“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

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Organisation/ Organization Författare/Author(s) Linnéuniversitetet Institutionen för teknik Łukasz Niedźwiecki Linnaeus University School of Engineering

Dokumenttyp/Type of Document Handled are/tutor Examinator/examiner Professor Björn Zethraeus Examensarbete/Diploma Work

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/Languag e Antal sidor/Number of pages

2011 English 63

Internet/WWW http://www.lnu.se

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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

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School of Engineering 351 95 Växjö tel 0772-28 80 00, fax 0470-76 85 40

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Table of contents 1. Introduction ………………....................…………………….......................... 1

1.1 General ....................................................................................................... 1

1.2 Comminution as one unit operation in the Biofuel supply chain..................... 2

1.3 Structure of biomass (wood) ......................................................................... 4

1.4 Elementary mechanics in the comminution process .............................................. 11

1.5 Comminution machinery ................................................................................ 14

2. Model introduction ………………………………………............................... 19 2.1 The reason for making model ......................................................................... 19

2.2 Models valid for brittle materials ........................................................................ 20

2.3 Identification of reliable parameters for the model ............................................... 23

2.4 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

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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

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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)

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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.

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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.

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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)

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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)

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Figure 1.5 - Macroscopic and microscopic view of different planes in the wood (U.S. Forest Products Labolatory,

2010)

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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)

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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 3 random

S1 10 50° ÷ 70°

S2 85 10° ÷ 30°

S3 2 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)

Component Mass

Polymeric state Molecular

derivatives Function

Softwood (%) Hardwood (%)

Cellulose 42 ±2 45 ±2

crystalline,

highly oriented,

large linear

molecule

glucose fibre

Hemicellulose 27 ±2 30 ±5

semicrystalline,

smaller

molecule

galactose,

mannose,

xylose

matrix

Lignin 28 ±3 20 ±4

amorphous,

large 3-D

molecule

phenylpropa

ne matrix

Extractives 3 ±2 5 ±2

principally

compounds

soluble in

organic solvents

terpenes,

polyphenols,

stilbenoids

extraneous

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).

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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)

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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)

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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.

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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)

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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)

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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)

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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.

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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]

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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.

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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.

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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:

���� � � · �� �2.1�

where:

�� - differential energy required

�� - change in typical dimension

K, n - are constants

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):

���� � · �� · ��

� · �� · ����� ��

��

� · �� · �1��

��

�� � · �� · � 1��

� 1��

�

� � · �� · � �

��� �

��� �2.2�

- 21 -

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):

���� � · �� · ��

� · �� · ����� ��

��

� · �� · �ln ������

�� � · �� · �� ���

��

�

� � �� · �� · � ����� �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 · ���2� 10 · ���1

where:

� - 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 � �

��� ��� ��/�� �2.4�

- 22 -

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 un-

uniform 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

- 23 -

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)

- 24 -

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)

- 25 -

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

Hardwood Green 13,78 2,31

12% 12,59 2,09

Softwood Green 5,18 1,41

12% 7,15 1,50

- 26 -

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]

- 27 -

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)

- 28 -

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)

- 29 -

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.

- 30 -

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).

- 31 -

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)

- 32 -

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)

- 33 -

• 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)

- 34 -

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)

- 35 -

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.

- 36 -

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)

- 37 -

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)

- 38 -

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���

� . · ; · � (3.2)

4 . · ; · � (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 > · ; · � · .� (3.4)

- 39 -

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.

��"��# ����. > · ; · � · .� · F�%�� (3 . 9 )

Where:

E&'&() *+ ,. - 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.

