Contribution of Particle Size and Moisture Content to Flowability of Fractionated  
Ground Loblolly Pine 
 
by 
 
Oluwatosin Jerry Oginni 
 
 
 
A thesis submitted to the Graduate Faculty of 
Auburn University 
in partial fulfillment of the 
requirements for the Degree of 
Master of Science 
 
Auburn, Alabama 
August 2, 2014 
 
 
Keywords: Loblolly pine, particle size, moisture content, physical and flow properties, fraction 
 
Copyright 2014 by Oluwatosin Jerry Oginni 
 
 
 
 
 
Approved by 
 
Oladiran Fasina, Chair, Professor of Biosystems Engineering 
Sushil Adhikari, Associate Professor of Biosystems Engineering 
John Fulton, Associate Professor of Biosystems Engineering 
 
 
 
 
 
 
 
 
ii 
 
 
 
 
 
 
 
Abstract 
 
 
 The use of woody biomass requires feedstock materials in particulate form; therefore there 
is a need for size reduction of the feedstock materials. Ground biomass typically has a non-uniform 
particle size and as a biological material, biomass will exchange moisture with the environment. 
Thus, ground biomass feedstock will have typical flow problems associated with bulk materials 
during storage. The objective of this research is to investigate the contribution of particle size and 
moisture content to flowability of fractionated ground loblolly pine. In this study, ground loblolly 
pines were fractionated into six size classes at five moisture content levels. The physical and flow 
characteristics of the fractionated samples that are related to flowability and design of the storage 
vessels were quantified. The geometric mean diameters for the fractions were in the range 0.10 - 
2.38 mm. Bulk and tap densities of the fractions increased with fraction size but particle density 
was not affected by fraction size. The densities (bulk, particle and tap) decreased with increase in 
moisture content. Porosity, Hausner ratio and compressibility increased with increase in moisture 
content and reduction in fraction size. The flowability of the fractions decreased with decrease in 
fraction size and increase in moisture content. Flow index values of 4.11, 4.17 and 4.29 were 
recorded for 1.40 mm fractions at moisture levels of 4.78%, 8.69% and 16.53%, respectively which 
implies easy flowing. However, a reduction in flowability from easy flowing to cohesive flowing 
was observed when 1.40 mm fractions were dosed with 0.50 mm fractions at 10:1, 10:2 and 10:3 
mass ratio respectively. Cohesive strength and angle of internal friction decreased with increase in 
fraction size. Moisture content caused an increase in angle of internal friction but had no significant 
iii 
 
effect on the cohesive strength of the fractions. Particle size and moisture content had a significant 
effect on the angle of wall friction of the fractions. There was a reduction in wall friction angle 
with increase in fraction size. Lower wall friction angles were obtained at lower moisture content 
when stainless and mild steel surfaces were used while Tivar 88 surface had a consistent low angle 
of wall friction at all moisture levels. The adjusted hopper outlet size varied between 1.20 and 
28.56 mm with 1.40mm fraction having the highest minimum hopper outlet size. The wall normal 
and vertical pressure acting on the cylindrical section of the silo increased from 9.35 to 45.42 kPa 
and 15.34 to 48.91 kPa, respectively with increase in fraction size and decrease in moisture content. 
The initial fill and flow induced pressures acting on the hopper section of the silo increased from 
15.34 to 48.91 kPa and 24.71 to 78.79 kPa, respectively with increase in fraction size and decrease 
in moisture content. The heating values (18-19 MJ/kg) and volatile matter (84.91 - 87.48% d.b) 
were not affected by the fraction size while ash content was found to increase with reduction in 
the fraction size.    
 
 
 
 
 
 
 
 
 
 
 
 
iv 
 
 
 
 
 
 
 
Acknowledgments 
 
 
 First of all, I thank God for his strength and grace on my life to successfully complete this 
research work. I would like to express my sincere gratitude to my academic advisor, Dr Oladiran 
Fasina for the opportunity he gave me to learn from his vast wealth of knowledge and experience 
in this research area and to earn my degree. I appreciate his patience and professional advice during 
the course of the program. My appreciation also goes to my committee members, Dr Sushil 
Adhikari and Dr John Fulton for the professional support and knowledge they gave during the 
research work. I would like to acknowledge Alabama Agricultural Experiment Station, 
Department of Energy (DOE), Southeastern Partnership for Integrated Biomass Supply Systems 
(IBSS) and National Institute of Food and Agriculture for the provision of research fund. In 
addition, I would like to appreciate Dr. Sunday Ogunsina and Mr Gbenga Olatunde for all their 
academic and moral supports.   
 My appreciation goes to my parents, Mr and Mrs Oginni for all the encouragement and 
prayers they offered throughout the course of my master?s program. Many thanks to my siblings 
Ayo and his wife Bukola, Titi, Mayowa, Tolulope for the moral supports I got from them. To all 
my families and friends back in Nigeria, thank you all.  
To all the group members under Dr Fasina; Anshu, Gurdeep, Jaskaran, Gbenga, Ujjain and 
Oluwafemi, I appreciate the time we spent working together. Thanks to all my Auburn friends and 
family for the time we had together.      
 
 
v 
 
 
 
 
 
 
Table of Contents 
 
 
Abstract ...........................................................................................................................................ii 
Acknowledgments .........................................................................................................................iv 
List of Figures  .............................................................................................................................viii 
List of Tables ..................................................................................................................................x 
Chapter 1 Introduction?????????????????????????????. 1 
Chapter 2 Literature review ?????????????????????????? ? 4 
2.1 Biomass: A Source of Renewable Energy???????????????.. ? ...4 
2.2 Biomass Supply Logistics ?????????????????????? ?. 6 
2.3 Size reduction and particle size ???????????????????? ?. 7 
2.4 Flow patterns and flow problems???????????????????... ..10 
2.5 Physical Properties ????????????????????????? ..14 
2.5.1 Bulk density ?????????????????????????? ..14 
2.5.2 Particle density ?????????????????????????..16  
2.5.3 Porosity ????????????????????????????.18  
2.5.4 Compressibility ?????????????????????????.19  
2.5.5 Hausner ratio ??????????????????????????.21  
2.6 Flow Properties ??????????????????????????..23  
2.6.1 Cohesion ????????????????? ??????????...25  
2.6.2 Angle of wall friction ???????????????????????27  
2.6.3 Flow function and index ?????????????????????...28  
2.6.4 Design of hopper for flow ?????????????????????.30  
Summary ??? ???????????????????????????...33  
Chapter 3 Particle Size and Moisture Effect on Physical of Fractionated Ground Loblolly Pine 34 
3.1. Abstract ?? ???????????????????????????...34  
3.2. Introduction ????????????????????????????.35  
3.3. Materials and Methods ????????????? ??????????....37  
vi 
 
3.3.1 Sample preparation and fractionation ????????????????.. .37 
3.3.2 Particle size distribution ?????????????? ????????38  
3.3.3 Bulk density ??????????????????????????..39  
3.3.4 Particle density ?????????????????????????..39      
3.3.5 Tap density, compressibility and hausner ratio ????????????? .40 
3.3.6 Composition and energy determination ????? ???????????41  
3.3.6.1  Sample preparation ?????????? ???????????...41  
3.3.6.2  Energy content ..............................................................................................41 
3.3.6.3  Ash content ......................???????????????????.41  
3.3.6.4  Volatile matter ...................... ?????????????????...42    
3.3.7 Experimental design and statistical analysis ?????????? ...? ??43  
3.4 Results and Discussion ...............................................................................................43 
3.4.1 Particle size distribution ??????????????????????43  
3.4.2 Bulk density ???????????????????????.???.49  
3.4.3 Tap density.......?????????????????????????..5 1 
3.4.4 Hausner ratio....??????????????????????... ...........53 
3.4.5 Compressibility ???????????????????????. ??5 4 
3.4.6 Particle density .??????????????????????? ??.5 6 
3.4.7 Porosity.............???????????????????????.??57  
3.4.8 Compositional analysis??????????????????????..5 9 
3.4.8.1 Energy content???????????????????????..59  
3.4.8.2 Ash content ????????????? ???????????..60  
3.4.8.3 Volatile matter ???????????????????????.61  
3.5 Conclusion ????????????????????????????..62   
Chapter 4 Sensitivity of Hopper Design Parameters to Measured Physical and Flow Properties of 
Fractionated Ground Loblolly Pine ...............................................................................................64 
4.1 Abstract? ????????????????????????????..6 5 
4.2 Introduction ???????????????????????????...6 5 
4.3 Materials and Methods ???????????????????????..6 7 
4.3.1 Sample preparation???????.????????????????...67  
4.3.2 Flow properties .....................................................................................................67 
vii 
 
4.3.3 Wall friction properties ?????????????????? ...?... ?69  
4.3.4 Hopper design calculation ????????????????? .????69  
4.3.4.1 Hopper half angle ?????????????????? .????69  
4.3.4.2 Minimum hopper outlet size ?????????????? .???69  
4.3.4.3 Silo wall loads ???????????????????????.. 70 
4.3.5 Experimental design and statistical analysis ............................................................72 
4.4 Results and Discussion ?????????????? ??? ....? ?? ?.. ..73 
4.4.1 Flow classification of fractionated ground loblolly pine ???? ...???.. ? .71 
4.4.2 Angle of internal friction ??????????????? .?.... ? ??..78  
4.4.3 Cohesive strength????.. ?????????????? .????.?..79  
4.4.4 Wall friction properties???????..????????? .????.?.. 80 
4.4.5 Hopper half angle and minimum discharge outlet size .........................................85 
4.4.6 Silo wall loads .......................................................................................................90 
4.5 Conclusion ???? ????????????????????????.95  
Chapter 5 Summary and Recommendation ?????????????????? ??..96  
5.1 Summary ?????????????????????????????.96  
5.2 Recommendation ??????????????????????????97  
References. ??? ??????????????????????????????99  
Appendix A..????????????????? ... .........................................................112 
Appendix B: SAS codes for statistical analysis???........?????????????... 123 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
viii 
 
 
 
 
List of Figures 
 
Figure 1.1 Hammer rash on bins with flow problems......................................................................2 
Figure 2.1 Flow chart of biomass supply logistics ..........................................................................7 
Figure 2.2 Types of flow patterns in storage vessel: (a) Funnel flow; (b) Mass flow  ..................11 
Figure 2.3 Typical flow problems associated with bulk solids ......................................................12 
Figure 2.4 Jenike shear cell ............................................................................................................24 
Figure 2.5 Typical plot of yield locus ............................................................................................25 
Figure 2.6 Flow function: easy versus di?cult ?ow .....................................................................29 
Figure 2.7 Hopper design chart for a conical hopper based on the Jenike?s theory ......................32 
Figure 2.8 Evaluation of critical applied stress ..............................................................................32 
Figure 3.1 Particle size distribution of unfractionated loblolly pine fractions ..............................44 
Figure 3.2a Particle size distribution of fractionated loblolly pine at 4.78% moisture level .........45 
Figure 3.2b Particle size distribution of fractionated loblolly pine at 8.69% moisture level ........45 
Figure 3.2c Particle size distribution of fractionated loblolly pine at 16.53% moisture level .......46 
Figure 3.2d Particle size distribution of fractionated loblolly pine at 22.21% moisture level ......46 
Figure 3.2e Particle size distribution of fractionated loblolly pine at 25.53% moisture level .......47 
Figure 3.2f Particle size distribution of fractions retained on screen size 0.05mm .......................47 
Figure 3.3 Particle size effect on energy content of fractionated loblolly pine .............................60 
Figure 3.4 Particle size effect on ash content of fractionated loblolly pine ...................................61 
Figure 3.5 Particle size effect on volatile matter of fractionated loblolly pine ..............................62 
Figure 4.1 Typical flow problems associated with bulk solids ......................................................65 
Figure 4.2: Powder flow tester and accessories ............................................................................68 
Figure 4.3 Silo subdivision into vertical and hopper section .........................................................71 
Figure 4.4 Initial fill and flow induced pressure on hopper section of a silo ................................72 
Figure 4.5a Flow function of fractionated loblolly pine at 4.78% moisture content......................73 
ix 
 
Figure 4.5b Flow function of fractionated loblolly pine at 8.69% moisture content??? .??. 74 
Figure 4.5c Flow function of fractionated loblolly pine at 16.53% moisture content??? .?... 74 
Figure 4.5d Flow function of fractionated loblolly pine at 22.21% moisture content??? .?... 75 
Figure 4.5e Flow function of fractionated loblolly pine at 25.53% moisture content ??? .?.. 75 
Figure 4.6 SEM images of stainless steel, mild steel and tivar 88 wall surfaces .............................84 
Figure 4.7 Effect of moisture content on hopper angle of 0.25mm fraction..................................87 
Figure 4.8 Effect of fraction size on hopper half angle at 4.78% moisture level...........................87 
Figure 4.9 Plot of wall friction angles and hopper half angle of ground loblolly pine??? .? ..88 
Figure 4.10 Flow function and flow factor of fraction size 0.25mm at 8.69 % moisture content..89 
Figure 4.11 Effect of moisture content on pressures acting on silo wall for 0.25 mm fraction .....92 
 
Figure 4.12 Effect of particle size on pressures acting on the cylindrical and hopper section of the 
silo wall .........................................................................................................................................92 
. 
Figure 4.13 Plot of vertical and wall pressure against cylindrical height for 0.05 mm fraction at 
4.78 % moisture level ...................................................................................................................93 
Figure 4.14 Plot of initial and flow induced loads against hopper height for 0.05 mm fraction at 
4.78 % moisture level.?.??????????????????????????...... 93 
 
 
 
 
 
 
 
 
x 
 
 
 
 
 
List of Tables 
 
 
Table 2.1 Flowability classification of bulk solids based on mechanical compressibility.......20 
Table 2.2 Flowability classification using Hausner ratio ..............................................................22 
Table 2.3 Jenike classi?cation of powder ?owability by ?ow index (?c) ....................................28 
Table 3.1 Geometric mean diameters of fractionated ground loblolly pine ..................................49 
Table 3.2 Bulk density (kg/m3) of fractionated ground loblolly pine .??..???? ?? .........50 
Table 3.3 Tap density (kg/m3) of fractionated ground loblolly pine .............................................52 
Table 3.4 Hausner ratio of fractionated ground loblolly pine ........................................................54 
Table 3.5 Compressibility of fractionated ground loblolly pine ....................................................55 
Table 3.6 Particle density (kg/m3) of fractionated ground loblolly pine .......................................57 
Table 3.7 Porosity of fractionated ground loblolly pine ................................................................59 
Table 4.1 Jenike classi?cation of powder ?owability by ?ow index (?c).....................................76 
Table 4.2 Flow classification of fractionated ground loblolly pine................................................76 
Table 4.3 Flow indices of mixture of 1.40mm and 0.50mm fractions??????? ??. ......77 
Table 4.4 Angle of internal friction of fractionated loblolly pine?????????.??... ..78 
Table 4.5 Cohesive strength (kPa) of fractionated ground loblolly pine???????? .?.. .80 
Table 4.6 Angle of wall friction of fractionated ground loblolly pine using stainless steel wall...81 
Table 4.7 Angle of wall friction of fractionated ground loblolly pine using mild steel wall.........82 
Table 4.8 Angle of wall friction of fractionated ground loblolly pine using Tivar 88 wall ?? ..83 
Table 4.9 Evaluation of hopper half angle, flow factor and hopper opening diameter (Dmin) for a 
cylindrical hopper using Jenike?s method .....................................................................................86 
Table 4.10 Silo wall loads of fractionated ground loblolly pine....................................................91 
Table A.1 Symbols and Nomenclatures .................................................................................?.1 12 
Table B.1: ANOVA result of particle size and moisture effect on particle density of fractionated 
ground loblolly pine? ?.. ???????????????????? ??????.. .113 
 
Table B.2: ANOVA result of particle size and moisture effect on bulk density of fractionated 
ground loblolly pine ?????????????????????????????113  
 
Table B.3: ANOVA result of particle size and moisture effect on tap density of fractionated ground 
loblolly pine? ????????????????????????? ............???.114  
xi 
 
 
Table B.4: ANOVA result of particle size and moisture effect on compressibility of fractionated 
ground loblolly pine ???????????????????????????? .?114  
 
Table B.5: ANOVA result of particle size and moisture effect on Hausner ratio of fractionated 
ground loblolly pine ?? ?????????????????????????? .?115  
 
Table B.6: ANOVA result of particle size and moisture effect on porosity of fractionated ground 
loblolly pine ??? ????????????????????????????? .115 
 
Table B.7: ANOVA result of particle size and moisture effect on angle of internal friction of 
fractionated ground loblolly pine ????????????????????????116  
 
Table B.8: ANOVA result of particle size and moisture effect on cohesion of fractionated ground 
loblolly pine ??? ?????????????????????????????116  
 
Table B.9-1: ANOVA result of particle size and moisture effect on angle of wall friction of 
fractionated ground loblolly pine using stainless steel ??????????????? ....117 
 
Table B.9-2: ANOVA result of particle size and moisture effect on angle of wall friction of 
fractionated ground loblolly pine using mild steel ????????????????? ..117 
 
Table B.9-3: ANOVA result of particle size and moisture effect on angle of wall friction of 
fractionated ground loblolly pine using Tivar 88 surface ??.??????????? .?.118  
 
Table B.10: ANOVA result of particle size effect on volatile matter (% db) of fractionated ground 
loblolly pine ???????????????????????????? .............?118  
 
Table B.11: ANOVA result of particle size effect on energy content of fractionated ground loblolly 
pine ??? ?????????????????????????? ..............???119  
 
Table B.12: ANOVA result of particle size effect on ash content (% db) of fractionated ground 
loblolly pine .................................................................................................................................119  
 
Table B.13 Effect of wall surface on angle of wall friction at 4.78% moisture level .................120  
Table B.14 Effect of wall surface on angle of wall friction at 8.69% moisture level??? ..?1 20  
Table B.15 Effect of wall surface on angle of wall friction at 16.53% moisture level????121   
Table B.16 Effect of wall surface on angle of wall friction at 22.21% moisture level????121   
Table B.17 Effect of wall surface on angle of wall friction at 25.53% moisture level????122  
 
 
 
 
 
Chapter 1  
Introduction 
Almost every manufactured product passes through a powder, granular or particulate 
phase in its manufacturing cycle which means that a large quantity of these materials are processed, 
handled, stored and conveyed in bulk. The size range of these bulk materials varies from sub-
micron sizes to sizes as large as 3 ? 6 mm diameter. The selection and implementation of suitable 
handling systems for these materials is therefore important and crucial to efficiency and cost of 
processing. Low cost automation, efficiency of handling, reliability of equipment, installed and 
operating costs, clean operating environment, suitability of equipment to handle the required 
materials and best available technology are factors that influence the design and selection of 
storage and handling equipment (Velan, 2012).  
Ineffective and unreliable handling systems contribute to processing plant startup delays, 
process inefficiencies and equipment downtime. The extent of this was confirmed in a six-year 
study by the Rand Corp. of 40 solids processing plants in the U.S. and Canada (Merrow, 1988). 
The findings revealed that 80% of all plants studied experienced bulk solids handling problems. 
Also, the affected facilities were slow in coming up to speed, with an average startup time for some 
types (raw, unprocessed solids feedstock) approaching 18 months. Once startup began, poor 
performance continued to affect these operations with capacity ranging between 40% and 50% of 
design values (Purutyan et al., 2001).  
Inconsistent or no flow of bulk materials from storage equipment is one of the problems 
associated with bulk solid handling. Bulk materials form an arch or rat-hole inside the storage 
2 
 
vessel, preventing discharge and requiring the action of hammering, vibration, aeration or other 
methods to promote flow. This results in hopper damage from hammering, popularly known as 
hammer rash (Figure 1.1). The flow interruptions give rise to production difficulties and 
inefficiencies, including operators diverting from the main tasks to hammering of storage vessels. 
Hammering leads to safety and health issues such as noise, hand injuries and back strain (Bradley 
et al., 2011). 
       
Figure 1.1: Hammer rash on bins with flow problems (Source: Bradley et al., 2011). 
Therefore to ensure successful processing operations and enhance production rate in these 
industries, a consistent and reliable flow of bulk materials from storage equipment without flow 
obstruction, excessive spillage or dust generation is required (Fitzpatrick et al., 2004). The design 
of storage hoppers and bins for reliable flow requires information on flow properties of the stored 
material. The flow properties are also needed in handling and processing operations (Knowlton et 
al., 1994; Peleg, 1977). Bulk material properties that influence flow or flowability are termed flow 
properties. Some key factors that influence flow properties include moisture, particle size and 
shape (Fasina, 2006). 
3 
 
According to EISA (2007), over 1 billion dry tons of biomass is estimated to be produced 
annually from the abundant biomass resources in the United States. The biomass can be converted 
to liquid fuel - a sustainable replacement for fossil fuel. Biomass logistics often requires the use of 
storage equipment to hold feedstock for certain amount of time. Also, the use of biomass requires 
feedstock in particulate form. As a biological material, biomass will exchange moisture with the 
environment. These changes in particle size and moisture content of biomass will influence 
biomass flow behavior during discharge out of storage equipment and structures. Thus, biomass 
feedstock will have typical flow problems associated with bulk solid materials. Therefore, the use 
of this large quantity of biomass resources requires an effective design and selection of storage 
and handling system which will ensure consistent flow of the feedstock material for its intended 
use. Improper designs can results in biomass degradation, material loss, flow blockage and/or 
safety problems (Gil et al., 2013).  
To our knowledge at the time of conducting this research, there is no reported study on 
the contribution of particle size and moisture to the flowability of fractionated ground loblolly 
pine. Therefore, the main objective of this study was to investigate the contribution of particle size 
and moisture content to flowability of fractionated ground loblolly pine. The specific objectives of 
this study were to:  
1. quantify the physical properties of fractionated ground loblolly pine and the effect of moisture 
content on these properties. 
2. quantify the flow properties of fractionated ground loblolly pine and perform sensitivity 
analyses on the physical and flow properties in relation to silo design. 
 
