“Energy requirements for comminution of
fibrous materials - qualitative chipping
model”
Växjö, 26.05.2011
Degree project in Bioenergy technology 2BT01E
Supervisor: Professor Björn Zethraeus, Linnaeus University, Bioenergy Technology department
Author: Łukasz Niedźwiecki
Organisation/ Organization
Linnéuniversitetet
Institutionen för teknik
Författare/Author(s)
Łukasz Niedźwiecki
Linnaeus University
School of Engineering
Dokumenttyp/Type of Document
Examinator/examiner
Examensarbete/Diploma Work
Handledare/tutor
Professor Björn Zethraeus
Titel och undertitel/Title and subtitle
Energy requirements for comminution of fibrous materials - qualitative chipping model
Abstract
This paper aims to derive qualitative model for energy requirements for wood chipping
process. There is relationship shown between energy requirements and properties of
biomass, which is quite variable material. Relationship between comminution machinery
and energy necessary for the process is highlighted. Derivation of the model is focused
on chipping but in general it’s possible, to make it available both for different types of
biomass (f. ex. agricultural residues) or for different type of comminution machinery (f.
ex. hammermills) just by using different material properties adjusted to machinery
mechanics. Properties used in derivation are mend to be easy to measure. Model is
mend to be used as a base for quantitative model that, thanks to measurements
performed on real comminution machinery and using wood with known properties, could
give answers for two important questions:
•
Would hypothetical changes in desired size of output material increase total
system efficiency, taking into consideration lowest efficiency of combustion
process (i. ex. higher amounts of unburned fuel)?
•
How to optimise comminution as an operation in biofuel supply chain, with
respect to energy used for the process?
Key Words
Biomass, wood, comminution, specific energy, total specific energy, effective specific
energy, chipping, chipper, moisture content, hardness, density.
Utgivningsår/Year of issue
Språk/Language
Antal sidor/Number of pages
English
63
2011
Internet/WWW
http://www.lnu.se
ii
Acknowledgements:
I’d like to thank Professor Björn Zethraeus, for his great support for me during writing this
thesis and substantial amount of time spent on giving valuable comments that contributed final
outcome of that thesis.
Łukasz Niedźwiecki
iii
School of Engineering
351 95 Växjö
tel 0772-28 80 00, fax 0470-76 85 40
iv
Table of contents
1. Introduction ………………....................…………………….......................... 1
1.1
1.2
1.3
1.4
1.5
General
....................................................................................................... 1
Comminution as one unit operation in the Biofuel supply chain..................... 2
Structure of biomass (wood) ......................................................................... 4
Elementary mechanics in the comminution process .............................................. 11
Comminution machinery ................................................................................ 14
2. Model introduction ………………………………………............................... 19
2.1
2.2
2.3
2.4
The reason for making model ......................................................................... 19
Models valid for brittle materials ........................................................................ 20
Identification of reliable parameters for the model ............................................... 23
Measuring the specific energy .............................................................................. 35
3. Qualitative chipping model ............................................................ 38
3.1 Derivation of the qualitative model for chipping ................................................... 38
4. Results and discussion .................................................................... 43
4.1 Coefficients for the equations ............................................................................... 43
5. Conclusions .................................................................................... 46
Bibliography ........................................................................................................... 47
APPENDIX A - different classifications of biomass comminution equipment .................... 50
APPENDIX B - technical specification of properties for solid biofuels ............................... 53
APPENDIX C - Janka Hardness and Dry density for some Softwoods and Hardwoods ..... 56
APPENDIX D - Janka Hardness and Moisture Content ....................................................... 59
APPENDIX E - different models of chippers and their basic parameters .......................... 62
v
1. Introduction
1.1 General
Comminution is a process in which solid materials are reduced in size. Fibre is a morphological
term for a substance characterised by its’ high ratio of length to cross sectional area, fineness and
flexibility.
Fibrous material is that kind of material that consist of fibres. In most of the cases fibrous
materials that are being comminuted are composite materials. These are materials that consist of
two or more constituent materials which have significantly different properties and remain separate
and distinct within the structure. Properties of the composite material are determined not only by
the constituents, but also by the way that they are combined.
Comminution of fibrous materials has many different applications. Usually comminuted fibrous
materials are of biological origin. Main reason for comminution is enabling bigger surface of
comminuted materials necessary for further processing.
The most common applications are:
• Food industry - comminution of food in order to enable highest possible surface of
ingredients in order to perform the most efficient and effective reaction between them. It
should be mentioned that eating process itself also starts with a comminution. People chew
food to enable new surface for digestion enzymes. Most of the people had an opportunity to
find out how does digestion reaction proceed in their stomach if they do not chew food
properly (especially one that is hard to digest).
• Pulp and paper industry - paper is made of cellulose fibres from ligno-cellulosic biomass
(wood). The goal is to keep the fibres unharmed as much as possible. Though they need to
be separated from hemicelluloses and lignin. In order to make that separation possible, by
chemical and thermal reaction or mechanical actions, more surface has to be enabled for
the process.
• Particleboard industry - comminution is made both in order to get the new surface for
adhesives, and to achieve relatively uniform size of the particles.
• Bioenergy - comminution is important in order to enable new surface either for biofuel
upgrade like gasification (conversion via chemical reactions) or for better and more
complete combustion (combustion is also chemical reaction). It’s also necessary for other
type of fuel upgrade - pelletizing. It’s a physical process and in general it’s about biomass
compaction. To make compaction possible structure needs to be broken down first.
This paper focus is mainly on woody biomass comminution for Bioenergy applications.
According to (I. M. Petre, 2006) there are three distinguished results of biomass comminution:
a) particle sizing and classifying (coarse and intermediate size reduction)
b) particle shaping
c) breaking connections between different material components
-1-
1.2 Comminution as one unit operation in the Biofuel supply chain
When biomass is used as an energy source in most of the cases comminution is necessary. It
is possible to use biomass in the forms of the full logs, and it has been done in a small scale home
appliances. But because of the low efficiency and other problems like high level of CO and volatile
emissions it’s definitely not recommended option.
It’s justified to say that comminution is placed in biofuel supply chain and it’s always placed
in-between biomass harvest and combustion stage. As previously stated some form of comminution
is necessary to achieve efficient combustion. It goes well with common sense because combustion is
a chemical reaction and comminution enables new surface for that reaction to happen so achieving
better efficiency of the reaction is totally logical conclusion.
In general any other operations between biomass harvest and utilisation are aiming in
enabling biomass to be used by the technology of the device where biomass is utilised - mostly
boiler. The goal is to utilise it in the most efficient way. Combustion reaction seems to be quite
simple when one uses macroscopic approach and analyses input and output only, without detailed
look into things that happen inside reactor - namely combustion chamber. To make reaction happen
two reactants must be at hand - fuel and oxygen. Both need to be delivered into reactor in a way
that allows to control amount of both in order to control the reaction.
To make it work proper feeding mechanism is necessary. That’s the main place in the supply
chain where comminution is necessary. Size of output material has to be adjusted to the feeding
mechanism - utilising device technology. In case when next stage of supply chain is not combustion
but for example densification of biomass, in order to make transportation more efficient by f. ex.
pelletizing, same general rule applies. It’s because pelletizer has acceptable size range for biomass
particles and only within that range can make his work.
On the other side of the comminution as an operation there is input size of the material.
That depends highly on technology of the comminution device itself and would be a subject of more
detailed discussion in further chapters of this paper.
It’s possible that size difference between material from the first operation (harvest) and final
operation is too big and more than one operation of comminution need to be introduced because
there is no suitable comminution device that can handle that difference singlehandly. There is also a
possibility that second stage of comminution is introduced separately in order to use residues from
the main process (Fig. 1.1).
Figure 1.1 - Example of placing comminution operations in supply chain (L.J. Naimi, 2006)
-2-
In general no operations are 100% efficient and there are always residues available. Residues
are present at basically every stage - even harvest. Ratio of residues to output material is very
operation dependent. In some case amount of residues is big enough to make usage of those
residues profitable.
It seems necessary to mention that need of the comminution might not be determined by
purely technical matters. Sometimes comminution is chosen only to introduce residues into existing
technology and is a cheaper substitute for right choice of the final utilisation unit. in order to reduce
investment cost.
Table 1.1 - Different type of devices utilising biomass with respect to the input material requirements (L.J.
Naimi, 2006)
Table 1.1 shows some examples of input material size and properties for different devices. It
shows high variability in terms of the acceptable input size. Other thing it shows is high variability in
required moisture content. That means the drying as an operation in supply chain could also be
present. That also indicates that biomass is highly variable material generally speaking.
One of the main question this thesis aims to answer is an existence of qualitative way to
determine possibility to optimize biofuel supply chain by lowering energy consumption during the
comminution stage.
-3-
1.3 Structure of biomass (wood)
Biomass has a composite structure. It consists of fibres which are made of cellulose and matrix
which binds fibres together. Matrix is hemicelluloses and in case of ligno-cellulosic (woody) biomass
also lignin. Biomass is highly anisotropic material which means that it has different properties,
strongly depending on coordinates - namely fibre (cell wall) direction.
The most important thing about wood that should be understood is a basic fact that it has
evolved for millions of years to serve three main functions in a plant as an organism (U.S. Forest
Products Labolatory, 2010):
• conduction of water from the roots to the leaves as well as nutrients
• mechanical support of the plant body
• storage of bio-chemicals
“There is no property of wood, no matter physical, mechanical, chemical, biological or
technological - that is not fundamentally derived from the fact that wood is formed to meet the
needs of the living tree. By understanding the function of wood in the living tree we, we can better
understand the strengths and limitation it presents.” (U.S. Forest Products Labolatory, 2010)
In most of the cases wood is used as a material in terms of trees, when stumps and leaves are
usually not utilised. In Bioenergy segment this statement is also true and in case of herbaceous
biomass stalk is the main part being used (straw) and although it looks little bit different it’s
designed by nature to meet the similar needs. Properties concerning comminution of woody
biomass are to some extend true also for other types of biomass as well as other fibrous materials
which are mostly of biomass origin.