- 40 -

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)

/�

0��

9 (3.13)

Since we assume that shrinkage has no significant influence:

/�

0��

0 I (3.14)

Taking that into consideration:

E&'&() *+ ,. α · β1 · r+ · C� · · m,-.+* (3.15)

Overall:

E&'&() *+ ,. α · β1 · r+2� · C� · m,-.+* (3.16)

and

P&'&() *+ ,. α · β1 · r+2� · C� · mP ,-.+* (3.17)

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& · R�x.3 , x'4&� · m,-.+* (3.18)

- 41 -

Where:

R�x.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 · V 9 W (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)

- 42 -

Coefficient a in the linear equation was calculated for each species using formula:

� �

567589%98789

�6 (3.20)

Where:

4; - Janka Hardness at green state

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& · R�x.3 , x'4&� · m,-.+* (3.21)

P&'&() *+ ,. �a · k 9 b� · β1 · r+2� · M& · R�x.3 , x'4&� · mP ,-.+* (3.22)

- 43 -

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)

- 44 -

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:

T �Y, YZ[\ · V 9 Z, ]^\_

Softwoods:

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

was roughly assumed to be 1000 b% +<� .

- 45 -

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

y = 17,62x2,386

y = 6,253x1,418

0

1

2

3

4

5

6

7

8

0 100 200 300 400 500 600 700 800

Ha

rdn

ess

[N

]

Dry density [kg/m^3]

Hardwood

Softwood

Hardwood (approx.)

Softwood (approx.)

- 46 -

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.

- 47 -

Bibliography: A. Bruce, J.W. Palfreyman. 1998. Forest products biotechnology. London : Taylor & Francis Ltd.,

1998. ISBN 0-7484-0415-5.

A. R. Womac, C.Igathinathane, P. Bitra, P. Miu, T. Yang, S. Sokhansanj, S. Narayan. 2007. Biomass

pre-processing size reduction with iInstrumented mills. Mineapolis : American Society of Agricultural

and Biological Engineers, 2007. ASABE meeting papers. 076046.

A.O. Gates, M.E.Mishawaka. 1915. Kick vs. Rittinger: an experimental investigation in rock crushing,

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C. Igathinathane, A.R. Womac, S.Sokhansanj, S. Narayan. 2007. Size reduction of wet and dry

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

relationships for clear southern pine. United States Department of Agriculture. Madison : Forest

Product Laboratory, 1995.

D.W. Green, M. Begel, W. Nelson. 2006. Janka hardness using non standard specimens. United

States Department of Agriculture. Madison : Forest Products Labolatory, 2006. FPL-RN-0303.

Dinwoodie, J.M. 2000. Timber: Its nature and behaviour. London : E. & F. N. Spon, 2000. ISBN:

0419255508.

E. Alakangas. 2007. CEN Technical Specification for solid biofuels - fuel specifications and classes and

fuel quality assurance. Jyväskylä : Technical Research Centre of Finland, 2007.

Earle, R.L. 1983. Units operation in food processing. : New Zealand Institute of Food Science and

Technology, 1983. available on-line: www.nzifst.org.nz/unitoperations - 2004 Web Edition. ISBN 0-

08-025536-1.

F. Stefansson. 1995. Mechanical properties of wood at microstructural level. Lund : Lund University,

1995. Master thesis. ISSN 0281-6679.

G.Young. 2003. Size reduction of particulate material. Educational Resources for Particle Technology.

[Online] 2003. www.erpt.org. Volume 4 #1.

I. M. Petre, A. R. Womac, C.Igathinathane, S. Sokhansanj. 2006. Analysis of biomass comminution

and separation process in rotary equipment – A review. Portland : ASAE Annual International

Meeting, 2006. 066169.

Igathinathane, C., A. R. Womac, P. I. Miu, M. Yu, S.Sokhansanj, and S. Narayan. 2006. Linear Knife

Grid application for biomass size reduction. Portland : ASABE, 2006. ASABE meeting paper. 066170.

- 48 -

J.M. Dinwoodie, H.E. Desh. 1996. Timber: structure, properties, conversion and use. London :

Macmillan Press Ltd, 1996. ISBN 0-333-60905-0.

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

Society of Bioengineering, 2006. 06-107.

M. Hoque, S.Sokhansanj, L. Naimi, X. Bi, J. Lim, A. Womac. 2007. Review and analysis of

performance and productivity of size reduction equipment for fibrous materials. Minneapolis :

American Society of Agricultural and Biological Engineers, 2007. ASABE meeting papers. 076164.

