Particle and feeding characteristics627253/...H = Hausner ratio [ ] ρ T = Tapped density [kg/m3] ρ...

Spring Term 2013

Master Thesis, 30 hp

Department of Applied Physics and Electronics

Master of Engineering in Energy Technology, 300 hp

Particle and feeding characteristics of biomass powders

Joel Falk

Spring Term 2013




Abstract Milling of biomass is a necessary key step in suspension gasification or powder combustion.

Milled biomass powders are often cohesive, have low bulk density and poor flowability leading to

costly problems in fuel handling. Two different milling methods with four different biomass

powders have been performed to correlate between particle and feeding properties.

Charcoal, Torrefied Norway spruce, Norway spruce and reed canary grass where milled (knife

mill or hammer mill) with a screen size of 1 mm. The resulting powders where analyzed using

both mechanical sieving and optical sieveless particle size analysis. After bulk and tapped density

tests, the powders were fed through a twin screw feeder onto an analytic scale that logged the

weight data on a pc. Two tests were made, one with constant screw speed and the other using a

built-in function called loss in weight feeding.

The hammer mill produced more homogenous powders with more fines than the knife mill. They

also had lower bulk and tapped density. The feeding tests were inconclusive as two materials

where easier fed when hammer milled and two when knife milled. Hammer milled materials had

better initial feeding stability. Another interesting observation was that two of the materials

showed good agreement with a feeding rate that could be predicted if assuming tapped density

while the other two behaved more similar to what would be the case for bulk density.

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Contents Introduction .................................................................................................................................. 1

Theoretical considerations ............................................................................................................ 2

Data pre-processing .................................................................................................................. 3

Material characterization .......................................................................................................... 3

Gravimetric feeding .................................................................................................................. 4

Material and Method .................................................................................................................... 4

Raw material ............................................................................................................................ 4

Powder characterization ........................................................................................................... 5

Feeding properties .................................................................................................................... 5

Results and discussion .................................................................................................................. 6

Particle characterization ........................................................................................................... 7

Feeding properties .................................................................................................................... 8

Conclusions ................................................................................................................................ 11

Acknowledgement ...................................................................................................................... 11

References .................................................................................................................................. 11

Appendix 1 ............................................................................................................................. 13

Appendix 2 ............................................................................................................................. 16

Appendix 3 ............................................................................................................................. 19

1 Spring Term 2013



Master of Engineering in Energy Technology, 300 hp 1

Introduction In an effort to reduce greenhouse gas emissions the European Union committed to a goal of

having 20 percent of their energy coming from renewable sources by 20201 and a long term goal

of 80-95 percent by 2050(Parlament 2011)To meet with both short and long term goals it is

necessary to develop the systems for using renewable and clean energy in all aspects of energy

production.

One important aspect of energy production is coal power plants, the biggest source of power in

the EU (Agency 2012).Coal could potentially be replaced with biomass, greatly reducing the

emission of greenhouse gases. Biomass as a renewable energy source shows great potential due to

its availability and versatility as it can be converted both as a solid, liquid and gaseous fuel

(McKendry 2002) as well as other chemical raw materials (Ragauskas, Williams et al. 2006). One

of the downside of biomass is its relatively low energy density, leading to high logistical costs. In

addition, varying availability may cause unstable fuel prices (Caputo, Palumbo et al. 2005).

Milling of biomass is a necessary step before end use in suspension gasification or powder

combustion. Gasification technology while still in development stage has several key advantages

over regular combustion technologies such as higher overall efficiency and easier flue gas

cleaning (McKendry 2002). In comparison with coal; biomass is significantly different when

milled and the most common method, crushing, has been ineffective both in energy consumption

and size reduction (Tillman 2000; Savolainen 2003). In addition, biomass powders have different

feeding characteristics dependent on milling method. This is due to changes in particle shape and

particle size distribution (Paulrud, Mattsson et al. 2002). Large variations in feeding

characteristics can also be seen between biomass fuels. The result is that biomass is hard to use

successfully in unmodified coal systems (Dai, Cui et al. 2012).