Trunk of the tree (stem) is composed of various materials present in the concentric bands (U.S.
Forest Products Labolatory, 2010):
• Outer bark (Fig. 1.2 - ob) provides mechanical protection of the softer inner bark and also
helps to limit evaporative water loss.
• Inner bark (Fig. 1.2 - ib) it’s the tissue through which sugars (food) produced by
photosynthesis are translocated from the leaves to the roots or growing parts of the tree.
Minerals and nutrients are also transported from the roots to the green parts.
• Vascular cambium (Fig. 1.2 - vc) is the layer between bark and the wood that produces both
of these tissues each year.
• Sapwood the active tissue which is responsible not only conduction of sap and water but
also for storage and synthesis of photosynthate like starch and lipids.
• Heartwood is a darker-coloured wood in the middle of most trees. It’s not conductive and
functions as a long term storage of biochemicals (extractives). Extractives are formed by
parenchyma cells at the heartwood-sapwood boundary and then exuded through pits into
adjacent cells [ (U.S. Forest Products Labolatory, 2010) refers to Hillis 1996].
• Pitch (Fig. 1.6 - p) is located at the very centre of the trunk and is the remnant of early
growth of the trunk before it was formed.
-4-
Figure 1.2 - Macroscopic view of a transverse section of a trunk (U.S. Forest Products Labolatory, 2010)
Among the woody biomass we can distinguish two major types softwood and hardwood.
Softwood are those species that come from gymnosperms (mostly coniferous). They have more
simple basic structure than hardwoods because they have only two cell types and relatively little
variation in structure between these cell types.
Hardwoods come from angiosperm. They are much more complicated in terms of their structure
because they have greater number of basic cell types and far greater degree of variability within the
cell types.
There are two basic cell orientation systems in wood structure - axial and radial. Axial cells
have their long axes running parallel to the long axis of the organ (stem). It’s being used as a long
distance transport. Radial cells are oriented like radius in a circle, from pitch to the bark.
Figure 1.3 - Growth of wood scheme (J.M. Dinwoodie, 1996)
-5-
In wood science there are three main perspectives distinguished that are being used in
description of wood:
•
•
•
Transverse plane of section (the cross section) which shows face that is exposed when a tree
is cut down (Fig. 1.5 - H).
Radial plane runs in pitch to bark direction and is parallel to the axial system. It provides
information about longitudinal changes in the stem from pith to bark (Fig. 1.5 - A).
Tangential plane is parallel to any tangent line that would touch the cylinder and it goes
along the length of the cylinder (Fig. 1.5 - A).
Other concept which is often used in wood science descriptions is grain. It’s a direction of
longitude axis of cell walls which is in most cases parallel to the longitude axis of a stem.
Figure 1.4 - Different sections of wood (J.M. Dinwoodie, 1996)
Cell wall give wood majority of its’ properties (U.S. Forest Products Labolatory, 2010), (J.M.
Dinwoodie, 1996).
It consists of three main regions:
• middle lamella
• primary wall
• secondary wall (S1, S2 and S3 layers)
-6-
Figure 1.5 - Macroscopic and microscopic view of different planes in the wood (U.S. Forest Products Labolatory,
2010)
-7-
Figure 1.6 - Cut away drawing of cell wall (U.S. Forest Products Labolatory, 2010)
In each region cell wall consists of three major components: cellulose, hemicelluloses and lignin.
Cellulose contains repeating units of β 1-4 linked D-glucose - is a glucose polymer. Number
of glucose units (degree of polymerisation) is variable and depends on the region of the cell. In
secondary cell wall it could be 8 000 - 10 000 [ (Dinwoodie, 2000) refers to Goring and Timell 1962],
while in primary cell wall degree of polymerisation varies between 2 000 and 4000 [ (Dinwoodie,
2000) refers to Simson and Timell 1978]. Cellulose is a core and dominant in quantity part of
microfibrill which have threadlike shape. Cellulose mostly formed in crystalline structures is binded
with hemicelluloses, with lignin on the outer surface. Microfibrills are differently oriented in
different parts of cell wall and they may have different angle of orientation with respect to the cell
long axis.
Figure 1.7 - Models of a microfibrill (Dinwoodie, 2000)
-8-
Table 1.2 -Microfibrillar orientation and percentage thickness of the cell wall layers in spruce (Picea abies)
(Dinwoodie, 2000)
Wall layer
Approximate thickness (%)
Angle to longitudal axis
P
S1
S2
S3
3
10
85
2
random
50° ÷ 70°
10° ÷ 30°
60° ÷ 90°
Cell wall has a composite structure itself - microfibrills (that consist mainly of cellulose) are
placed in the matrix that consist of hemicelluloses and lignin (Fig 1.7).
Table 1.3 - Chemical composition of wood (Dinwoodie, 2000)
Mass
Component
Softwood (%)
Polymeric state
Molecular
derivatives
Function
glucose
fibre
Hardwood (%)
Cellulose
42 ±2
45 ±2
crystalline,
highly oriented,
large linear
molecule
Hemicellulose
27 ±2
30 ±5
semicrystalline,
smaller
molecule
galactose,
mannose,
xylose
matrix
20 ±4
amorphous,
large 3-D
molecule
phenylpropa
ne
matrix
5 ±2
principally
compounds
soluble in
organic solvents
terpenes,
polyphenols,
stilbenoids
extraneous
Lignin
Extractives
28 ±3
3 ±2
Hemicellulose is heterogeneous class of polymers containing glucose, galactose, mannose, xylose
and other sugars (A. Bruce, 1998). Both degree of crystallisation and the degree of polymerisation
(approx. 200) of hemicellulose are generally low (Dinwoodie, 2000).
Lignin is a complex, three dimensional, aromatic molecule that consists of phenyl groups. It is non
crystalline, hydrophobic and its’ main constituent of composite matrix of woody biomass. Lignin is a
brittle material and its’ presence in middle lamella provides adhesion between the cells.
The primary wall is characterised by random orientation of cellulose microfibrills, where any
microfibrill angle from 0° to 90° with respect to long axis of the cell, ma be present. In cells in wood
the primary cell wall is thin and generally speaking indistinguishable from the middle lamella. Middle
lamella of two adjacent cells cannot be cannot be distinguished (U.S. Forest Products Labolatory,
2010).
-9-
The remaining cell wall domain is called secondary cell wall. It’s composed of three layers:
S1 is characterised by high microfibrill angles and is quite thin. Cellulose microfibrills are laid
down in a helical fashion and the angle between the mean microfibrill direction and the long axis of
the cell is between 50° to 70°.
The next layer - S2 - is arguably the most important cell wall layer in determining the
properties of the cell and, thus, the wood properties at a macroscopic level [ (U.S. Forest Products
Labolatory, 2010) refers to Panshin and deZeeuw 1980 and Kretschmann and others 1998]. This is
the thickest secondary cell wall layer. It’s characterised by a lower percentage of lignin and a low
microfibrill angle - 5° to 30°.
S3 is a relatively thin layer with high microfibrill angle and the lowest percentage of the
lignin. It’s because there has to be adhesion between the water molecules and the cell walls to
conduct water. Lignin is a hydrophobic macromolecule so its low concentration in S3 makes
adhesion of water possible and thus facilitates transpiration (U.S. Forest Products Labolatory, 2010).
It seems to be quite evident that properties of wood as a material would have ultimate
meaning in terms of energy expense in the comminution process. It is quite clear that woods’
mechanical properties are highly determined by its’ fibrous and porous structure.
Figure 1.8 - The transverse and tangential–longitudinal faces of Sitka spruce. Microscope magnification x60
(Moore, 2011)
- 10 -
1.4 Elementary mechanics in the comminution process .
Reduction of the material’s particle size means that large particles or lumps are fractured
into smaller particles. Fractures have to be initiated i.e. external forces have to be applied to the
particle. The actual size reduction depends on the amount of stress applied to the particle, the rate
at which it’s applied and the manner in which it’s applied (Size reduction solutions for hard to reduce
materials, 2002).
It’s well known from material sciences that there three fundamental types of stresses:
compression, tension and shear. It happens a lot that they occur in a kind of typical configuration
that could be distinguished from any other. Bending might be considered as one of them - in
microscopic scale it’s just combination on compression stresses on one side of the material sample
and tension stress on the other. Since it’s easy to distinguish and appearance in real life cases is
pretty common, bending stress is recognised in material science.
There are few types of actions that may be used to apply stress necessary to inflict fracture
to the particle. Each of them is a combination of fundamental stresses. They could be distinguished
during conceptual studies, although it’s not so easy in terms of real life comminution machinery,
since they tend to occur together during the process. This would be discussed further in the thesis in
the part that describes comminution machineries at present.
One may distinguish (I. M. Petre, 2006):
• cutting
• shearing
• tearing
• impact stress
• compression and friction (f. ex. in a disc milling)
Comminution process in any of machinery available nowadays involves at least one. Usually
it’s a combination of few. There is no possibility at present to quantify the exact influence from each
of the actions in real device comminution process, but seems possible to estimate which could be
dominant just by analyzing geometry of the tools in a comminution device and the way they interact
with comminuted material.