M.Yu, A.R. Womac, P. Miu, C. Igathinathane, S. Sokhansanj, and S. Narayan. 2006. Direct energy

measurement systems for rotary biomass grinder - hammermill. Portland : ASABE, 2006. ASABE

meeting papers. 066217.

Miyajima, H. 1973. The hardness test by static ball indentation for wood, especially for Nara-wood

under various moisture condition. Sapporo : Institute of forest utilisation, 1973.

Moore, J. 2011. Wood properties and uses of Sitka spruce in Britain. Edinburgh : Forestry

Commission, 2011. ISBN 978-0-85538-825-6.

Quality of wood chip fuel. Kofman, P.D. 2006. 6, 2006, Harvesting and Transportation. on-line:

www.woodenergy.ie.

R.T. Hukki. 1962. Proposal for a Solomonic settlement between the theories of Von Rittinger, Kick

and Bond. : American Institute of Mining Engineers, 1962.

Re-sourcing Associates Inc. 1997. Wood waste recovery: size reduction technology study. Seatle :

CWC, 1997. CDL-97-3.

S. Brennert, K. Edsmar. 1985. Materiallära-Metaller, plaster, gummi, smörjmedel, keramer och trä.

Stockholm : Maskin AB Karlebo, 1985. ISBN 918502631X (inb.).

S. Risovic, I. Dukic, K. Vuckovic,. 2008. Energy analysis of pellets made of wood residues. 2008.

S.van Loo, J.Koppejan. 2008. The handbook of biomass combustion and co-firing. 2008. available

online through: http://site.ebrary.com/lib/linne/. ISBN 978-1-84407-249-1.

SCAN-CM 40:01. 2001. technical standards. Stockholm : Scandinavian Pulp, Paper and Board Testing

Committee, 2001.

Size reduction solutions for hard to reduce materials. S.Wennerstrum, T. Kendick, J. Tomaka, J. Cain.

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.

U.S. Forest Products Labolatory. 2010. Wood handbook - wood as an engineering material.

Madison : U.S. Department of Agriculture, 2010. available on-line:

http://www.fpl.fs.fed.us/products/publications/.

- 49 -

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.

- 50 -

APPENDIX A - different classifications of biomass comminution equipment

Table A.1 - (I. M. Petre, 2006)

- 51 -

Table A.2 - (L.J. Naimi, 2006)

Table A.3 - (Re-sourcing Associates Inc., 1997)

- 52 -

Table A.4 - (M. Hoque, 2007)

Table A.5 - [ (M. Hoque, 2007)refers to CWC 1997-Wood waste size reduction technology study]

- 53 -

APPENDIX B - technical specification of properties for solid biofuels

Table B.1 - Specification of properties for hog fuel according to CEN (E. Alakangas, 2007)

- 54 -

Table B.2 - Specification of properties for wood chips according to CEN (E. Alakangas, 2007)

- 55 -

Table B.3 - CEN list of technical standards valid for biofuels (E. Alakangas, 2007)

- 56 -

APPENDIX C - Janka Hardness and Dry density

Table C.1 - Janka Hardness and Dry density for Softwoods (U.S. Forest Products Labolatory, 2010)

Species Hardness [N] Dry density [kg/m^3]

