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2019-07-01

Correlating Pressure, Fluidization Gas Velocities, andSolids Mass Correlating Pressure, Fluidization Gas Velocities, andSolids Mass

Flowrates in a High-PressureFluidized Bed Coal Feed System Flowrates in a High-PressureFluidized Bed Coal Feed System

Jacob Talailetalalelei Tuia Brigham Young University

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Correlating Pressure, Fluidization Gas Velocities, and

Solids Mass Flowrates in a High-Pressure

Fluidized Bed Coal Feed System

Jacob Tala’iletalalelei Tuia

A thesis submitted to the faculty of Brigham Young University

in partial fulfillment of the requirements for the degree of

Master of Science

Andrew R. Fry, Chair Dale R. Tree

Bradley C. Bundy

Department of Chemical Engineering

Brigham Young University

Copyright © 2019 Jacob Tala’iletalalelei Tuia

All Rights Reserved

ABSTRACT

Correlating Pressure, Fluidization Gas Velocities, and Solids Mass Flowrates in a High-Pressure

Fluidized Bed Coal Feed System

Jacob Tala’iletalalelei Tuia Department of Chemical Engineering, BYU

Master of Science

The goal of this thesis was to understand what parameters would be most impactful when delivering dry, pulverized coal in a dilute-phase, with a high-pressure feed-system to a pressurized oxy-combustion (POC) reactor. Many studies have conveyed materials in dense-phase plugs at high-pressure or in dilute-phase flows at atmospheric pressure. Very few studies have fluidized and conveyed materials in dilute-phase flows at high pressure, as we needed to. Additionally, studies which might have been applicable based upon system -pressure and -phase delivered findings that were empirically based and therefore not specifically applicable to non-similar systems.

220 different tests were ran using a bench-scale apparatus consisting of a hopper, connecting conveying pipes, and a filter point (representing the future reactor). The system was pressurized to 300 psi using CO2. Dry, pulverized coal with an average diameter of 50 microns and a bulk density of 800.9 kg/m3 was fluidized and conveyed with different combinations of fluidization inlet and fluidization outlet flowrates. Each specific flowrate combination was tested 3 to 5 times. The resulting coal flowrates were recorded and analyzed to see which flowrate combination delivered 13.6 kgs coal/hr and had the least variability between tests.

The fluidization inlet and outlet flowrates, coal moisture content, and system geometry were key parameters. In a 2-inch diameter hopper the fluidization inlet flowrate should be kept at 0.119 m/s or below to keep the fluidization regime within the hopper below the transition point to the bubbling fluidization regime. This was beneficial since less CO2 was needed by the system and smaller perturbations within the bed didn’t disrupt flow leaving the hopper. The fluidization outlet flowrate could still advance the fluidization regime within the hopper even if the fluidization inlet flowrate is kept at 0.119 m/s. For a ¼ inch diameter the outlet should be kept at 0.005 m/s or above. Additionally, the standard deviation in the measured coal flowrate decreased dramatically when flow of gas was allowed to exit through the top of the coal column (fluidization outlet). The standard deviation was 8.2 kg/hr with the fluidization outlet closed and 3.5 kg/hr with the fluidization outlet flowing to provide 0.005 m/s in the bed above the coal outlet. Coal should have a moisture content between 3% and 6% to ensure that electrostatic interactions between coal particles is kept to a minimum. Finally, these results were found for specific hopper and fluidization inlet and outlet diameters. If these diameters are changed then some calculation must be done for these results to be applicable to systems that are not like the one described later in this thesis.

Keywords: fluidized bed, dilute-phase, high pressure, oxy-combustion

ACKNOWLEDGEMENTS

I am grateful for the funding received from the United States Department of Energy, the

Brigham Young University Department of Chemical Engineering, and from Dr. Andrew R. Fry.