Figure 1.9 - Types of actions and corresponding particle shapes (I. M. Petre, 2006)
- 11 -
Cutting:
The difference between cutting and shearing is defined by both the amount of deformation
that occurs in the cross-section of the material and the way stress is being applied. Stress applied in
direction parallel to the surface unit vector (perpendicular to the surface) by sharp knife edge is
usually very big (very small surface where the force is applied). Fracture of the material is the result
of splitting effect of the knife. Deformation of the material occurs locally and progressively, close to
the tool tip and as e result cross-section of cut material is relatively smooth [ (I. M. Petre,
2006)refers to Schubert and Bernotat 2004; Woldt et al. 2004]. That is the ideal case of cutting,
where shear stress and tensile stress are applied locally, near the edge of a knife, and material is not
moving due to underlying support. In reality difference between cutting, shearing and tearing is not
so clear and much depends on the viewer. Main things that should be taken into consideration when
classifying the performed operation are: tool sharpness/bluntness, position of the support with
respect to cutting plane and the angle between the incoming blade and the comminuted material
surface.
Shearing:
Working tools with a wedge angle of 75° to 90° apply the shearing. During shearing action
performed in the comminution equipment fracture of material is a result of shear and to some
extend tensile stresses. Deformation zone extends before fracture , between wedges of cutter head
and stationary knife [ (L.J. Naimi, 2006) refers to Schubert and Bernotat 2004; Woldt et al. 2004]. In
shearing there is a distance between vertical plane along the tool is moving and the edge of the
supporting “anvil”. In shearing deformation energy is applied across a lot bigger volume of material
so it could be justified to assume that it is more energy consuming operation.
Tearing:
Tearing action involves combining tensile stresses with bending and torsion [ (I. M. Petre,
2006) refers to Schubert and Bernotat 2004; Woldt et al. 2004]. Particles that are a result of tearing
are very un-uniformed in shape. Tearing should be dominant when tool hits the material in angle
much smaller than normal to the materials’ surface. Also tensile stresses seem to be much more
significant comparing to cutting and shearing. Since biomass tensile strength is dominant comparing
to compression and shear strength it seems logical to assume that this operation would be more
energy consuming in comparison with cutting and shearing.
Milling:
Particles that come as a result of compression and friction are quite uniform in shape.
Compression of the material and friction against the tool implies internal friction working in the
material as well.
- 12 -
Impact:
Impact occurs when a moving tool, such as hammer, hits the material with a certain velocity.
Then the material usually absorbs part of the tool kinetic energy which inflicts fractures and makes
particle to break and go through a fixed rigid target such as perforated surface of the sieve [ (I. M.
Petre, 2006) refers to Schubert and Bernotat 2004; Woldt et al. 2004].
Biomass is as stated in 1.3 a highly anisotropic, composite material with properties strongly
dependent to coordinates. It seems to be quite clearly stated by this paragraph that different way to
apply stress may lead to the different result both in terms of energy necessary to break the structure
and to particle shape achieved as a result of the operation. That indicates comminuted material
properties (1.3) and used machinery (1.4) would have a meaning in terms of energy used in
comminution. Next paragraph will approach machinery in more detailed manner.
Figure 1.10 - Cell walls collapsing under compression (F. Stefansson, 1995)
- 13 -
1.5 Comminution machinery
There are many different designs and types of machines, that can handle high variability of
different input and output sizes and there is no one clear classification method. It’s good to make an
overview and describe shortly most common types with special emphasis of magnitude of input and
output sizes as well as types of stress that they apply. Few tabularised summaries are in Appendix A.
Figure 1.10 - Possible pathway of size reduction processes of agricultural residues (M. Hoque, 2007)
One of the most popular machines used for a first stage comminution are chippers. They are
rotary devices that have knives attached to the rotating part like drum or disk. Heavy rotating part
(drum/disc) plays the role of flywheel - every time knife cuts out the new chip part of energy is lost.
Input material is usually big in size - f. ex. whole logs. Rotating knives perform cutting and shearing
action. Chips are cut from unprocessed material which is supported with the in-feed spout (anvil).
Output material are chips - pieces that are more or less uniform in shape, size 5 - 50 mm (S.van Loo,
2008). Chips thickness is usually significantly smaller than two other dimensions which both are
quite similar in magnitude.
Figure 1.11 - Different chipper designs - disc and drum chipper (S.van Loo, 2008)
- 14 -
Figure 1.12 - Different chipper designs - disc chipper seen from different angle [ (L.J. Naimi, 2006) refers to
Hakkila 1989]
Figure 1.13 - Different chipper designs - cylindrical drum chipper(a) and V-drum chipper (b) [ (L.J. Naimi,
2006) refers to Hakkila 1989]
Figure 1.14 - Wood chips - CEN (see APPENDIX B) (E. Alakangas, 2007)
- 15 -
Other group of devices that offers little bit bigger and differently shaped output product are
chunkers. Chunk wood is defined as short, thick pieces of wood, where the majority of particles have
a relatively uniform length of 50 ÷ 250 mm in the grain direction and a variable cross-section area,
ranging from about finger size up to the diameter of the material reduced [ (L.J. Naimi, 2006) refers
to Hakkila 1989]. Input material is similar like in chippers. The advantage of chunkers is relatively low
power consumption comparing to chippers (S.van Loo, 2008).
Figure 1.15 Chunker: (a)spiral-head wood chunker; (b)involuted disk chunker; (c) double involuted disk chunker
[ (L.J. Naimi, 2006) refers to Hakkila 1989]
Linear knife grid performs cutting operation in different manner. It does not use rotary
movement. Cutting is performed in linear manner by knife grid through which material is being
pushed by hydraulic piston (Igathinathane, 2006), (C. Igathinathane, 2007).
Figure 1.16 Linear knife grid (C. Igathinathane, 2007)
Technology is though far from being mature yet.
- 16 -
There are machines that use rotating, blunt tools such as hammers to perform impact and
compression action on material therefore causing a fracture. They are called hammermills and
hammer hogs. The main way to distinct these two is a rotor speed. Hammermills operate at rotation
speed up to 3600 rpm, while limit for hammer hog is 1200 rpm, and most of them runs in range of
700 to 900 rpm [ (L.J. Naimi, 2006) refers to CWC 1997 - Wood waste size reduction technology
study]. Output size is being controlled by the screen - perforated surface, which have apertures of
one size. Only particles that are small enough can go through. Particles that are too big are
recalculated and fracture is performed once again. Damage inflicted by hammermills comes mostly
from impact which is related to tip speed of the hammer. In case of hogs more important is
compression force since rotation speed is not so significant. Hammerhogs produce material with
higher average diameter, but fraction of fine particles is more significant than in hammermills i.e.
output material is more un-uniform in size (L.J. Naimi, 2006).
Figure 1.17 - Hammermill (Re-sourcing Associates Inc., 1997)
Figure 1.18 - Hammer hog principle [ (L.J. Naimi, 2006) refers to Hakkila 1989]
- 17 -
Figure 1.19 - Hog fuel - CEN (see APPENDIX B) (E. Alakangas, 2007)
Figure 1.20 Hammermill photo (M.Yu, 2006)with belt transmission (on the right pic.)
Rotary knife mills are similar devices. They combine two comminution mechanisms: cutting and
impact. Instead of blunt tool, like in hammermills, they have knives mounted on the rotor. The
knives are not so sharp like those in chippers so they can tolerate much more contaminated material
(L.J. Naimi, 2006).
There are many other designs - Appendix A.
- 18 -
2. Model introduction
2.1 The reason for making a model
Comminution process isn’t usually ultimate goal itself, but is a part of some other process - f. ex.
upgrading process of biofuel. It strongly depends on input and output condition. In case of our
example we have the need for energy service fulfilled by some technology on one hand, and
available biomass supply estimated by proper assessment methods. We need to adjust collected
biomass to enable it to certain application process, and sometimes we need some intermediate
upgrade if we need for example transport it for further distance, or for some other reasons (like f.
ex. making more uniform product that has necessary storage and transport properties which would
allow to make it marketing product - f. ex. pellets).
Since comminution is a one (or two) stage of whole supply chain, with green biomass at the
beginning and final user at the end, it has to fit into the supply chain as a whole. That means a
necessity to have a qualitative model that would allow to choose proper comminution devices and
scale it up depending on the desired capacity.
Properties of biomass as a highly variable material would also play significant role. Different type
of wood from different forest would lead to different energy consumption of the comminution
device. During combustion size of the particle definitely has influence on total efficiency - by the
amount of unburned fuel in the ash. Having the qualitative model at hand would allow to estimate
roughly how much energy would be used for comminution and compare it to the unburned fuel
energy loss to choose a better option for real life cases. That kind of comparison would also require
proper combustion model with respect for the particle size and combustion technology.
The need of bioenergy is dictated by environmental issues, therefore wasting of the energy is
unacceptable and incorporation of maximised energy efficiency is a must.
- 19 -
2.2 Models valid for brittle materials
All three laws mentioned in this chapter were mend to be used as an comminution energy
estimation for brittle materials - minerals. They are also considered important in food industry as
well.
General assumption for all those theories is that energy, required to change by dL a size of the
particle of a typical dimension L, is simply power function of L:
where:
- differential energy required
- change in typical dimension
K, n - are constants
· 2.1
a) Rittinger’s law states: “The work done on a given mass is proportional to the reciprocal
(inversely proportional) to the diameter of the final product - assuming that all the mass has
been reduced to one exact size, which is only theoretically possible” (A.O. Gates, 1915). In
other words energy required for size reduction is proportional to the change in surface area
(Earle, 1983), (G.Young, 2003).