Baldcypress 1,7 420

Cedar, Atlantic white 1,3 310

Cedar, Eastern redcedar 2,9 440

Cedar, Incense 1,7 350

Cedar, Northern white 1,0 290

Cedar, Port-Orford 1,7 390

Cedar, Western redcedar 1,2 310

Cedar, Yellow 2,0 420

Douglas-fir, Coast 2,2 450

Douglas-fir, Interior west 2,3 460

Douglas-fir, Interior north 1,9 450

Douglas-fir, Interior south 1,6 430

Fir, Balsam 1,3 330

Fir, California red 1,6 360

Fir, Grand 1,6 350

Fir, Noble 1,3 370

Fir, Pacific silver 1,4 400

Fir, Subalpine 1,2 310

Fir, White 1,5 370

Hemlock, Eastern 1,8 380

Hemlock, Mountain 2,1 420

Hemlock, Western 1,8 420

Larch, Western 2,3 480

Pine, Eastern white 1,3 340

Pine, Jack 1,8 400

Pine, Loblolly 2,0 470

Pine, Lodgepole 1,5 380

Pine, Long 2,6 540

Pine, Ponderosa 1,4 380

Pine, Red 1,5 410

Pine, Short 2,0 470

Pine, Sugar 1,2 340

Pine, Virginia 2,4 450

Pine, Western white 1,2 360

Redwood, Old-growth 1,8 380

Redwood, Young-growth 1,6 340

Spruce, Black 1,5 380

Spruce, Engelmann 1,15 330

Spruce, Red 1,6 370

Spruce, Sitka 1,6 370

- 57 -

Spruce, White 1,2 330

Tamarack 1,7 490

Table C.2 - Janka Hardness and Dry density for Hardwoods (U.S. Forest Products Labolatory, 2010)

Species Hardness [N] Dry density [kg/m^3]

Alder, red 2,0 370

Ash, black 2,3 450

Ash, green 3,9 530

Ash, Oregon 3,5 500

Ash, white 4,3 550

Aspen,Qaking 1,3 350

Basswood, American 1,1 320

Beech, American 3,8 560

Birch, Paper 2,5 480

Birch, Sweet 4,3 600

Birch, Yellow 3,6 550

Butternut 1,7 360

Cherry, black 2,9 470

Chesnut, american 1,9 400

Cottonwood, black 1,1 310

Cottonwood, eastern 1,5 370

Elm, american 2,8 460

Elm, slippery 2,9 480

Hackberry 3,1 490

Hickory, Pecan 5,8 600

Hickory, true Mockernut 6,4 640

Hickory, true Pignut 6,8 660

Hickory, true Shagbark 6,5 640

Hickory, true Shellbark 7,4 620

Honeylocust 6,2 600

Locust, black 7,0 660

Magnolia, Cucumbertree 2,3 440

Magnolia, Southern 3,3 460

Maple, Bigleaf 2,8 440

Maple, Black 3,7 520

Maple, Red 3,1 490

Maple, Silver 2,6 440

Maple, Sugar 4,3 560

Oak, red Black 4,7 560

Oak, red Cherrybark 5,5 610

Oak, red Laurel 4,4 560

Oak, red Northern 4,4 560

Oak, red Pin 4,8 580

Oak, red Scarlet 5,3 600

- 58 -

Oak, red Southern 3,8 520

Oak, red Water 4,5 560

Oak, white Bur 4,9 580

Oak, white Chesnut 4,0 570

Oak, white Overcup 4,3 570

Oak, white Post 5,0 600

Oak, white Swamp chesnut 4,9 600

Oak, white Swamp white 5,2 640

Oak, White 4,7 600

Sweetgum 2,7 460

Sycamore, american 2,7 460

Tupelo, Black 2,8 460

Tupelo, Water 3,2 460

Walnut, black 4,0 510

Yellow poplar 2,0 400

- 59 -

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 Hardness at 12% m.c.

[N]

Hardness at Equilibrium m.c.