 
4 
 
 
 
 
 
 
Chapter 2 Literature Review 
 
2.1 Biomass: A Source of Renewable Energy 
In recent years, there has been a continuous increase in energy demand due to technological 
development and industrialization but development of energy sources is not keeping pace with the 
spiraling consumption. The major energy supply is obtained from fossil fuels which, according to 
the US Energy Information Administration (2014), meet around 72% of U.S. energy demand and 
87% of world energy demand. Fossil fuels are fuels formed by natural processes such as anaerobic 
decomposition of buried dead organisms and it primarily consist of coal, natural gas and petroleum 
(Saxena et al., 2009).  
Due to the adverse environmental impacts, non-renewable and finite nature of fossil fuels, 
it becomes imperative to develop sustainable and environmental friendly energy sources which 
will reduce world?s dependency on fossil fuels (Kirtay, 2011; Moriarty and Honnery, 2008; Guo 
et al., 2012). These energy sources are termed renewable energy sources (e.g. biomass, wind, solar 
and geothermal) because they are continuously replenished and therefore are abundant on earth. 
About 9% of the energy consumed (total of 97 quadrillion Btu energy) in United States was 
obtained from renewable resources in 2011 (EIA, 2013). In the spectrum of renewable energy 
sources, biomass is the only renewable carbon source which can be converted into carbon-based 
fuels that can then be substituted for fossil fuel (EIA, 2008; Ozbay et al., 2001). Biomass can be 
transformed into heat, power, transportation fuels and chemicals by two main pathways; 
thermochemical and biochemical conversion. The choice of the conversion technique depends on 
5 
 
factors such as amount and type of feedstock, desired form of energy, economic and environmental 
conditions (McKendry, 2002). 
Biomass are organic materials that are plant or animal based including but not limited to 
dedicated energy crops, agricultural crops and trees, food, feed and fiber crop residues, aquatic 
plants, forestry and wood residues, agricultural wastes, bio-based segments of industrial and 
municipal wastes, processing by-products and other non-fossil organic materials (ASABE, 2011). 
It accounts for 10% of global primary energy consumption making it the largest primary source of 
renewable energy (OECD/IEA, 2010). In the United States, biomass contributes nearly 3.9 quads 
and accounts for more than 4% of total U.S. primary energy consumption (EIA, 2010).  
The United States has abundant biomass resources and has continued to increase bioenergy 
production in order to reduce energy insecurity and environmental problems posed by the use of 
fossil fuel. Perlack and Stokes (2011) stated that the United States has the resources to produce 
over 1 billion dry tons of biomass annually which can be converted into 90 billion gallons of liquid 
fuels. This quantity can replace about 30% of the nation?s current annual petroleum consumption. 
According to the Energy Independence and Security Act (2007), the goal is to increase the amount 
of renewable fuels used in the United States transportation sector from 2012 level of 15 billion 
gallons to 36 billion gallons by 2022. The mandate further stipulates that, of the 36 billion gallons 
of renewable fuel, the goal is to produce 21 billion gallons of advanced biofuels derived mainly 
from cellulosic feedstock. The cellulosic feedstock will be from forest resources and dedicated 
energy crops. 
Woody biomass has been identified as a reliable and viable biomass source due to the 
abundant quantity of forest trees in United States. Forest trees are grown approximately on one 
third (749 million hectare) of the nation?s total land (Simmons et al., 2008). On a national basis, 
6 
 
forest lands in the contiguous United States are estimated to produce 370 million dry tons of woody 
biomass annually on a sustainable basis. The current discussion of using woody biomass continues 
a long history of relying on wood for energy production, both in the United States and in the world 
(White, 2010; Perlack and Stokes, 2011). Loblolly pine is an example of a potential significant 
source of woody biomass in the southeast United States. 
Loblolly pine is a commercially important species in the southeast United States. This is 
due to its rapid growth and ease of establishment making it dominant on about 11.7 million ha (29 
million acres) and makes up over one-half of the standing pine volume (Baker and Langdon, 2013; 
Cunningham et al., 2008). According to Williams and Gresham (2006), 15.2 Mg/ha of total 
biomass can be produced every year from loblolly pine tree by intensive management. This means 
that about 177.84 million tons of loblolly pine per year is potentially available for bioenergy. 
2.2 Biomass Supply Logistics  
Biomass supply logistics involves the unit operations that are used to prepare biomass 
feedstock for the bio-refinery process (Figure 2.1). These unit operations include biomass 
harvesting and collection, storage, pre-processing, transportation and handling. Without assurance 
of efficient feedstock flow from point of origin to the throat of bio-refinery conversion, biofuel 
production can be limited by capacity and cost-prohibitive factors (BRDB, 2010). Biomass supply 
logistics represent one of the major challenges for cost effective production in the emerging lingo-
cellulosic bio-refining industries (Sokhansanj and Hess, 2009).  
The low density and high moisture content of woody biomass make biomass supply 
logistics cost intensive. For example, the bulk density of switchgrass was reported to vary between 
49.4 to 266.5 kg/m3 within the moisture content range of 8 to 60% (wb). A similar trend was also 
observed for wheat straw in which the bulk density ranged from 24.2 to 111.1 kg/m3 within the 
7 
 
same moisture content range (Lam et al., 2007). This limits the amount of biomass that can be 
handled, transported and delivered to the bio-refinery. Also, there exist flowability problems due 
to irregular particle size and high moisture content of woody biomass. This is the focus of this 
research which is to quantify the influence of particle size and moisture content on the flowability 
of ground loblolly pine. 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 2.1: Flow chart of biomass supply logistics 
(Source: www.fs.fed.us; www.directindustry.com; www.glosco-wood.com; www.southeasttree.com). 
2.3 Size reduction and particle size  
Size reduction of woody biomass is necessary because current conversion technologies 
require the use of small sized particles that are typically less than 1 mm (Wei et al, 2009; Kumar 
et al, 2009). Size reduction as a pretreatment process changes the particle size, shape, particle 
density and bulk density of biomass. It increases the total surface area of the material and the 
Woody biomass harvesting  Wood chipping 
 Size reduction   Biomass storage  
8 
 
number of contact points for inter-particle bonding (Drzymala, 1993). More importantly, size 
reduction of lingo-cellulosic biomass minimizes mass and heat transfer limitations during 
conversion processes (Schell and Harwood, 1994). Chundawat et al. (2006) found that size 
reduction of corn stover and separation to various size fractions affected pretreatment and 
hydrolysis processes. The author further found that glucan and xylan conversions were enhanced 
by 15?20% when corn stover was ground to particle size of <0.15 mm.  
Size reduction of woody biomass usually involves two steps. The first step is wood 
chipping where a wood log is fed to the disk chipper and the wood chips produced usually have 
sizes ranging from 5 to 50 mm (Naimi et al., 2006). The second step is biomass milling, which 
further reduces the wood chips into smaller particles. Wood particles produced by biomass milling 
usually have sizes ranging from 0.1 to 10 mm (Zhang et al., 2010). Equipment such as hammer 
mills, knife mills, ball mills, needle mills, shredders, linear knife grids, and disk attrition mills are 
used for biomass milling (Igathinathane et al., 2009; Zhu et al., 2009). Hammer mill is the most 
commonly used size reduction equipment because it is relatively cheap, easy to operate, high 
throughput rate, versatility in grinding different materials and produce wide range of particles 
(Bitra et al., 2009; Lopo, 2002). Hammer mill utilizes impact load produced by a rotating shaft 
with attached fixed or swinging hammers to break down larger sized particles into smaller size 
particles (Austin, 2002).  
Size reduction is an energy intensive operation accounting for up to one-third of the power 
requirements of the entire bioconversion to ethanol (US Department of Energy, 1993). Energy 
consumption for grinding depends on biomass initial and final particle size, moisture content, 
material properties, mass feed rate and machine variables such as screen size and type of grinding 
equipment (Mani et al., 2004). Specific energies between 46 kJ/kg and 107 kJ/kg were reported 
9 
 
for size reduction of corn stover (Dilts, 2007). Mani et al. (2004) observed an increase in energy 
requirement with decreasing final particle size and increased moisture content for corn stover and 
barley straw. Size reduction of corn stover from particle size of 12.5 mm to particle sizes of 3.2 - 
0.8 mm respectively with increase in moisture content from 6.2 to 12% (wb) resulted in increased 
average energy requirement from 25.06 to 123.5 kJ/kg. Increase in average energy requirement 
from 49.6 to 358.2 kJ/kg was also reported for barley straw with size reduction from particle size 
of 20.52 mm to size range of 3.2-0.8 mm and moisture content increase from 6.2 to 12.0% (wb). 
Datta (1981) reported that coarse size reduction of hardwood chips (0.2?0.6 mm) required 72?144 
kJ/kg of energy. The grinding energy requirement increased five times (360- 720 kJ/kg) when the 
chips were ground to smaller particle size of 0.15?0.3 mm.  
Particles generated during size reduction are not uniformly sized. Therefore, particle size 
distribution is sometimes used as a measure of efficiency for the size reduction process (Bitra et 
al., 2009). Particle size distribution is a measure of the variation in size of particles after size 
reduction. The distribution for biomass materials are skewed (i.e., log-normal distribution). 
Examples of this can be found in studies published on alfalfa forage grinds (Yang et al., 1996), 
corn stover grind (Mani et al., 2004), barley, canola, oat and wheat straw (Adapa et al., 2009) and 
peanut hull (Fasina, 2008). This skewness is typically obtained for naturally occurring particle 
population (Rhodes, 1998).  
An effective way of expressing and comparing particle size distribution of ground material 
on a statistical basis is the geometric mean diameter and the geometric standard deviation. The 
geometric mean diameter is the median size of particles by mass or median size of particles 
retained on a sieve during a sieve analysis. It is used to describe the particle size and distribution 
of ground materials. The geometric standard deviation is the deviation of particle diameters by 
10 
 
mass in a log-normal size distribution curve (ASABE Standards, 2008). These two parameters are 
often used in characterizing the particle size of ground materials measured either by a sieving 
analysis or an image analysis.   
Particle size is dependent on the screen size of the milling equipment and the biomass 
material. Mani et al. (2004) reported geometric mean diameters for corn stover and switchgrass 
using a hammer mill screen size of 0.8, 1.6 and 3.2 mm to be 0.19 and 0.25 mm; 0.26 and 0.28 
mm; 0.41 and 0.44 mm respectively. It can be observed from the results that increase in the screen 
size resulted in increase in the geometric mean diameter. Also, although the same screen sizes 
were used for the two feedstock materials, there was a difference in the geometric mean diameters 
with switch grass having a higher geometric mean diameter as compared to corn stover. The 
variation in the particle sizes of ground biomass is an underlying factor which influences physical 
and flow behavior off ground biomass. 
2.4 Flow patterns and flow problems 
Flow is defined as the relative movement of bulk particles in comparison to neighboring 
particles or along the wall of a storage container. Flowability therefore is a measure of the 
cohesiveness and adhesiveness of bulk material (Peleg, 1977; Woodcock and Mason, 1987). 
Particles that do not flow well tend to have strong tendency to stick to one another (high cohesion) 
due to attractive forces between particles. Adhesion occurs when particles in storage silos or bins 
?stick? to the walls or exterior surface of the storage container. The two main types of flow patterns 
that exist when bulk materials are discharged from storage equipment are funnel flow and mass 
flow. 
Funnel flow (Figure 2.2a) occurs when the particles move out through a central ?funnel? 
that forms within the material, followed by collapse of particles against the walls and moving of 
11 
 
these collapsed particles through the funnel (Johanson, 2002; Purutyan, et al., 1998; Shamlou, 
1988). It is a first-in last-out flow pattern which is unsatisfactory for bulk solids that degrade with 
time. It is also unsatisfactory for fine bulk solids of low permeability. Such materials may aerate 
during discharge through flow channel and this can lead to flooding problem or uncontrolled 
discharge (Roberts, 1994). In mass flow (Figure 2.2b), the bulk solid is in motion at every point 
within the bin and is moving downwards towards the opening. Mass flow is a ?first-in first-out? 
flow pattern and it guarantees complete discharge of the bin contents at predictable flow rates 
(Roberts, 1994).  
     
(a) Funnel flow    (b) Mass flow 
Figure 2.2: Types of flow patterns in a storage vessel: (a) Funnel flow; (b) Mass flow.  
(Source: jenike.com) 
 
The two problems that are usually associated with these two flow patterns are shown in 
Figure 2.3 (cohesive arching for mass flow and ratholing for funnel flow). An arch (Figure 2.3a) 
is a stable obstruction that forms within the hopper section (i.e., the converging portion of the bin) 
usually near the bin outlet. Such an arch supports the rest of the bin?s contents preventing discharge 
of the remaining powder. A rathole (Figure 2.3b) is a stable pipe or vertical cavity that empties 
12 
 
above the bin outlet. Material is left stranded in stagnant zones that usually remain in place until 
an external force is applied to dislodge it. Flow problems such as ratholing and arching can result 
in structural failure and damaging of silos, process inefficiencies, and frequent equipment 
downtime (Prescott and Barnum, 2000; Johanson, 2002; Merrow, 1988). 
           
     (a) Cohesive arching                     (b) Ratholing    
Figure 2.3: Typical flow problems associated with bulk solids (Source: jenike.com) 
 
These flow problems have been documented to exist during the storage and handling of 
ground biomass feedstock. This is due to the non-uniform particle sizes obtained after size 
reduction and change in moisture content of biomass feedstock. Liu (2008) stated that ground corn 
and DDGS are a mix of particulate materials in which the relative amounts of particles present, 
sorted according to size affects the handling characteristics of the materials.  The ground material 
possesses a distribution of particle sizes which contributes differently to its flow behavior during 
discharge from storage vessels. For example, Gil et al. (2012) carried out an experiment on the 
handling characteristics of Cardoon (Cynara cardunculus L.), a herbaceous perennial plant used 
13 
 
as a biomass feedstock. Frequent and continuous bridging was observed during the discharge of 
the ground whole cardoon (comprising of the capitula, stems and leaves) with particle size range 
of 0.5 ? 1.0 mm. This problem was attributed to the interlocking elongated particles of the stem 
and the capitula hairs which possess a small diameter and a great length, hence having a tendency 
to entangle, build up structures that trap other small sized particles which ultimately impeded the 
flow. A better understanding of the contribution of the varying particle fractions to the overall 
flowability of the whole ground feedstock can be achieved through fractionation.  
Fractionation is the separation of a material into multiple component parts (Adapa et al., 
2004). Size sensitive fractionating or screening is a unit operation in which a mixture of various 
sizes of solid particles can be separated into two or more fractions by passing over a screen. Screens 
usually made from metal bars, perforated plates, perforated cylinders, woven cloth or fabrics are 
employed for this operation. Screening (known as sieving) is also used for particle size analysis to 
determine the size distribution of granular and powder materials (Brennan et al., 1969). Rosentrater 
et al. (2006) however stated that size sensitive fractionation has the potential to achieve the 
following: (i) more controlled particle size range manipulation to achieve desired specifications 
for certain applications. For example; a decrease in particle size of a given mass of material leads 
to an increase in the exposed surface area of the solid. This increase in area is of great importance 
in many rate-dependent processes; (ii) separation of desired constituents from a composite stream. 
Fractionation of ground woody biomass into size classes therefore will help in quantifying the 
contribution of particle size to the physical and flow properties of the whole ground material, which 
is the main focus of this research.  
 
 
14 
 
2.5 Physical Properties 
Physical properties that are relevant to the handling, storage, and processing of biological 
materials include bulk density, particle density, tap density, porosity and compressibility (Ortega-
Rivas, 2003). Ground loblolly pine is a bulk solid and therefore will possess typical flow issues 
associated with bulk material. Physical properties are used to design new and retrofit existing bins, 
hoppers and feeders; determine the basis of flow problems and understand differences between 
various bulk materials or grades of the same material (Fitzpatrick et al., 2004). Particle size and 
moisture content are two intrinsic factors that influence these physical properties; hence the need 
to study the effect of particle size and moisture on physical properties of ground loblolly pine.  
2.5.1 Bulk density  
Bulk density is the ratio of the mass of a bulk material to its bulk volume. Bulk density 
significantly impacts supply logistics, engineering design and operation of transportation 
equipment, material handling systems and processing in the bio-refinery (Sokhansanj and Fenton, 
2006; Woodcock and Mason, 1987). This is because bulk density is used in estimating storage 
capacity and the amount of space needed during biomass logistics. Bulk density of granular and 
biological materials, which is affected by particle size and moisture content, is also used in 
describing the flowability of the materials. Flow indicators such as compressibility index and 
Hausner ratio (HR) are calculated from the density values of the material (Abdullah and Geldart, 
1999; Probst et al., 2013).    
Bulk density generally decreases with increase in particle size. The larger particles 
occupies more pore volume than the smaller particles, hence the higher bulk density of the smaller 
particles up to a certain diameter. Mani et al. (2004) found an inverse relationship between bulk 
density and particle sizes of corn stover and switchgrass. The bulk density of corn stover decreased 
15 
 
from 158 to 131 kg/m3 with an increase in the particle size from 0.19 to 0.41 mm. A similar trend 
was reported for switchgrass with a decrease in the bulk density from 182 to 115 kg/m3 as particle 
size increased from 0.25 to 0.46 mm. Manickam and Suresh (2011) reported a decrease in the bulk 
density of coir pith from 200 to 100 kg/m3 with increased particle size from 0.655 to 0.925 mm. 
Similar trend was reported for the bulk densities of ground canola (203 to 144 kg/m3), barley (155 
to 99 kg/m3), oat (196 to 111 kg/m3) and wheat (154 to 107 kg/m3) with increase in particle size 
from 0.37 to 0.89 mm, 0.46 to 0.88mm, 0.40 to 0.94 mm and 0.45 to 0.99 mm respectively (Adapa 
et al., 2011).  
However, when switchgrass was fractionated into size classes from 0.25 to 0.71mm, Lam 
et al. (2008) reported that the bulk density was found to increase from 149 to 194 kg/m3 with 
increased particle size. This change is attributed to the fact that biomass grinds collected after 
fractionation exhibit different packing as compared to the unfractionated biomass grinds. A similar 
observation was reported for the bulk density of fractionated ibuprofen powder (a pharmaceutical 
powder). The bulk density increased from 350 kg/m3 to 440 kg/m3 with increase in particle size 
from 46 to 215 ?m. The bulk density of the larger fractions was also reported to be higher than the 
bulk density (401 kg/m3) of the bulk mixture (Liu et al., 2008). This is an indication that the larger 
particles have a strong effect on the bulk density of a bulk material. 
Moisture content is the amount of water present in the biomass feedstock. Several 
published studies have shown that moisture content significantly influences the bulk density of 
biomass. As moisture content increases, there is a corresponding decrease in bulk density. This is 
a result of the increase in mass due to moisture gain being lower than the accompanying volumetric 
expansion of the bulk. The amount of storage space required for a given material will therefore 
increase with moisture content increase (Colley et al., 2006). Peleg et al. (1973) and Peleg and 
16 
 
Moreyra (1979) studied the effect of moisture content on food powders? bulk density. They 
observed reduced bulk density of water-soluble powders upon increasing moisture content. The 
reduction in powder bulk density was attributed to the presence of inter-particle liquid bridges 
which kept them further apart and produced a more-open structure than if the particles were non-
cohesive. This effect also produced greater compressibility for moist powders than for dry 
powders. 
Bahram et al. (2013) reported a reduction in the bulk density of wormy compost from 854 
to 658 kg/m3 as moisture content increased from 25 to 35 % (wb). Probst et al. (2013) also reported 
that the bulk density of ground corn was found to decrease from 627.4 to 607.8 kg/m3 as moisture 
content increased from 10.4 to 19.6% (wb). Similar trends were documented for granular 
biological materials such as rice (Kibar et al., 2010), soybean (Deshpande et al., 1993) and green 
gram (Nimkar and Chattopadhyay, 2001). This shows that the volume necessary to store or 
transport biological materials (with identical mass) will increase as moisture content increases 
(Littlefield et al., 2011). 
2.5.2 Particle density 
Particle density is the ratio of the average mass to average volume of particle that form the 
bulk solid. Particle density measures the density of the particle matter excluding the air pores, 
hence it is called true density (Ileleji and Rosentrater, 2008). Although, particle density is not 
required in the design of storage silo, however it is an important parameter that is needed in the 
design of systems for ventilation and cooling of biomass during storage (Fasina and Sokhansanj, 
1995; Pabis et al., 1998). Particle density is also used as an indicator of the pelletability of a 
material. Higher values result in good quality pellets and easier pelletability since less energy is 
needed to achieve densification of the material (MacBain, 1966; Leaver, 1985). The relationship 
17 
 
between particle size and particle density of biological materials have been reported by several 
authors. Gil et al. (2013) reported an increase in particle densities of poplar and cornstover from 
1293 to 1457 kg/m3 and 1450 to 1472 kg/m3 respectively with a reduction in particle size from 
0.70 to 0.26 mm. Mani et al. (2004) also reported an increase in the particle density of switchgrass 
from 950 to 1170 kg/m3 as the particle size decreases from 0.46 to 0.25 mm at a moisture content 
of 8% (wb). The increased particle density due to particle size reduction is because the smaller the 
particle size, the lesser the air pores in the particle. This phenomenon has been confirmed for 
DDGS particles (Ileleji et al., 2007).  
Due to the exclusion of air pores during the measurement of particle density, the values 
reported for most biological materials are relatively higher than bulk density. For example, Adapa 
et al (2011) reported the particle density of barley at particle size of 0.46 mm to be 1149 kg/m3 
while bulk density was reported to be 155 kg/m3. This shows that reduction of pore spaces among 
particles will lead to higher density therefore enhancing effective logistics of biomass. However, 
this will result in reduced flowability as the material will become compacted.   
Similarly, particle density of biological material has been reported to generally decrease 
linearly with increase in moisture content. For example, at a geometric mean diameter of 0.68 mm, 
corn stover was reported to decrease in particle density from 1120 to 1112 kg/m3 with an increase 
in moisture content from 7 to 15% (wb) (Mani et al., 2004). Bahram et al. (2013) reported a particle 
density reduction from 1652 to 1443 kg/m3 of wormy compost with an increase in moisture content 
from 25 to 35% (wb). This implies that the volume of biological materials increases at a higher 
rate than the increase in mass as moisture content increases (McMullen et al., 2005).  
 
 
18 
 
2.5.3 Porosity 
Porosity is a measure of the void spaces in a material, and is a fraction of the volume of 
voids over the total volume with values that range between 0 and 100%. Porosity of a material can 
be classified based on the bulk density and particle density of the material. For example, food 
powders have bulk densities in the range of 300 to 800 kg/m3 while the particle density of most 
food powders is about 1,400 kg/m3, so these values are an indication that food powders have high 
porosity, which can be internal, external or both (Ortega- Rivas, 2009). Porosity can be a good 
prediction of the sphericity or irregularity of the particles in a bulk solid. An average porosity 
calculation of 0.4 is normal for spheroid particles, whereas irregular shaped or very small 
particulates have higher porosity values (Woodcock and Mason, 1987). High porosity values are 
a sign of logistical and economic problems that can be encountered during the storage and 
transportation of biomass, unless some form of densification is utilized (Fasina, 2007). 
Particle size and moisture content have a significant effect on porosity of biological 
materials. Lam et al., (2008) reported an increase in porosity of ground corn stover from 0.91 to 
0.94 with an increase in particle size from 0.25 to 0.71 mm. Littlefield (2010) also found the 
porosity of pecan shell to significantly increased (p < 0.05) from 0.67 to 0.71 as particle size 
increased from the 0.21 to 2.19 mm. However, Lam et al. (2008) reported that the porosity of 
switchgrass decreased from 0.87 to 0.82 with increase in particle size from 0.25 to 0.71 mm. The 
change in the trend may be due to the particle shape and type of the biomass. Although there was 
a reduction in the porosity of switchgrass and increase in the porosities of pecan shell and corn 
stover with increase in particle size, the values obtained for these three materials are typical of 
extremely irregular-shaped particles that have cohesive tendencies (Woodcock and Mason, 1987).   
19 
 
Bahram et al. (2013) reported the particle and bulk densities of wormy compost at a 
moisture content range of 25 to 35% (wb) and hammer mill screen size of 0.6mm to be 1554 ? 
1531 kg/m3 and 814 - 685 kg/m3. Based on these data, the porosity of wormy compost varies 
between 0.52 ? 0.45, which indicates a reduction in porosity with increase in moisture content. 
Manickam and Suresh (2011) also reported a reduction in the porosity of coir pith from 0.86 to 
0.62 with an increase in moisture content from 10.1% to 60.2% (wb). Increase in moisture content 
of biological material causes volumetric expansion which is faster than increase in the mass of the 
material, therefore this results to less air space among particles thereby leading to reduction in 
porosity.     
2.5.4 Compressibility 
Compressibility is a measure of the increase in strength (or density) of powder-like 
materials with increase in consolidating (normal) pressure and it is sometimes used to assess the 
flowability of bulk material (Table 2.1, Fayed and Skocir, 1997). It is a direct function of the 
elasticity of the material under applied pressure (Schulze, 1996). The two types of compressibility 
in relation to biological materials are vibrational and mechanical compressibility. 
Mechanical compressibility occurs due to applied weight above the material while 
vibrational compressibility occurs when a bulk solid material is subjected to tapping/vibration (e.g 
during transportation). Both mechanical and vibrational compressibility can occur at the same 
time. For example, during transportation of a deep bed sample, the portion of the sample at the 
bottom of the bed will experience both mechanical and vibrational compression (Fasina, 2008). 
Mechanical compressibility is used as a measure of flowability. Table 2.1 shows that materials 
with high compressibility are deemed to have low flowability (Fayed and Skocir, 1997). 
20 
 
The compressibility of biomass feedstock is dependent on its particle size as there is a 
direct relationship between the two properties. Littlefield et al. (2011) showed that the 
compressibility of pecan shell significantly decreased with an increase in particle size and applied 
pressure. Bernhart and Fasina (2009) reported the effect of particle fractions on compressibility of 
poultry litter. The result showed that the fine fraction of poultry litter was the most compressible 
while the coarse fraction was the least compressible. When compared to the compressibility of the 
raw sample, it was reported that the fine fraction was the dominant contributor to the 
compressibility of poultry litter. A similar trend was reported by Zhou et al. (2008) on the 
compressibility of corn stover. An increase in compressibility from 20.9 to 28.4 % as the particle 
size decreased from 6.4 to 1.6 mm at < 10 % moisture content was reported. There was also an 
increase in the compressibility of corn stover from 26.4 to 30.5 % with a particle size reduction 
from 6.4 to 1.6 mm at moisture content level greater than 20 %.   
 
