Biomass Conversion and Biorefinery
https://doi.org/10.1007/s13399-021-02063-y
ORIGINAL ARTICLE
Investigation of bulk density and friction coefficient of olive residues
and sawdust prior to pelletizing
Ayla Abou Haidar1 · Jihad Rishmany1
Received: 11 June 2021 / Revised: 15 October 2021 / Accepted: 23 October 2021
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021
Abstract
This paper focuses on the influence of numerous parameters involved in the pelletizing process on bulk density and friction
coefficient of olive residues and sawdust. The bulk density is measured for different grain size and mixture composition. The
bulk density of sawdust decreases is inversely proportional to the grain size, whereas for olive residues, there isn’t a clear correlation. Regarding the friction test, numerous experiments are conducted under different test conditions: pressure, grain size,
velocity, moisture content, temperature, and mixture composition. The friction coefficient decreases linearly with increasing
test velocity for both raw materials. An increase in temperature from 25 to 250 °C causes an exponential decrease for the
sawdust friction coefficient, whereas for olive residues, it remains constant between 25 and 150 °C and then decreases linearly
from 150 to 250 °C. Increasing the moisture content also results in an exponential increase of the friction coefficient for both
raw materials. All empirical correlations are embedded in a MATLAB code that predicts the presumed friction coefficient
of any mixture of sawdust and olive residues under different conditions. Finally, a better understanding of bulk density and
friction coefficient aids in improving pellet production in terms of reduced power consumption and enhanced pellet quality.
Keywords Granular biomass · Bulk density · Friction coefficient · Olive residue · Sawdust · Pellets
1 Introduction
The use of fossil fuels as primary energy source has led to
a negative impact on the environment. This is mainly due
to the negative effect they have on global warming, creating the greenhouse effect and increasing the amounts of
harmful gases in the Earth’s atmosphere. In order to help in
overcoming this problem, biofuel pellets from different raw
materials such as sawdust are being used as a new source
of energy [1]. The use of resources is a strategic factor at
every social level [2]. Biomass is versatile, having zero net
­CO2 and less S
­ O2 emissions than fossil fuels [3]. Different works have tried to characterize different forms of biomass, given its great diversity and different properties [4–6].
Among these forms are briquettes or pellets that are granular
biomass materials. However, for efficient design and operation of equipment for handling, storage, and processing, it
is necessary to acquire a vast knowledge of the mechanical
* Jihad Rishmany
jihad.rishmany@balamand.edu.lb
1
Department of Mechanical Engineering, University
of Balamand, P.O. Box 100, Tripoli, Lebanon
properties of granular biomass. Numerous studies investigate
this issue with coal as raw material [7–13]. Several engineering processes involve granular biomass technologies,
among which the most important are pneumatic conveying,
transport, size reduction, densification, mixing (blending),
segregation, weighing, metering, packaging, and storage
or bagging [6, 14]. Technological equipment used for their
processing should be properly designed to ensure optimum
conditions [15], and acquisition of accurate data regarding material parameters is mandatory to guarantee reliable
and efficient processing [9, 10, 16]. Some characteristics of
granular biomass are crucial in bioenergy tradition such as
bulk density, moisture content, and flowability.
Bulk density is one of the essential parameters of granular
materials as well as granular biomass [8, 17]. Awareness on
the correct value of the bulk density of granular material
is crucial for numerous applications. The bulk density of a
material has a major outcome on its mechanical characteristics. It is the parameter that is used for the prediction of the
forces caused by the pressure exerted by granular material
against the structure of the bin or silo. Besides, it is necessary for the precise prediction of container capacity.
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Biomass Conversion and Biorefinery
The main factor which determines the interaction between
surface and granular material is moisture content (m.c.).
Larsson [18] studied the friction of granular material against
construction materials by investigating the kinematic wall
friction coefficient of reed canary grass powder (scientific name, Phalaris arundinacea) at low and high normal
stresses. At low normal stress, the kinematic wall friction
was positively correlated to moisture content and negatively
correlated to normal stress. In the case of high normal stress,
kinematic wall friction also decreased with an increase in
normal stress, but no correlation with moisture content was
observed.