Investigating the effects of different fuel preparation methods is of utmost importance to be able

to choose the right equipment for the process. R.Grace pointed out that from industrial experience

the most common cause of failure in continuous biomass power facilities was feeding problems

(Dai, Cui et al. 2012)

Biomass powders generally have long or flaky particles due to its high fibrous content resulting in

a high aspect ratio (Abdullah and Wu 2009). Besides feeding characteristics, aspect ratio and

particle size distribution also have a large influence on feeding characteristics and combustion

properties of the fuel as the particle shape and size affects the particle specific surface area,

causing a large difference in any heat or mass transfer process (Lu, Ip et al. 2010).

Guo et al. found that with a decrease in particle size there was also a decrease in aspect ratio. This

was attributed to the decrease in difference of structure of the biomass particles (Guo, Chen et al.

1 European Council, 8/9 March 2007: By 2020, at least 20 % reduction in greenhouse gas emissions

compared to 1990 (30% if international conditions are right, European Council, 10-11 December 2009);

saving of 20 % of EU energy consumption compared to project

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2012). Aspect ratio is a common factor to describe the roundness of particles and is defined as its

largest dimension divided by its smallest.

Studies by Podczeck and Miah showed that particles with high aspect ratio have high internal

angle of friction(Podczeck and Miah 1996) and high shear strength (Cleary 2008). Unless proper

actions are taken for these characteristics major disruption in feeding are to be expected due to

bridging and rat holing (Cleary and Sawley 2002)This is a major concern in process where steady

feeding is essential. Feeding problems have such a significant effect that it overshadows other

factors that might affect the combustion process. This makes it hard to make definite conclusions

from experiments with poor feeding performance (Paulrud and Nilsson 2004). It also makes it

exceptionally hard to optimize the combustion process in practical applications.

Hann and Strazisar found that particle size distribution and particle shape had a significant

effect on feeding characteristics of a fuel. It was found that it was easier to get the fuels to flow

with a narrow particle size distribution and that bulk solids with rounded edges resulted in a

greater unconfined yield strength (Hann and Strazisar 2007).

While there has been studies on the difference in energy consumption for grinding biomass with

hammer and knife mills (Cadoche and Lopez 1989) the effect of milling method on particle size

distribution and type of biomass fuel hasn’t been fully explored. Paulrud and Mattson explored

the effect of milling method and found significant effect on particle shape, particle size

distribution and bridging tendencies (Paulrud, Mattsson et al. 2002). However their study only

included one biomass fuel. Since there is a large difference in particle shape and size depending

on raw material, those aspects are also important to study. Since the feedability of a fuel depends

on several factors the effect the milling process has on feeding is best evaluated through a feeding

test.

The objective of this study was to evaluate the effect of milling method (hammer mill and knife

mill) on:

1) Particle characterization (Particle size and mass distribution, tapped and bulk density)

2) Feeding properties (determined by standard deviation from mass flow in screw feeding)

with four biomass fuels(charcoal, torrefied Norway spruce, Norway spruce and reed canary

grass).

Theoretical considerations Theoretical knowledge needed to understand the resulted are presented in this chapter.

Nomenclature S = Standard deviation [g/h]

CMA = Central Moving Average [g/h]

xt = Weight at time t [g]

XCMAt = Average weight of the last 2*N+1 weighing’s at time t [g]

avg = Average flowrate of the previous 30 XCMAt [g/h]

S% = Standard deviation as percentage of average flowrate [%] H = Hausner ratio [ ]

ρT = Tapped density [kg/m3]

ρB = Loose density [kg/m3]

actual = Actual mass flow from feeder [g/h]

t = time [s]

Kp = Proportional gain [ ]

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Ki = Integral gain [ ]

Kd = Derivate gain [ ]

τ = Variable of integration [ ]

theoretical = Theoretical massflow at density ρ [g/h]

= olumetric massflow at output [m3/h]

%output = Percentage of max screw speed [%]

min = Minimum volumetric massflow [m3/h]

max = Maximum volumetric massflow [m3/h]

Data pre-processing The standard deviations of N samples is defined as:

√

∑( )

( )

The central moving average of 2N+1 samples is defined as:

(∑

) ( )

N is a positive integer larger than five.