The funding made it possible for me to generate impactful research that also helped me grow as a

researcher and reporter. In addition, I am incredibly grateful for the guidance and encouragement

given to me from my incredibly knowledgeable and patient advisor Dr. Andrew R. Fry. Meetings

with him made big problems seem manageable and manageable problems seem solvable.

Support from Arlene Cleverly and Serena Jacobson was key to my being able to stay on top of

incoming equipment, and make sure that my wife and I had food on the table without needing to

worry over much. Finally, I am incredibly thankful to my wife for always encouraging me and

knowing how to help and push me to do better.

iv

TABLE OF CONTENTS

LIST OF TABLES ....................................................................................................................... viii

LIST OF FIGURES ....................................................................................................................... ix

1 Introduction ......................................................................................................................... 1

1.1 Background ...................................................................................................................... 2

1.1.1 Existing Technologies ............................................................................................... 3

1.1.2 Oxy-Combustion Opportunities ................................................................................ 6

2 Coal Feed System ............................................................................................................... 8

2.1 Technical Theory.............................................................................................................. 9

2.2 Fluidized Beds .................................................................................................................. 9

2.3 Fluidization Regimes...................................................................................................... 10

2.4 Loop Seals ...................................................................................................................... 19

3 Conveying Gas Parameters ............................................................................................... 22

3.1 Saltation Velocity ........................................................................................................... 22

3.2 Pickup Velocity .............................................................................................................. 26

4 Other Considerations for Conveying ................................................................................ 28

4.1 System Geometry ........................................................................................................... 28

4.2 Coal Type ....................................................................................................................... 30

v

5 Apparatus .......................................................................................................................... 33

5.1 Materials of Construction ............................................................................................... 35

5.2 System Adjustments ....................................................................................................... 40

5.3 System Fuel .................................................................................................................... 41

5.4 Intended Operating Regimes .......................................................................................... 41

5.5 Quantities of Interest ...................................................................................................... 43

5.6 Opto 22 ........................................................................................................................... 45

6 Method .............................................................................................................................. 48

7 Safety ................................................................................................................................ 53

8 Results ............................................................................................................................... 55

8.1 Coal Flow vs. Fluidization Flow .................................................................................... 55

8.2 Other Impacting Factors ................................................................................................. 68

8.2.1 Operating Regime Transitions ................................................................................ 68

8.2.2 Coal Moisture Content ............................................................................................ 72

8.2.3 Final Coal Distribution ........................................................................................... 74

8.2.4 Bed Debris .............................................................................................................. 75

8.2.5 Control Parameters.................................................................................................. 76

9 Conclusions ....................................................................................................................... 80

Nomenclature ................................................................................................................................ 85

vi

Appendix 1 Load Cell Calibration .......................................................................................... 86

Appendix 2 Load Cell Accuracy ............................................................................................. 89

Appendix 3 MFC Impact on Load Cell Readings................................................................... 92

Appendix 4 C = Closed Raw Data .......................................................................................... 93

Appendix 4.1 Summarized Raw Data ........................................................................................ 94

Appendix 4.2 C = Closed Raw Coal Loading/Movement Data ................................................. 95

Appendix 5 C = 0.77 kg CO2/hr Raw Data ............................................................................. 96

Appendix 5.1 C = 0.771 kg CO2/hr Summarized Raw Data ..................................................... 97

Appendix 5.2 C = 0.771 kg CO2/hr Raw Coal Loading/Movement Data ................................. 98

Appendix 6 C = 1.528 kg CO2/hr Raw Data ........................................................................... 99

Appendix 6.1 C = 1.538 kg CO2/hr Summarized Raw Data ................................................... 100

Appendix 6.2 C = 1.538 kg CO2/hr Raw Coal Loading/Movement Data ............................... 101

Appendix 7 E = 2.92 kg CO2/hr Raw Data ........................................................................... 102

Appendix 7.2 E = 2.92 kg CO2/hr Summarized Raw Data ...................................................... 103

