Agriculture Reference
In-Depth Information
Table 2.1 Enginee ring properties of biomass
Characterization
methods/standards/
reference
Engineering
properties
Engineering application
Density
Supply logistics, transportation, and storage
of biomass in different forms: chips, logs, ground
particles and pellets, etc.
[ 17 , 18 ]
Particle size
Design parameter for efficient downstream conversion
[ 19 - 22 , 26 ]
Angle of repose
Design parameter for handling and storage facilities
[ 27 - 31 ]
Moisture content
Design parameter for drying and thermal conversion
processes
[ 38 , 39 ]
Calorific value
Energy recovery efficiency
[ 40 - 45 ]
Ash content
Estimation of the potential risk of slagging and fouling
issues during biomass combustion/gasification
[ 47 , 48 ]
Color
Quality control and a quick estimation of fuel properties
(e.g., heating value)
[ 42 , 49 ]
content, heating value, ash content, and color, which are all important engineering
properties for the design and operation of the downstream biochemical process.
They also highly affect the design of handling and transportation systems, storage
in hoppers and silos, and fuel conversion equipment [ 11 , 12 ].
In the following sections, we discuss the typical characterization method of the
physical properties of the biomass (Table 2.1 ) and also review recent progress in
understanding their engineering properties.
2.2
Characterization Methods of Biomass Engineering
Properties
2.2.1
Density
Density of a biomass is defined as the mass over its volume (kg/m 3 or lb/ft 3 ). In the
context of bioenergy, we divide density into two groups: bulk density and particle
density.
2.2.1.1
Bulk Density
Bulk density is an important characteristic of biomass that influences directly the
cost of feedstock delivered to a biorefinery and storage area [ 13 - 15 ]. The non-
uniform particle size and shape of the raw biomass including leaves and stems lead
to the high cost for transportation, storage, and feeding of the particles into each unit
operation. The standardization of the characterization method of the bulk density of
biomass for logistic optimization is of utmost importance (Fig. 2.1 ).
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