As a consequence n = -2 (in 2.1)
Assuming that · where:
- Rittinger’s constant
- theoretical strength necessary to crush the material
Putting it all to (2.1):
· · భ
1 భ
1
1
· · · · · · మ
మ
· · - 20 -
మ
భ
2.2
b) Kick’s law states: “The energy required for producing analogous changes of configuration of
geometrically similar bodies of equal technological state varies as the volumes or weights of
the bodies” [ (A.O. Gates, 1915) refers to H. Stadler 1910]. In other words required energy is
proportional to the size reduction ratio That implies: n= -1
(in 2.1)
Assuming that · where:
- Kick’s constant
- theoretical strength necessary to crush the material
Putting it all to (2.1):
· · భ
· · · · ln భమ · · మ
· · 2.3
c) Bond’s law is a kind of unification of the two preceding theories.
Bond suggested that n = -1/2 (Earle, 1983)
And proposed that:
10 ·
where:
10 ·
2
1
- amount of energy required to reduce unit mass of the material from an infinitely large particle
size down to a particle size of 100 μm (Earle, 1983).
Which after transformations gives (Earle, 1983):
· /
· 1 - 21 -
/
2.4
In Bond’s equation and are expressed in microns and is called Work Index. Bond
established three main test procedures for different types of mills and three different index
empirical tests (Starkey, 2003):
•
•
•
Bond Impact Work Index Test
Bond Rod Mill Work Index Test
Bond Ball Mill Work Index Test
Bond’s approach was little bit different comparing to Rittinger’s and Kick’s - instead of trying to
derive his formula from fundamental laws, he tried to derive some empirical formula basing on a
previous works by Rittinger and Kick and trying to find a compromise between both.
Since Rittinger’s and Kick’s models were published there was a big debate about applicability of
both and scientific society became divided between supporters of both of those models (A.O. Gates,
1915), (R.T. Hukki, 1962). Most of experiments evidenced in favour of Rittinger’s law but Kick’s law is
considered to be of fundamental nature in processes such as cutting, pressing, shaping and rolling of
metallic substances (R.T. Hukki, 1962). In general it is said that Kick’s law is more applicable to coarse
grinding, when there is little change in surface area. Rittinger’s law is more suitable for fine grinding,
where there is much greater change in surface area (Earle, 1983), (G.Young, 2003).
Because of its’ composite nature with anisotropic strength properties biomass produces very ununiform particles and until very fine particles size dimensions of the particle differ greatly,
comparing one to another. Often longitudal dimension (perpendicular to the fibre axis) is much
more significant comparing to other one. Particles are usually “flat”. Because of those properties it
seems highly unlikely that models valid for brittle materials could be useful for biomass. But they
give good general scope to the comminution process as such. They indicate factors that should be
included in any kind of comminution model, which are:
-
input and output size of the material
properties of the material
properties of the device
- 22 -
2.3 Identification of reliable parameters for the model
Modelling any kind of phenomenon that occurs in a real life cases always involves some kind
of mathematical apparatus that describes phenomenon. Apparatus, no matter if it’s simple linear
function, differential equation or some advanced discrete mathematics method (f. ex. Discrete
Element Method), always aims in establishing relation between input parameters that are possible
to measure, and outcome result that is an answer for the question/problem one may occur.
Qualitative model doesn’t need to give more or less exact result. It should rather identify
parameters that could play important role in the situation that is described by the model. It should
also give some possibility to estimate behaviour of the modelled system when parameters change.
From the practical reasons, the more simple to measure parameters are being used the
more useful model would be as such. Having qualitative model at hand also allows to derive a
quantitative version later if some standard equipment and materials are being used as a reference
and proper coefficients are used to indicate the difference between reference (lab) equipment and
equipment used in real life cases.
Using the knowledge that is already at hand thanks to material science (Figure 2.1) it seems
to be possible to spot the meaningful parameters that might be used in the qualitative model of
chipping.
Figure 2.1 - Strength of wood depending on type of stress mechanics, density and moisture content (S.
Brennert, 1985)
- 23 -
Using knowledge from material science identifying parameters for model seems to lead to
quite obvious choices in terms of wood strength properties: namely moisture content and dry
density (J.M. Dinwoodie, 1996), (U.S. Forest Products Labolatory, 2010), (S. Brennert, 1985). They
are both easy to measure. It is also necessary to relate those two to fracture mechanics and some
kind of test that could give some relation between those properties. Figure 2.1 indicates that stress
that causes a failure is dependent on the mechanics discussed in 1.3. High variability of wood
strength seems to be the obvious consequence of highly anisotropic nature. Choice of the right
property is important, and it may vary depending on comminution equipment and fracture
application by that equipment. It seems to be reasonable to assume that finding the test, that
resembles stress application in the considered device, should also lead to the right choice of the
property.
Hardness:
Hardness is a property that enables material to resist indentation. During tests it’s force is
usually applied by a prescribed specimen, with relatively small contact surface. Specimen is blunt not
sharp, but hardness test overall seem to resemble cutting mechanics quite well and is considered to
be related to materials cutting resistance (D.W. Green, 2006). There are different kinds of hardness
tests. The most commonly used for wood is Janka test. It’s performed by ball with 0,444 inch
diameter (approximately 11.1 mm) by using a fixed load and measuring diameter of impression at
the surface (it resembles Brinell and Vickers hardness test for metals) (D.W. Green, 2006).
Figure 2.2 - Equipment used to perform Janka test nowadays (D.W. Green, 2006)
- 24 -
Density:
Density is the property of wood that is quite easy to identify. Since porous and composite
nature of wood is important for its’ mechanical properties density seems to be a good indicator. One
thing that needs to be mentioned is the fact that density of the wood is being mentioned in a few
different way.
It should be defined as:
! "#$%&'
! ()*+#
Sometimes sources relate density to the standard moisture content:
! "#$%&'
()*+# ,' -. .. /%
Also Specific density is in use:
+,11 ) '&# +,'# $, ) 2 #13 . ()*+#
+,11 ) '&# ",'# ) 2 #13 . ()*+#
This is nothing more than just a ratio of dry density to water density and multiplying it by
density of water should give dry density as a result.
Janka, during his research found, that hardness is approximately proportional to the density
of wood [ (D.W. Green, 2006) refers to Kollmann and Cote 1968]. Newlin and Wilson, basing on
numerous measurements performed up to 1919, determined that the relationship between
hardness and specific gravity may be expressed as a power formula (D.W. Green, 2006):
4
5·
Where A and n were determined separately for green and dry wood (M.C. 12%), but there
was no difference indicated between hardwoods and softwoods. Later tests shown that (Table 2.1).
Table 2.1 - Relationship between Janka hardness and specific gravity for tested group of species - tests
performed by U.S. Forest Products Laboratory in 1999 (D.W. Green, 2006) - recalculated to SI as 1 lbf = 0,27 N
Species group
Moisture content
6 7 · 8 A
n
Green
13,78
2,31
12%
12,59
2,09
Green
5,18
1,41
12%
7,15
1,50
Hardwood
Softwood
- 25 -
Figure 2.3 - Janka hardness and specific gravity relationship chart (Hardness in pounds of force - U.S. customary
units system) (D.W. Green, 2006)
Since different moisture content changes wood hardness, for the prescribed specific gravity,
including that property into model seems quite obvious.
Moisture content:
As indicated by Figure 2.1 and 2.3 moisture plays an important role in terms of wood
strength, but it’s important to mention that it makes a difference only from oven-dry state up to the
saturation point (Figure 2.1). Water present as a liquid in cell cavities has no significant difference in
terms of wood properties.
Figure 2.4 - Effect of moisture on Brinell hardness of Pine (Hardness in Brinell number) [ (D.W. Green, 2006)
refers to Kollmann and Cote 1968]
- 26 -
Moisture content is usually defined in two ways:
•
Wet basis
+. 3.
•
+
+ 9 +
Dry basis
+. 3.
+
+
Where:
+ - mass of water in the material
+ - mass of dry material substance
+. 3.
+. 3. +. 3. 9 1
As a coarse estimation - for each 1% change in moisture content (dry basis), the “average”
change in side hardness would be approximately 2,75% for softwoods and 2,55% for hardwoods
(D.W. Green, 2006).
Relation between moisture content strength properties for wood isn’t usually considered
linear but in most of the cases tests are performed to check the relation only between moisture
content and strength or density and strength. If it’s analysed as a two variables function situation
becomes more complicated (Figures 2.5 - 2.8).
Figure 2.5 - Ultimate tensile stress as a function of specific gravity and moisture content (D. E. Kretschmann,
1995)
- 27 -
Figure 2.6 - Ultimate compressive stress as a function of specific gravity and moisture content (D. E.
Kretschmann, 1995)
Figure 2.7 - Modulus Of Rupture stress as a function of specific gravity and moisture content (D. E.
Kretschmann, 1995)
- 28 -
Figure 2.8 - Modulus Of Rupture stress as a function of specific gravity and moisture content (D. E.
Kretschmann, 1995)
It seems to be important to indicate that moisture content and density (i.e. specific gravity)
are related one with another and therefore are not fully independent variables. Relation of those
two is and effect of wood shrinkage (decrease in dimensions/volume) during the loss of moisture
and is more or less inversely proportional.
Figure 2.9 - Shrinkage as a function of moisture content (U.S. Forest Products Labolatory, 2010)
It does not indicate linear relation between moisture and hardness of wood, but it may lead
to the assumption that linear relation should be good enough for qualitative model.
Moisture is important parameter of biofuel and it’s easy to measure so it should not bring
any significant difficulties when using model for real life cases.