Appendix 7.3 E = 2.92 kg CO2/hr Raw Coal Loading/Movement Data .................................. 104

Appendix 8 Sufco 2010 Raw Data ........................................................................................ 105

vii

Appendix 8.2 Sufco 2010 Summarized Raw Data .................................................................. 106

Appendix 8.3 Sufco 2010 Raw Coal Loading/Movement Data .............................................. 107

Appendix 9 Clean Hopper Raw Data .................................................................................... 108

Appendix 9.2 Clean Hopper Summarized Raw Data .............................................................. 109

Appendix 9.3 Clean Hopper Raw Coal Loading/Movement Data .......................................... 110

Appendix 10 Black Thunder Raw Data .................................................................................. 111

Appendix 10.1 Black Thunder Summarized Raw Data ......................................................... 112

Appendix 10.2 Black Thunder Raw Coal Loading/Movement Data ..................................... 113

Appendix 11 Coal Moisture Content Raw Data ..................................................................... 114

viii

LIST OF TABLES

Table 1. Opto 22 Control Scheme Modules.................................................................................. 46

Table 2. Test Matrix 1 – Varying A for 3 Different C’s ............................................................... 49

Table 3. Test Matrix 2 – Constant E ............................................................................................. 51

Table 4. Test Matrix 3 - Testing Different Sufco Coals ............................................................... 52

Table 5. Moisture Content of Different Coals .............................................................................. 72

Table 6. Opto Tuning Parameters ................................................................................................. 78

ix

LIST OF FIGURES

Figure 1. Fluidization Regime Changes in a 2” Diameter Vertical Hopper with 50-

micron (average diameter); 50 lb/ft3 (bulk density) coal and CO2 motivating gas ....................... 12

Figure 2. Turbulent Bed Transitional Behavior [15] .................................................................... 15

Figure 3. Fast Fluidization Transitional Behavior [15] ................................................................ 18

Figure 4. Regime Transitions as a Function of Multiple Parameters [15] .................................... 18

Figure 5. Example of a Circulating Fluidized Bed with a Loop Seal Circled [14]....................... 20

Figure 6. Experimental Apparatus ................................................................................................ 34

Figure 7. Physical Experimental Apparatus Setup ....................................................................... 35

Figure 8. Physical Opto 22 Setup ................................................................................................. 46

Figure 9. Test 50 Data A=4.23 kg/hr CO2; C=1.54 kg/hr CO2 ..................................................... 56

Figure 10. Test 70 Data A=2.63 kg/hr CO2; C=0.77 kg/hr CO2 ................................................. 57

Figure 11. Test 113 Data A=2.46 kg/hr CO2; C=Closed ............................................................. 58

Figure 12. Coal (Pittsburgh 8/Illinois 6) Flowrate (D) vs CO2 Flowrate (A) when

Fluidization Outlet (C) = 0 kg CO2/hr (Replicates) ...................................................................... 60

x

Figure 13. Coal (Pittsburgh 8/Illinois 6) Flowrate (D) vs CO2 Flowrate (A) when

Fluidization Outlet (C) = 0 kg CO2/hr (Aggregate with Error Bars) ............................................ 60

Figure 14. Coal (Pittsburgh 8) Flowrate (D) vs CO2 Flowrate (A) when

Fluidization Outlet (C) = 0.77 kg CO2/hr (Replicates) ................................................................. 61

Figure 15. Coal (Pittsburgh 8) Flowrate (D) vs CO2 Flowrate (A) when

Fluidization Outlet (C) = 0.77 kg CO2/hr (Aggregate with Error Bars) ....................................... 61

Figure 16. Coal (Pittsburgh 8/Illinois 6) Flowrate (D) vs CO2 Flowrate (A) when

Fluidization Outlet (C) = 1.54 kg CO2/hr (Replicates) ................................................................. 63

