Engineering Properties of Biomass - Engineering and Science of Biomass Feedstock Production and Provision - page 29

Table 2.3 Flowability chart of different agricultural biomass ground particles at different particle
sizes; parenthesis shows the standard deviation with n = 5
Species Switchgrass Wheat straw C orn stover

Sieve
opening (mm)

Angle
of repose

Types
of powder

Angle
of repose

Types
of powder

Types
of powder Angle of repose

0.707 35.56 (1.21) Free flowing 43.05 (2.00) Fair flow 43.57 (1.23) Fair flow

0.5 38.60 (1.15) Free flowing 45.80 (2.60) Cohesive 45.40 (1.37) Cohesive

0.354 39.82 (0.48) Fair flow 47.53 (1.87) Cohesive 45.64 (0.73) Cohesive

0.25 43.03 (0.23) Fair flow 47.44 (1.61) Cohesive 46.12 (0.55) Cohesive

Table 2.3 shows that corn stover and wheat straw have fair flowability at the larg-
est particle size, while switchgrass shows the best overall free-flowing characteris-
tics for all the particle sizes. The angle of repose of wheat straw and corn stover
increases from 43° to 47° with decreasing particle size. The angle of repose of
switchgrass increases from 36° to 43° with decreasing particle size. The classifica-
tion of the powder type for the biomass grinds is based on the measured angle of
repose [ 32 ]. Wheat straw and corn stover with particle size of 0.707 mm change
from fair flow to cohesive with decreasing particle size of 0.25 mm. Switchgrass
particles exhibit a free-flowing behavior for the particles with sizes of 0.5-0.707 mm,
and the smaller particles with particle sizes of 0.25-0.354 mm have fair flow char-
acteristics. These results should be due to difference in forces existing on the sur-
faces between the inter-particles.

2.3.2 Color, Moisture Content, and Calorific Value

The color and calorific value of untreated and thermally treated biomass can be cor-
related. For example, it was known that the calorific value of thermally treated bio-
mass increases with the darkness (Fig. 2.4 ). For industries, development of efficient
characterization tools using color as a parameter would benefit them in grading
different products. For example, when the power generation utilities would like to
check the fuel quality of each million ton batch of delivered biomass, they may
prefer to have a quick fuel properties measurement instead of sending off many
small randomly selected samples to the certified laboratory for fuel properties mea-
surement (e.g., calorific value, moisture content, and hydrophobicity). As a result,
the development of new characterization protocols and standards is needed to
support the growth of the use of biomass for energy production.
Our recent work reported that a simple color measurement can quickly estimate
the calorific value of the thermally treated biomass using the statistical multi-linear
models [ 49 ]. It showed that correlation among color coordinates and compositional
properties of treated biomass is strong and could potentially lead to the development
of reliable instruments (Table 2.4 ). The typical multi-linear regression (MLR) was
used to model responses of the three color components, i.e., L * (whiteness or