Flowability is the ability of flowing of granular solids and
powders. Naturally, the flow behavior is multidimensional,
and it relays on many physical features. Flowability, in fact,
is a result of the combination of a material’s physical properties that affect material flow, environmental conditions, and
the equipment used for handling, storing, and processing
these materials [19].
Due to the process complexity, no single test can fully
quantify a product’s flowability. Some of the factors that
affect flowability of bulk solids and powders include moisture content, temperature, pressure, fat, particle size, and
flow agents. Stelte et al. (2011) [20] studied the effect of
lignin glass transition (Tg) and surface waxes on pelletizing
properties. Also, many studies have investigated Tg of wood
lignins [21–25] and have shown that they depend on species, moisture content, and sample preparation. In general,
Tg decreases with increasing moisture content (water acts as
plasticizer) and degree of substitution.
One of the important parameters for the pelletizing process is the pelletizing pressure (Px). The pelletizing pressure
is the pressure needed to enforce the raw materials to enter
the die in order to be converted into pellets. This pressure is
highly affected by many process parameters. For steady-state
conditions, it can be expressed as a function of the compression ratio, the pre-stressing pressure, the Poisson ratio, and
the friction coefficient.
The pelletizing pressure is given by the following mathematical formula [26, 27]:
Px =
)
PN0 ( 4𝜇v C
e LR − 1
vLR
where:
C is the compression ratio (length/diameter).
Px is the pressure build-up in the channel.
μ is the friction coefficient between metal and raw
material.
νLR is the Poisson’s ratio.
PN0 is the pre-stressing pressure.
Since the friction coefficient is one of the parameters
that is highly affected by the moisture content, temperature,
13
pressure, fat content, particle size, and the pelletizing pressure, it is essential to assess the behavior of this coefficient
under different combinations of the aforementioned parameters. This is accomplished experimentally through a set of
friction experiments that aim to correlate friction coefficient
(μ) between the raw material used for pellets and the die
material, to different parameters such as pressure, temperature, grain size, velocity, initial moisture content, and raw
material composition. During testing, one parameter is varied, while all the others are held constant. Moreover, the
friction coefficient has a major effect on other parameters
such as flowability.
In this regard, this study focuses on the investigation of
the initial conditions of two raw materials (sawdust and olive
residues) in terms of bulk density, grain size, and friction
coefficient. A mixture of both raw materials under different
proportions is then investigated. This provides insight on
setting the optimum parameters of the mixture prior to pelletizing, which will result in high-quality pellets in terms of
density and calorific value. Moreover, this in turn will have
a positive impact as well on the resulting pellet density, in
addition to optimizing the power consumption and the production rate of the pellet machine.
2 Materials and methods
2.1 Materials
The raw materials used in this study are sawdust (SD) (mixture of fir and frake) (scientific name, Abies and Terminalia superba) (Fig. 1a) and olive residues (OR) (Fig. 1b),
respectively.
First, both raw materials are dried to achieve a nearly 0%
moisture content by heating them to 50 °C for about 48 h.
Then the bulk density of both raw materials is computed
using a small container of known volume and a high precision balance.
Once this step is accomplished, a grain size control is
conducted via manual sieving. A total of six grain size
grades are prepared for each material (Table 1):
After sieving, raw materials are heated once more at
50 °C to achieve a near zero moisture content.
After calculating the bulk density of the different samples, the raw materials are stored in containers ready for
further testing.
2.2 Methods
The friction test is conducted on the Laboratory Universal Testing Machine (UTM) after applying some necessary
adjustments. In particular, a pulley is fixed at the upper
crosshead of the UTM, and a table and another pulley are
Biomass Conversion and Biorefinery
Fig. 1 Raw materials. a Sawdust mixture of fir and frake b
olive residues
Table 1 Particle grades versus
size
Grade
G1
G2
G3
G4
G5
G6
0.75<G2 1.15
1.15<G3 2.36
2.36<G4 4.75
4.75<G5 8.5
G6>8.5
Particle
Size
G1
0.75
(mm)
Sawdust
Olive
Residues
fixed at the lower crosshead in order to handle the second
material representing the die for the friction test (Fig. 2).