- 29 -
Size reduction:
To get the right scope on the role of the input and output size difference one has to get the
closer look into the geometrical aspects of comminution, namely geometry of the machine. Since
this thesis aims to formulate qualitative model for chipping - chipper is the obvious choice, but in
general that kind of approach should be valid for every comminution machinery.
As stated in 1.5 chipping is done by knives which cut through the wood. Knives are being
moved by the rotating drum/disk which they are attached to. Drum rotational movement is caused
by rotation of the shaft which the drum is attached to. Power is being “delivered” to the shaft by the
engine directly or via some kind of transmission (f. ex. belt transmission, Power Take Off). Drum with
the knives is rotating in a chamber.
Size of the output product is a subject of technical standardisation (SCAN-CM 40:01, 2001),
(E. Alakangas, 2007). There are some existing methods to control that size and to give the customer
valuable information if the output product would be suitable for his process. Its’ being done by using
screens that only prescribed size chips would be able to pass. Oversized chips are blocked by the
screen and undersized fines go down to the bottom. Chips with desired size are usually left on the
middle screens. Size distribution is a subject of standards (E. Alakangas, 2007).
Figure 2.10 - Five screens and a fines tray in the chip classifier (SCAN-CM 40:01, 2001)
One way to achieve desired output size is to use the screen to block oversized material going
out of the comminution chamber. Other is way relies on the machine setup, namely knives geometry
setup and sharpness to achieve desired product. In real life cases both are used.
Cutting is performed by the moving blade that cuts through the material that is supported
(kept in one place) by the anvil (sometimes support could be other blade as well - bed knife).
- 30 -
Figure 2.11 - Chip formation in the chipping process (W.F. Watson, 2007)
Figure 2.12 - Regulation of the chipping by knife adjustment (W.F. Watson, 2007)
Figure 2.13 - Setting up scheme for the chipper for size control: a. short chip; b. long chip (W.F. Watson, 2007)
- 31 -
It’s not so difficult to set the relative angle between the cutting knife and other parts of the
chipper namely the anvil. That angle is the angle between the knife blade and wood that’s being fed
into the chipper. But it’s not nearly the angle between the blade and the fibre because of the several
reasons:
•
Wood is a highly variable material which is caused by nature. Different specimen that grows
in a different locations is subsequent to the different forces. So it would grow in a different
way depending on variables such as slope of the soil, surrounding that determines the wind
speed, etc... Those factors along with any kind of “wounds” tree receives during its’ lifetime
causes local irregularities in terms of the structural geometry. Also every place on the log
where branches are situated is subsequent to geometry changes. Tree is considered by
mathematicians as a natural raw model of a fractal. Although fractal can be described by the
complex functions but in terms of chipping this description is irrelevant. Fibril angle could be
described as an average angle but it’s still subject to subsequent variations.
•
When the log is being fed first cut starts in a prescribed angle, but when the knife edge goes
deeper into the material relative angle between the knife and the material changes. It’s not
so clearly visible in one dimensional schemes, but when considerations go to 3D, which is
the real chipping case, it becomes pretty obvious - axis of rotation for disk chipper is not the
same as axis of the log, and edge of the knife is situated parallel to the disk radius (Figure
2.14). In the drum chipper situation is even more obvious. Change of the relative blade angle
during the movement of the knife blade causes the change in chipping mechanics before
chip is totally separated from the parent material. Closer to the end of the chip cutout there
is shear stress involved and at the very end the tearing is dominant (W.F. Watson, 2007) - as
a consequence tensile strength starting to play bigger role. Manipulating the sharpness of
the blade is even one of the methods to regulate the chip size - sharp blades produce more
thin chips, and blunt blades produce more thin ones (increased pull-in force).
Figure 2.14 - Chipping wood with disk chipper - 3D (W.F. Watson, 2007)
- 32 -
•
First cut is being done in the prescribed angle, but after the chip is cut the log surface
changes in pretty much random way, since chips are always more or less irregularly shaped
(Figure 2.14). Next blade that hits the wood log usually hits surface that changed shape after
the first cut - therefore the angle is different.
Figure 2.15 - Shape o the wood chip (Quality of wood chip fuel, 2006)
•
Some of the chips after the cut are still jumping around in the comminution chamber (too
big to go through the screen). They are in the chamber until they meet the knife edge once
again that cuts through them. In that situation the angle is totally unpredictable. Too big
amount of oversized material inside the chamber increases energy consumption because
chipper (engine) still uses power, but amount of output material is smaller. That decreases
productivity - therefore increases dull power consumption (like on no-load run). Some
chippers have specially designed features to minimise that effect - f. ex. Card breakers
(Figure 2.16), Post-processors, Blowing wings, etc...
Figure 2.16 - Card breakers in the disk chipper (W.F. Watson, 2007)
- 33 -
Overall it seems reasonable to assume that the angle between knife blade and wood fibre is
random during cutting (chipping).
Generally speaking parameters mentioned previously, namely moisture content and density
have influence on size distribution and sometimes it’s necessary to adjust the device for other type
of materials with other properties. Sometimes it could even be same type of material but during
harvest in a different season (W.F. Watson, 2007) as it’s shown on Figure 2.17.
Figure 2.17 - Woodchips size distribution depending on moisture content - seasonal dependence (W.F. Watson,
2007)
Demand for smaller chips - i.e. smaller screen size clearly increases number of cutting
operations performed by the knives. Relation between productivity and total amount of chips is
linear and inversely proportional, as shown on Figure 2.18 (C. Nati, 2010). This seems to be quite
logical since more cutting operations performed should make knives wear down faster.
Figure 2.18 - Productivity drop because of the knives wear (C. Nati, 2010)
- 34 -
2.4 Measuring the specific energy
Many studies report measuring specific energy for comminution using different methods.
Main issue to be pointed out is that energy used by the comminution device is not just energy
necessary for comminution. Strain energy stored in biomass before breaking is partly converted into
something else than fracture. It might become propagated stress energy, kinetic energy of
fragments and plastic deformation energy. Fraction of total energy that actually creates new surface
is extremely variable and strongly depends on operating conditions of the mill [ (V.S. Bitra, 2009)
refers to Austin and Klimpel 1964] and feedstock.
Any direct measurements in such a dynamic, rapid and variable process as grinding are very
difficult and in a way futile. Because of that most of the studies aim to measure indirect energy (V.S.
Bitra, 2009).
The simplest kind of measurements are limited just to the power of the motor that is coupled with
the rotary mill. It was performed either by using a wattmeter in case of an electric motor [ (V.S.
Bitra, 2009) refers to Balk 1964 and Schell 1994] or by engine fuel consumption rate in case of an
internal combustion engine [ (V.S. Bitra, 2009) refers to Arthur 1982]. It was a poor measurement
because it did not take into consideration engine’s energy conversion efficiency. Other research
used ampere meter and vacuum discharge [ (V.S. Bitra, 2009) refers to Esteban and Carrasco 2006].
Vacuum discharge was mend to eliminate energy losses related to operational issues - screen
clogging of the hammer mill. Most of the published values based on those methods (V.S. Bitra, 2009)
- the measured value was total specific energy.
Rotary mills need some energy even if they run with no-load. Total specific energy measures
energy used by the device which is to some extend sum of comminution energy and energy for
upkeep the rotation movement on no-load run. Comminution energy measured as a difference
between total specific energy and no-load energy is called effective specific energy. The difference
might be quite significant - total specific energy measured for comminution of switchgrass in
hammer mill was 114,4 MJ/Mg, while effective specific energy for the same operational conditions
(2000 rpm) was 57,5 MJ/Mg (V.S. Bitra, 2009). That is approximately half of the total energy which
shows significance of no-load power consumption.
Measurements for effective specific energy were generally done in two ways. First one was
more simple and less accurate watt meter measurements of power for both load and no-load
conditions to obtain the difference between those two, and then integration over time divided by
mass feed rate. That method is less accurate in terms of quantifying effective specific energy,
because it does not take into account engine efficiency and transmission efficiency. In terms of
electric engine efficiency is quite high but quotient of that and efficiency of transmission might
become quite significant.
Other method was direct monitoring of power input into the mill with a calibrated torque and speed
sensor on the mills driveshaft (Fig. 2.4). Total specific power was determined by integrating power quotient of torque and rotation speed - over time, divided by mass feed rate. No-load power
function was substracted from total power for effective specific energy (M.Yu, 2006), (V.S. Bitra,
2009), (V. S. Bitra, 2009), (A. R. Womac, 2007)]. Although it takes into account efficiency of the
engine it does not take into consideration efficiency of the transmission.
- 35 -
Figure 2.19 - Measuring effective specific energy by torque sensor (V. S. Bitra, 2009)
Other method is to use electronic monitoring of power consumed by engine (Figure 2.20). In
that case specific energy can be calculated, by numerical integration of data acquired by computer
shown on Figures 2.21 and 2.22. These figures also show that simple measurement of no-load power
and deducting it from nominal power is not an accurate measurement method at least for electric
engines, because effective power is subject to high fluctuations . Both figures also show that engine
is being periodically overloaded for short periods of time - both chippers were run on one main
engine with nominal power of 75 kW, two auxiliary engines 3 kW each (feeding rolls) and 3 kW
engine to produce vibrations for transport conveyor (S. Risovic, 2008). Power measured by
electronics reaches 140 kW in peak periods.
Figure 2.20 - Measuring effective specific energy by electronic devices (S. Risovic, 2008)
- 36 -
Figure 2.21 - Effective power of the chipper - unsharpened knives (S. Risovic, 2008)
Figure 2.22 - Effective power of the chipper - sharpened knives (S. Risovic, 2008)
- 37 -
3. Qualitative chipping model
3.1 Derivation of the qualitative model for chipping
As stated in the previous paragraphs energy necessary for comminution of wood would be
much dependant on both the material (wood properties) and the machine.