Figure 17. Coal (Pittsburgh 8/Illinois 6) Flowrate (D) vs CO2 Flowrate (A) when

Fluidization Outlet (C) = 1.54 kg CO2/hr (Aggregate with Error Bars) ....................................... 63

Figure 18. All Aggregates with Error Bars (Pittsburgh 8/Illinois 6) ............................................ 64

Figure 19. Relationship between conveying exit flowrate and overall coal mass

flowrate (Pittsburgh 8/Illinois 6) ................................................................................................... 65

Figure 20. Coal (Pittsburgh 8/Illinois 6) Flowrate (D) vs CO2 Flowrate (A) while

Hopper Conveying Exit (E) = 2.858 kg CO2/hr (Replicates) ....................................................... 66

Figure 21. Coal (Pittsburgh 8/Illinois 6) Flowrate (D) vs CO2 Flowrate (A) while

Hopper Conveying Exit (E) = 2.858 kg CO2/hr (Aggregate with Error Bars) ............................. 66

Figure 22. Sufco 2010 Coal Flowrate (D) vs CO2 Flowrate (A) when Fluidization

Outlet (C) = 0.77 kg CO2/hr (Aggregate with Error Bars) ........................................................... 67

xi

Figure 23. CFBB Fluidization Regimes when E varies - Zoomed In ........................................... 69

Figure 24. CFBB Fluidization Regimes when E = 2.858 kg CO2/hr - Zoomed In ....................... 70

Figure 25. CFBB Fluidization Regimes - Zoomed Out ................................................................ 71

Figure 26. Coal Moisture Content Impact, Coal Flowrate (D) vs CO2 Flowrate (A)

while Fluidization Outlet (C) = 0.77 kg CO2/hr ........................................................................... 73

Figure 27. Percentage of Coal Moved to Secondary Filter ........................................................... 75

Figure 28. Hopper Bottom Cleaning, Coal Flowrate (D) vs CO2 Flowrate (A)

when Fluidization Outlet (C) = 1.54 kg CO2/hr ........................................................................... 77

1

1 Introduction

The objective of the work summarized in this thesis was to generate 1) a new technology

in the form of a pressurized dry coal feed system, 2) a listing of uncertainty sources associated

with the new technology and 3) how to minimize those uncertainties. Fluidized bed technology

utilizing loop seal principles formed the basis of the pulverized coal feed system. Loop seals are

a component in circulating fluidized bed systems used to move particles from low to high

pressure areas in a system. To implement this technology, the behavior of fluidized coal moving

through a loop seal and then being conveyed at pressures up to 20 atm was analyzed. A bench-

scale apparatus representing a pressurized fluidized loop seal was constructed and operated. Data

in the form of coal mass flowrates, fluidization gas mass flowrates, location of moved coal, and

system pressure were collected, analyzed, and interpreted. A series of relationships were

developed that leveraged fluidized bed theory and correlations in the literature that will highlight

the operating conditions that will achieve the required coal injection rate at the desired system

pressure. Additional experiments were performed to generate data sets used to validate the

relationships. Finally, the relationships provided design constraints for an industrial-scale feed

system. The body of this thesis provides information detailing the need for this technology and

reviews our current understanding of particle transport in pressurized systems. Details of the

bench-scale apparatus used during this investigation are given and an overview of the

experimental matrix detailing how data was gathered come next. Data is summarized and

2

recommendations are offered for the demonstration reactor’s feed system based on the

relationships observed.