2.2.1 Experimental settings
The experiments are divided into 5 parts in order to study
the friction behavior in function of five different parameters. The pressure range, though significantly lower than
the pelletizing pressure, reveals its influence on the friction
coefficient. Based on the bulk density, pellet density, and
the perforated area of the die, the velocity of the pellets
is in the range of 1–6 mm/s depending on the raw material type. The typical moisture content during pelletizing ranges between 10 and 15%. Consequently, a wider
range was considered during testing (0–35%). During
pelletizing, the friction between the raw materials and the
die wall generates heat, which increases the die temperature to around 100 °C. The effect of temperature on the
friction coefficient is tested by considering the following
temperatures: 25, 50, 100, 150, 200, and 250 °C. Table 2
summarizes all the experiment parts and parameters.
2.2.2 Condition of experiments
• During each experiment, one parameter is varied while
maintaining all other parameters constant.
• The sliding distance should be constant for all experi-
ments (not to exceed 30 mm).
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Biomass Conversion and Biorefinery
– Different raw materials mixture ratio: 75%SD-25%OR,
50%SD-50%OR, 25%SD-75%OR
2.2.3 Experimental procedure
The experimental procedure consists of the following steps:
1. Measure the temperature and moisture content of the raw
material prior to testing.
2. Adjust the ring and fill it with the raw material (Fig. 3a).
3. Place a cylinder inside the ring and turn left and right
in order to distribute well the raw material on the entire
area and then add the mass needed.
4. Start the test.
5. In case of a high-temperature test, heat is generated
using a hot air blower located at the bottom of the metal
sheet (Fig. 3b), and a delay time of 30–40 s is required
before starting the test in order to obtain a uniform temperature distribution over the metal sheet.
3 Results and discussion
3.1 Bulk density
The bulk density of different grain size samples of both raw
materials as well as samples containing a mixture of all grain
sizes are shown in Fig. 4 at zero percent moisture content
(MC0%).
Then, the bulk density of a mixture of both raw materials
(%SD-%OR, 25–75, 50–50, 75–25) having the same grain
size is obtained by a linear interpolation of the original densities (100%SD, 100%OR) (Fig. 4).
Since the raw material grain size of olive residues is
originally less than 8.5 mm, the bulk density for grain size
greater than 8.5 mm (G6) was not taken into account. It is
noticed that when the raw material contains all grain sizes,
its bulk density is closest to G4.
Moreover, the bulk density of olive residues increases
until a grain size of 4.75 mm. The main reason of this
increase is the multiphase nature of the raw material.
Fig. 2 Table and pulley fixed at the lower and upper crossheads of the
UTM machine
• Determine in which direction the metal sheet has the
highest friction coefficient, and then conduct all friction
tests in this direction.
• For each condition, the experiment should be repeated at
least 3 times to validate the results.
• All experiments should be repeated for different proportions of biomass mixture (sawdust, olive residues):
– 100% sawdust (SD) and 0% olive residue (OR)
– 0% sawdust and 100% olive residue
Table 2 Test parameters for
each experiment part
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Experiment
Pressure (kPa)
Velocity
(mm/s)
Grain size
MC (%)
Temperature (°C)
Part I
Part II
Part III
Part IV
1.98–11.86
5.93
5.93
5.93
1
1–6
1
1
G1, G3, and G4
G1
G1–G6
G1
25 °C
25 °C
25 °C
25 °C
Part V
5.93
1
G1
0
0
0
5, 10, 15, 20, 25,
30, and 35%
0
25, 50, 100,
150, 200, and
250 °C
Biomass Conversion and Biorefinery
Fig. 3 a Ring mounted on the
friction table filled with raw
material. b Hot air blower added
to the friction table
Fig. 4 Mean bulk density of raw
material function of grain size
and mixture composition for
zero moisture content
Density (kg/m3)
600
OR100% All Grain Sizes - Experimental
25%SD-75%OR - predicted
75%SD-25%OR - predicted
SD 100% All Grain Sizes - Experimental
OR 100% - Experimental
50%SD-50%OR - predicted
SD 100% - Experimental
508.9
500
400
300
200
128.53
100
0
G1
G2
G3
G4
G5
G6
Grain Size Grade
During the milling process for the olive oil production,
the pits, pulp, and the skin are crushed (Fig. 5). However,
the pit grains are harder than the other components (pulp
and skin), which results in coarser grains with respect to
the skin and the pulp. As a result, the increasing percentage of pit grain causes a higher olive residues bulk density
from G2 to G5.