I seems justified to make an assumption that energy necessary to break the structure would
correlate with forces resistance to the force. In case of chipping Hardness should be decisive
parameter. Hardness is dependent on density and moisture content (if m.c is below equilibrium
point) which was already pointed out.
Relative angle between the cutting knife and the fibre direction in wood surface is assumed
to be random (2.3).
Assuming that:
: . · 5 · ; ·
(3.1)
Where:
: - force necessary to perform complete cut operation (cut piece of material falls off).
5 - cross sectional area of the cut
- dry density
2
- exponent, value can be derived experimentally
; - experimentally derived coefficient
.
- some experimental function
To introduce Hardness:
:
5 . · ; ·
4 . · ; ·
(3.2)
(3.3)
Although test results of Janka Hardness are given in Newtons, proper SI unit is < =, ,
+
it’s because the force is given for standardised specimen, so surface is known and force value is
enough for comparisons.
To introduce dependence between hardness and moisture content.
4 > · ; ·
- 38 -
· .
(3.4)
Where:
> - is a dependence between moisture content and hardness
. - some experimental function
As stated in chapter 2.3 it’s reasonable to assume linear relationship.
To introduce energy first formula 3.1 could be used with some changes, namely:
5 , · ?
(3.5)
Since 5 is a surface of a cross sectional cut area, , , ? could be considered as
width and length of newly produced chips. That means one of them can be considered as the depth
the chipping knife goes through the comminuted material - say ? .
: , · ? · > · ; ·
· .
(3.6)
One may claim that energy for single cut operation, is equal work performed by knife to go through
material. Using definition of work:
∆ B : · C
(3.7)
Where:
: - is a force necessary to move the object (in this case edge of the knife is being moved from the
side of wood surface to the point where chip splits).
C - is the distance, namely depth on which knife goes through material
Equation 3.6 can resemble 3.7 by multiplying both sides by C which in this particular case
would be ? .
: · ? , · ? · > · ; ·
· . · ?
(3.8)
One of the first overall assumption for the model is that chips are cut in a random relative
angle. Also size of the chips is not strictly uniform and it must sometimes become a subject of more
cutting operations before it leaves the chipping chamber. That makes the general background for
the assumption that a !! and b !! may be considered random, but in total there would always be
some surface as a result. When thickness of chips is taken into consideration it gives volume. That
makes possible to introduce model into macro scale to consider chipping some prescribed amount
of the material as one operation.
"# . > · ; ·
Where:
E&'&() *+
,.
· . · F%
(3.9)
- total specific energy for comminution chips volume of V,-.+*
In general for description of biofuel it’s recommended to use mass along with moisture content.
To introduce mass one should consider that wood could be chipped with different moisture
content. Since moisture content is already introduced one has to assume that biomass was chipped
at the green state and it’s moisture content is at equilibrium.
- 39 -
From general equation for density:
(3.10)
In case of the chipped material:
(3.11)
Assuming that wood/chips are at equilibrium moisture content and that shrinkage in case of
future drying would is negligible:
·
(3.12)
0ೢ9
/
ు్
(3.13)
Since we assume that shrinkage has no significant influence:
/ೢ
0ు్
0
I
(3.14)
· m,-.+*
(3.15)
Taking that into consideration:
E&'&() *+
,.
α · β1 · r
+ · C ·
E&'&() *+
,.
α · β1 · r
+2 · C · m,-.+*
(3.16)
α · β1 · r
+2 · C · mP,-.+*
(3.17)
Overall:
and
P&'&() *+
,.
Where:
mP,-.+* - is an output mass flow of the chipper
P&'&() *+ ,. - total specific Power for chipping
Next parameter that needs to be introduced is size reduction function. There is also a
necessity to establish dependence between the model and the machine since importance of
machine was already stated.
E&'&() *+
,.
α · β1 · r
+2 · M& · Rx.3 , x'4& · m,-.+*
- 40 -
(3.18)
Where:
Rx.3 , x'4& - experimental function describing relationship between input ( x.3 ) and output ( x'4& )
size of the material.
M&
- experimental machine dependant coefficient
Assuming that α is a linear function of moisture content:
T U·V9W
(3.19)
Where:
, and ? - derived experimentally coefficients
k
- moisture content
Data set contained Janka Hardness for an extensive amount of deciduous and coniferous
species at 12% moisture content and moisture content at green state. Since moisture content above
equilibrium point does not seem to have any significant impact on strength properties of wood
moisture was assumed to be in equilibrium point. Saturation point was assumed to be 21% for each
case. This is not completely true since equilibrium moisture content depends on conditions in
surrounding atmosphere. With desorption of water during drying woods’ ability to water adsorption
also decreases (U.S. Forest Products Labolatory, 2010) (especially when the drying time is long).
Figure 3.1 - Moisture content–relative humidity relationship for wood under adsorption and various desorption
conditions (U.S. Forest Products Labolatory, 2010)
- 41 -
Coefficient a in the linear equation was calculated for each species using formula:
ܽൌ
56 7589%
98789
ு6
(3.20)
Where:
- Janka Hardness at green state
4;
4% - Janka Hardness at 12% moisture content
Since 4; is the bottom limit for hardness in terms of moisture content - i.e. further moisture
content rising would not decrease hardness in any way - coefficient b in the linear function of
moisture is assumed to be equal 4; .
Final formula for the qualitative chipping model:
E&'&() *+
,.
a · k 9 b · β1 · r
+2 · M& · Rx.3 , x'4& · m,-.+*
(3.21)
P&'&() *+
,.
a · k 9 b · β1 · r
+2 · M& · Rx.3 , x'4& · mP,-.+*
(3.22)
- 42 -
4. Results and discussion
4.1 Coefficients for the equations
Within the timeframe of the bachelor thesis there was no possibility to perform tests using
real chipper. Finding coefficients and functions for the part of the equation concerning wood
properties was not so difficult. There is extensive amount of data present in the literature that is
treats wood as a construction material. Although general purpose of those publications was to give
knowledge necessary to preserve wood structure and the goal of comminution is to break down the
structure - same data set is valid for both. However without real tests there is no possibility to
estimate value for machine coefficient M& .
Size reduction:
Reading substantial amount of producers catalogues brought no result. Data compiled from
different producers and retailers websites are compiled in Appendix E. Attempts to establish some
kind of relation by approximation using trend line in MS Excel did not bring any reliable result. Trend
line was in all possible configurations (approximating functions) resembled function f(x)=C where C is
so constant value. That would suggest no correlation at all, but common sense and analysis
performed in chapter 3 claim something different. The reason is that data compiled in Appendix E
comes from the different type of producers and from the different models of chippers. Testing
material is not mentioned in any of those catalogues. All of them contain warning that those values
are only a rough estimates and may vary depending on the comminuted material and chipper
settings. Most of the producers doesn’t even publish estimated values and limit themselves only to
the statement that values might be highly variable.
(C. Nati, 2010) indicates that size energy necessary for comminution is dependent on size reduction.
Figure 4.1 - Fuel consumption of the chippers’ engine related to screen size and amount of chips produced with
the same knives (C. Nati, 2010)
- 43 -
Figure 4.1 shows that difference is constant between two different screen sizes, but paper
was aiming more to show difference in fuel consumed by chipper depending on different sharpness
of the knives. Screen size described as “Medium” on that chart was 40 mm and size of “Large” was
240mm (C. Nati, 2010). Opening diameter of the “Medium” screen is far bigger than all of the chip
sizes in Appendix E. “Large” diameter is as big (and in some of the cases) even bigger than input size
for the chippers in Appendix E.
Under those circumstances it seems reasonable to claim that Figure 4.1 isn’t capable to
show what kind of function describes correlation between comminution energy and size reduction,
but it still proves that some kind of dependence exist since amount of fuel is different for different
screen size. The need for laboratory tests seems to be evident.
Moisture content:
To find relationship between the moisture content and comminution energy literature data
were used. According to model described in chapter 3 and it’s theoretical assumptions relationship
between moisture content and Janka Hardness was investigated. Data collected from (U.S. Forest
Products Labolatory, 2010) are available in Appendix D.
For every tree species coefficients a and b were calculated according to equations 3.19 and 3.20.
Average values of this coefficients were calculated separately for hardwoods and softwoods.
Hardwoods:
Softwoods:
T Y, YZ[\ · V 9 Z, ]^\_
T Y, Y\[_ · V 9 _, `aa\
Interesting observation is that change in moisture content has generally bigger influence on
Hardness for softwoods than for hardwoods. That could be also confirmed by Figure 2.3 from (D.W.
Green, 2006). When taking a closer look at that figure one may notice that difference between the
hardness curves, between green and 12% m.c. state, for the same Specific gravity is bigger for
softwoods than for hardwoods. That confirms the model is going to the right direction, but general
assumption that dependence between hardness and m.c. is linear could not being proven without
laboratory tests.
Density:
Hardness as it was stated in chapter 3 depends both on moisture content and hardness.
Model was aiming to separate those two relationships into the separate functions, although in real
life there is connection between them - namely shrinkage.
Assumption was made that laboratory tests should give some correction coefficients that in
total would anticipate that effect.
Extensive amount of literature data (Appendix C) gave possibility to find relationship
between Janka Hardness and Dry density. Density in (U.S. Forest Products Labolatory, 2010) was
stated as Specific density. For compilation in Appendix C it was multiplied by Density of water which
b%
was roughly assumed to be 1000 < .
+
- 44 -
Density of water is in reality a function of temperature. Using more accurate values for
specified temperature, f. ex. 20 ℃ , would give more accurate result, but for the purpose of the
qualitative model value was assumed to be good enough.