Table 2.1: Flowability classification of bulk solids based on mechanical compressibility 
(Fayed and Skocir, 1997). 
Compressibility (%) Bulk Solid Description Flow 
5 - 15 free-flowing granules excellent flow 
12 - 16 free-flowing powdered granules good flow 
18 - 21 flowable powdered granules fair to passable flow 
23 - 28 very fluid powders poor flow 
28 - 35 fluid cohesive powders poor flow 
33 - 38 fluid cohesive powders very poor flow 
> 40 cohesive powders extremely poor flow 
 
Increase in moisture content causes an increase in the compressibility of bulk materials 
because of increased formation of liquid bridges between particles that increases its cohesiveness 
(Teunou and Fitzpatrick, 1999; Barbosa?Canovas et al., 2005). Biological materials also become 
21 
 
softer and therefore deform more when they absorb moisture. The compressibility of ground corn 
stover with particle size of 1.6mm was reported to increase from 28.4 to 30.5 % as the moisture 
content increased from 10 to 20 % (wb).  Littlefield et al. (2011) and Bernhart and Fasina (2009) 
also reported the effect of moisture content on compressibility of pecan shells and poultry litter 
respectively and found that the compressibility of pecan shells and poultry litter increased with 
moisture content.  
2.5.5 Hausner ratio 
The ratio between tapped (defined as a certain number of taps) and aerated bulk density is 
known as the Hausner ratio (Geldart et al., 1984). Hausner ratio (HR) is an empirical constant that 
is sometimes used to assess the flowability of a bulk material (Table 2.2) (Fitzpatrick, 2003). 
Abdullah et al. (2010) observed a reduction in the Hausner ratio of silica gel with increase in 
particle size. Two distinctive sizes were observed as bordering criteria; silica gel of less than 28 
?m particle size had a Hausner ratio < 1.25, hence classified as cohesive, silica gel with particle 
size greater than 36 ?m had a Hausner ratio >1.4, hence classified as free- flowing powder and 
silica gel with particle size in between 28 and 36 ?m were said to be in transition group (i.e 
exhibiting mixed cohesive and free flowing powder behavior). Liu et al. (2008) also reported a 
reduction in the Hausner ratio of fractionated ibuprofen powder 1.39 to ~1.25 with increased 
particle size from 46 to 215 ?m. This is an indication of improved flowability with increase in 
particle size. Liu et al. (2008) further observed that the fractionated powder had a lower Hausner 
ratio as compared to the bulk powder in which even the smallest size fraction has a Hausner ratio 
smaller than that of the bulk powder. Similar trend of reduction in Hausner ratio with increased 
particle size were also reported for biological materials (wheat straw, switchgrass and corn stover) 
by Lam et al. (2008).   
22 
 
Table 2.2: Flowability classification using Hausner ratio (Source: Carr, 1965). 
Hausner ratio Flow character 
1.00-1.11 Excellent 
1.12-1.18 Good 
1.19-1.25 Fair 
1.26-1.34 Passable 
1.35-1.45 Poor 
1.46-1.59 Very poor 
>1.60 Very, very poor 
 
On the other hand, moisture content has been reported not to have significant effect on 
Hausner ratio. This is because the reduction rate of bulk density is similar to the rate of decrease 
of tap density as moisture content decreases (Bernhart and Fasina, 2009). Zhou et al. (2008) 
observed that there was no significant difference between the Hausner ratio values obtained for 
wet (> 20% MC) and dry (< 10% MC) corn stover samples within the particle size range of 6.4-
1.6 mm. The values were in the range of 1.3-1.5 which was indicative of poor flow characteristic. 
This was also in accordance to the result obtained by Emery et al. (2009) for Hydroxypropyl 
Methylcellulose (HPMC, a pharmaceutical powder). Moisture content (0% ? 10 % wb) was 
observed not to have any significant effect on the Hausner ratio of HPMC. Also, a similar trend 
was observed by Emery et al. (2009) for Aspartame powder with moisture content range of 2 to 
10% (wb). However the values reported for both powders (1.3?1.7) were above the threshold value 
of 1.25, which is an indication of poor flow characteristics. Probst et al. (2013) also reported that 
moisture content (10.39 ? 19.64% wb) had no significant effect on Hausner ratio (1.5- 1.6) of 
ground corn.       
23 
 
2.6 Flow Properties  
 Bulk material properties that influence flow or flowability are termed flow properties. Flow 
properties are used in designing and sizing equipment for storage, transportation, or general 
handling of bulk solids that will lead to reliable and consistent flow of bulk solids out of hoppers 
and feeders. Flow properties are also used in investigating the cause of flow problems of bulk 
solids (Prescott and Barnum, 2000; Schwedes, 2003). Flow properties of bulk solid materials 
includes: flow function, cohesion, angle of internal friction and angle of wall friction. 
 Particle size and moisture content are one of the most important intrinsic bulk material 
characteristics which affect the flowability (or flow properties) of bulk materials. In general, 
materials with narrow particle size distribution have a better flow than materials with wider particle 
size distribution (Benkovic and Bauman, 2009). Also, it is generally considered that materials with 
particle sizes larger than 200 ?m are free flowing, while fine powders with particle sizes less than 
200 ?m are subject to cohesion and flowability problem. The reduced flowability at smaller 
particle sizes is because of the increased surface area per unit mass of the material. There is more 
surface area or surface contacts available for frictional forces to resist flow (Fitzpatrick, 2005; 
Teunou et al., 1999; Fitzpatrick, 2007).  
Flowability of bulk solids is commonly determined using procedures developed by Jenike 
(1964). The procedure employs the principle of plastic failure with the Mohr Coulomb failure 
criteria. The Jenike shear cell unit (Figure 2.4) is used in quantifying properties such as unconfined 
yield strength, major consolidation stress, angle of internal friction and flow function (Bhadra et 
al., 2009; Thomson, 1997). 
24 
 
 
Figure 2.4 Jenike shear cell (Zulfiqar et al., 2006). 
 
Jenike?s method involves pre-consolidating the samples to be tested under different normal 
stresses until a steady state is reached. Upon reaching a steady state, a consolidating pressure and 
a horizontal shear force are applied to the sample. The shear stress required to cause the sample to 
fail under the applied consolidation stress will be measured. A yield locus (Figure 2.5), which is a 
plot of the failure shear stress versus normal stress for a given consolidation stress is then plotted. 
The test can be replicated to obtain different yield loci (Chen et al., 2012; Bhadra et al., 2009; 
Fitzpatrick et al., 2004).  
Measurement of wall friction properties with Jenike shear tester involves replacing the base 
of the shear cell with a sample of the wall material to be examined (such as stainless steel, mild 
steel or galvanized steel) as shown in Figure 2.4 (Chen et al., 2012). This test is used in determining 
the wall material needed for consistent and reliable flow out of a storage silo or bin.  
25 
 
 
 
Figure 2.5: Typical plot of yield loci of a bulk solid (Schulze, 2008). 
 
2.6.1 Cohesion   
Cohesion is the mutual attraction and resistance to separation of contacting particles of 
identical material (Nokhodchi, 2005). Cohesion in bulk solid materials is commonly caused by 
liquid bridges and Van der Waals forces (Weber et al., 2004). Liquid bridges are formed by small 
regions of liquid in the contact area of particles, in which due to surface tension effects, a low 
capillary pressure prevails. Van der Waals? force is a weak intermolecular force that exists between 
particles (Schulze, 2006). High moisture content and small particle size enhances high cohesive 
strength in biological materials which can lead to flow problems such as caking, arching and 
ratholing.  
Krantz et al. (2009) measured the flow properties of two coating powder samples 
(Polyester-Epoxy and Polyurethane) with particle sizes ranging between 22 and 31 ?m. The 
authors found that the cohesion increased with decreasing particle size for both powder 
formulations. This resulted because the finer the particle size, the more contact area between 
particles, which leads to greater cohesive forces among the particles (Marinelli and Carson, 1992). 
26 
 
Gil et al. (2013) reported the particle size effect on cohesion of ground poplar and corn stover. The 
authors also observed an increase in cohesion from 0.14 to 0.64 kPa for ground poplar with 
reduction in particle size from 0.61 to 0.30 mm. The cohesion of ground corn stover was also 
reported to increase from 0.16 to 0.68 kPa with reduction in particle size from 0.70 to 0.26 mm. A 
similar trend was documented for wormy compost where cohesion increased from 0.23 to 0.81 
kPa as particle size reduced from 1.18 to 0.30 mm (Bahram et al., 2013).  
Moisture content is an important variable that also affects cohesive strength of bulk solids 
(Johanson, 1978) during storage with cohesion generally increasing with moisture content 
(Fitzpatrick et al., 2004). The cohesion of pecan shells was found to increase from 0.36 to 1.69 
kPa as moisture content increased from 4.2 to 24.6% wb (Littlefield et al., 2011). Increased 
cohesion due to increase in moisture content was reported for flour powder, tea powder and whey 
permeate powder by Teunou and Fitzpatrick (1999). The authors observed that the strength of 
liquid bridges formed between particles depends on the amount of moisture adsorbed by the 
particles. This trend was also in accordance with Rennie et al. (1999) work on whole milk powder 
and skimmed milk powder. Buma (1971) hence concluded that increase in cohesion at higher 
moisture content was due to increased plasticity of powder particles. The increased moisture 
content could have softened the water soluble constituents of the bulk material, resulting in 
deformation of the particles hence leading to higher contact surface and cohesiveness.  In another 
research, Hargreaves et al. (2010) reported the cohesion of superheated steam dried distiller?s spent 
grain of 0% soluble content to increase between 0.078 to 0.324 kPa within moisture content range 
of 5 to 15% (wb). Unloading of bulk material using gravity discharge alone requires that cohesive 
strength do not exceed a critical value of 2 kPa (Puri, 2002).  
 
27 
 
2.6.2 Angle of wall friction 
Angle of wall friction is the resistance to flow of bulk solids along the hopper/silo wall 
material. Wall friction also represents the adhesion of bulk solid to the wall material of the storage 
equipment. Increase in angle of wall friction during storage can lead to difficulties in unloading 
bulk material from storage equipment. This flow property is a function of the bulk material and 
the wall surface in contact with it (Prescott et al., 1999; Iqbal and Fitzpatrick, 2006). 
Wall friction is a critical parameter in the design and selection of storage equipment. A low 
wall friction value results in higher normal loads being transferred onto the wall surfaces of the 
silo (Iqbal and Fitzpatrick, 2006).Wall friction value is also required in determining the minimum 
hopper angle of hopper and selection of the type of surface finish to be used in lining wall of the 
storage equipment. Wall friction characteristics are influenced by factors such as wall surface 
characteristics (e.g surface roughness, wear and corrosion), properties of the bulk solids (e.g. 
particle size and moisture content) and storage/handling conditions (Iqbal and Fitzpatrick, 2006). 
Smaller particle sizes tend to increase wall friction angle, as there is greater contact surface 
area between smaller particles and the wall surface. This is in accordance with Fitzpatrick et al. 
(2004). The wall friction angle (18.20) of soy flour with particle size of 20.2 ?m was found to be 
higher than wall friction angle (130) of corn flour with particle size of 49 ?m.  
Moisture content plays a fundamental role in combination with the kind of wall surface. 
The effect of moisture content on angle of wall friction varies with the type of wall surface used. 
Increased moisture content will cause the particles to become stickier resulting in increased 
adhesion of the particles to the wall of storage containers (Iqbal and Fitzpatrick, 2006). Duffy and 
Puri (1996) observed that the angle of wall friction of confectionery sugar on stainless and 
aluminum surface decreased from 31.00 to 24.20 and 32.20 to 29.20 respectively with increase in 
28 
 
moisture content from 0.3 to 3.2% (wb). However, increase in angle of wall friction was observed 
for detergent powder on stainless steel (14.60 to 20.80), galvanized steel (16.40 to 29.00) and 
aluminum surface (25.60 to 33.40) with increase in moisture content from 1.38 to 4.22 % (wb). 
Increased wall friction angle with increase in moisture content have been documented for ground 
poplar and corn stover (Gil et al., 2013) and flour, tea and whey permeate flour (Iqbal and 
Fitzpatrick, 2006). 
2.6.3 Flow function and index   
Flowability of a bulk solid is characterized mainly by its unconfined yield strength as a 
function of the consolidating normal stress. The unconfined yield strength of a material is the force 
or stress required to deform or break a material when it is not confined by a container (free 
unstressed surface. It can also be expressed as the stress required to fail or fracture a consolidated 
mass of material to initialize flow. Major consolidation stress is the force required to 
consolidate/compress a mass of material. The slope of the plot of the unconfined yield strength of 
the powder versus major consolidating stress is the flow function (Figure 2.6). A flow function 
lying towards the bottom of the graph represents easy flow, and more difficult flow is represented 
as the flow function move upwards in an anticlockwise direction. The flow index (ffc) is defined 
as the inverse of the flow function. Jenike (1964) used the flow index to classify powder flowability 
(Table 2.3).  
 
Table 2.3: Jenike classi?cation of powder ?owability by ?ow index (?c). 
 
Flowability Hardened Very cohesive Cohesive Easy ?ow Free ?owing 
Flow index (?c ) 
 
<1                     <2 <4 <10       >10 
                         
 
 
29 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 2.6: Flow function: easy versus di?cult ?ow (Schulze, 2008). 
 
Fitzpatrick et al. (2004) measured the flow indices for 13 food powders. Six of the samples 
(tomato, salt 200, cocoa, corn flour, sugar 140 and wheat flour) were classified as very cohesive, 
four (soy flour, corn starch, tea and NFM) were cohesive and the remaining three (maltodextrin, 
cellulose and salt 140) were easy flow. The powders that were classified as very cohesive have a 
particle size range between 320 - 51 ?m and moisture content of 17.8- 10% (w/w) while the easy 
flow have a particle size range of 12 - 55 ?m and moisture content of 0.04 - 4.3% (w/w). The 
difficult flow nature of the powders with higher particle was attributed to high moisture contents 
of the powders. Littlefield et al. (2011) further found that as the moisture content of pecan shells 
increased from 4.2 to 24.6%, the flow index values reduced from 15.77 to 3.14, indicating that 
flowability reduced from free flowing to cohesive flowing. Emery et al (2009) also reported a 
similar trend for a pharmaceutical powder named Hydroxypropyl Methylcellulose (HPMC). The 
author also classified four pharmaceutical powders (HPMC, Aspartame, API and Respitose) as 
cohesive powder within a moisture content range of 0 to 10 % (wb).    
Cagli et al. (2007) studied the effect of particle size on flow index of 3 different sand 
samples (Yalikoy, Safaalani and yellow), soda, limestone, dolomite and clay. The authors reported 
an increase in the flow index from 2.8 to 13.8 with increase in particle size from 43 to 413 ?m. 
30 
 
Clay which has a particle size of 43 ?m was found to have the lowest flow index of 2.8, which is 
an indication of cohesive flow while the soda with flow index of 13.8, is classified as free flowing 
material. The other materials were classified as easy flowing. The high flow indices observed for 
these materials is in accordance with Woodcock and Mason (1993) conclusion, that free flowing 
materials such as dry sand, have zero unconfined yield stress, and hence a cohesive arch cannot 
occur. Similarly, Liu et al. (2008) observed an increase in the flow index of fractionated 
magnesium stearate lubricated ibuprofen powder from 5.1 to 11.1 with increase in particle size 
from 53 to 250 ?m. It was also noted that the smallest fraction with particle size 53 ?m has a flow 
index slightly lower than the bulk mixture. However, based on Jenike classification, the 
fractionated magnesium stearate lubricated ibuprofen powder is classified as east flowing.           
2.6.4  Design of hopper for mass flow 
A hopper is the conical or converging section of a powder storage vessel through which 
the stored materials flows out (Holdich, 2002). The storage equipment is very crucial in any bulk 
solids handling installation. This is because occurrence of flow problems adversely affects the 
downstream production line because of the erratic supply of material. For a system to operate 
satisfactorily, bulk solid must flow from the hopper when required and in a predictable manner. 
Thus, as with any other part of the handling system, gravity-flow storage hoppers should be 
designed or selected to handle the actual product under consideration (Woodcock and Mason, 
1987). 
One of the important applications of flow properties is the design of discharge hoppers. 
Design of a discharge hopper to ensure consistent and reliable discharge involves determining the 
minimum hopper half angle (to the vertical) and discharge opening size. The minimum hopper half 
angle is designed to ensure a mass flow (Figure 2.2b), which is the preferred flow pattern for a 
31 
 
consistent and reliable flow. If the hopper half angle is less than this angle, then it is likely that a 
funnel flow pattern (Figure 2.2a) will exist (Holdich, 2002; Teunou et al., 1999; Fitzpatrick, 2007; 
Iqbal and Fitzpatrick, 2006). The flow properties required for designing a discharge hopper are 
flow function (FF), the effective angle of internal friction, angle of wall friction and bulk density. 
Jenike?s mathematical methodology is the engineering standard practice for designing a 
hopper i.e for calculating the minimum hopper angle and opening size for mass flow. Jenike?s 
design approach is based on calculation of stresses inside the hopper and postulates that the major 
consolidating stress (?1) in the lower part of hopper is proportional to the distance from the vertical 
hopper apex. Jenike (1964) solved the stress equations and determined the borderlines between 
funnel flow and mass flow in conical or wedge shaped hoppers as a function of angle of wall 
friction, hopper half angle and the effective angle of internal friction, as shown in design chart 
(Figure 2.7). The steps employed in using the flow properties are (Fitzpatrick et al., 2004): 
? Values of effective angle of internal friction and angle of wall friction are used in calculating 
the hopper half angle (?) and the flow factor (ff). 
? The critical applied stress (CAS) is determined from the intersection of the flow function and 
the flow factor line (Figure 2.8) 
? The hopper opening size is then calculated using the values of CAS, hopper half angle and 
bulk density. For example, the opening diameter for a conical hopper is given below  
? = ?(?).CAS?
?.?
 
where H is a function of the hopper half angle, ?B is the bulk density and g is the gravitational 
acceleration constant.   
32 
 
 
Figure 2.7 Hopper design chart for a conical hopper based on the Jenike?s theory.  
(Source: Maynard, 2013) 
 
 
 
 
 
 
 
 
 
 
Figure 2.8: Evaluation of critical applied stress (CAS).  
(UYS is the unconfined yield strength and MCS is the major consolidation stress). 
 
 
 
Flow factor   
line 
Flow function 
Critical 
Applied Stress 
Major Consolidation Stress (kPa) 
Unconfined 
Yield Stress 
(kPa) 
 Funnel Flow 
Mass Flow 
33 
 
Summary  
The necessity for an effective and efficient storage and handling vessels for lignocellulosic 
biomass is due to the large amount estimated to be produced annually from the abundant biomass 
resources in the United States. Therefore. improper design and selection of storage vessels can 
results in biomass degradation, material loss, flow blockage and/or safety problems. 
The use of biomass requires feedstock in particulate form. However, ground biomass 
obtained after size reduction have non- uniform particle size and also as a biological material, it 
has a tendency to exchange moisture with the environment. Therefore, ground biomass will have 
the typical flow problems associated with bulk materials during storage.  
Characterization of particle size and moisture effect on physical and flow properties of 
biomass will enhance a better prediction of biomass flow behavior and design of an appropriate 
storage vessel. Obtaining a reliable and consistent flow out of storage equipment is critical to 
successful biofuel production. Hence, the design of storage equipment requires the understanding 
of the physical and flow properties of the biomass. The physical and flow properties include 
density (bulk, tap and particle), compressibility, Hausner ratio, porosity, flow index and frictional 
properties (cohesion, angles of wall friction and internal friction).   
Loblolly pine, an energy feedstock which has been identified as a potentially significant 
source of fuel, is the most commercially important species in the southeast United States due to its 
rapid growth and ease of establishment. Hence, the focus of this research is to investigate the 
contribution of particle size and moisture content to flowability of fractionated ground loblolly 
pine in order to ensure a proper design of silo which will allow easy flow of biomass without 
obstruction or dust generation. 
 
 
34 
 
 
Chapter 3: Particle Size and Moisture Effect on Physical Properties of Fractionated 
Ground Loblolly Pine 
 
3.1 Abstract 
Particle size and moisture content are two intrinsic biomass characteristics that influence its 
physical properties. This study focused on the contribution of particle size and moisture content to 
the physical properties of fractionated ground loblolly pine. Loblolly pine chips were ground 
through a hammer mill fitted with a 3.18 mm screen and the moisture content of the ground 
biomass was adjusted between 4.78 and 25.53% (wb). The moisture adjusted ground biomass was 
fractionated into six size classes with 250 ?m to 1.40 mm screen aperture and the physical 
properties of the fractions were quantified. The particle size distribution of the unfractionated 
sample was unimodal and skewed to the left. An increase in moisture content resulted in a wider 
spread of the particles in the particle size distribution of the fractionated samples. The geometric 
mean diameters for the fractions ranged from 0.10 mm to 2.38 mm. Bulk and tap densities of the 
fractions increased with fraction size while particle density generally decreased with increase in 
fraction size. The densities (bulk, particle and tap) and porosity decreased with increased moisture 
content. Moisture content had no significant effect on compressibility and Hausner ratio. The 
heating values (18-19 MJ/kg) and volatile matter (84.91 - 87.48% d.b) were not affected by the 
fraction size while ash content (0.22 - 2.64% d.b) increased with reduction in the fraction size.    
 
 
 
 
 
35 
 
 
3.2 Introduction 
Loblolly pine grows naturally in the southern region of the United States because of its 
adaptability to variety of soil, its rapid growth rate and ease of establishment. It grows on about 
11.7 million ha (29 million acres) in the south, which is about one-half of the standing pine volume 
in this region. Therefore, it has been identified as the most commercially important species in the 
southeast United States (Baker and Langdon, 2013; Cunningham et al., 2008) and also as a 
potentially significant renewable and sustainable source of biomass feedstock that can be 
converted to useful energy forms.  
In the southern United States, woody biomass for energy is typically harvested, pre-
processed, transported and used, all within several days. Due to supply and demand imbalances 
that relate to inclement weather and energy prices (Rupar and Sanati, 2004), there is a need for 
adequate storage capabilities. Proper storage of woody biomass during excess production when 
demand exceeds supply is an important step in ensuring a reliable, continuous supply of feedstock. 
Selection and design of biomass handling and storage equipment strongly depends on the physical 
properties of biomass feedstock, therefore, the physical properties of biomass need to be 
determined (Wu et al., 2011). 
Physical properties of biomass are used in designing handling and logistic systems, 
estimating capacity of storage vessels, determining quality of feedstock supplied to the refinery 
and final conversion process (Tumuluru et al., 2014). Physical properties required in the selection 
and design of an appropriate storage vessel includes densities (bulk, tap and particle), porosity, 
compressibility and Hausner ratio.  
36 
 
Bulk density is the ratio of the mass of a bulk material to the bulk volume. Knowledge of 
bulk density is essential in designing and estimating the capacity of storage bins, hoppers, 
conveying and conversion equipment. Particle density is the ratio of the average mass to the 
average volume of the particles. Higher particle density signifies higher compression and energy 
density (Mani et al., 2006). Tap density is an increased bulk density attained after mechanically 
tapping a vessel containing the material (US Pharmacopeiai, 2011). Porosity is a measure of the 
void spaces in a material (Rahman, 2005). Compressibility is a measure of the increase in strength 
of powder-like material with increase in consolidating normal pressure (Schulze, 1996). Hausner 
ratio is an empirical constant which indicates the ratio of tapped density and bulk density. It is used 
to assess flowability of bulk solid (Fitzpatrick, 2003).    
The use of loblolly pine will require the feedstock to be ground into particulate form. 
However, ground biomass obtained after the size reduction process possesses non-uniform particle 
sizes. Particle size and moisture content have been documented to significantly affect the physical 
properties of biological materials (Manickam and Suresh, 2011; Adapa et al., 2011; Bahram et al., 
2013; Probst et al., 2013). Also, fractionation of biomass into size classes has been documented to 
enable the fundamental understanding of contribution of fractions to the properties of bulk 
biological materials (Ndegawa et al., 1991; Bernhart and Fasina, 2009). Therefore, the objectives 
of this study were (1) to quantify the effect of particle size on the physical and compositional 
properties, and (2) quantify the effect of moisture content on the physical properties of fractionated 
ground loblolly pine.   
 