Furthermore, the bulk density of olive residues
decreases for a grain size between 4.75 and 8.5 mm
(Fig. 4). The main reason for this decrease is the presence
of large olive residues grains that lead to a high volume
of air cavitation between the particles, which results in a
lower mass with respect to volume.
For the sawdust, the bulk density decreases with increasing grain size (Fig. 4). This is mainly due to the air cavitation
between particles as stated earlier.
The raw materials used for pelletizing could be a mixture
of different raw materials with different grain size. Consequently, the bulk density of the mixture is derived for different grain size mixture through linear interpolation of the
measured bulk densities.
3.2 Friction test results
A total of 444 friction experiments were conducted.
These experiments mainly aimed at gathering information
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Biomass Conversion and Biorefinery
the compression of particles in the sliding direction. Once
this is completed, the steady-state sliding starts (Region 2).
The static and kinetic forces are averaged over Region 3,
which is a portion of Region 2 and constitutes about 30% of
the total sliding distance.
3.2.1 Friction coefficient behavior
Fig. 5 Olive grain composition [28]
concerning pressure, velocity, grain size, moisture content,
temperature, and raw material mixture.
A sample test result for the friction test is shown in Fig. 6.
The graph is divided into three regions. Region 1 refers to
Fig. 6 Typical experimental friction curve
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The results of all conducted experiments were plotted in
order to assess the behavior of friction coefficient under different test conditions (Figs. 7, 8, 9, 10, 11 and 12).
Both static and kinetic friction coefficients present the
same behavior, but their values differ slightly. This is why,
for the next series of graphs, most of them show only the
kinetic friction coefficient which is nearly 85% of the static
coefficient:
3.2.1.1 Pressure–grain size The results obtained during
this set of experiments correspond to a maximum pressure of 11.86 kPa, whereas the pelletizing pressure is usually in the order of MPa. Consequently, these results (pres-
Biomass Conversion and Biorefinery
Fig. 7 Mean value of kinetic
friction coefficient with 95%
confidence interval function of
the applied pressure
0.7
Friction Coefficient
0.6
0.5
0.4
0.3
0.2
OR100 MC5-G1-T25-V1
OR100 MC5-G4-T25-V1
SD100 MC0-G3-T25-V1
fied
0.1
0
2
4
6
8
Applied pressure (kPa)
10
12
14
0.6
0.55
Fricon coefficient
Fig. 8 Mean value of kinetic
friction coefficient with 95%
confidence interval function of
velocity
0
OR100 MC5-G3-T25-V1
SD100 MC0-G1-T25-V1
SD100 MC0-G4-T25-V1
0.5
0.45
0.4
0.35
0.3
SD100 G1-MC0-T25
0
1
2
OR100 G1-MC5-T25
3
4
5
fied
6
7
Velocity (mm/s)
sure–grain size) constitute only a qualitative assessment of
the raw material behavior under these conditions. Results
(Fig. 7) show nearly the same behavior for both raw materials. However, for any set of conditions, the friction coefficient of sawdust is always higher than that of olive residues
for all pressure values. The friction coefficient of olive residues increases with finer grain size, whereas less dependency on grain size grade is noticed for sawdust.
3.2.1.2 Velocity The friction coefficient seems to decrease
with velocity for both raw materials (Fig. 8). At a velocity
of 6 mm/s, the friction coefficient for the sawdust is affected
about 12% of its highest value (at 1 mm/s) and about 15%
for the olive residues.