Hardness in a green state was used, because of general assumption for model to separate
m.c. and density influence into separate functions - that could lead to some insignificant errors.
According to part of formula 3.4 that concerns density:
β1 · r
+
Coefficient β1 and exponent p were approximated separately for hardwood and softwood, using
exponential trend line in MS Excel to perform approximation:
Hardwood:
_a, `^Y · d= >,@AB
Softwood:
`, ^[Z · d= C,DCA
Results are quite close to values given by literature in Table 2.1 (D.W. Green, 2006).
Figure 4.2 - Janka Hardness as a function of Dry density for Hardwood and Softwood
8
Hardwood
Softwood
7
Hardness [N]
6
Hardwood (approx.)
y = 17,62x2,386
Softwood (approx.)
y = 6,253x1,418
5
4
3
2
1
0
0
100
200
300
400
500
Dry density [kg/m^3]
- 45 -
600
700
800
5. Conclusions
After reading extensive amount of literature size reduction seems to be one of the links in
the fuel supply chain that still has some potential for optimisation and savings in terms of the
energy.
Most of the chipper producers does not give any reliable data about the energy used by their
devices, some give only coarse estimates. Optimisation can bring benefits not only in terms of the
energy use, but also financial. Biomass, especially one that is used as a solid fuel, is very variable in
terms of the properties. Model that could give the answer for the energy use, by performing analysis
on the biomass properties related to the device, could not only show the need for energy necessary
to perform comminution. It could help to optimise product output from the device before
comminution process would even start. That would obviously help to lower the energy use for
comminution by minimising proportion of no-load energy to total specific energy used. Knowledge
about the output could help to optimise energy use and in the same time it could help to optimize
supply chain as well for example by decreasing operational delay time. It’s because comminuted
material properties also affect the productivity of the comminution device.
Aim of this thesis was to produce some kind of qualitative model describing chipping. The
same kind of the approach could possibly, as a result, produce qualitative model for any type of
comminution device - f. ex. hammermill.
Transformation of the qualitative model into quantitative one would be necessary to get
some reliable data. It would need some laboratory tests to separate influence of the each parameter
and the influence of the machine as such.
Similar approach, like that used by Bond for brittle materials, seems to be necessary to make
model useful for real cases. Having quantitative model at hand, and standardised coefficients for the
variety of devices could potentially help to optimise the comminution process.
Under those circumstances quantitative model could be useful to check if changes in output
size, namely using bigger particles (chips/chunk), could help to save the energy. It would also give
possibility to compare those savings with the increased loses in unburned fuel.
Nowadays making Assessment of Biomass for energy aims to give a proposition for the
technology to utilise those resources. Having complete quantitative model and reliable standards for
devices would also make possible to include full supply chain into the assessment because both
biomass properties and machine properties would be known. It would be possible to give some
preliminary proposition for comminution devices at that stage.
As a final conclusion one may state that both qualitative and quantitative model of
comminution are useful tools in terms of efficient and sustainable usage of biomass for energy,
which is one of the priorities of the modern world.
- 46 -
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1998. ISBN 0-7484-0415-5.
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biomass by Linear Knife Grid device. Minneapolis : ASABE, 2007. 076045.
C. Nati, R. Spinelli. 2010. How blade wear of chippers can affect fuel consumption and wood chips
size distribution. Padova : FORMEC conference materials, 2010.
D. E. Kretschmann, D.W. Green. 1995. Modeling moisture content - mechanical property
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D.W. Green, M. Begel, W. Nelson. 2006. Janka hardness using non standard specimens. United
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0419255508.
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fuel quality assurance. Jyväskylä : Technical Research Centre of Finland, 2007.
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J.M. Dinwoodie, H.E. Desh. 1996. Timber: structure, properties, conversion and use. London :
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L.J. Naimi, S. Sokhansanj, S. Mani, M.Hoque, T. Bi, A.R. Womac, S. Narayan. 2006. Cost and
performance of woody biomass size reduction for energy production. Edmonton : The Canadian
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Committee, 2001.
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2002. January 2002, Powder and bulk engineering.
Starkey, J. 2003. Accurate, economical grinding design using SPI and Bond. Ontario : Principal
Consulting Engineer, Starkey & Associates, 2003.
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Madison : U.S. Department of Agriculture, 2010. available on-line:
http://www.fpl.fs.fed.us/products/publications/.
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V. S. Bitra, , A.R. Womac, C. Igathinathane, P.I. Miu, Y.T. Yang, S. Sokhansanj. 2009. Comminution
energy consumption of biomass in Knife Mill and its particle size characterization. Reno : American
Society of Agricultural and Biological Engineers, 2009. ASABE meeting papers. 095898.
V.S. Bitra, A.R. Womac, N. Chevanan, P.I. Miu, C. Igathinathane, S.Sokhansanj, D.R. Smith. 2009.
Direct mechanical energy measures of hammer mill comminution of switchgrass, wheat straw, and
corn stover and analysis of their particle size distributions. 2009. Powder Technology 193 p.32-45.
W.F. Watson, R. Stevenson. 2007. The effect of seasonal moisture content change on chip size and
craft pulping. 2007.
- 49 -
APPENDIX A - different classifications of biomass comminution equipment
Table A.1 - (I. M. Petre, 2006)
- 50 -
Table A.2 - (L.J. Naimi, 2006)
Table A.3 - (Re-sourcing Associates Inc., 1997)
- 51 -
Table A.4 - (M. Hoque, 2007)
Table A.5 - [ (M. Hoque, 2007)refers to CWC 1997-Wood waste size reduction technology study]
- 52 -
APPENDIX B - technical specification of properties for solid biofuels
Table B.1 - Specification of properties for hog fuel according to CEN (E. Alakangas, 2007)
- 53 -
Table B.2 - Specification of properties for wood chips according to CEN (E. Alakangas, 2007)
- 54 -
Table B.3 - CEN list of technical standards valid for biofuels (E. Alakangas, 2007)
- 55 -
APPENDIX C - Janka Hardness and Dry density
Table C.1 - Janka Hardness and Dry density for Softwoods (U.S. Forest Products Labolatory, 2010)
Species
Baldcypress
Cedar, Atlantic white
Cedar, Eastern redcedar
Cedar, Incense
Cedar, Northern white
Cedar, Port-Orford
Cedar, Western redcedar
Cedar, Yellow
Douglas-fir, Coast
Douglas-fir, Interior west
Douglas-fir, Interior north
Douglas-fir, Interior south
Fir, Balsam
Fir, California red
Fir, Grand
Fir, Noble
Fir, Pacific silver
Fir, Subalpine
Fir, White
Hemlock, Eastern
Hemlock, Mountain
Hemlock, Western
Larch, Western
Pine, Eastern white
Pine, Jack
Pine, Loblolly
Pine, Lodgepole
Pine, Long
Pine, Ponderosa
Pine, Red
Pine, Short
Pine, Sugar
Pine, Virginia
Pine, Western white
Redwood, Old-growth
Redwood, Young-growth
Spruce, Black
Spruce, Engelmann
Spruce, Red
Spruce, Sitka
Hardness [N]
Dry density [kg/m^3]
1,7
1,3
2,9
1,7
1,0
1,7
1,2
2,0
2,2
2,3
1,9
1,6
1,3
1,6
1,6
1,3
1,4
1,2
1,5
1,8
2,1
1,8
2,3
1,3
1,8
2,0
1,5
2,6
1,4
1,5
2,0
1,2
2,4
1,2
1,8
1,6
1,5
1,15
1,6
1,6
420
310
440
350
290
390
310
420
450
460
450
430
330
360
350
370
400
310
370
380
420
420
480
340
400
470
380
540
380
410
470
340
450
360
380
340
380
330
370
370
- 56 -
Spruce, White
Tamarack
1,2
1,7
330
490
Table C.2 - Janka Hardness and Dry density for Hardwoods (U.S. Forest Products Labolatory, 2010)
Species
Alder, red
Ash, black
Ash, green
Ash, Oregon
Ash, white
Aspen,Qaking
Basswood, American
Beech, American
Birch, Paper
Birch, Sweet
Birch, Yellow
Butternut
Cherry, black
Chesnut, american
Cottonwood, black
Cottonwood, eastern
Elm, american
Elm, slippery
Hackberry
Hickory, Pecan
Hickory, true Mockernut
Hickory, true Pignut
Hickory, true Shagbark
Hickory, true Shellbark
Honeylocust
Locust, black
Magnolia, Cucumbertree
Magnolia, Southern
Maple, Bigleaf
Maple, Black
Maple, Red
Maple, Silver
Maple, Sugar
Oak, red Black
Oak, red Cherrybark
Oak, red Laurel
Oak, red Northern
Oak, red Pin
Oak, red Scarlet
Hardness [N]
2,0
2,3
3,9
3,5
4,3
1,3
1,1
3,8
2,5
4,3
3,6
1,7
2,9
1,9
1,1
1,5
2,8
2,9
3,1
5,8
6,4
6,8
6,5
7,4
6,2
7,0
2,3
3,3
2,8
3,7
3,1
2,6
4,3
4,7
5,5
4,4
4,4
4,8
5,3
- 57 -
Dry density [kg/m^3]
370
450
530
500
550
350
320
560
480
600
550
360
470
400
310
370
460
480
490
600
640
660
640
620
600
660
440
460
440
520
490
440
560
560
610
560
560
580
600
Oak, red Southern
Oak, red Water
Oak, white Bur
Oak, white Chesnut
Oak, white Overcup
Oak, white Post
Oak, white Swamp chesnut
Oak, white Swamp white
Oak, White
Sweetgum
Sycamore, american
Tupelo, Black
Tupelo, Water
Walnut, black
Yellow poplar
3,8
4,5
4,9
4,0
4,3
5,0
4,9
5,2
4,7
2,7
2,7
2,8
3,2
4,0
2,0
- 58 -
520
560
580
570
570
600
600
640
600
460
460
460
460
510
400
APPENDIX D - Janka Hardness and Moisture Content - along with coefficients for linear function of
moisture in the chipping model
Table D.1 - Janka Hardness and Moisture Content for Softwoods (U.S. Forest Products Labolatory, 2010)
Species
Baldcypress
Cedar, Atlantic white
Cedar, Eastern redcedar
Cedar, Incense
Cedar, Northern white
Cedar, Port-Orford
Cedar, Western redcedar
Cedar, Yellow
Douglas-fir, Coast
Douglas-fir, Interior west
Douglas-fir, Interior north
Douglas-fir, Interior south
Fir, Balsam
Fir, California red
Fir, Grand
Fir, Noble
Fir, Pacific silver
Fir, Subalpine
Fir, White
Hemlock, Eastern
Hemlock, Mountain
Hemlock, Western
Larch, Western
Pine, Eastern white
Pine, Jack
Pine, Loblolly
Pine, Lodgepole
Pine, Long
Pine, Ponderosa
Pine, Red
Pine, Short
Pine, Sugar
Pine, Virginia
Pine, Western white
Redwood, Old-growth
Redwood, Young-growth
Spruce, Black
Spruce, Engelmann
Spruce, Red
Hardness at 12% m.c.