 
 
 
 
 
37 
 
3.3 Materials and Methods 
3.3.1 Sample preparation    
Clean loblolly pine wood chips used in this study were collected from West Fraser Inc. 
Sawmill, Opelika, Alabama. Before use, the samples were ground through 3.18 mm screen using 
a hammer mill (Model 358, New Holland grinder, New Holland, PA).  
Experiments were carried out on the ground samples that were adjusted to five moisture 
content levels between 4.78% and 25.56% (wb). The initial moisture content of the samples after 
grinding was 8.69% (w.b). To adjust the moisture content of the samples to the desired level, the 
samples were either dried using a humidity chamber (ESL-2CA, Espec North America, Inc.) set 
at a temperature of 50 0C and relative humidity of 20% (for moisture content reduction) or the 
samples were sprayed with a known volume of water (to increase the moisture content of samples). 
After moisture adjustment, the samples were stored in an air tight container for 24 hours to allow 
moisture equilibration to take place. The moisture contents of samples were then verified with a 
moisture analyzer (model MB 45, Ohaus Corporation, Pine Brook, NJ).   
A sieve shaker (RO-TAP Model RX- 29, WS Tyler, OH) was used in fractionating the 
moisture adjusted ground samples into six fractions by fitting the sieve shaker with a #12 (1.4 mm 
aperture), #18 (1.0 mm aperture), #25 (710 ?m aperture), #35 (500 ?m aperture), #60 (250 ?m 
aperture) screens and pan. The choice of sieve sizes was based on preliminary study on the particle 
size distribution of the raw ground samples. The particle size distributions of the raw and 
fractionated samples were determined according to ASABE Standard S319.3 (ASABE Standards, 
2008). The physical properties of the fractions were carried out at each moisture level while the 
compositional properties were carried out on a dry basis.   
 
38 
 
3.3.2 Particle size distribution 
A digital image analysis system (Model Camsizer, Retsch Technology, Haan, Germany) 
equipped with two digital cameras was used to measure the particle size of the sample fractions. 
Approximately, 50 g mass of the sample was loaded onto the hopper of the instrument. The sample 
was then conveyed and dropped via a vibratory feeder onto the measurement field of the cameras. 
The particle size distribution on volume basis of the sample was recorded and analyzed by the 
software provided by the equipment manufacturer. The procedure was carried out in triplicate after 
which the geometric mean diameter and geometric mean standard deviation were calculated from 
the data obtained from the equipment software according to ASABE Standard S319.3 (2008) as 
follows: 
dgw= log-1 [? (Wilogd?i)ni=1? W
ini=1
]     3.1  
 Slog=[? (logd?i-log dgw)
2n
i=1
? Wini=1 ]
1/2
     3.2 
Sgw= 12dgw [log-1Slog-(log-1Slog)-1]    3.3 
where; dgw = geometric mean diameter or median size of particles by mass (mm); 
Slog = geometric standard deviation of log normal distribution by mass in 10-based logarithm 
(dimensionless); 
Sgw = geometric standard deviation of particle diameter by mass (mm); 
Wi = mass on ith sieve (g); 
n= number of sieves plus one pan; 
di = (di?di+1)1/2 
di = nominal sieve aperture size of the ith sieve (mm); 
di+1 = nominal sieve aperture size of the ith+1 sieve (mm) 
39 
 
3.3.3 Bulk density 
Bulk density was determined by a bulk density measuring apparatus (Burrows Co., 
Evanston, Illinois, US) and according to ASABE Standard S269.4 (ASABE, 2007). This method 
involves pouring the sample fraction into a container (volume of 1137 mm3) from a funnel. The 
material was leveled across the top of the surface of the container and weighed. The bulk density 
(?b) of the fraction was taken as the mass of sample in the container (mc) divided by the volume 
(Vc) of the container (Equation 3.4) (Littlefield et al., 2011). This procedure was performed in 
triplicate.  
?? = ???
?
      3.4 
3.3.4 Particle density 
A gas comparison pycnometer (Model AccuPyc 1340, Micromeritics Instrument Corp., 
Norcross, GA) was used to determine the particle density of the sample. In the pycnometer, helium 
under pressure was allowed to flow from a previously known reference volume into a cell 
containing a sample of the material. By applying the ideal gas law to the pressure change from the 
reference cell to the sample cell, the pycnometer calculates the volume of the material in the sample 
cell. Particle density was taken as the ratio of the mass of material in the sample cell to the volume 
measured by the pycnometer. A digital balance accurate to 0.001 g (Model AR3130, Ohaus Corp, 
Pinebrook, NJ) was used to measure the sample mass. The particle density measurements were 
conducted in triplicate and the average values were used (Bernhart and Fasina, 2009). 
Porosity (?) was calculated from the values of bulk density and particle density using the 
equation below: 
? = 1 - ?bulk ?
particle 
      3.5 
 
40 
 
3.3.5 Tap density, compressibility and hausner ratio 
Tap bulk density of the sample was measured using an automated tap density meter (Model 
TD-12, Pharma-Alliance Group Inc., Valencia, CA) and according to ASTM Standard B527 
(ASTM, 2005). A 250 mL graduated cylinder was filled with the sample and weighed. The cylinder 
was then placed in the tap density tester. Tapping of the cylinder (500 times) at a rate of 300 
taps/min was then carried out by the tester. Each tap consisted of the cylinder being raised 14 mm 
and then dropped under its own weight. After the first 500 taps, the new volume of the sample was 
recorded. The cylinder was then tapped 750 times and a second new volume recorded. If the 
difference in volume after the 500 taps and the 750 taps was >2%, the process was repeated; 
otherwise the experiment was completed. After the completion of tapping, the tap density (?t) of 
the sample was taken as the mass of sample in the container (mc) divided by the volume (Vt) of 
the sample after the completion of the tapping (Equation 3.6) (Bernhart and Fasina, 2009). This 
procedure was performed in triplicate. 
?t = ???
?
             3.6 
Compressibility is a measure of the relative volume change of a fluid or solid as a response 
to a pressure change. The compressibility values for the sample fractions at each moisture level 
were obtained from the same equipment used for tap density. 
Hausner ratio is the ratio of average tap density to average bulk density of the sample 
(Equation 3.7). The Hausner ratio for each fraction was also provided by the software of the tap 
density equipment. 
?? = ???
?
           3.7 
 
 
41 
 
3.3.6 Composition and energy determination 
3.3.6.1 Sample preparation 
According to ASTM standards E 872, the fractionated samples with geometric mean 
diameter above 1 mm were ground through a Wiley mill with screen size of 1mm for further size 
reduction to ensure thorough intermix and homogeneity of the samples. The size-adjusted samples 
were analyzed for energy, ash and volatile content.  
3.3.6.2 Energy content  
The heating value of the sample fractions was measured using a bomb calorimeter (Model 
No. C200, IKA Works Inc., Wilmington, NC). Approximately 0.5 g of a sample was compressed 
with a press (Model No.-C21, IKA Works Inc., Wilmington, NC) to form a pellet and then placed 
in a steel container. Cotton thread connected to an ignition wire was used to ignite the sample after 
the sample was placed in the container and pressurized to 30 bars. The bomb calorimeter was filled 
with water and the pressurized steel container placed in the bomb calorimeter where combustion 
occurred. The heating value after the combustion process was displayed on the software screen 
provided by the manufacturer.  
3.3.6.3 Ash content   
Ash content of the sample fractions was determined according to the NREL Laboratory 
Analytical Procedure (LAP, 2005). About 1g ? 0.1 of the sample was placed in a crucible and then 
transferred into a muffle furnace (Model No.-F6020C, Thermoscientific, Dubue, IO). The furnace 
was programmed to heat up to 105?C, ramped to 250?C at 10?C/minute and held at this temperature 
for 30 minutes. After this, the temperature was ramped to 575?C at 20?C/min and held for 180 
minutes and then finally lowered to 105?C. Crucibles and contents were then placed in the 
desiccator for 1 hour and allowed to cool to room temperature. The mass of the samples was 
42 
 
measured to 0.1 mg using a weighing balance. Ash content on dry basis was calculated according 
to equation 3.8.  
Ash (% d.b) =[100(Mcs-Mca)M
cs- Mc
]- (100 Mwb100-M
wb
)       3.8 
Mca is the mass of crucible and ash (g)  
Mc is the mass of the crucible (g)  
Mcs is the mass of crucible and sample before heating (g)  
Mwb is the moisture content on wet basis (% w.b) 
3.3.6.4 Volatile matter  
Volatile matter of the sample fractions was measured according to ISO 562 (ISO 562, 
2010). About 1g ? 0.1 of sample was placed in crucibles. The crucibles were placed in a volatile 
matter furnace (Model No.-VMF 10/6/3216P, Carbolite, Hope Valley, England) at 900?C for 7 
mins. Crucibles and contents were then removed from the furnace and placed in a desiccator to 
cool down to room temperature. The final mass of the crucibles with sample was measured and 
the volatile matter (Vd) on dry basis was calculated as follows; 
Vd=[100(M2-M3)M
2- M1
]- (100 Mwb100-M
wb
)            3.9 
 
M1 is the mass of the empty crucibles with lid (g);  
M2 is the mass of the crucibles and sample with lid before heating (g);  
M3 is the final mass of the crucibles and sample with lid after heating (g);  
Mwb is the moisture content on wet basis (% w.b) 
 
 
 
43 
 
3.3.7 Experimental design and statistical analysis  
Particle size and moisture content of fractionated ground loblolly pine were the predictors 
while the response variable was the physical properties. Aside from the particle size distribution, 
all the experiments were carried out in triplicate.  
Microsoft Excel 2010 was used in summarizing and generating graphs. A significant test 
(? <0.05) using the Proc GLM procedure in the statistical software SAS 9.3 (SAS Institute Inc., 
Cary, NC) was conducted to show the effect of particle size and moisture content on the physical 
properties. The Tukey test was also used to compare the means of values of these properties at the 
different moisture contents and particle sizes. The results were presented in mean and standard 
deviation. 
 
3.4 Results and Discussion 
3.4.1 Particle size distribution 
Figure 3.1 shows the particle size distribution of the unfractionated ground loblolly pine. 
The curves are left skewed which represent naturally occurring particle population (Rhodes, 1998). 
A similar trend has been reported for biological materials (Probst et al., 2013; Yang et al., 1996; 
Mani et al., 2004).The particle size distributions of the unfractionated ground samples are 
unimodal. Also, at the 25.53% moisture levels, a wider distribution existed with most of the 
particles falling uniformly between 0 and 6 mm as compared to the other curves. This result is an 
indication of wider spread of particles at higher moisture level. Probst et al. (2013) also reported a 
similar result for ground corn at 10.39% moisture content having a narrower distribution and a 
wider distribution at higher moisture content of 16.02 and 19.64% (wb).  
44 
 
 
Figure 3.1: Particle size distribution of unfractionated ground loblolly pine. 
Figure 3.2(a-f) shows the particle size distributions of the fractionated ground loblolly pine 
at the five moisture levels. As the size of the fraction increases, the particle size distribution move 
from been left skewed to a symmetric distribution. This change was more vivid with the particle 
distribution of fraction size 1.40 mm. The change in particle size distribution with increase in 
fraction size, shows that the log-normal distribution of biological materials is as a result of fine 
particles in the material. Benkovic and Bauman (2009) observed that powders with narrow particle 
size distributions have a better flow than powders with wider particle size distributions. Therefore, 
an increase in moisture content may cause a reduction in flowability. In Figure 3.2f, the particle 
size distributions of fractions retained on the pan (hereafter referred to as size 0.05mm based on 
ASABE Standards S319.3, 2008) are similar for all moisture levels except for 8.69% which had a 
narrow distribution. The narrow distribution is an indication of better flow. The distributions have 
multi-peaks which indicate that the samples can still be further separated into different fractions 
based on these peaks (Bernhart and Fasina, 2008).       
0
5
10
15
20
25
0 2 4 6 8
Volu
me
 Re
tain
ed
 (%
)
Sieve Size (mm)
4.78% MC
8.69% MC
16.53% MC
22.21% MC
25.53% MC
45 
 
           
Figure 3.2a: Particle size distribution of fractionated ground loblolly pine at 4.78% 
moisture level. 
 
 
 
Figure 3.2b: Particle size distribution of fractionated ground loblolly pine at moisture 
content of 8.69% (wb). 
 
 
0
4
8
12
16
20
24
28
32
36
40
0 1 2 3 4 5 6 7
Volu
me
 Re
tain
ed
 (%
)
Sieve Size (mm)
1.40mm
1.00mm
0.71mm
0.50mm
0.25mm
0
4
8
12
16
20
24
28
32
36
40
0 1 2 3 4 5 6 7
Volu
me
 R
etain
ed (%
)
Sieve Size (mm)
1.40mm
1.00mm
0.71mm
0.50mm
0.25mm
46 
 
 
Figure 3.2c: Particle size distribution of fractionated ground loblolly pine at moisture 
content of 16.53% (wb). 
 
 
Figure 3.2d: Particle size distribution of fractionated ground loblolly pine at moisture 
content of 22.21% (wb). 
 
0
4
8
12
16
20
24
28
32
36
40
0 1 2 3 4 5 6
Volu
me
 Re
tain
ed
 (%
)
Sieve Size (mm)
1.40mm
1.00mm
0.71mm
0.50mm
0.25mm
0
4
8
12
16
20
24
28
32
36
40
0 1 2 3 4 5 6 7
Volu
me
 Re
tain
ed
 (%
)
Sieve Size (mm)
1.40mm
1.00mm
0.71mm
0.50mm
0.25mm
47 
 
 
Figure 3.2e: Particle size distribution of fractionated ground loblolly pine at moisture 
content of 25.53% (wb). 
 
 
Figure 3.2f: Particle size distribution of fractions retained on the pan (size 0.05mm). 
 
0
4
8
12
16
20
24
28
32
36
40
0 1 2 3 4 5 6 7
Volu
me
 Re
tain
ed
 (%
)
Sieve Size (mm)
1.40mm
1.00mm
0.71mm
0.50mm
0.25mm
0
10
20
30
40
50
60
70
0.02 0.07 0.12 0.17 0.22 0.27
Volu
me
 Re
tain
ed
 (%
)
Sieve Size (mm)
4.78% MC
8.69% MC
16.53% MC
22.21% MC
48 
 
 Table 3.1 shows the geometric mean diameters and geometric standard deviations of the 
fractionated and unfractionated ground samples. There was no fraction of size 0.05mm at 25.53% 
moisture level. Due to the high moisture content leading to increase particle size and stickiness 
between particles, particles did not pass through a screen size of 0.25mm, hence there was no 
fraction retained on screen size 0.05mm. The geometric mean diameters of the fractionated 
samples varied between 0.10 and 2.38 mm with fractions at the 25.53% moisture level having the 
highest geometric mean diameters. This shows that increased moisture content will lead to particle 
swelling hence increase in the particle size. However, it is generally considered that particles with 
sizes larger than 200 ?m are free flowing, while particle with sizes less than 200 ?m are subject to 
cohesion and flowability problem. The reduced flowability at smaller particle sizes is because of 
the increased surface area per unit mass of the powder. There is more surface area or surface 
contacts available for frictional forces to resist flow (Fitzpatrick, 2005; Teunou et al., 1999; 
Molenda et al., 2002). Therefore, ground loblolly pine fraction of size 0.05 mm and having 
geometric mean diameters between 0.10 and 0.15 mm is expected to be a source of flowability 
problem. An increase in the quantity of this fraction within the unfractionated ground sample will 
results in reduced flowability as well. Furthermore, the geometric mean diameter of the 
unfractionated ground sample which varies between 1.31 and 2.19 mm falls within the range of 
acceptable particle sizes needed for most biomass conversion processes.    
 
 
 
 
 
 
 
 
 
49 
 
Table 3.1: Geometric mean diameters (mm) and geometric standard deviations of 
fractionated ground loblolly pine.  
 
Screen size 
(mm) 
Moisture content (% wb) 
4.78 8.69 16.53 22.21 25.53 
0.05 0.11 ? 0.06 0.15 ? 0.03 0.10 ? 0.06 0.10 ? 0.05 NC* 
0.25 0.85 ? 0.68 0.81 ? 0.72 0.70 ? 0.51 0.64 ? 0.41 0.86 ? 0.92 
0.50 1.16 ? 0.69 0.97 ? 0.59 1.01 ? 0.55 0.84 ? 0.42 1.33 ? 0.90 
0.71 1.38 ? 0.67 1.28 ? 0.68 1.33 ? 0.62 1.17 ? 0.53 1.46 ? 0.84 
1.00 1.72 ? 0.70 1.54 ? 0.69 1.69 ? 0.69 1.55 ? 0.6 1.73 ? 0.75 
1.40 2.16 ? 0.66 2.14 ? 0.83 2.17 ? 0.63 2.18 ? 0.67 2.38 ? 0.82 
Raw 1.31 ? 1.00 1.36 ?1.27 1.33 ? 1.12 1.39 ? 0.99 2.19 ? 1.39 
NC*: Experiment was not conducted at this moisture level 
3.4.2 Bulk Density 
Statistical analysis indicated that particle size and moisture content had a significant effect 
(p<0.05) on the bulk density (Table 3.2). Bulk density of the loblolly pine fractions significantly 
increased with increase in fraction size and with decrease in moisture content. The bulk densities 
ranged from 136.7 to 277.7 kg/m3. Lam et al. (2008) reported a similar result with an increase in 
the bulk density of fractionated switchgrass from 149 to 194 kg/m3 as the particle size increased 
from 0.25 to 0.71 mm. The increased bulk density is attributed to the fact that biomass grinds 
collected after fractionation exhibit different packing as a result of particles having the same size 
as compared to the unfractionated biomass grinds which comprises of different particle size range. 
Liu et al. (2008) also reported an increase in the bulk density of fractionated ibuprofen powder 
from 350 to 440 kg/m3 as particle size increased from 46 to 215 ?m.  
 
 
 
50 
 
Table 3.2: Bulk density (kg/m3) of fractionated ground loblolly pine. 
Screen 
size (mm) 
Moisture content level (% w.b) 
4.78 8.69 16.53 22.21 25.53 
0.05 162.53[f,w] ?0.81 159.40[f,w] ?3.27 141.69[g,x] ? 0.47 136.67[f,y] ?0.62 NC* 
0.25 184.60[e,w]  ?2.25 179.28[e,w] ?1.85 157.99[f,x] ?1.81 146.64[e,y] ?1.57 140.84[f,z] ?2.88 
0.50 205.02[d,w] ?2.21 210.38[d,w] ?2.98 176.02[e,x] ?1.58 165.94[d,y] ?5.46 159.46[e,y] ?0.62 
0.71 247.11[c,w]  ?2.47 247.58[c,w] ?3.80 204.05[d,x] ?1.76 186.65[c,y] ?1.46 185.96[d,y] ?1.86 
1.00 265.30[b,w] ?0.57 255.98[b,x] ?1.69 227.09[c,y] ?2.89 217.86[b,z] ?2.75 220.52[c,z] ?1.86 
1.40 277.66[a,w] ?1.31 272.37[a,w] ?2.24 238.46[b,y] ?2.29 234.22[a,y] ?3.53 244.68[a,x] ?0.35 
Raw 266.83[b,x] ?0.81 275.53[a,w] ?1.93 232.51[a,y] ?1.52 227.36[a,z] ?0.46 234.04[b,y] ? 1.84 
Particle size effect: values in each column with same letter (a-f) are not significantly different (p<0.05).  
Moisture effect: values in each row with same letter (w-z) are not significantly different (p<0.05).  
NC* experiment was not conducted because there was no fraction at 25.53% moisture level. 
 
Effect of moisture content on bulk density of fractionated ground loblolly pine is similar 
to other published works on biological materials such as wormy compost (Bahram et al., 2013),  
switchgrass (Lam et al., 2007), soybean (Kashaninejad et al., 2008). The reduction in bulk density 
with increased moisture content is because of the increase in mass due to moisture gain being lower 
than the accompanying volumetric expansion of the bulk (Colley et al., 2006). The amount of 
storage space required for a ground loblolly pine will therefore increase with moisture content 
which will lead to increased cost of logistics. However, there was no significant difference in the 
bulk density at a moisture level of 4.78% and 8.69 % (wb) while there was a sharp drop in the bulk 
density from moisture content level of 8.69% to 16.53% (wb). The difference indicated that at 
lower moisture content, there was no significant change in bulk density hence, there may be no 
need to expend energy in drying the material to a moisture level of 4.78% (wb).      
51 
 
Abdullah and Geldart (1999) stated that a bulk solid with a strong structural strength will 
resist collapse when dispersed in a container and will have a low bulk density, while a structurally 
weak bulk solid will collapse easily and have a high bulk density. High friction between the 
particles results in a low bulk density. As fraction size decreases, the bulk density decreases, this 
implies that 0.05 mm and 0.25 mm fractions will have higher friction between their particles hence 
resulting in low bulk density values. High friction between particles is an indication of possible 
flowability problem. It is more pronounced as the moisture content increase. Fractions of sizes 
1.40 mm and 1.00 mm had the highest bulk density values. Therefore, increased quantity of 1.40 
mm and 1.00 mm fractions in the unfractionated ground sample may improve flowability of ground 
loblolly pine. 
 
3.4.3 Tap Density  
 Tap density represents an increased bulk density attained after mechanically tapping a bulk 
material and allowing it to fall under its own mass. Result of the statistical analysis of particle size 
and moisture effect on tap density of fractionated ground loblolly pine is presented in Table 3.3. 
The result showed that particle size and moisture content had a significant (p<0.05) on tap density 
of the fractionated samples. The tap density significantly increased with increase in fraction size 
and reduction in moisture content. The tap density ranged from 218.3 to 330.0 kg/m3. The tap 
density of the unfractionated sample was significantly higher than the fractionated sample. Tap 
density value is observed to have a higher value as compared to bulk density. This depicts that a 
reduction in volume of bulk material due to efficient packing of particles when subjected to 
vibration (e.g. during transportation) will result in increased density.  
 
 
52 
 
Table 3.3: Tap density (kg/m3) of fractionated ground loblolly pine. 
Screen  
size (mm) 
Moisture content level (w.b) 
4.78 % 8.69% 16.53% 22.21% 25.53% 
0.05 262.67[d,w] ? 4.04 267.00[de,w] ?1.00 232.00[e,x] ?2.65 230.00[d,x] ?1.00 NC* 
0.25 247.00[e,x] ? 2.00 258.33[e,w] ?1.16 218.33[d,z] ?2.08 223.00[d,z] ?6.08 235.67[e,y] ?1.53 
0.50 264.67[d,x] ? 0.58 276.67[d,w] ?2.52 226.67[e,y] ?0.58 222.00[d,z] ?1.73 230.00[e,y] ?1.00 
0.71 309.67[c,x] ? 1.53 318.00[bc,w] ?1.73 252.00[d,y] ?1.00 249.33[c,y] ?2.31 251.00[d,y] ?1.00 
1.00 323.67[b,w] ? 2.08 314.67[c,x] ?1.53 275.33[c,y] ?4.04 270.67[b,y] ?0.58 277.33[c,y] ?3.06 
1.40 327.67[b,w] ? 2.31 330.00[b,w] ?3.46 287.00[b,x] ?2.00 279.00[b,y] ?2.65 286.67[b,x] ?3.22 
Raw 354.33[a,w] ? 5.86 359.67[a,w]? 11.02 303.67[a,x] ?0.58 303.67[a,x] ?3.06 311.67[a,x] ?1.53 
Particle size effect: values in each column with same letter (a-f) are not significantly different (p<0.05).  
Moisture effect: values in each row with same letter (w-z) are not significantly different (p<0.05).  
NC* experiment was not conducted because there was no fraction at 25.53% moisture level. 
 