The standard deviation can be calculated as a percentage of the average mass flow to give a

deviation that is comparable at different mass flows:

( )

where avg is defined as:

∑

( )

Material characterization An important particle property, especially when using optical characterization methods, is the

Feret diameter. It describes the width and length of irregularly shaped particles. It is defined as the

distance between two parallel tangents of the particle at an arbitrary angle as if using a slide

gauge. Minimum and maximum Feret diameters are either obtained at a 90˚ angle or independent

of each other (Min/Max Feret 90˚ or Min/max Feret). The maximum Feret is the length of the

particle and the minimum Feret is the width of the particle.

When analyzing powder densities, the Hausner ratio is useful for describing the internal friction

between particles during feeding. It is the ratio between tapped density and bulk density of a

powder. High values indicate that the bulk density is low due to internal friction between

particles. It is not an absolute property of a material as there is no standardized method for

calculating it. It is used as an indicator of flowability where a value above 1.4 indicates poor

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flowability and below 1.25 indicates good flowability (Geldart, Harnby et al. 1984). It is

commonly used in industry and is empirical proven rather than a theoretically.

( )

Gravimetric feeding Gravimetric feeding while more advanced than volumetric feeding can handle large varieties in

fuel density and has long term accuracy and reproducibility. The feeding is built around a

continuous weighing of fuel leaving the system. By subtracting the previous value and with a

known time step the mass flow leaving the system is known which serve as input for a closed loop

controller;

( ) ( )

( )

The closed loop controller can be defined as the standard form:

( ) ( ( )

∫ ( )

( )) ( )

Where e(t) is the difference in setpoint and actual mass flow:

( ) ( )

This allows the screw feeder to feed by mass flow rather than volumetric flow as it reacts to

disturbances and changes in density while running by increasing or decreasing the speed of the

screw.

Theoretical mass flow of the feeder was calculated by multiplying the fuels powdered density

with the volumetric flow from the feeder at constant speed.

( )

Where the volumetric flow is defined as:

( ) ( )

Materials and Methods

Raw materials Four biomass materials where chosen for the experiments. Charcoal, torrefied Norway spruce and

Norway spruce were chosen as they represent different degrees of thermal treatment. They were

chosen in order to evaluate the effect on the resulting flow properties. Reed canary grass was

chosen to include grass like fuel. The charcoal (Ica, Poland) consisted of a blend of charred

hardwood and had a particle size of several centimeters. The reed canary grass was spring

harvested and shredded (screen size; 15 mm). Norway spruce chips and torrefied Norway spruce

had a chip size of several centimeters. The torrefied Norway spruce were lightly torrefied with

resulting mass yield of 76%.

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Materials were taken from cold winter storage and milled in two different mills: A knife mill

(Retsch SM200, Haan, Germany) and a hammer mill (Kamas, Malmö, Sweden) with screen sizes

of 1 mm. Hammer milled materials are seen in Figure 1. Particle mass size distribution, particle

number size distribution, tapped and bulk densities were then used to evaluate the milling process.

Figure 1. Left: Hammer milled materials Upper left corner: Norway spruce. Lower left corner: torrefied Norway

spruce. Upper right corner: Reed canary grass. Lower right corner: Charcoal. Right: Scale picture of knife milled

Norway spruce

Powder characterization The milled powders where analyzed for bulk and tapped densities. The materials weights were

loosely poured into a previously weighed container of known volume (96.32 cm3). Excess

materials were carefully scraped off before the container was weighed. An extension of the

container was added and filled with more material. The container was then tapped until no

noticeable volume change could be observed (charcoal ~450, torrefied Norway spruce ~700,

Norway spruce ~500, reed canary grass ~500 times). Before weighing the extension was removed

and excess materials scraped off. The equipment used can be seen to the left of Figure 2.