3.2.1.3 Grain size Again a contradictory behavior is noticed
in this case. For sawdust, up to 8.5 mm particle size, the
friction coefficient increases (Fig. 9). With increasing particle size, the mechanical interlocking between particles is
more likely to occur. Once this happens, less relative motion
between the particles ensues, causing them to act as one
body, thus causing high friction. The olive residues behave
in a different manner. It seems that the friction coefficient
is constant for grain size less than 1.18 mm. Since the raw
material is a double-phase mixture, the amount of crushed
pits is increasing for grain size higher than 1.18 mm, as it
is constituted from different material than the pulp and the
skin; it causes a lower friction coefficient. This result indicates that crushed pits have a lower friction coefficient than
the remaining constituents of olive residues. For a sawdust
13
Biomass Conversion and Biorefinery
0.6
0.55
Fricon coefficient
Fig. 9 Mean value of kinetic
friction coefficient with 95%
confidence interval function of
grain size grade
0.5
0.45
0.4
0.35
0.3
0.25
0.2
SD100 MC0-T25-V1
G1
G2
OR100 MC5-T25-V1
G3
G4
G5
fied
G6
Grain size grade
0.8
Fricon coefficient
Fig. 10 Mean value of kinetic
friction coefficient with 95%
confidence interval function of
moisture content
0.7
0.6
0.5
0.4
0.3
SD100 G1-T25-V1
0
10
OR100 G1-T25-V1
20
30
fied
40
Moisture content (%)
particle size higher than 8.5 mm, the friction coefficient
decreases due to the large amount of air cavitation between
particles leading to less contact surface with the metal sheet.
coefficient of sliding friction. This is mainly attributed to
the occurrence of free water on the surface of the biomass
material particles acting as a lubricant.
3.2.1.4 Moisture content Nearly the same behavior of friction coefficient could be noticed under different conditions
of moisture content for both raw materials (Fig. 10). Friction
coefficients for both materials seem to increase with moisture content till MC = 35% and then decreases. The same
behavior is noticed by Mateusz et al. [29, 30] with slightly
lower friction values.
As the moisture content of raw materials increases,
the wall friction increases significantly. This is due to the
increased adhesion between the biomass material particles
and the steel surface at higher moisture content [31]. Further
increase in the moisture content of the material reduced the
3.2.1.5 Temperature Figure 11 shows the friction coefficient results for experiments conducted in an interval of
temperature between 25 and 250 °C with a step of 50 °C.
The sawdust particles behave in a different manner than
olive residue particles. The friction coefficient of sawdust
at 150 °C decreases about 50% of its original value (0.51
at 25 °C). Between 100 and 150 °C, it increases from 0.33
to 0.35. This little augmentation may be the result of glass
transition of lignin in the sawdust that acts as an adhesive at
150 °C, and then at 200 °C, it will be softened and therefore
acts as a lubricant. This creates a doubt that 150 °C is most
likely the glass transition temperature of polymers in saw-
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Biomass Conversion and Biorefinery
0.6
SD100 MC0-G1-V1
Fricon coefficient
Fig. 11 Mean value of kinetic
friction coefficient with 95%
confidence interval function of
temperature
OR100 G1-T25-V1
fied
0.5
0.4
0.3
0.2
0
50
100
150
200
250
300
Temperature ( C)
Fig. 12 Mean value of kinetic
friction coefficient with 95%
confidence interval function of
raw material mixture
0.6
Friction coefficient
0.55
MC0-T25-V1
MC15-T100-V1
MC15-T100-V5
fied
0.5
0.45
0.4
0.35
0.3
0.25
0.2
-25
0
25
50
75
100
125
% OR in mixture
dust. The same behavior was recorded by Nielsen et al. [32]
with an increase in friction coefficient at 150 °C.
Unlike sawdust, the friction coefficient for OR remains
constant (0.38) till a temperature of 150 °C. Beyond this
temperature, the friction coefficient decreases linearly about
40%, until it reaches 0.2454 at 250 °C which signals that
150 °C is most likely the glass transition temperature of the
polymers present in the olive residues.
3.2.2 Friction coefficient function of raw material mixture
For MC = 15%, T = 100 °C, and V = 1 mm/s, the friction coefficient increases as the percent of OR increases
(Fig. 12). This is due to two main reasons: the dependency
of the sawdust friction coefficient on temperature and the
stability of the olive residues friction coefficient from 25 to
150 °C. Note that this increase does not seem to be linear
especially for sawdust. However, for MC = 15%, T = 100 °C,
and V = 5 mm/s, the friction coefficient increases slightly as
the % of olive residues increases.
It can be noticed as well that there is no big difference
of results for different velocities (1 mm/s and 5 mm/s) at
MC15-100 °C. However, in the range of 50 to 100% olive
residues, the friction coefficient is nearly the same for the
three conditions. Figure 13 shows sample images of raw
materials mixture after conducting the friction test; the
image was taken from the bottom of the cylinder.