 
Volume reduction due to re-arrangement of particles after tapping may lead to difficulty in 
unloading the material from storage vessels (Bernhart and Fasina, 2009). The reduction in tap 
density with moisture increase further confirms the moisture content ? density relationship 
previously discussed indicating that bulk volume increased at a rate faster than the mass of the 
bulk. This result signifies that a flow problem will exist due to vibration during the transport, 
loading and unloading of ground loblolly pine from storage vessels. The material will compact as 
a result of vibrations hence resulting in difficulties in unloading ground loblolly pine from 
transport vehicles. Similar trends have been reported for other biological materials (Lam et al., 
2008; Bernhart and Fasina, 2009). 
Because the inter-particulate interactions influencing the properties of a bulk material are 
also the interactions that interfere with its flow, a comparison of the bulk and tapped densities can 
53 
 
provide a measure of the relative importance of these interactions in a given material. Such a 
comparison is often used as an index representing the ability of the powder to flow (WHO, 2012). 
Such index include compressibility value and Hausner ratio.  
3.4.4 Hausner ratio 
 Hausner ratio (ratio of tap density to bulk density) is used at times to characterize the 
flowability of bulk material (Table 2.2). The Hausner ratio of fractionated loblolly pine 
significantly decrease (p<0.05) from 1.6 to 1.2 with increase in fraction size from 0.05 to 1.40 mm 
(Table 3.4). Moisture content had no significant effect (p<0.05) on the Hausner ratio of 
unfractionated loblolly pine: 0.05, 1.00 and 1.40 mm fractions. However, there was a significant 
increase in the Hausner ratio with moisture content for 0.25, 0.50 and 0.71 mm fractions. 
 Size fractions of 0.05, 0.25, 0.50 and 0.71mm had a poor flow behavior while 1.00 and 
1.40 mm fractions had a fair/good flow behavior. The results obtained for the Hausner ratio 
confirms that the reduction in volume after tapping of the 0.05 mm fractions was higher than the 
1.40 mm fractions. Therefore, 0.05 mm fractions have higher tendency of becoming compacted or 
compressed due to vibration hence, resulting in flow problems.  
 
 
 
 
 
 
 
 
54 
 
 
Table 3.4: Hausner ratio of fractionated ground loblolly pine. 
Screen  
size (mm) 
Moisture Content Level (w.b) 
4.78 % 8.69% 16.53% 22.21% 25.53% 
0.05 1.50[a,w] ? 0.06 1.59[a,w] ?0.09 1.52[a,w] ?0.01 1.59[a,w] ?0.01 NC* 
0.25 1.27[bc,z] ? 0.01 1.39[b,xy] ?0.02 1.35[b,y] ?0.02 1.44[b,x] ?0.01 1.62[a,w] ?0.05 
0.50 1.27[bc,y] ? 0.05 1.30[bc,xy] ?0.03 1.28[c,y] ?0.03 1.38[c,wx] ?0.01 1.43[b,w] ?0.01 
0.71 1.24[bc,y] ? 0.03 1.27[bc,xy] ?0.03 1.26[cd,xy] ?0.03 1.31[d,wx] ?0.01 1.34[c,w] ?0.03 
1.00 1.22[c,w] ? 0.00 1.25[c,w] ?0.01 1.22[de,w] ?0.01 1.25[e,w] ?0.00 1.25[d,w] ?0.03 
1.40 1.21[c,w] ? 0.04 1.23[c,w] ?0.07 1.17[e,w] ?0.01 1.21[f,w] ?0.01 1.21[d,w] ?0.01 
Raw 1.34[b,w] ? 0.06 1.31[bc,w] ?0.02 1.31[bc,w] ?0.02 1.33[d,w] ? 0.01 1.34[c,w] ? 0.04 
Particle size effect: values in each column with same letter (a-f) are not significantly different (p<0.05).  
Moisture effect: values in each row with same letter (w-z) are not significantly different (p<0.05).  
NC* experiment was not conducted because there was no fraction at 25.53% moisture level. 
 
3.4.5 Compressibility  
Compressibility is a measure of the increase in strength of powder-like materials with 
increase in consolidating pressure. Statistical analysis showed that there was a significant reduction 
(p<0.05) in compressibility with increase in particle size. As reported earlier for moisture effect 
on the Hausner ratio, moisture content had no significant effect on compressibility of 
unfractionated samples and size fraction of 0.05, 1.00 and 1.40mm while there was a significant 
increase (p<0.05) in compressibility of size fractions 0.25, 0.50 and 0.71mm with increase in 
moisture content (Table 3.5). This is because Hausner ratio and compressibility values are obtained 
from the same values of bulk and tap density. The compressibility value ranged from 17.3% to 
38.3%.  
 
55 
 
Table 3.5: Compressibility (%) of fractionated ground loblolly pine. 
Screen  
size (mm) 
Moisture content level (w.b) 
4.78 % 8.69% 16.53% 22.21% 25.53% 
0.05 33.07[a,w] ?2.81 36.93[a,w] ?3.45 34.27[a,w] ?0.61 37.20[a,w] ?0.40 NC* 
0.25 21.47[bc,z] ?0.61 28.00[b,xy] ?0.80 25.73[b,y] ?1.29 30.53[b,x] ?0.61 38.27[a,w] ?1.80 
0.50 21.33[bc,y] ?3.23 23.20[bc,xy] ?1.60 21.60[c,y] ?1.83 27.33[c,wx] ?0.61 30.27[b,w] ?0.23 
0.71 19.33[bc,y] ?1.80 21.20[c,xy] ?1.83 20.27[cd,y] ?1.89 23.73[d,wx] ?0.46 25.20[c,w] ?1.44 
1.00 18.13[c,w] ?0.23 19.73[c,w] ?0.46 17.73[de,w] ?0.92 20.13[e,w] ?0.23 19.87[d,w] ?1.97 
1.40 17.33[c,w] ?2.44 18.67[c,w] ?4.62 14.80[e,w] ?0.40 17.33[f,w] ?0.46 17.60[d,w] ?0.69 
Raw 25.33[b,w] ?3.63 23.73[bc,w] ? 0.92 23.73[bc,w] ? 0.92 24.93[d,w] ? 0.61 25.07[c,w] ?2.05 
Particle size effect: values in each column with same letter (a-f) are not significantly different (p<0.05).  
Moisture effect: values in each row with same letter (w-z) are not significantly different (p<0.05).  
NC* experiment was not conducted because there was no fraction at 25.53% moisture level. 
 
Compressibility is a measure of flowability - the greater the compressibility of a bulk solid, 
the less flowable it is (Ganesan et al., 2008). This shows that 0.05 mm fraction is more 
compressible and would be less flowable during unloading from storage vessels. This is also in 
accordance with the results obtained for the other physical properties showing that at increased 
moisture content and reduced particle size; the material becomes more compressible hence 
resulting in flowability problem. The difficult flow behavior that characterizes ground loblolly 
pine at high moisture content is attributable to the formed liquid bridges between particles thereby 
making them more cohesive (Teunou and Fitzpatrick, 1999). Also as moisture content increases, 
biological materials become softer thus deformation of the material is greater at higher moisture 
contents (Bernhart and Fasina, 2009) which might result in unloading difficulty of materials from 
storage or transport vessels. 
 
56 
 
3.4.6 Particle density 
Table 3.6 shows the effect of particle size and moisture content on the particle density of 
ground loblolly pine fractions. Significant test (p< 0.05) showed that particle size and moisture 
had a significant effect on particle density. The particle density of the fractionated ground loblolly 
pine varied from 1382.8 to 1497.1 kg/m3. The particle density was observed to generally decrease 
with increase in fraction size however at a moisture content level of 4.78 % (wb), there was no 
significant difference (p<0.05) in the particle densities of the loblolly pine fractions. This may be 
due to shrinkage of the particles hence nullifying particle size effect on particle density at lower 
moisture content. Mani et al. (2004) reported a reduction in the particle density of corn stover from 
1210 to 1085 kg/m3 with increase in particle size from 0.41 to 0.68 mm. The authors asserted that 
the decrease in particle density may be due to reduction in porosity of the ground corn stover when 
the particles are reduced to a smaller size.  
Particle density was highest at 16.53% moisture level giving a distinction between the 
particle densities at 4.78% and 8.69% moisture levels and the particle densities at 22.21% and 
25.53% moisture levels. The particle densities at 4.78% and 8.69% moisture levels were higher 
than that of 22.21% and 25.53% moisture levels. The decline in particle density with increased 
moisture content is due to the volumetric expansion of the particles, occurring at a faster rate than 
the increase in mass of particles due to addition of moisture (McMullen et al., 2005). Bahram et 
al., (2013) reported a particle density reduction from 1652 to 1443 kg/m3 of wormy compost with 
an increase in moisture content from 25 to 35% (wb).   
 
 
 
57 
 
Table 3.6: Particle density (kg/m3) of fractionated ground loblolly pine. 
Screen  
size (mm) 
Moisture content level (% w.b) 
4.78  8.69 16.53 22.21 25.53 
0.05 1464.10[a,x] ? 2.63 1460.23[b,x] ? 5.95 1485.60[a,w] ? 6.18 1440.47[a,y] ? 2.74 NC* 
0.25 1464.23[a,wx] ?0.15 1459.77[b,wx] ? 5.53 1486.50[a,w] ?2.71 1437.47[a,xy] ?2.71 1411.53[ab,y] ?2.82 
0.50 1464.53[a,x] ?0.99 1454.27[bc,x] ? 3.35 1493.83[a,w] ?7.41 1423.33[b,y] ?0.25 1421.97[a,y] ?9.58 
0.71 1462.93[a,w] ?2.19 1448.80[bc,x] ? 4.46 1455.83[bc,wx] ?5.07 1412.50[c,y] ?2.85 1411.27[ab,y] ?6.44 
1.00 1462.43[a,w] ?1.08 1443.93[c,x] ? 4.80 1462.03[b,w] ?7.49 1413.20[c,y] ?3.92 1401.10[ab,y] ?8.67 
1.40 1459.43[a,x] ?4.22 1497.13[a,w] ? 6.25 1459.20[bc,x] ?1.31 1415.60[c,y] ?2.46 1382.77[b,z] ?3.42 
Raw 1459.30[a,w] ? 2.85 1445.13[c,x] ? 3.89 1444.10[c,x] ? 5.37 1417.80[bc,y] ? 0.40 1387.50[ab,z] ?0.40 
Particle size effect: values in each column with same letter (a-f) are not significantly different (p<0.05).  
Moisture effect: values in each row with same letter (w-z) are not significantly different (p<0.05).  
NC* experiment was not conducted because there was no fraction at 25.53% moisture level. 
 
Particle density measures the density of the particle matter excluding the air pores, hence 
it is called true density (Ileleji and Rosentrater, 2008). This shows that reduction of pore spaces 
within particles will lead to higher density hence resulting in flowability problem as the material 
will have higher compressibility. Therefore, the higher particle density of the fine fraction at screen 
size of 0.05 mm and 0.25 mm is an indication of reduced flowability. Also, their particle densities 
are significantly higher than the particle density of the unfractionated sample. This shows that a 
large quantity of these fine fractions in unfractionated ground loblolly pine will lead to difficulty 
in effective discharge of ground loblolly pine from storage vessels.       
3.4.7 Porosity 
 Porosity measures the pore spaces between particles. It was found to significantly increased 
(p< 0.05) from 0.81 to 0.91 with decrease in fraction size from 1.40mm to 0.05mm and increase 
in moisture content from 4.78% to 25.53% (wb) (Table 3.7). An average porosity calculation of 
58 
 
0.4 is normal for spheroid particles, whereas irregular shaped or very small particulates have higher 
porosity values (Woodcock and Mason, 1987). The porosities of the loblolly pine fractions are 
higher than 0.4 which is an indication of highly irregular shaped particles. The shape irregularities 
of the particles can be attributed to the size reduction process of using hammer mill for loblolly 
pine wood chips. Lam et al., (2008) reported that the porosity of switchgrass decreased from 0.87 
to 0.82 with increase in particle size from 0.25 to 0.71 mm. Based on the data of Bahram et al. 
(2013), the porosity of wormy compost varied between 0.52 ? 0.45, and reduced with increase in 
moisture content. Manickam and Suresh (2011) also reported a reduction in the porosity of coir 
pith from 0.86 to 0.62 with an increase in moisture content from 10.1% to 60.2% (wb). The values 
obtained for these biological materials are also typical of extremely irregular-shaped particles that 
have cohesive tendencies (Woodcock and Mason, 1987). 
High porosity value is an indication of highly compressible material. Therefore, the 
reduced particle size and increase in moisture content resulting in increased porosity leads to 
ground loblolly pine becoming more compressible and compactable. This will therefore lead to 
flow problem as the particles sticks tightly together after compression and compaction.  
 
 
 
 
 
 
 
 
59 
 
Table 3.7: Porosity of fractionated ground loblolly pine. 
Screen  
Size (mm) 
Moisture Content Level (w.b) 
4.78 % 8.69% 16.53% 22.21% 25.53% 
0.05 0.889[a,x] 0.891[a,x] 0.905[a,w] 0.905[a,w] NC* 
0.25 0.874[b,y] 0.877[b,y] 0.893[b,x] 0.898[b,wx] 0.900[a,w] 
0.50 0.860[c,y] 0.855[c,y] 0.882[c,x] 0.883[c,wx] 0.887[b,w] 
0.71 0.831[d,y] 0.829[d,y] 0.859[d,x] 0.867[d,w] 0.868[c,w] 
1.00 0.818[e,x] 0.823[e,x] 0.845[e,w] 0.846[e,w] 0.843[d,w] 
1.40 0.810[f,z] 0.818[f,y] 0.839[f,w] 0.835[f,w] 0.823[f,x] 
Raw 0.817[e,y] 0.809[g,z] 0.837[f,w] 0.840[f,w] 0.831[e,x] 
Particle size effect: values in each column with same letter (a-f) are not significantly different (p<0.05).  
Moisture effect: values in each row with same letter (w-z) are not significantly different (p<0.05).  
NC* experiment was not conducted because there was no fraction at 25.53% moisture level. 
 
3.4.8 Compositional analysis 
3.4.8.1 Energy content 
Figure 3.3 shows the effect of particle size on energy content of fractionated ground 
loblolly pine. Statistical analysis showed that particle size had no significant effect (p<0.05) on 
energy content of ground loblolly pine. The energy content was between 18-19 MJ/kg. Similar 
results were reported by Garcia et al. (2012) for miscanthus (18.1 MJ/kg), coffee husk (18.3 MJ/kg) 
and walnut shell (18.4 MJ/kg) but higher than other biological materials such as sorghum (11.9 
MJ/kg), barley (16.5 MJ/kg) and wheat bran (17.4 MJ/kg). The high energy content value recorded 
for loblolly pine as compared to other biological materials is confirmed by its low ash content (see 
Figure 3.5), which is an indication of large amount of combustible material which are primarily 
carbon and hydrogen (Fasina, 2006).      
60 
 
 
Figure 3.3: Particle size effect on energy content of fractionated loblolly pine. 
3.4.8.2 Ash content 
Ash content is a measure of amount of inorganic components in material. It represents the 
bulk mineral materials left over after combustible elements of a material are given off during 
combustion. The ash content of the fractionated ground loblolly pine is presented in Figure 3.4. 
Statistical analysis showed that particle size had a significant effect (p<0.05) on the ash content of 
ground loblolly pine. The ash content values (db) were between 0.22% and 2.64%. The ash content 
increased with reduction in the particle size. The low ash content of ground loblolly pine 
corroborate the results obtained for energy content showing that loblolly pine contains large 
amount of combustible material which are primarily carbon and hydrogen. The ash content 
obtained for the loblolly pine is low as compared to other biological materials such as rice straw 
(18.67% db), switchgrass (8.97% db), wheat straw (7.02% db) and rice hulls (20.26% db) (Jenkins 
et al., 1998). Information on ash content of ground loblolly pine is essential for the choice of an 
appropriate combustion and gas cleaning technologies. Also, ash deposit formation, fly ash 
emissions and ash handling as well as ash utilization/disposal options are dependent on this 
parameter (Obernberger, 1997; CEN/TC, 2003). The low ash content value of ground loblolly pine 
0
2.5
5
7.5
10
12.5
15
17.5
20
22.5
Raw 0.05 0.25 0.50 0.71 1.00 1.40
En
ergy Conte
nt (
M
J/k
g)
Screen Size (mm)
61 
 
shows that there will be a low deposit of bulk inorganic material after its combustion. Published 
works had shown that woody biomass has a relatively low amount of ash. For example, coniferous 
and deciduous wood without bark have 0.30% (db) of ash content and short rotation coppice 
willow has a 2.0% (db) ash content (CEN/TC, 2003).  
 
Figure 3.4: Particle size effect on ash content of fractionated loblolly pine. 
3.4.8.3 Volatile matter 
Volatile matter refers to the components of a material except for moisture, which are 
liberated at a high temperature in the absence of air. It is an indication of the burning characteristics 
of a material. Statistical analysis showed that particle size had no significant effect (p<0.05) on the 
volatile matter of the fractionated ground loblolly pine (Figure 3.5). The volatile matter ranged 
from 84.55% to 85.38% (db). The high volatile matter value is an indication that ground loblolly 
pine possesses low fixed carbon and can therefore be easily ignited. Jenkins et al (1998) reported 
similar results for sugarcane bagasse (85.61% db) and hybrid poplar (84.81% db) while lower 
values were reported for biological materials such as wheat straw (75.27% db), switchgrass 
(76.69% db) and rice hulls (63.52% db).  
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Raw 1.40 1.00 0.71 0.50 0.25 0.05
Ash Con
ten
t (
%
 db
)
Screen Size (mm)
62 
 
 
Figure 3.5: Particle size effect on volatile matter of fractionated loblolly pine.  
 
3.5 Conclusion 
In this study, ground loblolly pine was fractionated into six sizes. The physical and 
compositional properties of the fractionated samples were quantified at five moisture levels. It was 
found that: 
? Reduction in particle size and increased moisture content were found to influence the 
physical properties of the ground loblolly pine and resulting into possible flow problem. 
This is further characterized in chapter 4. The bulk and tap densities were found to increase 
with increase in fraction size while particle density generally decreased with increase in 
fraction size. The porosity, Hausner ratio and compressibility of the fractions were also 
found to decrease with increase in the size of the fraction. Furthermore, increased moisture 
content was found to significantly cause a reduction in the densities (bulk, tap and particle) 
and porosity however, it had no significant effect on hausner ratio and compressibility. 
80
81
82
83
84
85
86
87
Raw 1.40 1.00 0.71 0.50 0.25 0.05
Volatil
e M
att
er 
(%
 db
)
Screen Size (mm)
63 
 
? The heating value of the fractions which was found to be 18-19 MJ/kg and volatile matter 
(84.91 - 87.48% d.b) were not significant affected by particle size but the ash content was 
found to increase with reduction in the size of the fraction.  
The results of this work can be used in conjunction with the flow properties of the ground 
loblolly pine in designing and selecting the appropriate storage and handling vessels. Also, 
information on the compositional properties influences the choice of an appropriate conversion 
system and gas cleaning technologies for ground loblolly pine.   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
64 
 
CHAPTER 4: Particle size and moisture effect on flow properties of fractionated ground 
loblolly pine and sensitivity of silo design parameters to flow properties  
 
4.1 Abstract 
The flow properties of fractionated ground loblolly pine were quantified with analysis conducted 
on the sensitivity of silo design parameters to change in flow and physical properties. Flow index 
values of 4.11, 4.17 and 4.29 were recorded for fractions of size 1.40 mm at moisture content levels 
of 4.78%, 8.69% and 16.53% respectively. However, a reduction in flowability was observed when 
the 1.40 mm fraction was dosed with 0.50 mm fractions. Lower angles of wall friction were 
obtained at lower moisture contents when stainless steel and mild steel surfaces were used. Tivar 
88 wall surface had low angles of wall friction ranging from 10.88 to 15.540 at all the moisture 
levels. Sensitivity analysis indicated that there was a reduction in the hopper half angle with 
increased moisture content and reduction in the fraction size. The hopper half angle also decreased 
with increase in angle of wall friction. The adjusted hopper outlet sizes varied between 1.20 and 
28.56 mm. The wall normal and vertical pressure acting on the cylindrical section of the silo 
increased from 9.35 to 45.42 kPa and 15.34 to 48.91 kPa respectively with increase in fraction size 
and decrease in moisture content. The initial fill and flow induced pressures acting on the hopper 
section of the silo increased from 15.34 to 48.91 kPa and 24.71 to 78.79 kPa respectively with 
increase in fraction size and decrease in moisture content.  
 
 
 
 
 
 
65 
 
4.2 Introduction   
 Bulk material handling operations are key operations in process industries such as food, 
chemicals and pharmaceuticals industries (Opalinski et al., 2012). In order to ensure a successful 
production operation, a consistent and reliable flow of bulk materials from storage vessels without 
dust generation and flow obstruction are required. However, two major flow problems are 
associated with bulk solid handling, namely ratholing and arching. An arch (Figure 4.1a) is a stable 
obstruction that forms with the hopper section usually near the bin outlet. The arch has enough 
strength to supports the rest of the bin?s content hence preventing the discharge of the remaining 
content. A rathole (Figure 4.1b) is a stable pipe or vertical cavity that empties above the bin outlet. 
The silo content in the stagnant zones remains stationary until an external force is applied to 
dislodge it. Ratholing and arching can result in structural failure of silos, process inefficiencies 
and frequent equipment downtime (Prescott and Barnum, 2000; Johanson, 2002; Merrow, 1988).    
                             
        (a) Cohesive arching                      (b) Ratholing 
Figure 4.1: Typical flow problems associated with bulk solids (Source: jenike.com). 
66 
 
Silo design requires information about the flow properties of the bulk material. These 
include unconfined yield strength, major consolidation stress, flow index, angle of internal friction, 
angle of wall friction, cohesion and bulk density. Flow properties are used in the design of 
discharge hoppers, hopper opening size, hopper half angle (to the vertical) and estimation of silo 
wall pressures. The hopper opening size is selected in order to ensure that arching (the flow 
problem related with mass flow pattern) does not occur and the required flow rate is achieved 
(Roberts, 1994). The minimum hopper half angle is needed for mass flow, the preferred flow 
pattern for a consistent and reliable flow. If the hopper half angle is less than the minimum, then 
it is likely that a funnel flow pattern will exist (Holdich, 2002; Teunou et al., 1999; Fitzpatrick, 
2007; Iqbal and Fitzpatrick, 2006). A detailed description of Jenike?s methodology for hopper 
design is found in the chapter 2 (subsection 2.6.4) of this thesis work.  
Several studies have been documented on the contribution of particle size and moisture 
content to flow properties of biological materials (Kashaninejad et al., 2008; Bahram et al., 2013; 
Iqbal and Fitzpatrick, 2006; Teunou et al., 1999). The design and selection of an efficient storage 
vessel for ground loblolly pine requires a fundamental understanding of the impact of particle size 
and moisture content on the flow properties of the ground material. Therefore the objectives of 
this work are to: 
1. quantify the effect of particle size and moisture content on the flow properties of fractionated 
ground loblolly pine;  
2. investigate the sensitivity of silo design parameters to the physical and flow properties.  
 
 
 
67 
 
4.3 Materials and Methods 
4.3.1 Sample preparation    
Clean loblolly pine wood chips used in this study were collected from West Fraser Inc. 
Sawmill, Opelika, Alabama. Before use, the samples were ground through a 3.18 mm screen using 
a hammer mill (Model 358, New Holland grinder, New Holland, PA).  
Experiments were carried out on the ground samples at five moisture content levels 
between 4.78% and 25.56% (wb). The initial moisture content of the samples after grinding was 
8.69% (wb). To adjust the moisture content of the samples to the desired level, the samples were 
either dried using a humidity chamber (ESL-2CA, Espec North America, Inc.) set at a temperature 
of 500C and relative humidity of 20% (for moisture content reduction) or the samples were sprayed 
with a known quantity of water (to increase the moisture content of samples). After moisture 
adjustment, the samples were stored in an air tight container for 24 hours to allow moisture 
equilibration to take place. The moisture contents of the samples were then verified with a moisture 
analyzer (Model MB 45, Ohaus Corporation, Pine Brook, NJ).   
A sieve shaker (RO-TAP Model RX- 29, WS Tyler, OH) was thereafter used in 
fractionating the moisture adjusted ground samples into six fractions by fitting the sieve shaker 
with #12 (1.4 mm aperture), #18 (1.0 mm aperture), #25 (710 ?m aperture), #35 (500 ?m aperture), 
#60 (250 ?m aperture) screens and pan. The choice of sieve sizes was based on preliminary study 
on the particle size distribution of the unfractionated ground samples. At each moisture level, the 
flow properties of the fractions were carried out and recorded. 
4.3.2 Flow properties   
A powder flow tester (Powder Flow 230VAC, Brookfield Engineering Laboratories, Inc., 
Middleboro, MA) was used to quantify the flow behavior of the samples. The tester (Figure 4.2a) 
68 
 
is equipped with a 152.4 mm diameter annular split cell (Figure 4.2c) and a vane lid (with 18 small 
compartments). The vane lid (Figure 4.2b) is used to trap the sample particles and cause them to 
shear against the sample particles in the trough.  
             