Particle mass size distribution was obtained using a sieve shaker (Fritsch Gmbj, Germany) with

Retsch test sieves 200 mm (middle of Figure 2) with aperture size: 200 µm, 300 µm, 400 µm,

600 µm, 700 µm, and 800 µm. Optimum amplitude for sieving each material was found through a

screening with four 5 minute test with increasing amplitudes. The optimum amplitude for each

material was chosen as the test which passed the most material to the lower layers. Sieving at

optimal amplitude for 20 min was carried out three times to give an average.

Sieving results were complemented by a sieveless particle size analysis (QicPic, Sympatec Gmbh,

Germany). The analysis is done by image analysis of digital images of a stream of particles.

Particle shape and size is determined using computer algorithms that condense irregular contour

data into usable data. The information is described by several different particle shape factors such

as Feret diameter, elongation and aspect shape.

Feeding properties The fuels were fed through a loss in weight screw feeder (K20, K-tron, Switzerland) at constant

motor speed. The continuous fuel flow was monitored 10-11 times per second on a XP 404 s

digital scale (Mettler Toledo, Columbus, Ohio) and logged on a PC. By subtracting the previous

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value, mass loss from the feeder was attained. Every 21 values were compressed into a central

moving average (CMA) (see equation (2)). The time step was chosen to 21 values (~2 seconds)

which is comparable to the residence time of the particles in an entrained flow reactor. The

standard deviation (see equation (3)) from average fuel feed was calculated using thirty

continuous CMA values over thirty CMA Values (~60 seconds.

The same was test was done to evaluate the performance of the loss in weight function with a

setpoint of 1000 grams per hour. The feeding test rig can be seen to the right of Figure 2.

Figure 2. Left: Device used to test bulk and tapped density. Middle: Sieve shaker for granulometric analysis. Right:

Rig used for feeding tests: a twin screw feeder, analytical scale and PC for logging scale output.

Results and discussion Here the results from the experiments are presented and discussed.

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Particle characterization The results from sieving analysis of the different powders are shown in Figure 3. Compared to

knife milling, hammer milling produced a much finer powder. This is in agreement with the

findings of Paulrud and Mattsson who also found that impact mills produced finer powders than

knife mills when milling spruce (Paulrud, Mattsson et al. 2002). The different hammer milled

materials were more similar to each other than the knife milled materials. Only hammer milled

torrefied spruce stood out, having a significantly smaller mass size distribution.

When visually inspecting the materials it was obvious that the sieves contained particles a lot

longer than the sieve size would allow (right of Figure 1). This has previously been observed by

Igathinathane and Pordesimo who compared the length of sieved materials with sieve size using a

sieveless particle size distribution analysis (Igathinathane, Pordesimo et al. 2009). They found

there was a large difference in the two methods since mechanical sieving is unable to sieve

particles based on length. It is a known fact that mechanical sieving sorts particles on width rather

than length (Mora, Kwan et al. 1998) which was observed to be true during the experiments

Figure 3. Cumulative mass size distribution of the biomass powders measured by sieving analysis

Cumulative number size distribution, measured by the sieveless analysis showed results

comparable with the cumulative mass size distribution. Hammer milled materials had smaller

particle sizes and the variation was larger for knife milled materials (illustrated in Figure 4 by the

minimum Feret diameter).

0

10

20

30

40

50

60

70

80

90

100

0 200 400 600 800 1000

Cu

mu

lati

ve M

ass

Pe

rce

nta

ge [

%]

Sieve mesh size [μm]

Charcoal KM

Charcoal HM

Reed Canary Grass KM

Reed Canary Grass HM

Spruce KM

Spruce HM

Torrefied Spruce KM

Torrefied Spruce HM

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Figure 4. Cumulative percentage of particles as a function of their minimum Feret diameter.

Densities, measured as bulk and tapped, are presented in Figure 5. In all cases, hammer milling

produced powders with a lower density than knife milling both for bulk and tapped densities.

With decreasing density, the Hausner ratio (see Equation (5)) increased. All fuels had Hausner

ratios indicating poor flowability.

Figure 5. Bulk and tapped densities with corresponding Hausner ratio for the eight biomass powders.

