Particle and feeding characteristics of biomass powders

Spring Term 2013 Master Thesis, 30 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.

Spring Term 2013

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

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 2020

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

Spring Term 2013

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]

x

= Weight at time t [g]

X

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

avg

= Average flowrate of the previous 30 X

[g/h]

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

H = Hausner ratio [ ]

ρ

= Tapped density [kg/m

]

ρ

= Loose density [kg/m

]

actual

= Actual mass flow from feeder [g/h]

t = time [s]

K

= Proportional gain [ ]

Spring Term 2013

K

= Integral gain [ ]

K

= Derivate gain [ ]

τ = Variable of integration [ ]

theoretical

= Theoretical massflow at density ρ [g/h]

= olumetric massflow at

[m

/h]

%

= Percentage of max screw speed [%]

= Minimum volumetric massflow [m

/h]

= Maximum volumetric massflow [m

/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

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

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

Spring Term 2013

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%.

Spring Term 2013

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 cm

). 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

Spring Term 2013

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.

Spring Term 2013

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

Cumulative Mass Percentage [%]

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

Spring Term 2013

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

Cumulative Size Percentage [%]

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

0 100 200 300 400 500 600

Hausner Ratio [Tapped Density/Bulk density]

Density [kg/m^3]

Bulk Density Tapped Density Haussner Ratio

Spring Term 2013

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

Stable mass flow [g/hour]

Powder density [g/dm^3]

Bulk density vs massflow HM

Bulk density vs massflow KM

Theoretical Massflow

Tapped density vs massflow HM

Tapped density vs massflow KM

1. Charcoal

2. Reed Canary grass 3. Spruce

4. Torrefied Spruce 1B 1T

2B 2T

3B 3T

4B 4T

Spring Term 2013

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[%]

Std +- 2σ[%]

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.

Spring Term 2013

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.

References

Abdullah, H. and H. W. Wu (2009). "Biochar as a Fuel: 1. Properties and Grindability of Biochars Produced from the Pyrolysis of Mallee Wood under Slow-Heating Conditions." Energy &

Fuels 23(8): 4174-4181.

Agency, E. E. (2012). Electricity production by fuel (ENER 027) - Assessment published Apr 2012, European Enviroment Agency.

Cadoche, L. and G. D. Lopez (1989). "Assessment of size-reduction as a preliminary step in the production of ethanol from lignocellulosic wastes." Biological Wastes 30(2): 153-157.

Caputo, A. C., M. Palumbo, et al. (2005). "Economics of biomass energy utilization in combustion and

gasification plants: effects of logistic variables." Biomass & Bioenergy 28(1): 35-51.

Spring Term 2013

Cleary, P. W. (2008). "The effect of particle shape on simple shear flows." Powder Technology 179(3): 144-163.

Cleary, P. W. and M. L. Sawley (2002). "DEM modelling of industrial granular flows: 3D case studies and the effect of particle shape on hopper discharge." Applied Mathematical Modelling 26(2):

89-111.

Dai, J. J., H. P. Cui, et al. (2012). "Biomass feeding for thermochemical reactors." Progress in Energy and Combustion Science 38(5): 716-736.

Geldart, D., N. Harnby, et al. (1984). "Fluidization of cohesive powders." Powder Technology 37(JAN-): 25-37.

Guo, Q., X. L. Chen, et al. (2012). "Experimental research on shape and size distribution of biomass particle." Fuel 94(1): 551-555.

Hann, D. and J. Strazisar (2007). "Influence of particle size distribution, moisture content, and particle shape on the flow properties of bulk solids." Instrumentation Science & Technology 35(5):

571-584.

Igathinathane, C., L. O. Pordesimo, et al. (2009). "Sieveless particle size distribution analysis of particulate materials through computer vision." Computers and Electronics in Agriculture 66(2): 147-158.

Lu, H., E. Ip, et al. (2010). "Effects of particle shape and size on devolatilization of biomass particle."

Fuel 89(5): 1156-1168.

McKendry, P. (2002). "Energy production from biomass (part 2): conversion technologies."

