013. 

Highlights

• •
  Biomass particle size and shape assessment by computer processed images.
• •
  Agglomeration by adhesion of finer particles on larger is evaluated on lower than 4%.
• •
  Particle width is the measured dimension in standard sieving process.
• •
  Sieving efficiency for biomass powder is evaluated around 70%.
• •
  High aspect ratio and shape irregularities in particles promote sieving inefficiencies.

Abstract

Particle size distribution, obtained under standard sieving method, is usually given as a function of a single characteristic length of the particle. It is fully characterized for spherical particles, but it presents uncertainties when the particle has more complex morphologies as it is the case of biomass powders. The aim of this work is to characterize the standard sieving method in order to determine which particle dimension is being measured, as well as the repercussions of non-spherical shapes on a correct size classification. For this purpose, samples of milled poplar and corn stover have been classified in six size ranges between 0 and 5 mm. Each group of particles has been studied by means of scanned imaging to characterize their real 2D dimensions (width and length) and their shapes according to six different categories: circle, square, rectangle, rectangle fibrous, hook and hook fibrous. Results from image analysis show that sieve size corresponds mostly with particle width (shorter dimension), finding a sieving efficiency around 70%. Most wrongly classified particles showed a high aspect ratio, a hook shape or silhouette irregularities at fracture section, thus proving the importance of particle shape in the classifying process.

Keywords

Biomass

Particle characterization

Particle shape and size analysis

Sieving

Image processing

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Nomenclature

AR

aspect ratio

CFD

computational fluid dynamics

D_equiv

equivalent diameter

D_length

length dimension

d_p

particle size

D_width

width dimension

Os_x

sieve with x mm opening size

Os_x1-x2

particle size range with opening size sieve from x1 to x2 mm

SRF

short rotation forestry

B_L

length of the smallest oriented bounding rectangle

B_W

width of the smallest oriented bounding rectangle

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