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Biomass Conversion and Biorefinery
Fig. 13 Sample images of
SD-OR mixture after testing, a
75–25, b 50–50, c 25–75
Table 3 Kinetic friction coefficient correlations for both raw materials
Parameter
Velocity
Grain size grade
Moisture content
Temperature
Sawdust
Olive residues
Friction equation
Coefficient of
determination
(R2)
Friction equation
Coefficient of
determination
(R2)
µSD,V = − 0.01x + 0.5376
µSD,G = − 0.0025x4 + 0.03
3x3 − 0.1483x2 + 0.2706
x + 0.3314
µSD,MC = 0.368x0.2157
µSD,T = 1.2732x−0.294
0.8375
0.9637
µOR,V = − 0.0103x + 0.4432
µOR,G = 0.4294x−0.187
0.7851
0.7395
0.9848
0.8853
µOR,MC = 0.2598x0.3019
µOR,T25–150 = 5E − 05x + 0.3775 µOR,T150–250 = − 0.0017x
+ 0.6468
µOR = (µOR,V + µOR,G + µOR,MC + µOR,T) / 4
0.9316
0.5029 0.9996
µSD = (µSD,V + µSD,G + µSD,MC + µSD,T) / 4
Global friction
equation for each
raw material
µ = µSD × R + µOR × (1 − R)
Global friction
equation for the
raw material
composition
Note: R is the proportion of sawdust in the raw material mixture (SD-OR)
After plotting the results of all experiments, trendlines
were added using Microsoft Excel from which empirical
correlations relating the friction coefficient to each corresponding parameter were deduced (Table 3).
Furthermore, a MATLAB code was developed for all
the friction correlations in order to predict the friction coefficient for any set of input parameters. For a given set of
conditions specified by the user (moisture content, velocity,
grain size, temperature, and raw material mixture), the code
automatically calculates the resulting friction coefficient.
As an example, for the following set of parameters,
SD100-G2-MC5-T50-V3, the code computes the friction
coefficient for each parameter separately: grain size (Fig. 9),
MC (Fig. 10), temperature (Fig. 11), and velocity (Fig. 8).
Then, the resulting friction coefficient of SD is calculated as
the average of the four computed values. In case of different
raw materials, a rule of mixture is applied where the friction
coefficient for each raw material is calculated separately,
and then the overall friction coefficient is computed as the
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weighted average of both raw materials with respect to the
volume proportion (global friction equations in Table 3).
In the next series of graphs (Figs. 14, 15 and 16), the predicted friction coefficient is compared to the measured values for different raw material mixtures, starting from 100%
SD (zero on the axis) to reach 100% OR (one on the axis).
The red points represent the experimental values, whereas
the blue curve is the predicted one based on the MATLAB
code. The results are in good agreement especially for
G1-MC5-T25-V1 (Fig. 14) where this set of experiments is
conducted at 25 °C. For G1-MC15-T100-V1 and G1-MC15T100-V5 (Figs. 15 and 16), the discrepancy in results is due
to the controversial effect that some parameters cause when
they are present simultaneously. For example, the presence
of moisture content leads to higher friction under optimal
test conditions; however, in case of high temperature, a
vapor film is generated between the raw material and the
metal sheet, and since the pressure is not high enough, this
phenomenon tends to lower the friction coefficient. By
Biomass Conversion and Biorefinery
Fig. 14 Kinetic friction coefficient function of raw material
mixture (G1-MC5-T25-V1)
Fig. 15 Kinetic friction coefficient function of raw material
mixture (G1-MC15-T100-V1)
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Biomass Conversion and Biorefinery
Fig. 16 Kinetic friction coefficient function of raw material
mixture (G1-MC15-T100-V5)
comparing the last two cases, even for high temperature and
MC, it is noticed that increasing the velocity results in a
lower friction coefficient.
4 Conclusion
The main objective in this work is to study the raw material behavior for different test conditions prior to pelletizing.
The major output is that the bulk density and friction coefficient for any composition of a mixture of sawdust and olive
residues could be predicted without the need to conduct any
experiment. The findings will be used for further studies by
conducting a new set of experiments (PIN test) to study the
maximal raw material compression ratio and the pressure
build in the channel in order to estimate the required pelletizing process power and energy consumption.