Feeding properties From the feeding tests, an expected positive correlation was found between mass flow and bulk

density since the volumetric mass flow (40 % output) was kept constant throughout the

experimental series. Powders from Norway spruce and torrefied Norway spruce followed the

theoretical mass (see equation (9)) flow of a material at bulk density whereas reed canary grass

and charcoal followed a theoretical mass flow at tapped density (Figure 6).

0

10

20

30

40

50

60

70

80

90

100

0 500 1000 1500

Cu

mu

lati

ve S

ize

Pe

rce

nta

ge [

%]

Minimum Feret [μm]

Charcoal KM

Charcoal HM

Reed Canary Grass KM

Reed Canary Grass HM

Spruce KM

Spruce HM

Torrefied Spruce KM

Torrefied Spruce HM

1.00

1.20

1.40

1.60

1.80

2.00

2.20

0

100

200

300

400

500

600H

ausn

er

Rat

io [

Tap

pe

d D

en

sity

/Bu

lk

de

nsi

ty]

De

nsi

ty [

kg/m

^3]

Bulk Density

Tapped Density

Haussner Ratio

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This difference in feeding behavior between the biomass fuels is most apparent in reed canary

grass and Norway spruce that had similar bulk and tapped densities but a large difference in mass

flow. While almost identical in tested variables (bulk density, particle mass distribution and

particle size distribution) reed canary grass had a 75% higher stable mass flow. Indicating there is

an unknown property affecting the feedability of the materials. This property would place

torrefied Norway spruce and Norway spruce in one group where the material is fed close to bulk

density. Reed canary grass and charcoal in another where material is feed closer to tapped density.

This matter needs further examination.

Figure 6. Theoretical mass flows at varying powder densities when compared to actual values if biomass powder is at

bulk or tapped density.

The mass flow of knife milled materials, except charcoal, increased or decreased at the start of

the feeding experiments before reaching a stable mass flow. The difference in initial and stable

feed rate as a percentage of the stable mass flow is shown in Table 1. A negative value indicates

decreasing mass flow and a positive value an increased mass flow. The standard deviation value at

2σ represents the most stable sixty seconds of feeding during stable flowrate.

The best feeding performance as a result of milling method could not be found . For charcoal and

Norway spruce the feedability was better for hammer milled material whereas the opposite was

seen for reed canary grass and torrefied Norway spruce.

One attribute only seen in hammer milled materials was that the mass flow changes little during

the feeding test. In knife milled material the mass flow increased (Norway spruce, reed canary

grass) or decreased (torrefied Norway spruce, charcoal) during initial feeding until reaching stable

mass flow (appendix 1). The reason for this was likely due to the stirring motion used in the

hopper that prevent bridging and rat holing. This could have important implications for processes

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

70 170 270 370 470

Stab

le m

ass

flo

w [

g/h

ou

r]

Powder density [g/dm^3]

Bulk density vs massflow HM

Bulk density vs massflow KM

Theoretical Massflow

Tapped density vs massflowHM

Tapped density vs massflowKM

1. Charcoal 2. Reed Canary grass 3. Spruce 4. Torrefied Spruce

1T 1B

2B 2T

3B 3T

4B 4T

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with short or fluctuating feeding. It has less significance for the long term stability of the feeding

since all the fuels where relatively stable after a few minutes.

Table 1. Left: Mass flow which the flow stabilized at after continuous fuel feed. Middle: Change in mass flow from

initial test until stable mass flow. Right: Smallest feeding variation during one minute of stable mass flow at +- two

standard deviations.

Fuel Powder Average stable mass flow [g/h]

Flow Change during feeding[%]1

Std +-2σ[%]2

Charcoal KM 4190 -5.0% 4.9%

Charcoal HM 3440 -7.3% 1.7% Reed Canary Grass KM 2460 13.2% 5.1% Reed Canary Grass HM 2290 1.9% 7.5%

Spruce KM 1730 28.3% 12.3%

Spruce HM 1310 -7.4% 6.8%

Torrefied Spruce KM 1090 -39.0% 5.7%

Torrefied Spruce HM 640 -0.1% 7.6% 1, 2 For raw data, see appendix 1, 2

To evaluate the difference in methods, the sieveless analysis was made looking at the width of the

particles (minimum ferret diameter. The optical sieveless analysis gave the powders particle

number size distribution seen in figure 4. As mechanical sieving sort particles on width they

should be comparable. Direct comparison isn’t possible however a relative comparison between

the different materials can be made. The fuels with the most fibrous and long particles, reed

canary grass and Norway spruce had striking similarities with the particle mass size distribution.