 
 
          
 
  
 
Figure 4.2: Powder flow tester and accessories. 
 
To run a flow test, the mass of a test sample that filled the space between the inner and 
outer rings of the sample trough was recorded. The software provided by the equipment 
manufacturer was activated. This caused the lid to descend to a position slightly above the sample 
in the trough. The axial load and the torsional load test data were automatically recorded by the 
software. These load data are then used to calculate the cohesion, angle of internal friction, flow 
function, major consolidating stress, and unconfined yield strength. This procedure was carried 
out in triplicate for each test sample. 
 
 
b) Vane Lid 
c) Sample Trough a) Powder Flow Tester 
69 
 
4.3.3 Wall friction properties   
Wall friction properties were determined by the flow tester using the procedure similar to 
that used for the flow properties determination. Instead of the annular vane lid, the flow tester was 
fitted with a smooth bottom surface lid that was manufactured with the wall material of interest. 
The three wall surfaces that were tested in this study are stainless steel, mild steel or Tivar 88. The 
angles of wall friction of the sample on these surfaces were obtained from this test.  
4.3.4 Hopper design calculation 
 Silo design involves the bulk material properties, geometric design (to prevent arching, 
ratholing and to ensure proper flow pattern) and structural design (distribution of pressure and 
shear stresses on walls caused by stored materials). Conical hopper geometry was designed using 
the works of Enstad (1981) and Jenike (1964). Details of the symbols and nomenclatures used in 
the equations are presented in Appendix A.  
4.3.4.1 Hopper half angle 
Hopper half angle was determined using the following equations: 
                                         ? =?2 ? 12cos-1 [1-sin?2sin?]- ?                                          4.1 
where:     ? = ?w+sin
-1[sin?w
sin? ]
2                                                       4.2 
As a margin of safety in silo design, the hopper half angle is reduced by 30. 
4.3.4.2 Minimum hopper outlet size  
Hopper outlet size was determined by evaluating for cohesive arching tendency. The 
procedure involves calculation of flow function (FF) and flow factor (ff) from equations 4.3 and 
4.4 respectively. 
Flow Function:  FF = Unconfined yield stressMajor consolidating stress = UYSMCS                                       4.3  
70 
 
Flow factor:    ff =Y(1+sin?)H(?)2(X-1)sin?                                                        4.4 
where    1H(?)=[ 65130+?]m[ 200200+?]1-m                                               4.5 
 (m =1 for conical hoppers)              
X = 2
msin?
1-sin? {
sin(2?+?)
sin?  +1}          4.6 
A=[2(1-cos(?+?))]m(?+?)1-msin?                          4.7 
B=sin? sin1+m(?+?)                                     4.8 
C=(1-sin?)sin2+m(?+?)                                     4.9 
 Y=A+BC                                                                       4.10 
The critical applied stress (?c) represents the critical value of the unconfined yield strength 
at which a stable arch can be formed. This was obtained by the intersection of the flow function 
and flow factor (Figure 2.8). The value of the critical applied stress was used in equation 4.11 to 
calculate the minimum hopper outlet size. 
                                               Dmin.=H(?)?g ?c                                                            4.11 
The hopper outlet size was multiplied by 1.20 (0.20% greater) in order to achieve the desired flow 
rate. 
4.3.4.3 Silo wall loads 
 The silo is divided in to two sections: cylindrical and hopper sections (Figure 4.3). The 
vertical and wall normal pressure exerted by the ground loblolly pine in a 100 feet (30.48 m) high 
and 50 feet (15.24 m) diameter silo was estimated using Janseen?s equations (Janseen, 1985). 
4.3.4.3.1 Stresses in the cylindrical section  
Janseen?s equations for estimating the vertical and wall normal pressure in the cylindrical 
section are given below: 
71 
 
Vertical pressure:     Pv= ?gAK?C[1-exp(-?KCA h)]           4.12 
Wall pressure:     Pw= ?gA?C [1-exp(-?KCA h)]                     4.13 
 
Figure 4.3: Silo subdivision into vertical and hopper section (Schulze, 2008). 
  
4.3.4.3.2 Stresses in the hopper section  
 The stresses exerted by ground loblolly pine during storage and flow (Figure 4.4) were 
estimated using the equations below (Rotter, 2001). 
Initial fill load:    Pvf= Pvft (xh
h
)n+ ?hhn-1[(xh
h
)-(xh
h
)n]      4.14 
 n=2a?hcot(?)       4.15 
Flow induced load:        Pve= Pvft (xh
h
)n+ ?hhn-1[(xh
h
)-(xh
h
)n]       4.16 
?= ?w+ sin-1(sin?wsin? )          4.17 
Fe= 1+sin?cos?1-sin?cos (2?+?)         4.18 
n=2(Fe?hcot(?)+Fe-1)       4.19  
72 
 
 
Figure 4.4: Initial fill and flow induced pressure on the hopper section of a silo. 
4.3.5 Experimental design and statistical analysis  
Particle size and moisture content of fractionated ground loblolly pine were the predictors 
while the response variables was the flow properties. The type of wall material was also used as a 
predictor during the angle of wall friction experiment. All the experiments were carried out in 
triplicate.  
Microsoft Excel 2010 was used in summarizing and generating graphs. A significant test 
(? <0.05) using the Proc GLM procedure in the statistical software SAS 9.3 (SAS Institute Inc., 
Cary, NC) was conducted to show the effect of particle size and moisture content on the flow 
properties. The Tukey test was used to compare the means of values of these properties at the 
different moisture contents and particle sizes. The results were presented in mean and standard 
deviation. 
 
 
 
 
 
 
 
73 
 
4.4 Results and Discussion 
 
4.4.1 Flow classification of fractionated ground loblolly pine 
The flow function curves (plot of unconfined yield strength and major consolidating stress) 
for the fractions at the five moisture levels are shown in Figure 4.5(a-e). The curves show that a 
linear increase of unconfined yield strength (UYS) occurred as major consolidating stress (MCS) 
increased. The flow index (inverse of the flow function) was used to compare the effects of particle 
size and moisture content on the UYS versus MCS relationship and to characterize the flow 
properties of the fractions.  
 
 
Figure 4.5a: Flow function of fractionated loblolly pine at 4.78% moisture content. 
 
0
1
2
3
4
5
6
7
8
0 2 4 6 8 10 12 14 16
Unconf
ine
d Y
ield
 Str
en
gth (kP
a)
Major Consolidating Stress (kPa)
1.40mm
1.00mm
0.71mm
0.50mm
0.25mm
0.05mm
Raw
74 
 
 
 
Figure 4.5b: Flow function of fractionated loblolly pine at 8.69% moisture content. 
 
 
 
 
Figure 4.5c: Flow function of fractionated loblolly pine at 16.53% moisture content. 
 
 
0
1
2
3
4
5
6
7
8
0 2 4 6 8 10 12 14 16
Unconf
ine
d Y
ield
 Str
en
gth (kP
a)
Major Consolidating Stress (kPa)
1.40mm
1.00mm
0.71mm
0.50mm
0.25mm
0.05mm
Raw
0
1
2
3
4
5
6
7
8
0 2 4 6 8 10 12 14 16
Unconf
ine
d Y
ield
 Str
en
gth (kP
a)
Major Consolidating Stress (kPa)
1.40mm
1.00mm
0.71mm
0.50mm
0.25mm
0.05mm
Raw
75 
 
 
 
Figure 4.5d: Flow function of fractionated loblolly pine at 22.21% moisture content. 
 
 
Figure 4.5e: Flow function of fractionated loblolly pine at 25.53% moisture content. 
 
The flowability classification of the fractionated ground loblolly pine using flow index was 
based on Jenike?s powder flow classification (Table 4.1). The flow index increased with increase 
0
1
2
3
4
5
6
7
8
0 2 4 6 8 10 12 14 16
Unconf
ine
d Y
ield
 Str
en
gth (kP
a)
Major Consoliodating Stress (kPa)
1.40mm
1.00mm
0.71mm
0.50mm
0.25mm
0.05mm
Raw
0
1
2
3
4
5
6
7
8
0 2 4 6 8 10 12 14 16
Unconf
ine
d Y
ield
 Str
en
gth (kP
a)
Major Consolidating Stress (kPa)
1.40mm
1.00mm
0.71mm
0.50mm
0.25mm
Raw
76 
 
in particle size and decrease in moisture content. Except for 1.40 mm fraction at moisture levels 
of 4.78%, 8.69% and 16.53%, all of the samples were cohesive (Table 4.2). Based on Jenike?s 
classification, flow index value greater than 4 is classified as easy flowing material. Hence, the 
1.40mm fraction at moisture levels of 4.78%, 8.69% and 16.53% were classified as easy flowing 
materials. However, at moisture levels of 22.21% and 25.53%, the flow indices of 1.40mm 
fractions were 3.37 and 3.41 respectively, which indicates cohesive flow. The flow indices 
obtained for the unfractionated ground loblolly pine was between 2.54 and 3.19, which also 
indicate a cohesive flow. This result is due to the fact that all the other fractions below size 1.40 
mm were classified as cohesive therefore, making the whole ground material a cohesive material. 
The implication is that ground loblolly pine with large amount of fractions from size 0.05 to 1.00 
mm will experience flowability problem during discharge out of storage bins and hopper.  
Table 4.1: Jenike classi?cation of powder ?owability by ?ow index (?c). 
 
Flowability Hardened Very cohesive Cohesive Easy ?ow Free ?owing 
Flow index (?c ) 
 
<1                     <2 <4 <10       >10 
 
Table 4.2: Flow classification of fractionated ground loblolly pine. 
 
Screen 
(mm) 
Flow Index Classification 
4.78% 8.69% 16.53% 22.21% 25.53% 
1.40 4.29 4.17 4.11   3.37*   3.41* Easy flow 
1.00 3.80 3.80 3.49 3.37 2.73 Cohesive 
0.71 3.62 2.92 2.91 2.63 2.83 Cohesive 
0.50 3.16 2.86 2.44 2.34 2.29 Cohesive 
0.25 2.52 2.21 2.24 2.29 2.48 Cohesive 
0.05 2.38 2.26 2.27 2.08 NC* Cohesive 
Raw 3.19 2.89 2.54 2.70 2.61 Cohesive 
NC* experiment was not conducted because there was no fraction at 25.53% moisture level.  
 * Material have a cohesive flow 
77 
 
Grafton et al. (2009) characterize the flowability of 11 commercial agricultural limes with 
5% moisture addition by weight. The authors observed the flowability of the materials altering 
from easy flow to cohesive flow with increase in moisture content. Teunou et al. (1999) also 
classified the flowability of four food powders (flour, skim milk, tea and whey permeate) and 
determined the flow index to be 2.71, 11.04, 4.22 and 5.85 respectively. The authors reported that 
skim milk powder was classified as free flowing due to its low moisture content (4.6% wb) and 
large particle size (197 ?m). However, flour with a flow index of 2.71 was classified as cohesive. 
This was due to its high moisture content of 12.6% (wb) and low particle size of 73 ?m. 
Further analysis was carried out to examine the change in flowability of fraction of size 
1.40mm when mixed with different quantity of fractions with smaller particle size. The flow 
analysis was based on the assumption that reduction in the void spaces among the large particles 
will result in reduced flowability. Table 4.3 presents the flowability results of mixture of fractions 
retained on screen sizes 1.40 mm and 0.50mm at three mixing ratios of 10:1, 10:2 and 10:3 (Table 
3.4). As expected, increase in the amount of 0.50 mm fraction and moisture content resulted in 
flowability reduction from easy flow to cohesive flow. This implies that the presence of fine 
fraction in unfractionated ground loblolly pine is responsible for ratholing and cohesive arching 
flow problems.  
 
Table 4.3: Flow indices of mixture of 1.40mm and 0.50mm fractions. 
Moisture content  
(% wb) 
Ratio 
10:1 10:2 10:3 
4.78 3.92 3.75 3.45 
8.69 4.00 3.90 3.41 
16.53 3.70 3.23 - 
     *Ratio 10:1 represent mixture mass ratio of 1.40mm: 0.50mm fractions 
 
78 
 
4.4.2 Angle of internal friction 
The angle of internal friction represents friction between particles during movement of bulk 
materials. Table 4.4 shows the angle of internal friction obtained for the fractionated and 
unfractionated ground loblolly pine. The angle of internal friction for the fractionated sample 
varied between 40.400 and 52.660. The angle of internal friction significantly increased (p<0.05) 
with decrease in fraction size and increase in moisture content. The angles of internal friction of 
the unfractionated samples were also found to increase with moisture content from 43.29 and 
48.930. Gil et al. (2013) reported a similar result for corn stover and poplar. The angle of internal 
friction for poplar (300 - 320) and corn stover (260 - 290) increased with moisture content increase 
from 7 to 33% (wb) and decrease in particle size from 0.61 to 0.30mm for poplar and 0.70 to 0.26 
mm. Kibar et al. (2010) also reported increase in angle of internal friction from 29.700 to 32.530 
as the moisture content increased from 10% to 14% (db) for rice grains.  
Table 4.4: Angle of internal friction of fractionated ground loblolly pine. 
Screen 
size (mm) 
Moisture content levels (% wb) 
4.78 8.69 16.53 22.21 25.53 
0.05 49.88[a,x] ? 0.89 52.66[a,v] ? 0.91 51.74[a,vw] ?1.12 51.55[a,w] ? 1.12 NC* 
0.25 46.57[b,y] ? 0.99 48.15[b,x] ? 0.99 49.43[b,w] ? 1.09 50.89[ab,v] ? 1.17 50.69[a,v] ?1.36 
0.50 43.88[c,x] ? 2.23 45.29[c,x] ?2.18 47.37[c,w] ? 1.28 49.52[bc,v] ? 1.43 49.49[b,v] ? 1.12 
0.71 42.12[cd,x] ? 2.46 43.85[cd,w] ?1.86 46.67[cd,v] ? 1.04 47.95[c,v] ? 0.91 48.09[c,v] ? 0.55 
1.00 41.63[e,x] ? 1.82 42.78[d,x] ? 1.88 46.13[d,w] ? 0.88 48.23[c,v] ? 1.75 48.36[c,v] ? 0.90 
1.40 40.40[e,z] ? 1.55 42.09[d,y] ? 1.50 44.70[e,x] ? 0.61 48.15[c,v] ?1.86 46.41[d,w] ? 0.88 
Raw 43.29[cd,x] ?2.60 45.51[c,w] ? 1.89 47.40[c,v] ? 0.99 48.93[c,v] ? 1.88 48.08[c,v] ? 0.80 
Particle size effect: values in each column with same letter (a-f) are not significantly different (p<0.05).  
Moisture effect: values in each row with same letter (v-z) are not significantly different (p<0.05).  
NC* experiment was not conducted because there was no fraction at 25.53% moisture level. 
 
79 
 
The increased angle of internal friction with moisture content and reduction in fraction size 
of fractionated ground loblolly pine was an indication of increased frictional resistance between 
particles of smaller sizes. This implies that increasing amount of the smaller particles at higher 
moisture content in the unfractionated ground loblolly pine will cause the typical flow problems 
associated with bulk solids therefore leading to difficulty in unloading the ground material from 
storage vessels.  
Also, the measured angles of internal friction for the fractionated and raw samples were 
greater than the critical values of less than 300 required for gravity discharge of bulk materials 
from storage bins and silos (Puri, 2002). Therefore, it shows that unloading ground loblolly pine 
will be impossible with gravity discharge alone; there would be a need for a flow aid. Zulfiqar et 
al. (2006) reported the angle of internal friction for different blends of coal and sawdust/coal 
mixture to be in the range of 54.360 to 62.080. The angle of internal friction documented for other 
biological materials such as switchgrass (39.40 ? 46.70), wheat straw (41.60- 46.70), corn stover 
(46.70 - 49.50) and 41.250 for pecan shell are above the critical values making them not amendable 
to gravity discharge also (Chevanan et al., 2009; Littlefield et al., 2011).    
4.4.3 Cohesive strength  
Statistical analysis showed that particle size had a significant effect (p<0.05) on cohesive 
strength (Table 4.5). However, moisture content was found to have no significant effect (p<0.05) 
on the cohesive strength of the fractions. The cohesive strength of the fractionated and 
unfractionated ground loblolly pine ranged between 0.42 and 1.05 kPa. Cohesive strength 
decreased with increase in particle size  i.e. fractions of size 0.05 mm had the highest cohesive 
strength while fractions of size 1.40 mm had the lowest cohesive strength. The increased cohesive 
80 
 
strength in finer fraction is attributable to the increased total surface area and number of contact 
points for inter-particle bonding (Drzymala, 1993) that exists in fraction with smaller particles.  
4.4.4 Wall friction properties  
Particle size and moisture effect on wall friction properties of the fractions were measured 
on three wall surfaces (stainless steel, mild steel and Tivar 88). Statistical analysis showed that 
particle size and moisture content had a significant effect on angle of wall friction of fractionated 
ground loblolly pine with an increase in the angle of wall friction as fraction size decrease and 
moisture content increased.  
 
Table 4.5: Cohesive strength (kPa) of fractionated ground loblolly pine. 
Screen size 
(mm) 
Moisture content levels (% wb) 
4.78 8.69 16.53 22.21 25.53 
0.05 1.05[a,v] ? 0.47 1.01[a,v] ?0.45 0.92[a,v] ?0.42 0.91[a,v] ?0.40 NC* 
0.25 0.82[ab,v] ?0.33 0.88[ab,v] ? 0.37 0.90[ab,v] ? 0.44 0.93[a,v] ? 0.45 0.91[a,v] ?0.44 
0.50 0.63[bc,v] ? 0.24 0.70[bc,v] ? 0.29 0.76[ab,v] ?0.37 0.87[ab,v] ? 0.44 0.88[a,v] ? 0.45 
0.71 0.52[bc,v] ? 0.21 0.58[c,v] ? 0.27 0.66[ab,v] ? 0.33 0.73[ab,v] ? 0.37 0.72[a,v] ? 0.39 
1.00 0.48[c,v] ? 0.21 0.49[c,v] ? 0.22 0.55[ab,v] ? 0.28 0.46[c,v] ? 0.35 0.74[a,v] ? 0.41 
1.40 0.43[c,v] ? 0.20 0.45[c,v] ? 0.22 0.45[b,v] ? 0.22 0.39[c,v] ? 0.33 0.60[a,v] ? 0.32 
Raw 0.65[bc,v] ? 0.26 0.69[bc,v] ? 0.31 0.78[ab,v] ? 0.40 0.70[ab,v] ? 0.45 0.75[a,v] ? 0.38 
Particle size effect: values in each column with same letter (a-f) are not significantly different (p<0.05).  
Moisture effect: values in each row with same letter (v-z) are not significantly different (p<0.05).  
NC* experiment was not conducted because there was no fraction at 25.53% moisture level. 
 
 
The angle of wall friction on stainless steel surface (Table 4.6) varied between 8.96 and 
24.800. The implication is that a high value of wall friction caused by reduction in particle and 
increase in moisture content leads to greater adhesion of the particles to the surface of storage wall 
81 
 
hence resulting in flow problem during material discharge. Fitzpatrick et al. (2004) stated that 
angle of wall friction represents the adhesion of powder to the silo wall (the higher the angle, the 
more difficult it is to move the powder along the surface). This implies that a strong adhesion will 
be developed by fractionated ground loblolly pine at low fraction size or increased moisture 
content, hence making it difficult for the ground biomass to flow along the wall surface of the 
storage vessel.  
Table 4.6: Angle of wall friction of fractionated loblolly pine using stainless steel wall.  
 
Screen 
size (mm) 
Moisture Content Level (% wb) 
4.78 8.69 16.53 22.21 25.53 
0.05 12.30[a,y] ?1.28 14.90[a,x] ? 2.05 17.14[a,w] ? 2.75 26.49[a,v] ? 4.61 NC* 
0.25 9.83[b,z] ? 0.52 12.39[b,y] ? 1.27 14.00[c,x] ? 1.54 19.50[b,w] ? 2.64 24.80[a,v] ? 3.96 
0.50 9.45[c,z] ? 0.50 11.24[c,y] ? 0.90 13.79[c,x] ? 1.43 17.60[cd,w] ? 1.96 21.62[b,v] ? 2.80 
0.71 9.39[c,z] ? 0.49 12.72[b,y] ? 1.48 14.22[c,x] ? 1.47 16.72[d,w] ? 1.73 20.98[bc,v] ? 2.58 
1.00 9.49[c,z] ? 0.50 11.44[c,y] ?1.00 14.40[c,x] ? 1.38 17.35[cd,w] ? 1.83 20.06[cd,v] ? 2.51 
1.40 8.96[d,z] ? 0.38 10.82[c,y] ? 0.97 14.18[c,x] ? 1.31 16.52[d,w] ? 1.65 18.76[d,v] ? 2.05 
Raw 9.53[bc,z] ? 0.53 10.92[c,y] ? 1.27 16.23[b,x] ? 2.21 18.13[c,w] ? 1.85 20.56[bc,v] ? 2.54 
Particle size effect: values in each column with same letter (a-f) are not significantly different (p<0.05)  
Moisture effect: values in each row with same letter (v-z) are not significantly different (p<0.05)  
NC* experiment was not conducted because there was no fraction at 25.53% moisture level 
 
 
The angle of wall friction on mild steel surface ranged between 10.480 and 19.730  (Table 
4.7) with the fractions of size 0.05 mm having the highest wall friction value while the fractions 
on sieve size 1.40 mm had the lowest wall friction angle. However, the angles of wall friction 
recorded on mild steel surface were in the range of the values obtained for stainless steel.  
 
 
82 
 
Table 4.7: Angle of wall friction of fractionated loblolly pine using mild steel wall. 
 
Screen 
size (mm) 
Moisture Content Level (% wb) 
4.78 8.69 16.53 22.21 25.53 
0.05 12.33[a,x] ? 1.10 16.10[a,w] ? 2.63 15.22[a,w] ? 1.72 21.35[a,v] ? 3.15 NC* 
0.25 10.48[d,z] ? 0.45 13.11[b,y] ? 1.21 14.29[c,x] ? 1.32 18.12[bc,w] ? 2.08 22.56[a,v] ? 3.42 
0.50 10.50[cd,z] ? 0.39 12.09[c,y] ? 0.72 15.07[a,x] ? 1.36 18.18[bc,w] ? 1.70 19.52[b,v] ? 2.55 
0.71 10.54[cd,z] ? 0.35 12.17[c,y] ? 0.71 15.31[a,x] ? 1.34 17.42[c,w] ? 1.58 19.73[b,v] ? 2.28 
1.00 10.81[b,z] ?0.36 12.43[c,y] ? 0.76 15.01[ab,x] ? 1.34 17.99[c,w] ? 1.53 18.87[bc,v] ? 2.18 
1.40 10.76[bc,y] ? 0.31 12.38[c,x] ? 0.59 14.22[c,w] ? 1.13 18.00[c,v] ? 1.42 18.30[c,v] ? 1.90 
Raw 10.55[bc,y] ?0.37 12.16[c,x] ?0.92 14.53[bc,w] ?1.30 19.04[b,v] ?1.77 19.39[bc,v] ?2.29 
Particle size effect: values in each column with same letter (a-f) are not significantly different (p<0.05).  
Moisture effect: values in each row with same letter (w-z) are not significantly different (p<0.05).  
NC* experiment was not conducted because there was no fraction at 25.53% moisture level. 
 
The angle of wall friction recorded using the Tivar 88 surface (ultra-high weight molecular 
polyethylene) surface ranged between 10.880 and 15.540 (Table 4.8). There was a significant 
increase (p<0.05) in the angles of wall friction with reduction in fraction size for the three wall 
surfaces. This is because there is greater contact surface area between smaller particles and the 
wall surface (Iqbal and Fitzpartick, 2006) which led to the high wall friction angle recorded for 
fractions of size 0.05 mm. 
The increased wall friction angle due to increase in moisture content had also been reported 
for other biological materials using different wall surfaces. Mani et al. (2004) reported a significant 
increase in angle of wall friction of corn stover grinds from 0.180 to 0.260 as the moisture content 
increased from 7% to 15% (wb) using a steel surface. The authors asserted that the increased wall 
friction angle is due to increased adhesion between corn stover grinds and the steel surface at 
higher moisture content. Iqbal and Fitzpatrick (2006) observed an increase from 9.50 to 14.60 of 
83 
 
wall friction angle for flour as moisture content increased from 12.6% to 15.1% (wb). The authors 
reported similar trend for tea and whey permeate powder. Grafton et al. (2009) also reported an 
increase in wall friction angle of different commercial agricultural limes with increased moisture 
content.    
 