[N]
2,30
1,60
4,00
2,10
1,40
2,80
1,60
2,60
3,20
2,90
2,70
2,30
1,70
2,20
2,20
1,80
1,90
1,60
2,10
2,20
3,00
2,40
3,70
1,70
2,50
3,10
2,10
3,90
2,00
2,50
3,10
1,70
3,30
1,90
2,10
1,90
2,40
1,75
2,20
- 59 -
Hardness at Equilibrium m.c.
[N]
1,70
1,30
2,90
1,70
1,00
1,70
1,20
2,00
2,20
2,30
1,90
1,60
1,30
1,60
1,60
1,30
1,40
1,20
1,50
1,80
2,10
1,80
2,30
1,30
1,80
2,00
1,50
2,60
1,40
1,50
2,00
1,20
2,40
1,20
1,80
1,60
1,50
1,15
1,60
a
-0,0392
-0,0256
-0,0421
-0,0261
-0,0444
-0,0719
-0,0370
-0,0333
-0,0505
-0,0290
-0,0468
-0,0486
-0,0342
-0,0417
-0,0417
-0,0427
-0,0397
-0,0370
-0,0444
-0,0247
-0,0476
-0,0370
-0,0676
-0,0342
-0,0432
-0,0611
-0,0444
-0,0556
-0,0476
-0,0741
-0,0611
-0,0463
-0,0417
-0,0648
-0,0185
-0,0208
-0,0667
-0,0580
-0,0417
Spruce, Sitka
Spruce, White
Tamarack
2,30
1,80
2,60
1,60
1,20
1,70
-0,0486
-0,0556
-0,0588
Average a
Average b
-0,0451
1,6774
Table D.2 - Janka Hardness and Moisture Content for Hardwoods (U.S. Forest Products Labolatory, 2010)
Species
Alder, red
Ash, black
Ash, green
Ash, Oregon
Ash, white
Aspen,Qaking
Basswood, American
Beech, American
Birch, Paper
Birch, Sweet
Birch, Yellow
Butternut
Cherry, black
Chesnut, american
Cottonwood, black
Cottonwood, eastern
Elm, american
Elm, slippery
Hackberry
Hickory, Pecan
Hickory, true Mockernut
Hickory, true Pignut
Hickory, true Shagbark
Hickory, true Shellbark
Honeylocust
Locust, black
Magnolia, Cucumbertree
Magnolia, Southern
Maple, Bigleaf
Maple, Black
Maple, Red
Maple, Silver
Maple, Sugar
Hardness at 12% m.c.
[N]
Hardness at Equilibrium m.c.
[N]
a
2,60
3,80
5,30
5,20
5,90
1,60
1,80
5,80
4,00
6,50
5,60
2,20
4,20
2,40
1,60
1,90
3,70
3,80
3,90
8,10
8,80
9,50
8,40
8,10
7,00
7,60
3,10
4,50
3,80
5,20
4,20
3,10
6,40
2,00
2,30
3,90
3,50
4,30
1,30
1,10
3,80
2,50
4,30
3,60
1,70
2,90
1,90
1,10
1,50
2,80
2,90
3,10
5,80
6,40
6,80
6,50
7,40
6,20
7,00
2,30
3,30
2,80
3,70
3,10
2,60
4,30
-0,0333
-0,0725
-0,0399
-0,0540
-0,0413
-0,0256
-0,0707
-0,0585
-0,0667
-0,0568
-0,0617
-0,0327
-0,0498
-0,0292
-0,0505
-0,0296
-0,0357
-0,0345
-0,0287
-0,0441
-0,0417
-0,0441
-0,0325
-0,0105
-0,0143
-0,0095
-0,0386
-0,0404
-0,0397
-0,0450
-0,0394
-0,0214
-0,0543
- 60 -
Oak, red Black
Oak, red Cherrybark
Oak, red Laurel
Oak, red Northern
Oak, red Pin
Oak, red Scarlet
Oak, red Southern
Oak, red Water
Oak, white Bur
Oak, white Chesnut
Oak, white Overcup
Oak, white Post
Oak, white Swamp chesnut
Oak, white Swamp white
Oak, White
Sweetgum
Sycamore, american
Tupelo, Black
Tupelo, Water
Walnut, black
Yellow poplar
5,40
6,60
5,40
5,70
6,70
6,20
4,70
5,30
6,10
5,00
5,30
6,00
5,50
7,20
6,00
3,80
3,40
3,60
3,90
4,50
2,40
4,70
5,50
4,40
4,40
4,80
5,30
3,80
4,50
4,90
4,00
4,30
5,00
4,90
5,20
4,70
2,70
2,70
2,80
3,20
4,00
2,00
Average a
Average b
- 61 -
-0,0165
-0,0222
-0,0253
-0,0328
-0,0440
-0,0189
-0,0263
-0,0198
-0,0272
-0,0278
-0,0258
-0,0222
-0,0136
-0,0427
-0,0307
-0,0453
-0,0288
-0,0317
-0,0243
-0,0139
-0,0222
-0,0354
3,8241
APPENDIX E - different models of chippers and their basic parameters
Table E.1 - different models of chippers: power, productivity and size of input and output material [source:
producers and retailers websites]
Nominal
power
[kW]
10,0
35,0
20,0
50,0
20,0
55,0
20,0
50,0
30,0
75,0
30,0
75,0
80,0
150,0
[kg/h]
1400
4200
2800
5600
4900
14000
2800
7000
4900
14000
4900
21000
21000
70000
Output
size
[mm]
4
12
5
12
3
15
3
15
3
18
3
18
5
20
Input
size
[mm]
100
100
170
170
250
250
190
190
250
250
250
250
450
450
19,9
5600
9
120
21,0
5600
9
120
28,3
8400
9
160
47,1
12600
9
250
22,0
5600
20
140
37,0
7000
11
120
37,0
8400
10
120
45,0
14000
20
160
45,0
5600
10
200
110,0
14000
35
200
22,0
5600
9
120
30,0
8400
9
160
45,0
12600
9
250
Productivity
- 62 -
Chipper
model
HJ 4
HJ 4
HJ 5
HJ 5
HJ 10
HJ 10
HJ 200 GGT
HJ 200 GGT
HJ 260 GGT
HJ 260 GGT
HJ 260 C
HJ 260 C
HJ 500 C
HJ 500 C
SKORPION
120 S
SKORPION
120 SD
SKORPION
160 SD
SKORPION
250 SDT
SKORPION
280 EB
SKORPION
350 EBS/28
SKORPION
350 EB/4
SKORPION
500 EB/2
SKORPION
500 EBZ/2
SKORPION
650 EB/2
SKORPION
120 E
SKORPION
160 E
SKORPION
250 E
Producer
Type
Jukkari
Jukkari
Jukkari
Jukkari
Jukkari
Jukkari
Jukkari
Jukkari
Jukkari
Jukkari
Jukkari
Jukkari
Jukkari
Jukkari
Disk Chipper
Disk Chipper
Disk Chipper
Disk Chipper
Disk Chipper
Disk Chipper
Disk Chipper
Disk Chipper
Disk Chipper
Disk Chipper
Disk Chipper
Disk Chipper
Disk Chipper
Disk Chipper
Teknamotor
Disk Chipper
Teknamotor
Disk Chipper
Teknamotor
Disk Chipper
Teknamotor
Disk Chipper
Teknamotor
Teknamotor
Teknamotor
Teknamotor
Teknamotor
Teknamotor
Drum
Chipper
Drum
Chipper
Drum
Chipper
Drum
Chipper
Drum
Chipper
Drum
Chipper
Teknamotor
Disk Chipper
Teknamotor
Disk Chipper
Teknamotor
Disk Chipper
45,0
5600
7
250
30,0
5600
6
80
SKORPION
250 E/4
SKORPION
250 EB/4
15,0
1470
15
200
600
30,0
2450
15
250
800
- 63 -
Teknamotor
Disk Chipper
Teknamotor
Drum
Chipper
Kowloon
Machine
Manufacturing
Ltd
Kowloon
Machine
Manufacturing
Ltd
Disk Chipper
Disk Chipper