This was not the case for the rounder particles found in charcoal and torrefied Norway spruce. It

seems digital image analysis is a good alternative method to mechanical sieving, however only if

there is a large difference in the length and width of the particle.

The best feeding properties were, as expected, with the charcoal tests. However this might be a

result of the higher mass flow as it allows for larger variation in weight. For example a 50 g

variation in a 500 g/h mass flow gives the same standard deviation as 500g variation in a 5000g/h

mass flow. This can be seen when comparing appendix 2 and right column of table 1. More

experiments should be performed where the mass flow is kept constant while the speed of the

screw is varied. This would give better comparison of feedability when feeding the biomass fuels

at similar feed rates.

On the performance of the Ktron K20 loss in weight feeder it managed to successfully feed all the

materials with varying success. However the feeding characteristics of the powders couldn’t be

determined. Feeding performance couldn’t be distinguished from the closed loop performance (7)

making it impossible to make conclusions based on fuel powder. The difficulty of feeding the

materials when comparing knife milled and hammer milled gave almost the same result. Hammer

milled charcoal and Norway spruce performed better than its knife milled counterpart and the

opposite for reed canary grass. The feeding stability of the torrefied materials where equal for the

knife and hammer milled material. The data can be found in appendix 3.

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Conclusions The difference between the two milling methods showed that there is a large difference in flow

properties due to milling method.

-Hammer mills produce finer biomass powders then knife mills when particle size is

determined by a screen size

-Powders produced in ihammer mills have similar particle mass size distribution except

for torrefied Norway spruce

-Bulk and tapped density decrease with finer powders

-Hausner ratio increased with decreasing density

-All materials tested had a Hausner ratio indicating poor flowability

These results where conclusive for all of the biomass materials which indicate that this should be

of consideration when choosing milling method. Especially when grinding brittle materials the

impact mill produced powders far smaller than the screen size would indicate. Mechanical sieving

sorting particles on width has one important implication. When using a screen size for milling

biomass materials, length will not be restricted by the screen size, producing particles far larger

than the screen size would indicate.

While the effect of milling method on long term feeding performance was largely inconclusive it

was found that:

-Hammer milled materials are easier to feed initially as they change less in mass flow

during initial feeding when compared to knife milled materials

-Reed Canary grass and charcoal at stable mass flow have close to tapped density when

fed while torrefied Norway spruce and Norway spruce are closer to bulk density

The reason for this behavior needs to be examined further as none of the variables tested

explained this behavior.

The K20 feeder could successfully feed all the different biomass powder with acceptable

performance. This is impressive considering all of the fuels indicated very poor flowability and in

some cases both low bulk densities and high Hausner ratio.

Acknowledgement Thanks to Per Holmgren for exchanging ideas and analyzing sieving results. Thanks to BTC and

their personal for letting me use their mills, materials and equipment. BioEnDev AB is

acknowledged for kindly supplying the torrefied spruce that was treated in their 20 kg/h pilot

scale torrefaction reactor.

Big thanks to my supervisors Sylvia Larsson and Markus Broström for their continued support

and ideas in everything during the thesis. Their exceptional effort at the end of the project

allowed me to complete the thesis in time.

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Appendix 1

Figure 7. Central moving average of mass flow over ~one minute for hammer milled Charcoal. The mass flow

decreases before reaching stable mass flow.

Figure 8 Central moving average of mass flow over ~one minute for knife milled Charcoal. The mass flow decreases

before reaching stable mass flow.

Figure 9. Central moving average of mass flow over ~one minute for hammer milled torrefied Norway Spruce. The

mass flow decreases slightly from start to finish on all tests.