[N] a

Baldcypress 2,30 1,70 -0,0392

Cedar, Atlantic white 1,60 1,30 -0,0256

Cedar, Eastern redcedar 4,00 2,90 -0,0421

Cedar, Incense 2,10 1,70 -0,0261

Cedar, Northern white 1,40 1,00 -0,0444

Cedar, Port-Orford 2,80 1,70 -0,0719

Cedar, Western redcedar 1,60 1,20 -0,0370

Cedar, Yellow 2,60 2,00 -0,0333

Douglas-fir, Coast 3,20 2,20 -0,0505

Douglas-fir, Interior west 2,90 2,30 -0,0290

Douglas-fir, Interior north 2,70 1,90 -0,0468

Douglas-fir, Interior south 2,30 1,60 -0,0486

Fir, Balsam 1,70 1,30 -0,0342

Fir, California red 2,20 1,60 -0,0417

Fir, Grand 2,20 1,60 -0,0417

Fir, Noble 1,80 1,30 -0,0427

Fir, Pacific silver 1,90 1,40 -0,0397

Fir, Subalpine 1,60 1,20 -0,0370

Fir, White 2,10 1,50 -0,0444

Hemlock, Eastern 2,20 1,80 -0,0247

Hemlock, Mountain 3,00 2,10 -0,0476

Hemlock, Western 2,40 1,80 -0,0370

Larch, Western 3,70 2,30 -0,0676

Pine, Eastern white 1,70 1,30 -0,0342

Pine, Jack 2,50 1,80 -0,0432

Pine, Loblolly 3,10 2,00 -0,0611

Pine, Lodgepole 2,10 1,50 -0,0444

Pine, Long 3,90 2,60 -0,0556

Pine, Ponderosa 2,00 1,40 -0,0476

Pine, Red 2,50 1,50 -0,0741

Pine, Short 3,10 2,00 -0,0611

Pine, Sugar 1,70 1,20 -0,0463

Pine, Virginia 3,30 2,40 -0,0417

Pine, Western white 1,90 1,20 -0,0648

Redwood, Old-growth 2,10 1,80 -0,0185

Redwood, Young-growth 1,90 1,60 -0,0208

Spruce, Black 2,40 1,50 -0,0667

Spruce, Engelmann 1,75 1,15 -0,0580

Spruce, Red 2,20 1,60 -0,0417

- 60 -

Spruce, Sitka 2,30 1,60 -0,0486

Spruce, White 1,80 1,20 -0,0556

Tamarack 2,60 1,70 -0,0588

Average a -0,0451

Average b 1,6774

Table D.2 - Janka Hardness and Moisture Content for Hardwoods (U.S. Forest Products Labolatory, 2010)

Species Hardness at 12% m.c.

[N]

Hardness at Equilibrium m.c.