Bioresource Technology 83(1): 47-54.

Mora, C. F., A. K. H. Kwan, et al. (1998). "Particle size distribution analysis of coarse aggregate using digital image processing." Cement and Concrete Research 28(6): 921-932.

Parlament, T. E. (2011). "Communication from the commision to the European parlament, the council, the European economics and social committee and the committee of the regions

", from http://ec.europa.eu/energy/energy2020/roadmap/doc/com_2011_8852_en.pdf.

Paulrud, S., J. E. Mattsson, et al. (2002). "Particle and handling characteristics of wood fuel powder:

effects of different mills." Fuel Processing Technology 76(1): 23-39.

Paulrud, S. and C. Nilsson (2004). "The effects of particle characteristics on emissions from burning wood fuel powder." Fuel 83(7-8): 813-821.

Podczeck, F. and Y. Miah (1996). "The influence of particle size and shape on the angle of internal friction and the flow factor of unlubricated and lubricated powders." International Journal of Pharmaceutics 144(2): 187-194.

Ragauskas, A. J., C. K. Williams, et al. (2006). "The path forward for biofuels and biomaterials."

Science 311(5760): 484-489.

Savolainen, K. (2003). "Co-firing of biomass in coal-fired utility boilers." Applied Energy 74(3-4):

369-381.

Tillman, D. A. (2000). "Biomass cofiring: the technology, the experience, the combustion

consequences." Biomass & Bioenergy 19(6): 365-384.

Spring Term 2013

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 64 127 190 253 316 379 442 505 568 631 694 757 820 883 946 1009 1072 1135 1198 1261 1324 1387 1450 1513 1576 1639 1702 1765

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 85 127 169 211 253 295 337 379 421 463 505 547 589 631 673 715 757 799 841 883 925 967 1009 1051 1093 1135 1177 1219 1261 1303 1345

Test 1 Test 2 Test 3

550.00 570.00 590.00 610.00 630.00 650.00 670.00 690.00

1 190 379 568 757 946 1135 1324 1513 1702 1891 2080 2269 2458 2647 2836 3025 3214 3403 3592 3781 3970 4159 4348 4537 4726 4915 5104 5293 5482 5671

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

1 169 337 505 673 841 1009 1177 1345 1513 1681 1849 2017 2185 2353 2521 2689 2857 3025 3193 3361 3529 3697 3865 4033 4201 4369 4537 4705 4873 5041 5209 5377 5545 5713

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

1 43 85 127 169 211 253 295 337 379 421 463 505 547 589 631 673 715 757 799 841 883 925 967 1009 1051 1093 1135 1177 1219 1261 1303 1345 1387 1429 1471 1513 1555 1597 1639 1681 1723 1765 1807 1849 1891 1933 1975 2017 2059 2101 2143 2185 2227 2269 2311 2353 2395 2437 2479 2521 2563 2605 2647 2689 2731 2773 2815 2857 2899 2941 2983 3025 3067

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

1 85 169 253 337 421 505 589 673 757 841 925 1009 1093 1177 1261 1345 1429 1513 1597 1681 1765 1849 1933 2017 2101 2185 2269 2353 2437 2521 2605 2689 2773 2857 2941 3025

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 increases before reaching stable mass flow.

1200.00 1250.00 1300.00 1350.00 1400.00 1450.00 1500.00

1 169 337 505 673 841 1009 1177 1345 1513 1681 1849 2017 2185 2353 2521 2689 2857 3025 3193 3361 3529 3697 3865 4033 4201 4369 4537 4705 4873 5041 5209 5377 5545 5713

Test 1 Test 2 Test 3

1200.00 1300.00 1400.00 1500.00 1600.00 1700.00 1800.00 1900.00

1 169 337 505 673 841 1009 1177 1345 1513 1681 1849 2017 2185 2353 2521 2689 2857 3025 3193 3361 3529 3697 3865 4033 4201 4369 4537 4705 4873 5041

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 increases before reaching stable 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 increases before reaching stable 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%