3400.00

3450.00

3500.00

3550.00

3600.00

3650.00

3700.00

1

64

12

7

19

0

25

3

31

6

37

9

44

2

50

5

56

8

63

1

69

4

75

7

82

0

88

3

94

6

10

09

10

72

11

35

11

98

12

61

13

24

13

87

14

50

15

13

15

76

16

39

17

02

17

65

Test 1

Test 2

Test 3

4100.00

4150.00

4200.00

4250.00

4300.00

4350.00

4400.00

4450.00

4500.00

1

43

85

12

7

16

9

21

1

25

3

29

5

33

7

37

9

42

1

46

3

50

5

54

7

58

9

63

1

67

3

71

5

75

7

79

9

84

1

88

3

92

5

96

7

10

09

10

51

10

93

11

35

11

77

12

19

12

61

13

03

13

45

Test 1

Test 2

Test 3

550.00

570.00

590.00

610.00

630.00

650.00

670.00

690.00

11

90

37

95

68

75

79

46

11

35

13

24

15

13

17

02

18

91

20

80

22

69

24

58

26

47

28

36

30

25

32

14

34

03

35

92

37

81

39

70

41

59

43

48

45

37

47

26

49

15

51

04

52

93

54

82

56

71

Test 1

Test 2

Test 3

Spring Term 2013




Figure 10. Central moving average of mass flow over ~one minute for knife milled torrefied Norway Spruce. The mass

flow decreases by a large amount before reaching stable mass flow.

Figure 11. Central moving average of mass flow over ~one minute for hammer milled reed canary grass. The mass

flow is stable during the experiment.

Figure 12. Central moving average of mass flow over ~one minute for knife milled reed canary grass. The mass flow

increases before reaching stable mass flow.

1000.00

1100.00

1200.00

1300.00

1400.00

1500.00

1600.00

11

69

33

75

05

67

38

41

10

09

11

77

13

45

15

13

16

81

18

49

20

17

21

85

23

53

25

21

26

89

28

57

30

25

31

93

33

61

35

29

36

97

38

65

40

33

42

01

43

69

45

37

47

05

48

73

50

41

52

09

53

77

55

45

57

13

Test 1

Test 2

Test 3

2200.00

2220.00

2240.00

2260.00

2280.00

2300.00

2320.00

2340.00

2360.00

2380.00

2400.00

14

38

51

27

16

92

11

25

32

95

33

73

79

42

14

63

50

55

47

58

96

31

67

37

15

75

77

99

84

18

83

92

59

67

10

09

10

51

10

93

11

35

11

77

12

19

12

61

13

03

13

45

13

87

14

29

14

71

15

13

15

55

15

97

16

39

16

81

17

23

17

65

18

07

18

49

18

91

19

33

19

75

20

17

20

59

21

01

21

43

21

85

22

27

22

69

23

11

23

53

23

95

24

37

24

79

25

21

25

63

26

05

26

47

26

89

27

31

27

73

28

15

28

57

28

99

29

41

29

83

30

25

30

67

Test 1

Test 2

Test 3

2100.00

2150.00

2200.00

2250.00

2300.00

2350.00

2400.00

2450.00

2500.00

2550.00

2600.00

18

5

16

92

53

33

74

21

50

55

89

67

37

57

84

19

25

10

09

10

93

11

77

12

61

13

45

14

29

15

13

15

97

16

81

17

65

18

49

19

33

20

17

21

01

21

85

22

69

23

53

24

37

25

21

26

05

26

89

27

73

28

57

29

41

30

25

Test 1

Test 2

Test 3

Spring Term 2013




Figure 13. Central moving average of mass flow over ~one minute for hammer milled Norway spruce. The mass flow

decreases slightly from start to finish on all tests.