[N] a

Alder, red 2,60 2,00 -0,0333

Ash, black 3,80 2,30 -0,0725

Ash, green 5,30 3,90 -0,0399

Ash, Oregon 5,20 3,50 -0,0540

Ash, white 5,90 4,30 -0,0413

Aspen,Qaking 1,60 1,30 -0,0256

Basswood, American 1,80 1,10 -0,0707

Beech, American 5,80 3,80 -0,0585

Birch, Paper 4,00 2,50 -0,0667

Birch, Sweet 6,50 4,30 -0,0568

Birch, Yellow 5,60 3,60 -0,0617

Butternut 2,20 1,70 -0,0327

Cherry, black 4,20 2,90 -0,0498

Chesnut, american 2,40 1,90 -0,0292

Cottonwood, black 1,60 1,10 -0,0505

Cottonwood, eastern 1,90 1,50 -0,0296

Elm, american 3,70 2,80 -0,0357

Elm, slippery 3,80 2,90 -0,0345

Hackberry 3,90 3,10 -0,0287

Hickory, Pecan 8,10 5,80 -0,0441

Hickory, true Mockernut 8,80 6,40 -0,0417

Hickory, true Pignut 9,50 6,80 -0,0441

Hickory, true Shagbark 8,40 6,50 -0,0325

Hickory, true Shellbark 8,10 7,40 -0,0105

Honeylocust 7,00 6,20 -0,0143

Locust, black 7,60 7,00 -0,0095

Magnolia, Cucumbertree 3,10 2,30 -0,0386

Magnolia, Southern 4,50 3,30 -0,0404

Maple, Bigleaf 3,80 2,80 -0,0397

Maple, Black 5,20 3,70 -0,0450

Maple, Red 4,20 3,10 -0,0394

Maple, Silver 3,10 2,60 -0,0214

Maple, Sugar 6,40 4,30 -0,0543

- 61 -

Oak, red Black 5,40 4,70 -0,0165

Oak, red Cherrybark 6,60 5,50 -0,0222

Oak, red Laurel 5,40 4,40 -0,0253

Oak, red Northern 5,70 4,40 -0,0328

Oak, red Pin 6,70 4,80 -0,0440

Oak, red Scarlet 6,20 5,30 -0,0189

Oak, red Southern 4,70 3,80 -0,0263

Oak, red Water 5,30 4,50 -0,0198

Oak, white Bur 6,10 4,90 -0,0272

Oak, white Chesnut 5,00 4,00 -0,0278

Oak, white Overcup 5,30 4,30 -0,0258

Oak, white Post 6,00 5,00 -0,0222

Oak, white Swamp chesnut 5,50 4,90 -0,0136

Oak, white Swamp white 7,20 5,20 -0,0427

Oak, White 6,00 4,70 -0,0307

Sweetgum 3,80 2,70 -0,0453

Sycamore, american 3,40 2,70 -0,0288

Tupelo, Black 3,60 2,80 -0,0317

Tupelo, Water 3,90 3,20 -0,0243

Walnut, black 4,50 4,00 -0,0139

Yellow poplar 2,40 2,00 -0,0222

Average a -0,0354

Average b 3,8241

- 62 -

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 Productivity

Output

size

Input

size Chipper

model Producer Type

[kW] [kg/h] [mm] [mm]

10,0 1400 4 100 HJ 4 Jukkari Disk Chipper

35,0 4200 12 100 HJ 4 Jukkari Disk Chipper

20,0 2800 5 170 HJ 5 Jukkari Disk Chipper

50,0 5600 12 170 HJ 5 Jukkari Disk Chipper

20,0 4900 3 250 HJ 10 Jukkari Disk Chipper

55,0 14000 15 250 HJ 10 Jukkari Disk Chipper

20,0 2800 3 190 HJ 200 GGT Jukkari Disk Chipper

50,0 7000 15 190 HJ 200 GGT Jukkari Disk Chipper

30,0 4900 3 250 HJ 260 GGT Jukkari Disk Chipper

75,0 14000 18 250 HJ 260 GGT Jukkari Disk Chipper

30,0 4900 3 250 HJ 260 C Jukkari Disk Chipper

75,0 21000 18 250 HJ 260 C Jukkari Disk Chipper

80,0 21000 5 450 HJ 500 C Jukkari Disk Chipper

150,0 70000 20 450 HJ 500 C Jukkari Disk Chipper

19,9 5600 9 120 SKORPION

120 S Teknamotor Disk Chipper

21,0 5600 9 120 SKORPION

120 SD Teknamotor Disk Chipper

28,3 8400 9 160 SKORPION

160 SD Teknamotor Disk Chipper

47,1 12600 9 250 SKORPION

250 SDT Teknamotor Disk Chipper

22,0 5600 20 140 SKORPION

280 EB Teknamotor

Drum

Chipper

37,0 7000 11 120 SKORPION

350 EBS/28 Teknamotor

Drum

Chipper

37,0 8400 10 120 SKORPION

350 EB/4 Teknamotor

Drum

Chipper

45,0 14000 20 160 SKORPION

500 EB/2 Teknamotor

Drum

Chipper

45,0 5600 10 200 SKORPION

500 EBZ/2 Teknamotor

Drum

Chipper

110,0 14000 35 200 SKORPION

650 EB/2 Teknamotor

Drum

Chipper

22,0 5600 9 120 SKORPION

120 E Teknamotor Disk Chipper

30,0 8400 9 160 SKORPION

160 E Teknamotor Disk Chipper

45,0 12600 9 250 SKORPION

250 E Teknamotor Disk Chipper

- 63 -

45,0 5600 7 250 SKORPION

250 E/4 Teknamotor Disk Chipper

30,0 5600 6 80 SKORPION

250 EB/4 Teknamotor

Drum

Chipper

15,0 1470 15 200 600

Kowloon

Machine

Manufacturing

Ltd

Disk Chipper

30,0 2450 15 250 800

Kowloon

Machine

Manufacturing

Ltd

Disk Chipper