Table 4.8: Angle of wall friction of fractionated loblolly pine using Tivar 88 wall surface. 
 
Screen 
size (mm) 
Moisture Content Level (% wb) 
4.78 8.69 16.53 22.21 25.53 
0.05 14.80[a,vw] ?1.71 15.54[a,v] ?2.25 14.52[a,w] ? 1.79 15.50[a,v] ? 2.64 NC* 
0.25 13.61[b,w] ?1.09 13.48[bc,w] ? 1.31 13.14[b,w] ? 1.28 13.33[c,w] ?1.70 15.23[a,v] ? 2.46 
0.50 12.48[c,w] ? 0.87 12.87[cd,vw] ?1.07 12.83[b,vw] ?1.12 12.36[d,w] ? 1.35 13.06[b,v] ? 1.64 
0.71 12.10[cd,v] ? 0.98 12.32[de,v] ? 1.03 12.01[c,v] ? 1.05 12.02[d,v] ?1.58 11.76[c,v] ? 1.47 
1.00 11.59[d,w] ? 0.87 11.72[ef,w] ? 0.97 11.24[d,w] ? 0.99 12.81[cd,v] ? 1.89 11.46[c,w] ? 1.40 
1.40 10.88[e,y] ? 0.96 11.47[f,vw] ? 1.15 11.61[cd,w] ? 1.02 12.44[cd,v] ? 1.74 10.98[c,xy] ? 1.32 
Raw 11.75[d,x] ?0.90 14.07[b,v] ?1.35 12.17[c,wx] ?1.30 14.45[b,v] ?2.28 12.55[b,w] ?1.58 
 
Particle size effect: values in each column with same letter (a-f) are not significantly different (p<0.05).  
Moisture effect: values in each row with same letter (v-z) are not significantly different (p<0.05).  
NC* experiment was not conducted because there was no fraction at 25.53% moisture level. 
 
Statistical analysis showed that the wall surface had a significant effect (p<0.05) on the 
angle of wall friction of the fractionated ground loblolly pine (see appendix for tables). At lower 
moisture level, the stainless steel and mild steel had a lower wall friction angle compared to Tivar 
88 surface but as the moisture content increased, the angle of wall friction for the stainless steel 
and mild steel surface increased significantly. The high angles of wall friction recorded by stainless 
steel and mild steel can be attributed to their roughness factors which are 45?m and 15 ?m 
respectively while Tivar 88 (classified as plastic) has a roughness factor of 1.5 ?m (Darby, 2001). 
84 
 
Also, a scanning electron microscope images (Figure 4.6) of the stainless steel, mild steel and 
ultra- high weight molecular polyethylene surfaces showed that Tivar 88 surface has the smoothest 
surface which enhanced its low wall friction angles. This indicates that Tivar 88 surfaces will be a 
good wall lining material in the design of storage and handling vessel for ground loblolly pine with 
high moisture content while stainless and mild steel will perform well at lower moisture content. 
     
a) stainless steel  b) mild steel       c) ultra- high weight molecular 
          polyethylene (Tivar 88) 
 
Figure 4.6: SEM images of stainless steel, mild steel and Tivar 88 wall surfaces  
(Sources: Zhou and Komvopoulos, 2005; G?nen et al., 2014; Farhat and Quraishi, 2010). 
 
Previous studies had shown the effect of wall material on angle of wall friction on 
biological materials. For example, Wu et al. (2011) compared the effect of four wall surfaces (Tivar 
88, concrete, mild steel and stainless steel) on wall friction angles of wood pellets and wood chips. 
The authors observed that Tivar 88 surface had the lowest wall friction angles (11-170) when 
compared with the other three surfaces with wall friction angle varying between 16 and 350. This 
difference was attributed to the surface roughness of material with concrete having the coarsest 
surface, hence having the highest angle of wall friction and Tivar 88 having the smoothest surface 
hence it low wall friction angle. Fitzpatrick et al. (2004) reported the angle of wall friction for 13 
85 
 
different biological materials using a stainless steel surface. The wall friction angles ranged 
between 11.80 and 27.30. Chen et al. (2012) found the angle of wall friction for brown coal, hard 
coal and saw dust to be 260, 27.80 and 31.40 respectively using a stainless steel as well. The wall 
friction between the hopper wall material and the bulk materials is very important in determining 
whether mass flow or funnel flow pattern will be obtained during discharge from a silo (Fitzpatrick, 
2007). Therefore, in order to ensure reliable flow, the angle of wall friction of the storage vessel 
wall lining material must be low. This is an indication of a limited adhesion of the bulk material 
to the wall surface of the storage vessel.  
4.4.5 Hopper half angle and minimum hopper outlet size  
Jenike?s methodology for estimating the conical hopper half angle was employed (Jenike, 
1964). The measured angle of internal friction and wall frictions using the three surfaces were 
applied in the methodology. The hopper half angle varied between 18.370 and 41.440. As a margin 
of safety during hopper design, the hopper half angle was reduced by 30 making the angle varied 
between 15.370 and 38.440 (Table 4.9). There was a reduction in the hopper half angle with 
increased moisture content and reduction in the fraction size (Figure 4.7 & 4.8). However, moisture 
content does not have an effect on hopper half angle using Tivar 88 surface when compared to 
stainless and mild steel surface (Figure 4.7). This is attributable to the low variation in angles of 
wall friction of Tivar 88 surface at all moisture levels. 
 
 
 
 
 
 
86 
 
Table 4.9: Evaluation of hopper half angle, flow factor and minimum hopper opening size 
(Dmin) for a cylindrical hopper using Jenike?s method. 
 
 
Screen 
Size (mm) 
Moisture 
Content (%) 
Particle 
diameter 
(mm) 
Reduced Hopper Half Angle Flow 
factor 
Adjusted 
Dmin (mm) Stainless Steel Mild Steel Tivar 88 
0.05 
4.78 0.11 32.19 32.15 29.27 1.06 1.32 
8.69 0.15 28.82 27.45 28.09 1.04 1.80 
16.53 0.10 26.34 28.55 29.36 1.05 1.20 
22.21 0.10 15.37 21.42 28.25 1.09 1.20 
0.25 
4.78 0.85 35.72 34.94 31.17 1.09 10.20 
8.69 0.81 32.36 31.51 31.07 1.08 9.72 
16.53 0.70 30.27 29.93 31.28 1.07 8.40 
22.21 0.64 23.66 25.28 30.84 1.07 7.68 
25.53 0.86 17.39 20.06 28.67 1.09 10.32 
0.50 
4.78 1.16 36.82 35.52 33.07 1.13 13.92 
8.69 0.97 34.29 33.26 32.30 1.12 11.64 
16.53 1.01 30.83 29.29 31.97 1.09 12.12 
22.21 0.84 26.01 25.33 32.17 1.08 10.08 
25.53 1.33 21.23 23.74 31.36 1.09 15.96 
0.71 
4.78 1.38 37.37 35.92 33.95 1.17 16.56 
8.69 1.28 32.78 33.46 33.28 1.14 15.36 
16.53 1.33 30.42 29.10 33.08 1.11 15.96 
22.21 1.17 27.20 26.36 32.79 1.09 14.04 
25.53 1.46 22.08 23.59 33.12 1.11 17.52 
1.00 
4.78 1.72 37.39 35.71 34.72 1.18 20.64 
8.69 1.54 34.62 33.38 34.27 1.16 18.48 
16.53 1.69 30.29 29.55 34.12 1.11 20.28 
22.21 1.55 26.46 25.69 31.87 1.09 18.60 
25.53 1.73 23.18 24.61 33.43 1.10 20.76 
1.40 
4.78 2.16 38.44 36.12 35.97 1.20 25.92 
8.69 2.14 35.58 33.60 34.75 1.17 25.68 
16.53 2.17 30.81 30.76 33.97 1.13 26.04 
22.21 2.18 27.47 25.70 32.34 1.09 26.16 
25.53 2.38 24.93 25.49 34.37 1.12 28.56 
Raw 
4.78 1.31 36.87 35.61 34.11 1.15 15.72 
8.69 1.36 34.63 33.13 30.80 1.12 16.32 
16.53 1.33 27.89 29.93 32.76 1.10 15.96 
22.21 1.39 25.44 24.36 29.81 1.09 16.68 
25.53 2.19 22.59 24.01 32.19 1.10 26.28 
 
87 
 
 
Figure 4.7: Effect of moisture content on hopper half angle of 0.25 mm fraction. 
 
Figure 4.8: Effect of fraction size on hopper half angle at the 4.78% moisture level.  
 
Figure 4.9 illustrates angles of wall friction versus hopper half angles obtained for the 
fractionated ground loblolly pine. The hopper half angle decreased with increase in angle of wall 
friction. The angles of wall friction recorded for stainless steel and mild steel had a wider spread 
of hopper half angles while tivar 88 had a small variation in its hopper half angle. The variation in 
15
18
21
24
27
30
33
36
39
0 5 10 15 20 25 30
Hop
pe
r Hal
f Angl
e (
0 )
Moisture Content (% wb)
Stainless steel
Mild steel
Tivar 88
25
27
29
31
33
35
37
39
41
0.00 0.25 0.50 0.75 1.00 1.25 1.50
Hop
pe
r Hal
f Angl
e (0)
Fraction Size (mm)
Stainless Steel
Mild Steel
Tivar 88
88 
 
the hopper half angles for the three surfaces is attributable to the particle size and moisture effect 
on their angles of wall friction. 
 Jenike (1970) also designed a chart (Figure 2.7) showing the combination of the angle of 
wall friction and the hopper half angle. The chart indicates allowable hopper half angles for mass 
flow or funnel flow for given values of wall friction angles. The highest hopper half angle for the 
fractionated loblolly pine was 38.440 and the highest angle of wall friction recorded was 24.80. 
Using the design chart provided by Jenike, the combination of these two data shows that mass flow 
pattern will exist during discharge of ground loblolly pine from a storage silo. Therefore, the 
hopper design was based on mass flow pattern.  
    
         
Figure 4.9: Plot of hopper half angles and wall friction angle of ground loblolly pine. 
 
The intersection of the flow function and the flow factor lines are used in estimating the 
critical applied stress. Generally, it is assumed that the flow function and flow factor lines will 
intersect in order to obtain the critical applied stress. However, the flow function lines for the 
0
10
20
30
40
50
0 5 10 15 20 25 30
Hop
pe
r Hal
f Angl
e (
0 )
Angle of Wall Friction (0)
Stainless Steel
Mild Steel
Tivar 88
89 
 
fractions lie below the flow factor lines (Figure 4.10) resulting in no critical applied stress. This 
result implies that the applied stress exceeds the unconfined yield strength of the fraction. 
The calculation of the minimum hopper outlet size was therefore not on the basis of 
cohesive arching but rather to prevent formation of mechanical arching. Purutyan and Barnam 
(2001) stated that in estimating the minimum hopper outlet size designed to ensure mass flow and 
prevent mechanical arching; the hopper outlet size should be at least six to eight times bigger than 
the largest particle diameter of the material. The minimum hopper outlet sizes were estimated by 
multiplying the geometric mean diameter by 10. The actual outlet dimensions were then multiplied 
by 1.20 (20% greater) in order to ensure the desired flow rate (Table 4.9). As expected, the 
minimum hopper outlet size followed the trend of the geometric mean diameters and it varied 
between 1.20 and 28.56 mm with 1.40 mm fraction having the highest minimum hopper outlet 
sizes. 
 
           
Figure 4.10: Flow function and flow factor of fraction size 0.25 mm at 16.53% moisture   
content. 
0
3
6
9
12
15
0 3 6 9 12 15
Unconf
ine
d Y
ield
 Str
en
gth (kP
a)
Major Consolidating Stress (kPa)
Flow function
Flow factor
90 
 
The non- intersection of the flow function and flow factor lines (leading to design of hopper 
outlet size to prevent mechanical arching) is in contrast to the results obtained from the flow 
properties tests, which showed that fractionated ground loblolly pine was cohesive in nature. 
However, due to the small sizes obtained for the hopper outlets, there is tendency for cohesive 
arching to occur at the hopper outlet. Even though the hopper outlet sizes were calculated to 
prevent mechanical arching, the selection of the hopper outlet sizes must be large enough to 
prevent formation of cohesive arch as well.  
4.4.6 Silo wall loads 
Table 4.10 presents the estimated vertical and wall pressure exerted on the cylindrical 
section and also the initial fill and flow induced pressure exerted on hopper section of the designed 
silo with a height of 30.48 m (100 feet) and diameter of 15.24 m (50 feet). The wall pressure acting 
on the cylindrical section of the silo varied between 9.35 and 45.42 kPa while the vertical pressure 
ranged between 15.34 and 48.91 kPa. The pressures acting on the cylindrical and hopper section 
of the silo increased with increase in fraction size and decrease in moisture content (Figure 4.11 & 
4.12). These results imply that during storage of ground loblolly pine in a storage bin, a large 
quantity of big particles at lower moisture content will exert more pressure on the cylindrical 
section of the silo wall. 
 
 
 
 
 
 
 
91 
 
Table 4.10: Silo wall loads of fractionated ground loblolly pine. 
Screen Size 
(mm) 
Moisture 
Content (%) 
Cylindrical Section Hopper section 
Wall Pressure 
(kPa) 
Vertical 
Pressure (kPa) 
Initial Fill 
Load(kPa) 
Flow Induced 
Pressure (kPa) 
0.05 
4.78 21.71 25.07 25.07 41.07 
8.69 18.46 22.59 22.59 36.39 
16.53 14.64 18.87 18.87 30.40 
22.21 9.35 15.34 15.34 24.71 
0.25 
4.78 28.58 31.33 31.33 50.46 
8.69 23.82 27.57 27.57 44.41 
16.53 19.20 23.02 23.02 37.08 
22.21 13.54 18.47 18.47 29.76 
25.53 10.32 16.16 16.16 26.03 
0.50 
4.78 32.50 35.35 35.35 56.95 
8.69 29.89 33.75 33.75 54.37 
16.53 21.63 25.82 25.82 41.59 
22.21 16.76 21.84 21.84 35.19 
25.53 13.38 19.25 19.25 31.02 
0.71 
4.78 39.33 42.72 42.72 68.82 
8.69 32.29 37.64 37.64 60.63 
16.53 24.50 29.52 29.52 47.56 
22.21 19.69 25.13 25.13 40.48 
25.53 16.05 22.73 22.73 36.61 
1.00 
4.78 41.95 45.67 45.67 73.57 
8.69 35.94 40.75 40.75 65.65 
16.53 27.00 32.67 32.67 52.64 
22.21 22.28 28.86 28.86 46.49 
25.53 19.84 27.45 27.45 44.22 
1.40 
4.78 45.42 48.91 48.91 78.79 
8.69 39.68 44.41 44.41 71.54 
16.53 28.69 34.55 34.55 55.65 
22.21 24.96 31.70 31.70 51.07 
25.53 23.38 31.33 31.33 50.47 
Raw 
4.78 42.09 45.86 45.86 73.87 
8.69 39.90 44.75 44.75 72.08 
16.53 25.14 31.72 31.72 51.10 
22.21 22.39 29.55 29.55 47.60 
Raw 20.58 28.84 28.84 46.46 
 
 
92 
 
              
Figure 4.11: Effect of moisture content on pressures acting on silo wall for 0.25 mm fraction 
at a wall height of 100 feet (30.48m). 
 
 
 
Figure 4.12: Effect of particle size on pressures acting on the cylindrical and hopper section 
of the silo wall at a wall height of 100 feet (30.48m). 
 
Figure 4.13 illustrates the vertical and wall pressure versus the cylindrical height (from top 
of the silo to the bottom) for the 0.05 mm fractions at the 4.78 % moisture level. The vertical and 
the wall pressures exerted on the cylindrical section of the silo by the material increased with 
0
10
20
30
40
50
60
0 5 10 15 20 25 30
Pr
essu
re 
(kP
a)
Moisture Content (% wb)
Wall pressure
Vertical Pressure
Initial Fill load
Flow Induced Pressure
0
10
20
30
40
50
60
70
80
90
0.00 0.25 0.50 0.75 1.00 1.25 1.50
Pr
essu
re 
(kP
a)
Fraction Size (mm)
Wall Pressure
Vertical Pressure
Initial Fill Pressure
Flow Induced Pressure
93 
 
height. These pressures increased downward which indicated that there is a tendency for the silo 
to expand at the lower part of the silo due to the pressures exerted on the silo wall. 
Figure 4.14 shows the change in the initial fill and flow induced pressures as the hopper 
height changes. The initial and flow induced pressures represent the pressures exerted on the 
hopper section of the silo when the silo is filled with bulk solid and during discharge respectively. 
The estimated initial fill and flow induced pressures for the fractionated ground loblolly pines are 
presented in Table 4.10. The initial fill loads varied between 15.34 and 48.91 kPa while the flow 
induced pressures varied between 24.71 and 78.79 kPa. The initial fill and flow induced pressures 
also increased with increase in fraction size and decrease in moisture content. The values obtained 
for the initial fill and flow induced pressures indicates the estimated peak pressures that can be 
attained when a silo of height 100 feet (30.48m) and diameter 50 feet (15.24m) is filled to capacity.  
 
Figure 4.13:Plot of vertical and wall pressure against cylindrical height for the 0.05 mm 
fraction at 4.78 % moisture level. 
 
0
5
10
15
20
25
30
35
0 5 10 15 20 25 30
Cyl
ind
eri
cal
 H
eight 
(m
)
Pressure (kPa)
Wall Pressure (kPa)
Vertical Pressure (kPa)
94 
 
 
Figure 4.14:Plot of initial and flow induced loads against hopper height for the 0.05 mm 
fraction at 4.78 % moisture level. 
 
The initial fill and flow induced pressures increased as the hopper height increased. 
However, the initial fill pressure became constant at a certain hopper height. This shows that the 
pressure exerted on the hopper wall as the silo is filled with material reaches a maximum and 
remains constant at a certain hopper height.  
 
4.5 Conclusion 
The design of a silo bin to allow easy flow of material represents important aspect of bulk 
solid handling. In this study, the flow properties of fractionated ground loblolly pine were 
quantified and a sensitivity analysis carried out on the silo design parameters. It was found that; 
? The flowability of the fractions increased with increase in fraction size and decrease in 
moisture content. Dosing of large and small sized fractions resulted in reduced flowability. 
This result implied that the presence of small particles resulted in reduced flowability. Also, 
the wall friction properties were found to perform differently using three different wall 
0
2
4
6
8
10
12
14
0 10 20 30 40 50
Hop
pe
r Heigh
t (
m)
Pressure (kPa)
Initial Fill
Flow induced
95 
 
surfaces. Stainless steel and mild steel had better performance at lower moisture content 
while Tivar 88 surface had a good performance at higher moisture content. 
? The hopper half angle (varied between 15.370 and 38.440) decreased with increase in 
moisture content and decrease in fraction size. The minimum hopper outlet sizes ranged 
from 1.20 to 28.56 mm. The vertical and wall normal pressures acting on the cylindrical 
section increased with increase in fraction size and decrease in moisture content. The initial 
fill and flow induced pressure also increased with increase in fraction size and decrease in 
moisture content.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
96 
 
Chapter 5: Summary and Recommendation 
5.1 Summary 
Particle size and moisture content contributed significantly to the physical and flow 
properties of ground loblolly pine. At varying fraction size and moisture content, the physical and 
flow properties of the fractionated ground loblolly pine was found to behave differently. The bulk 
and tap densities were found to increase with increase in fraction size while particle density was 
not significantly affected by fraction size. The porosity, Hausner ratio and compressibility of the 
fractions were also found to decrease with increase in the size of the fraction. Also, increased 
moisture content was found to significantly cause a reduction in the densities (bulk, tap and 
particle) and porosity while it had no significant effect on Hausner ratio and compressibility. 
Meanwhile, the flowability of the fraction increased with increase in fraction size and reduced 
moisture content. Dosing of large sized fraction and small sized fraction resulted in reduced 
flowability. This implies that the presence of small particles results in reduced flowability. Also, 
wall friction characteristics were found to perform differently. Stainless and mild steel had better 
performance at lower moisture content while Tivar 88 surface had a consistent and desirable results 
at different moisture content levels and across the particle sizes. The heating value of the fractions 
and volatile matter were not significant affected by fraction size. However, the ash content was 
found to increase with reduction in the size of the fraction. These compositional data are needed 
to design appropriate biomass conversion systems.  
The sensitivity analysis indicated that the flow factor and flow function lines did not 
intersect and therefore a critical applied stress was not obtained. This implies that the design of the 
minimum hopper outlet size is to handle mechanical arching. This is in contrast to the flow 
properties test carried out on the fractions describing the loblolly fraction as a cohesive material. 
97 
 
However, the minimum discharge outlet sizes obtained for the fractions varied from 1.20 to 28.56 
mm. This implies that with such minimum hopper outlet size, there is a tendency for cohesive 
arching to occur during material discharge. The vertical and wall normal pressures acting on the 
cylindrical section of the silo alongside the initial fill and flow induced pressures increased with 
increase in fraction size and decrease in moisture content. Also, the pressures increased as the 
height of the cylindrical and hopper sections increased.   
The results obtained from this work shows that an increasing quantity of small sized 
fractions and moisture content will lead to typical flow problems associated with bulk materials. 
Therefore, in the design and selection of appropriate storage, handling and transport vessels for 
ground woody biomass (e.g loblolly pine), it is imperative to understand the proportion of varying 
sizes of fractions in the bulk material as this tends to significantly influence the physical and flow 
properties of ground loblolly pine. The design and selection of storage vessels should take into 
consideration the change in flow problems caused by particle size and moisture content especially 
in the estimation of hopper outlet size for mass flow in order to prevent cohesive and mechanical 
arching.  
 