4.1 Bulk density results
The bulk density of raw materials is highly affected by the
material grain size and quality. For sawdust, the bulk density
decreases with increased grain size; this is mainly related
to the void space between particles. The larger the grain
size, the more void space between particles, which leads to
a lighter bulk density. In contrast, the olive residues bulk
density increases with increasing grain size. This is related
13
to the hybrid material nature of olive residues. Generally,
the density of pits is greater than the pulp and skin, causing
a higher bulk density for larger grain size. A decrease at a
high grain size (G6) is caused by void space between the
particles as noticed in the case of sawdust.
4.2 Friction test results
The friction coefficient is highly affected by the raw material
temperature, moisture content, and the friction test velocity.
A temperature increase from 25 to 250 °C causes an
exponential decrease in the sawdust friction coefficient,
accompanied with a slight increase at 150 °C due to further
polymer fusion. As for olive residues, the friction coefficient
remains constant till 150 °C and then decreases linearly to
reach 0.2268 at 250 °C.
Due to moisture content increase, an exponential increase
for both raw materials friction coefficient is observed, starting from 0.45 to reach a maximum of 0.75 at 30% moisture
content.
The friction coefficient decreases linearly with increasing
test velocity for both raw materials.
By studying the bulk density and friction coefficient function of process parameters, a deeper knowledge is acquired,
which in turn facilitates further studies regarding pelletizing
pressure and process power consumption.
Biomass Conversion and Biorefinery
Data availability The datasets generated during and/or analyzed during the current study are available from the corresponding author on
reasonable request.
Code availability Not applicable.
Declarations
Ethics approval Not applicable.
Consent to participate Not applicable.
Consent for publication Not applicable.
Conflict of interest The authors declare no competing interests.
References
1. Paredes-Rojas JC, Torres San Miguel CR, Flores Vela Al, BravoDíaz B, De la Cruz Alejo C, Ramírez DP (2020) Design Proposal
of a Prototype for Sawdust Pellet Manufacturing through Simulation. Adv Mater Sci, 9565394, p 10. https://d​ oi.o​ rg/1​ 0.1​ 155/2​ 020/​
95653​94
2. Varela LG, Gómez MA, Garabatos M, Glez-Pena D, Porteiro J
(2021) Improving the bed movement physics of inclined grate
biomass CFD simulations. Appl Therm Eng 182:116043
3. Carrillo-Parra A, Contreras-Trejo JC, Pompa-García M, Pulgarín-Gámiz MÁ, Rutiaga-Quiñones JG, Pámanes-Carrasco G,
Ngangyo-Heya M (2020) Agro-pellets from oil palm residues/
pine sawdust mixtures: relationships of their physical, mechanical
and energetic properties, with the raw material chemical structure.
Appl Sci 10(18):6383
4. Niño A, Arzola N, Araque O (2020) Experimental study on the
mechanical properties of biomass briquettes from a mixture of
rice husk and pine sawdust. Energies 13(5):1060
5. Gendek A, Aniszewska M, Malat’ák J, Velebil J (2018) Evaluation of selected physical and mechanical properties of briquettes
produced from cones of three coniferous tree species. Biomass
Bioenergy 117:173–179
6. Cui H, Grace JR (2006) Pneumatic conveying of biomass particles: a review. China Particuology 4(3–4):183–188. https://​doi.​
org/​10.​1016/​S1672-​2515(07)​60259-0 (ISSN 1672-2515)
7. Zulfigar M, Moghtaderi B, Wall TF (2006) Flow properties of
biomass and coal blends. Fuel Process Technol 87:281–288
8. Gil M, Schott D, Arauzo I, Teruel E (2013) Handling behavior
of two milled biomass: SRF poplar and corn stover. Fuel Process
Technol 112:76–85
9. Guo Z, Chen X, Liu H, Lu H, Guo X, Gong X (2014) Effect of
storage time on the flowability of biomass-coal granular system.