Figure 14. Central moving average of mass flow over ~one minute for knife milled Norway spruce. The mass flow


1200.00

1250.00

1300.00

1350.00

1400.00

1450.00

1500.00

1

16

9

33

7

50

5

67

3

84

1

10

09

11

77

13

45

15

13

16

81

18

49

20

17

21

85

23

53

25

21

26

89

28

57

30

25

31

93

33

61

35

29

36

97

38

65

40

33

42

01

43

69

45

37

47

05

48

73

50

41

52

09

53

77

55

45

57

13

Test 1

Test 2

Test 3

1200.00

1300.00

1400.00

1500.00

1600.00

1700.00

1800.00

1900.00

1

16

9

33

7

50

5

67

3

84

1

10

09

11

77

13

45

15

13

16

81

18

49

20

17

21

85

23

53

25

21

26

89

28

57

30

25

31

93

33

61

35

29

36

97

38

65

40

33

42

01

43

69

45

37

47

05

48

73

50

41

Test 1

Test 2

Test 3

Spring Term 2013




Appendix 2 Thirty continuous central moving average values are combined to calculate the standard deviation.

Figure 15. Central moving average of mass flow over ~two seconds for hammer milled charcoal. The mass flow

decreases before reaching stable mass flow

Figure 16. Central moving average of mass flow over ~two seconds for knife milled Charcoal. The mass flow decreases

before reaching stable mass flow.

Figure 17. Central moving average of mass flow over ~two seconds for hammer milled torrefied Norway spruce. The

mass flow decreases slightly from start to finish on all tests.

3000.00

3200.00

3400.00

3600.00

3800.00

4000.00

0 500 1000 1500 2000 2500

Test 1

Test 2

Test 3

3900.00

4000.00

4100.00

4200.00

4300.00

4400.00

4500.00

0 500 1000 1500 2000

Test 1

Test 2

Test 3

500.00

550.00

600.00

650.00

700.00

750.00

800.00

0 1000 2000 3000 4000 5000 6000 7000 8000

Test 1

Test 2

test 3

Spring Term 2013




Figure 18. Central moving average of mass flow over ~ two seconds for knife milled torrefied Norway Spruce. The

mass flow decreases by a large amount before reaching stable mass flow.

Figure 19. Central moving average of mass flow over ~ two seconds for hammer milled reed canary grass. The mass

flow is stable during the experiment.

Figure 20. Central moving average of mass flow over ~ two seconds for knife milled reed canary grass. The mass flow


800.00

900.00

1000.00

1100.00

1200.00

1300.00

1400.00

1500.00

1600.00

1700.00

0 1000 2000 3000 4000 5000 6000 7000 8000

Test 1

Test 2

Test 3

1900.00

2000.00

2100.00

2200.00

2300.00

2400.00

2500.00

2600.00

2700.00

0 500 1000 1500 2000 2500 3000 3500 4000

Test 1

Test 2

Test 3

1900.00

2000.00

2100.00

2200.00

2300.00

2400.00

2500.00

2600.00

2700.00

2800.00

0 500 1000 1500 2000 2500 3000 3500 4000

Test 1

Test 2

Test 3

Spring Term 2013




Figure 21. Central moving average of mass flow over ~ two seconds for hammer milled Norway spruce. The mass flow

decreases slightly from start to finish on all tests.

Figur 22. Central moving average of mass flow over ~ two seconds for knife milled Norway spruce. The mass flow


1000.00

1100.00

1200.00

1300.00

1400.00

1500.00

1600.00

0 1000 2000 3000 4000 5000 6000 7000

Test 1

Test 2

Test 3

1000.00

1200.00

1400.00

1600.00

1800.00

2000.00

2200.00

0 1000 2000 3000 4000 5000 6000

Test 1

Test 2

Test 3

Spring Term 2013




Appendix 3 Table 2

Fuel Powder Average flow rate [g/h] Stdev 2σ [%]

Spruce HM 1012 8,4%

Torrefied Spruce KM 1003 8,7%

Charcoal HM 1011 9,1%

Torrefied Spruce HM 981 9,2%

Charcoal KM 1013 10,4%

Reed Canary Grass KM 1007 11,2%

Reed Canary grass HM 1038 13,4%

Spruce KM 1026 17,4%

Particle and feeding characteristics627253/...H = Hausner ratio [ ] ρ T = Tapped density [kg/m3] ρ...

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