5.2 Recommendation and future works 
This work investigated the contribution of particle size and moisture content to the physical 
and flow properties of fractionated ground loblolly pine. In order to avoid flow problem during 
unloading of ground loblolly pine from storage vessels, ensuring large particles of sizes 1.40 mm 
and moisture content range of 4 ? 10% (wb) will be appropriate. Also, in the selection of the type 
of wall lining material to be used for storage vessel, Tivar 88 surface will be desirable because of 
its low angle of wall friction at all moisture levels and particle sizes.  
98 
 
This research work focused mainly on characterization of the instantaneous physical and 
flow properties of the fractionated ground loblolly pine. Since there is a time difference between 
the storage of ground loblolly pine and when it is used, it is recommended that further analysis 
should be carried out on the effect of storage time (time consolidation) on the physical and flow 
properties of fractionated ground loblolly pine at different moisture content. Also, in the present 
study, a dosing experiment of two fractions was only carried out. Therefore, it is recommended 
that a dosing experiment involving the mixture of varying quantity of each fraction to determine 
the point at which flowability will change from easy flow to cohesive flow should be conducted.   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
99 
 
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112 
 
Appendix A 
 
Table A.1: Symbols and Nomenclatures  
 
Symbols Nomenclature Unit 
?p Particle Density kg/m3 
?b Bulk Density  kg/m3 
?T Tap Density  kg/m3 
FF Flow function - 
FI Flow index - 
?w Angle of wall friction  Degree 
? Angle of internal friction Degree  
? Hopper half angle Degree 
? Characteristic of the material/wall relationship Degree 
Dmin Minimum hopper outlet size m 
H(?) Emprical factor depend on shape of hopper and hopper angle - 
?c Critical applied stress  Pa 
Pw Wall pressure on the cylinderical portion of the silo Pa 
Pv Vertical pressure on the cylinderical portion of the silo Pa 
g Acceleration due gravity m/s2 
?h Hopper wall friction coefficient  - 
K Pressure coefficient - 
H Height of the cylindrical portion of the silo m 
? Wall fricition coefficient for the hopper - 
Pnf Normal pressure on hopper wall while filling Pa 
Pvf Mean vertical stress in the silo at the transition after filling Pa 
Pne Normal pressure on hopper wall while emptying Pa 
Pve Mean vertical stress in the silo at the transition after emptying Pa 
ff Flow factor - 
 
 
 
 
 
 
 
 
 
 
 
113 
 
ANOVA results 
Table B.1: ANOVA result of particle size and moisture effect on particle density of 
fractionated ground loblolly pine 
 
The GLM Procedure 
 
Dependent Variable: PD    
                                           Sum of 
     Source                      DF         Squares     Mean Square    F Value    Pr > F 
 
     Model                       33     83672.22520      2535.52198      57.95    <.0001 
     Error                       68      2975.26000        43.75382 
     Corrected Total            101     86647.48520 
 
                       R-Square     Coeff Var      Root MSE       PD Mean 
 
                       0.965662      0.457950      6.614667      1444.407 
 
    Source                      DF       SS     Mean Square    F Value    Pr > F 
 
    PS                           6      9909.45586      1651.57598      37.75    <.0001 
    MC                           4     62010.71172     15502.67793     354.32    <.0001 
    PS*MC                       23     11752.05762       510.95903      11.68    <.0001 
 
 
 
Table B.2: ANOVA result of particle size and moisture effect on bulk density of 
fractionated ground loblolly pine 
 
The GLM Procedure 
 
Dependent Variable: BD    
                              Sum of 
       Source                      DF        Squares     Mean Square    F Value    Pr > F 
 
       Model                       33     189319.0971       5736.9423    1164.84    <.0001 
 
       Error                       68        334.9062          4.9251 
 
       Corrected Total            101     189654.0033 
 
                      R-Square     Coeff Var      Root MSE       BD Mean 
 
                       0.998234      1.064513      2.219255      208.4761 
 
       Source                      DF        SS        Mean Square    F Value    Pr > F 
 
       PS                           6     148915.5648      24819.2608    5039.35    <.0001 
       MC                           4      37276.7487       9319.1872    1892.19    <.0001 
       PS*MC                       23       3126.7836        135.9471      27.60    <.0001 
 
 
 
 
 
 
 
 
114 
 
Table B.3: ANOVA result of particle size and moisture effect on tap density of fractionated 
ground loblolly pine 
 
The GLM Procedure 
 
Dependent Variable: TD    
                                               Sum of 
       Source                      DF         Squares     Mean Square    F Value    Pr > F 
 
       Model                       33     153584.7941       4654.0847     469.55    <.0001 
 
       Error                       68        674.0000          9.9118 
 
       Corrected Total            101     154258.7941 
 
                       R-Square     Coeff Var      Root MSE       TD Mean 
 
                       0.995631      1.141295      3.148296      275.8529 
 
       Source                      DF        SS     Mean Square    F Value    Pr > F 
 
       PS                           6     100864.2775      16810.7129    1696.04    <.0001 
       MC                           4      48920.4694      12230.1174    1233.90    <.0001 
       PS*MC                       23       3800.0472        165.2194      16.67    <.0001 
 
 
Table B.4: ANOVA result of particle size and moisture effect on compressibility of 
fractionated ground loblolly pine 
 
The GLM Procedure 
 
Dependent Variable: Compressibility    
 
                                               Sum of 
       Source                      DF         Squares     Mean Square    F Value    Pr > F 
 
       Model                       33     3837.140392      116.276982      36.41    <.0001 
 
       Error                       68      217.173333        3.193725 
 
       Corrected Total            101     4054.313725 
 
                  R-Square     Coeff Var      Root MSE    Compressibility Mean 
 
                  0.946434      7.382317      1.787100                24.20784 
 
       Source                      DF        SS        Mean Square    F Value    Pr > F 
 
       PS                           6     3029.655059      504.942510     158.10    <.0001 
       MC                           4      429.032254      107.258063      33.58    <.0001 
       PS*MC                       23      378.453079       16.454482       5.15    <.0001 
 
 
 
 
 
 
 
115 
 
Table B.5: ANOVA result of particle size and moisture effect on Hausner ratio of 
fractionated ground loblolly pine 
 
The GLM Procedure 
 
Dependent Variable: HR    
 
                                               Sum of 
       Source                      DF         Squares     Mean Square    F Value    Pr > F 
 
       Model                       33      1.38885502      0.04208652      38.91    <.0001 
 
       Error                       68      0.07354733      0.00108158 
 
       Corrected Total            101      1.46240235 
 
                       R-Square     Coeff Var      Root MSE       HR Mean 
 
                       0.949708      2.474156      0.032887      1.329235 
 
       Source                      DF        SS          Mean Square    F Value    Pr > F 
 
       PS                           6      1.07234157      0.17872359     165.24    <.0001 
       MC                           4      0.15379908      0.03844977      35.55    <.0001 
       PS*MC                       23      0.16271437      0.00707454       6.54    <.0001 
 
Table B.6: ANOVA result of particle size and moisture effect on porosity of fractionated 
ground loblolly pine 
 
The GLM Procedure 
 
Dependent Variable: Porosity   
                                               Sum of 
       Source                      DF         Squares     Mean Square    F Value    Pr > F 
 
       Model                       33      0.09110681      0.00276081    1003.67    <.0001 
 
       Error                       68      0.00018705      0.00000275 
 
       Corrected Total            101      0.09129386 
 
                      R-Square     Coeff Var      Root MSE    Porosity Mean 
 
                      0.997951      0.193844      0.001659         0.855599 
 
       Source                      DF          SS          Mean Square    F Value    Pr > F 
 
       PS                           6      0.07559100      0.01259850    4580.06    <.0001 
       MC                           4      0.01367591      0.00341898    1242.94    <.0001 
       PS*MC                       23      0.00183990      0.00008000      29.08    <.0001 
 
 
 
 
116 
 
Table B.7: ANOVA result of particle size and moisture effect on angle of internal friction of 
fractionated ground loblolly pine 
 
The GLM Procedure 
 
Dependent Variable: Internal_friction    
 
                                               Sum of 
       Source                      DF         Squares     Mean Square    F Value    Pr > F 
 
       Model                       33     4909.529588      148.773624      69.32    <.0001 
 
       Error                      476     1021.613333        2.146246 
 
       Corrected Total            509     5931.142922 
 
                 R-Square     Coeff Var      Root MSE    Internal_friction Mean 
 
                 0.827754      3.117284      1.465007                  46.99627 
 
       Source                      DF        SS          Mean Square    F Value    Pr > F 
 
       Particle_size                6     2380.074955      396.679159     184.82    <.0001 
       Moisture                     4     2191.393605      547.848401     255.26    <.0001 
       Particle_si*Moisture        23      338.061029       14.698306       6.85    <.0001 
 
Table B.8: ANOVA result of particle size and moisture effect on cohesion of fractionated 
ground loblolly pine 
 
The GLM Procedure 
 
Dependent Variable: Cohesion    
 
                                               Sum of 
       Source                      DF         Squares     Mean Square    F Value    Pr > F 
 
       Model                       33     16.79996855      0.50908996       4.07    <.0001 
 
       Error                      476     59.48413173      0.12496666 
 
       Corrected Total            509     76.28410028 
 
                      R-Square     Coeff Var      Root MSE    Cohesion Mean 
 
                      0.220229      50.26351      0.353506         0.703306 
 
       Source                      DF        SS            Mean Square    F Value    Pr > F 
 
       Particle_size                6     13.96265015      2.32710836      18.62    <.0001 
       Moisture                     4      1.33298185      0.33324546       2.67    0.0318 
       Particle_si*Moisture        23      1.50433655      0.06540594       0.52    0.9681 
 
 
 
 
 
 
117 
 
Table B.9-1: ANOVA result of particle size and moisture effect on angle of wall friction of 
fractionated ground loblolly pine using stainless steel 
 
The GLM Procedure 
 
Dependent Variable: Stainless    
                                               Sum of 
       Source                      DF         Squares     Mean Square    F Value    Pr > F 
 
       Model                       33     52568.53652      1592.98596     417.67    <.0001 
 
       Error                     2516      9595.99760         3.81399 
 
       Corrected Total           2549     62164.53412 
 
                     R-Square     Coeff Var      Root MSE    Stainless Mean 
 
                     0.845635      12.85727      1.952944          15.18941 
 
       Source                      DF        SS      Mean Square    F Value    Pr > F 
 
       Particle_size                6      3182.27183       530.37864     139.06    <.0001 
       Moisture                     4     46157.07183     11539.26796    3025.51    <.0001 
       Particle_si*Moisture        23      3229.19286       140.39969      36.81    <.0001 
 
Table B.9-2: ANOVA result of particle size and moisture effect on angle of wall friction of 
fractionated ground loblolly pine using mild steel 
 
The GLM Procedure 
Dependent Variable: Mildsteel   
 
                                               Sum of 
       Source                      DF         Squares     Mean Square    F Value    Pr > F 
 
       Model                       33     30789.45774       933.01387     350.22    <.0001 
 
       Error                     2516      6702.77707         2.66406 
 
       Corrected Total           2549     37492.23481 
 
                     R-Square     Coeff Var      Root MSE    Mildsteel Mean 
 
                     0.821222      10.70273      1.632195          15.25027 
 
       Source                      DF           SS          Mean Square    F Value    Pr > F 
 
       Particle_size                6       532.79849        88.79975      33.33    <.0001 
       Moisture                     4     28973.33199      7243.33300    2718.91    <.0001 
       Particle_si*Moisture        23      1283.32725        55.79684      20.94    <.0001 
 
 
 
 
 
 
 
 
118 
 
Table B.9-3: ANOVA result of particle size and moisture effect on angle of wall friction of 
fractionated ground loblolly pine using Tivar 88 surface 
 
The GLM Procedure 
 
Dependent Variable: TIVAR    
 
                                               Sum of 
       Source                      DF         Squares     Mean Square    F Value    Pr > F 
 
       Model                       33     4169.265400      126.341376      57.05    <.0001 
 
       Error                     2516     5572.281067        2.214738 
 
       Corrected Total           2549     9741.546467 
 
                       R-Square     Coeff Var      Root MSE    TIVAR Mean 
 
                       0.427988      11.65509      1.488200      12.76867 
 
       Source                      DF        SS       Mean Square    F Value    Pr > F 
 
       Particle_size                6     3206.808280      534.468047     241.32    <.0001 
       Moisture                     4      260.570614       65.142653      29.41    <.0001 
       Particle_si*Moisture        23      701.886506       30.516805      13.78    <.0001 
 
 
 
Table B.10: ANOVA result of particle size effect on volatile matter (% db) of fractionated 
ground loblolly pine  
 
The GLM Procedure 
 
Dependent Variable: matter 
 
                                               Sum of 
       Source                      DF         Squares     Mean Square    F Value    Pr > F 
 
       Model                        5     17.57471921      3.51494384       1.24    0.3502 
 
       Error                       12     34.04084058      2.83673671 
 
       Corrected Total             17     51.61555979 
 
                       R-Square     Coeff Var      Root MSE    matter Mean 
 
                       0.340493      1.964800      1.684261       85.72176 
 
       Source                      DF       SS      Mean Square    F Value    Pr > F 
 
       size                         5     17.57471921      3.51494384       1.24    0.3502 
 
 
 
 
 
 
 
 
119 
 
Table B.11: ANOVA result of particle size effect on energy content of fractionated ground 
loblolly pine  
 
The GLM Procedure 
 
Dependent Variable: energy_content 
 
                                               Sum of 
       Source                      DF         Squares     Mean Square    F Value    Pr > F 
 
       Model                        5      1.08365667      0.21673133       1.28    0.3361 
 
       Error                       12      2.03869333      0.16989111 
 
       Corrected Total             17      3.12235000 
 
                   R-Square     Coeff Var      Root MSE         Mean 
 
                   0.347064      2.214783      0.412178               18.61033 
 
       Source                      DF       SS       Mean Square    F Value    Pr > F 
 
       sample                       5      1.08365667      0.21673133       1.28    0.3361 
 
 
 
Table B.12: ANOVA result of particle size effect on ash content (% db) of fractionated 
ground loblolly pine  
 
                                        The GLM Procedure 
 
Dependent Variable: content 
 
                                               Sum of 
       Source                      DF         Squares     Mean Square    F Value    Pr > F 
 
       Model                        5     12.55626822      2.51125364     286.03    <.0001 
 
       Error                       12      0.10535626      0.00877969 
 
       Corrected Total             17     12.66162447 
 
                      R-Square     Coeff Var      Root MSE    content Mean 
 
                      0.991679      10.83524      0.093700        0.864771 
 
       Source                      DF       Type I SS     Mean Square    F Value    Pr > F 
 
       size                         5     12.55626822      2.51125364     286.03    <.0001 
 
 
 
 
 
 
 
120 
 
Table B.13: Effect of wall surface on angle of wall friction at 4.78% moisture level. 
Screen 
size (mm) 
Type of Wall Materials 
Stainless steel Mild steel Tivar 88 
0.05 12.30[b] ? 1.28 12.33[b] ?1.10 14.80[a] ?1.71 
0.25 9.83[c] ? 0.52 10.48[b] ? 0.45 13.61[a] ? 1.09 
0.50 9.45[c] ? 0.50 10.50[b] ? 0.39 12.48[a] ?0.87 
0.71 9.39[c] ? 0.49 10.54[b] ? 0.35 12.10[a] ? 0.98 
1.00 9.49[c] ? 0.50 10.81[b] ? 0.36 11.59[a] ? 0.87 
1.40 8.96[b] ? 0.38 10.76[a] ? 0.31 10.88[a] ? 0.96 
Raw 9.53[c] ? 0.53 10.55[b] ? 0.37 11.75[a] ? 0.90 
Superscripts shows comparison of means using Tukey test at ?< 0.05 significant level 
Values across the row with the same letter are not significantly different  
 
 
 
Table B.14: Effect of wall surface on angle of wall friction at 8.69%moisture level. 
Screen 
size (mm) 
Type of Wall Materials 
Stainless steel Mild steel Tivar 88 
0.05 14.9[b] ? 2.05 16.10[a] ? 2.63 15.54[a,b] ?2.25 
0.25 12.39[b] ? 1.27 13.11[a] ? 1.21 13.48[a] ?1.31 
0.50 11.24[c] ? 0.90 12.09[b] ? 0.72 12.87[a] ? 1.07 
0.71 12.72[a] ? 1.48 12.17[b] ? 0.71 12.32[a,b] ? 1.03 
1.00 11.44[b] ? 1.00 12.43[a] ? 0.76 11.72[b] ? 0.97 
1.40 10.82[c] ? 0.97 12.38[a] ? 0.59 11.47[b] ? 1.15 
Raw 10.92[c] ? 1.27 12.16[b] ? 0.92 14.07[a] ? 1.35 
Superscripts shows comparison of means using Tukey test at ?< 0.05 significant level 
Values across the row with the same letter are not significantly different  
 
 
 
 
 
121 
 
Table B.15: Effect of wall surface on angle of wall friction at 16.53%moisture level.  
Screen 
size (mm) 
Type of Wall Materials 
Stainless steel Mild steel Tivar 88 
0.05 17.14[a] ? 2.75 15.22[b] ? 1.72 14.52[b] ?1.79 
0.25 14.00[a] ? 1.54 14.29[a] ? 1.32 13.14[b] ? 1.28 
0.50 13.79[b] ? 1.43 15.07[a] ? 1.36 12.83[c] ? 1.12 
0.71 14.22[b] ? 1.47 15.31[a] ? 1.34 12.01[c] ? 1.05 
1.00 14.40[b] ? 1.38 15.01[a] ? 1.34 11.24[c] ? 0.99 
1.40 14.18[a] ? 1.31 14.22[a] ? 1.14 11.61[b] ? 1.02 
Raw 16.23[c] ? 2.21 14.53[b] ? 1.30 12.17[a] ? 1.30 
Superscripts shows comparison of means using Tukey test at ?< 0.05 significant level 
Values across the row with the same letter are not significantly different  
 
 
 
 Table B.16: Effect of wall surface on angle of wall friction at 22.21% moisture level.  
Screen 
size (mm) 
Type of Wall Materials 
Stainless steel Mild steel Tivar 88 
0.05 26.49[a] ? 4.61 21.38[b] ? 3.15 15.50[c] ? 2.64 
0.25 19.50[a] ? 2.64 18.12[b] ? 2.08 13.33[c] ? 1.70 
0.50 17.60[a] ? 1.96 18.18[a] ? 1.70 12.36[b] ? 1.35 
0.71 16.72[b] ? 1.73 17.42[a] ? 1.58 12.02[c] ? 1.58 
1.00 17.35[a] ? 1.83 17.99[a] ? 1.53 12.81[b] ? 1.89 
1.40 16.52[b] ? 1.65 18.00[a] ? 1.42 12.44[c] ? 1.74 
Raw 18.13[b] ? 1.85 19.04[a] ? 1.77 14.45[c] ? 2.28 
Superscripts shows comparison of means using Tukey test at ?< 0.05 significant level 
Values across the row with the same letter are not significantly different  
 
 
 
 
 
 
122 
 
 
Table B.17: Effect of wall surface on angle of wall friction at 25.53% moisture level.  
Screen 
size (mm) 
Type of Wall Materials 
Stainless steel Mild steel Tivar 88 
0.25 24.80[a] ? 3.96  22.56[b] ? 3.42 15.23[c] ? 2.46 
0.50 21.62[a] ? 2.80 19.52[b] ? 2.55 13.06[c] ? 1.64 
0.71 20.98[a] ? 2.58 19.73[b] ? 2.28 11.76[c] ? 1.47 
1.00 20.06[a] ? 2.51 18.87[b] ? 2.18 11.46[c] ? 1.40 
1.40 18.76[a] ? 2.05 18.30[a] ? 1.90 10.98[b] ? 1.32 
Raw 20.56[a] ? 2.54 19.39[b] ? 2.29 12.55[c] ? 1.58 
Superscripts shows comparison of means using Tukey test at ?< 0.05 significant level 
Values across the row with the same letter are not significantly different 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
123 
 
Appendix B: SAS codes for statistical analysis  
 
/*Importing files for physical properties*/ 
proc import datafile = 'C:\Users\ojo0002\Dropbox\Final_arrangement.xlsx' 
out = properties DBMS=EXCEL Replace; 
Getnames= yes; 
SCANTEXT=YES; 
USEDATE=YES; 
SCANTIME=YES; 
Range = 'physical$A1:H103'; 
Run; 
 
/*ANOVA test on physical properties using GLM*/ 
proc glm data = properties; 
class ps mc; 
model PD BD TD Compressibility HR Porosity= ps mc ps*mc; 
means ps mc ps*mc/tukey; 
run; 
 
/*ANOVA test of particle size effect on physical properties using GLM*/ 
proc glm data = properties; 
class ps mc; 
model PD BD TD Compressibility HR Porosity= ps; 
means ps/tukey; 
by mc; 
run; 
 
/*Data sorting for effect of Moisture content on physical properties*/ 
proc sort data = properties 
 Out = sortedproperties; 
 by ps; 
 run; 
 
/*ANOVA test of moisture content effect on physical properties using GLM*/ 
proc glm data = sortedproperties; 
class ps mc; 
model PD BD TD Compressibility HR Porosity= mc; 
means mc/tukey; 
by ps; 
run; 
 
/*Analysis for internal friction and cohesion*/ 
proc import datafile = 'C:\Users\ojo0002\Dropbox\Final_arrangement.xlsx' 
out = cohesion DBMS=EXCEL Replace; 
Getnames= yes; 
SCANTEXT=YES; 
USEDATE=YES; 
SCANTIME=YES; 
Range = 'Angleofinternalfriction$A1:d511'; 
Run; 
 
 
/*General ANOVA test on internal friction and cohesion*/ 
proc glm data = cohesion; 
class Particle_size Moisture; 
model internal_friction Cohesion = Particle_size|Moisture; 
124 
 
means Particle_size|Moisture/tukey; 
run;  
 
/*Effect of particle size on internal friction and cohesion*/ 
proc glm data = cohesion;  
class Particle_size Moisture; 
model internal_friction Cohesion = Particle_size; 
means Particle_size/tukey;  
by moisture; 
run;  
 
/*Sorting data for effect of moisture content*/ 
proc sort data = cohesion 
 Out = sortedcohesion; 
 by Particle_size; 
 run; 
 
/*Effect of moisture content on internal friction and cohesion*/  
proc glm data = sortedcohesion; 
class  Particle_size Moisture; 
model internal_friction Cohesion = Moisture; 
means moisture/tukey;  
by Particle_size; 
run;   
 
/*Analysis for wall friction*/ 
proc import datafile = 'C:\Users\ojo0002\Dropbox\Final_arrangement.xlsx' 
out = WF DBMS=EXCEL Replace; 
Getnames= yes; 
SCANTEXT=YES; 
USEDATE=YES; 
SCANTIME=YES; 
Range = 'Angleofwallfriction$A1:e2551'; 
Run; 
 
/*General ANOVA test on angle of wall friction*/ 
proc glm data = WF; 
class Particle_size Moisture; 
model Stainless Mildsteel TIVAR =Particle_size|Moisture; 
means Particle_size|Moisture/tukey; 
run;  
 
/*Effect of particle size on angle of wall friction*/ 
proc glm data = WF; 
class Particle_size Moisture;  
model Stainless Mildsteel TIVAR =Particle_size; 
means Particle_size/tukey; 
by Moisture; 
run;  
 
/*Sorting data for effect of moisture content on wall friction*/ 
proc sort data = WF 
Out = sortedWF; 
 by Particle_size; 
 run; 
proc print data = sortedWF;run;  
 
125 
 
/*Effect of moisture content on angle of wall friction*/ 
proc glm data = sortedWF; 
class Particle_size Moisture;  
model Stainless Mildsteel TIVAR =Moisture; 
means Moisture/tukey; 
by Particle_size; 
run;  
 
/*Effect of wall material on angle of wall friction*/ 
proc import datafile = 'C:\Users\ojo0002\Dropbox\Final_arrangement.xlsx' 
out = wall_type DBMS=EXCEL Replace; 
Getnames= yes; 
SCANTEXT=YES; 
USEDATE=YES; 
SCANTIME=YES; 
Range = 'MC4.78$A2:f1352'; 
Run; 
 
/*Sorting data for effect of wall material on wall friction*/ 
proc sort data = wall_type 
Out = sortedwall_type; 
 by Particle_size; 
 run; 
 
/*General ANOVA test on wall material*/ 
proc glm data = sortedwall_type;  
class Particle_size material; 
model  MC5 MC9 MC15 MC20 = material; 
means material/tukey; 
by Particle_size;  
run; 
 
/*Volatile matter*/ 
data volatile; 
input size matter; 
datalines; 
2.14 84.84118783 
2.14 85.15598639 
2.14 85.17072722 
1.54 84.83283142 
1.54 84.77222336 
1.54 85.13296634 
1.28 85.30450814 
1.28 84.72281068 
1.28 85.30450814 
0.97 85.72084866 
0.97 90.99627324 
0.97 85.70658378 
0.81 85.34423753 
0.81 84.87114629 
0.81 89.82996463 
0.15 84.97309511 
0.15 84.97309511 
0.15 85.33875314 
; 
run; 
proc glm data = volatile; 
126 
 
class size; 
model matter = size; 
means size/tukey; 
run; 
  
proc means data =volatile; 
var matter; 
class size; 
run; 
 
*Ash content of fraction; 
data ash; 
input size content; 
datalines; 
2.14 0.217727694 
2.14 0.326916507 
2.14 0.217080337 
1.54 0.217944338 
1.54 0.217511479 
1.54 0.218596866 
1.28 0.541742825 
1.28 0.677109678 
1.28 0.691328245 
0.97 0.426178823 
0.97 0.554948894 
0.97 0.391909849 
0.81 0.938467972 
0.81 0.92103963 
0.81 1.077430782 
0.15 2.45407148 
0.15 2.721530982 
0.15 2.754333398 
; run; 
proc glm data = ash; 
class size; 
model content = size; 
means size/tukey; 
run; 
  
proc means data =ash; 
var content; 
class size; 
run; 
 
/*Energy content*/ 
data energy; 
input sample energy_content; 
datalines; 
1.40 18.101 
1.40 18.514 
1.40 18.618 
1.00 18.614 
1.00 18.623 
1.00 18.798 
0.71 18.532 
0.71 18.663 
0.71 18.710 
127 
 
0.50 18.802 
0.50 17.149 
0.50 18.816 
0.25 18.639 
0.25 18.559 
0.25 18.710 
0.24 19.019 
0.24 19.081 
0.24 19.038 
; 
run; 
proc glm data = energy; 
class sample; 
model energy_content = sample; 
means sample/tukey; 
run;