Fuel Process Technol 125:59–66
10. Guo Z, Chen X, Liu H, Chen H (2014) Gravity discharge characteristics of biomass-coal blends in a hopper. Fuel 125:137–143
11. Guo Z, Chen X, Xu Y, Liu H (2015) Effect of granular shape
on angle of internal friction of binary granular system. Fuel
150:298–304
12. Ganesan V, Rosentrater KA, Muthukumarappan K (2008) Flowability and handling characteristics of bulk solids and powders – a
review with implications for DDGS. Biosyst Eng 101:425–435
13. Wu MR, Schott DL, Lodewijks G (2011) Physical properties of
solid biomass. Biomass Bioenergy 35:2093–2105
14. Tumuluru JS, Wright CT, Kenney KL, Hess RJ (2010) A technical review on biomass processing: densification, preprocessing,
modeling and optimization. Published by the American Society
of Agricultural and Biological Engineers, St. Joseph, Michigan.
https://​doi.​org/​10.​13031/​2013.​29874
15. Stasiak M, Molenda M, Bańda M, Horabik J, Wiącek J, Parafiniuk
P ... & Oniszczuk T (2020) Friction and shear properties of pine
biomass and pellets. Materials 13(16): 3567
16. Adapa P, Taabil L, Schoenau G (2009) Compaction characteristics
of barley, canola, oat and wheat straw. Biosyst Eng 104:335–344
17. Littlefield B, Fasina OO, Shaw J, Adhikari S, Via B (2011) Physical and flow properties of pecan shells – particle size and moisture
effect. Powder Technol 212:173–180
18. Larsson SH (2010) Kinematic wall friction properties of reed
canary grass powder at high and low normal stresses. Powder
Technol 198:108–113
19. Prescott JK, Barnum RA (2000) On Powder Flow ability, Pharm.
Technol 24:60–84
20. Stelte W, Clemons C, Holm JK, Ahrenfeldt J, Henriksen UB,
Sanadi AR (2012) Fuel pellets from wheat straw: the effect of
lignin glass transition and surface waxes on pelletizing properties.
Bioenergy Res 5(2):450–458
21. Bouajila J, Dole P, Joly C, Limare A (2006) Some laws of a lignin
plasticization. J Appl Polym Sci 102:1445–14451. https://d​ oi.o​ rg/​
10.​1002/​app.​24299
22. Salmen L, Olsson AM (1998) Interaction between hemicelluloses,
lignin and cellulose: structure-property relationships. J Pulp Paper
Sci 24:99–103
23. Kelley SS, Rials TG, Glasser WG (1987) Relaxation behavior of
the amorphous components of wood. J Mater Sci 22:617–624.
https://​doi.​org/​10.​1007/​BF011​60778
24. Olsson AM, Salmen L (1992) Viscoelasticity of in situ lignin
as affected by structure: softwood vs. hardwood. In: Glasser W
(ed) Viscoelasticity of biomaterials. American Chemical Society,
Washington, pp 133–143
25. Sjostrom E (1983) Wood chemistry: fundamentals and applications. Academic Press, London
26. Holm JK, Henriksen UB, Hustad JE, Sørensen LH (2006) Toward
an understanding of controlling parameters in softwood and hardwood pellets production. Energy Fuels 20(6):2686–2694
27. Holm JK, Henriksen UB, Wand K, Hustad JE, Posselt D (2007)
Experimental verification of novel pellet model using a single
pelleter unit. Energy Fuels 21(4):2446–2449
28. Olive grain composition (n.d.) Retrieved from https://​images.​app.​
goo.​gl/​tr4DP​WA3DV​C1wDq​z7. Accessed 20 Dec 2020
29. Stasiak M, Molenda M, Banda M, Gondek E (2015) Mechanical
properties of sawdust and woodchips. Fuel 159:900–908
30. Stasiak M, Molenda M, Banda M, Horabik J, Wiacek J, Parafiniuk
P, Wajs J, Gancarz M, Gondek E, Lisowski A, Oniszczuk T (2020)
Friction and shear properties of pine biomass and pellets. Materials 13:3567
31. Mani, Sudhagar, et al (2003) “Mechanical properties of corn
stover grind.” 2003 ASAE Annual Meeting. American Society of
Agricultural and Biological Engineers
32. Nielsen NPK et al (2009) Importance of temperature, moisture
content, and species for the conversion process of wood residues
into fuel pellets. Wood Fiber Sci 41(4):414–425
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