1.1 Background

As countries continue to industrialize, they require an ever-increasing amount of

electricity. In 2015, 40% of the electricity generated in the United States came from coal [1]. The

International Energy Agency (IEA) also estimates that 40% of the world’s electricity came from

coal [2]. Coal-fired power plants produce more CO2 per kWh than any other major energy

source. The Organization for Economic and Commercial Development (OECD) found that while

coal produced about 19% of its 35 member countries’ Total Primary Energy Supply (TPES), it

produced 33% of member countries CO2 emissions [3]. Concerned citizens, environmentalists,

and many scientists, have called for less reliance on coal. The real concern is that coal is a

significant contributor to global warming. Governments and organizations, like the

Environmental Protection Agency (EPA), are responding by working on, passing, and enforcing

regulations that limit coal-fired power plants’ emissions [4]. There are roughly four broad

‘categories’ of CO2–reducing technologies: bolt-on technologies, gasification, chemical looping,

and oxy-combustion. The Department of Energy (DOE) has a specific interest in the last three

categories and has allotted 28 million dollars to their study in the last 10 years. 10 million of

those dollars have gone toward researching advanced oxy-combustion reactors, with 1 million

going specifically toward developing a pressurized dry coal feed system for those reactors.

3

1.1.1 Existing Technologies

Two widely used bolt-on technologies are post-combustion CO2 scrubbers and cryogenic

capture units. CO2 scrubbers are “absorbers” that pass a scrubbing agent, which preferentially

binds to CO2, through a flue-gas stream. The scrubbing agent regenerates in a separate tower and

is recycled. Advantages of these absorber units include: 1) they are mature technologies that are

already available and 2) power plants can easily retrofit these technologies. The other bolt on

technology, cryogenic capture units, primarily consist of desublimation units that cool flue-gas

streams below the sublimation point of CO2. The solid CO2 is then separated from the remaining

gases and liquefied for utilization in enhanced oil recovery or for storage underground.

Advantages of these cryogenic carbon capture (CCC) units include being retrofittable onto

existing plants, highly efficient at removing a wide range of pollutants, and more efficient and

economically sound compared to scrubber processes [5]. Both technologies are candidates for

reducing CO2 emissions from coal-fired utility boilers. Bolt-on technologies result in reduced

efficiency and increased cost for the production of electricity. Although attractive as immediately

available technologies, both require enhanced greenfield design improvements to become

economically competitive.

Gasification is a mature process that centers around converting materials that contain

carbon into syngas; a mixture of CO, CO2, H2O, and H2. The conversion process consists of

exposing carbonaceous material, like coal, to steam and sub-stoichiometric amounts of oxygen,

at elevated temperatures and pressures. Chemical reactions occur producing syngas rather than

combustion products. Syngas produced using air and then combusted does not produce a

concentrated CO2 stream. Syngas produced using pure oxygen rather than air results in a highly

4

concentrated CO2 stream upon combustion. Purification and sequestration of this concentrated

CO2 stream is relatively easy compared to a stream of CO2 mixed with N2. This helps make

gasification appealing and qualifies it as a carbon capture technology. Additionally, if built, the

overall efficiency of a modern combined-cycle gasification plant should be around 50% while

the efficiency of a typical mature coal-fired plant is about 33%. One disadvantage of this system

is that it is prohibitively expensive in comparison to other energy generation plant designs.

Another disadvantage is that current gasification plant designs vary based on the carbon source

being used to produce the syngas, making adapting to any fluctuations in fuel cost and/or fuel

availability a problem. Finally, the plant availability, or percentage of time that a power plant is

actually producing power, for gasification plants is only about 50% compared to 95% for coal

fired power plants. [6]

Chemical looping combustion (CLC) is a process which attempts to solve many

emissions problems using an innovative two reactor system. One of the reactors seeks to address

one of the largest downsides to using pure oxygen for combustion, the expense of separating

oxygen from nitrogen. CLC overcomes this problem by providing oxygen for combustion via the

reduction of an oxygen-carrier inside of the ‘fuel-reactor’. Oxygen-carriers usually consist of a

solid, metal-based compound that, along with fuel, enters a ‘fuel reactor’ operated at elevated

temperatures. The fuel becomes oxidized by the oxygen-carrier and the now reduced oxygen-

carrier travels back to the ‘air reactor’ to be oxidized again. The ‘air reactor’, or the oxygen-

carrier regeneration reactor, always produces a hot spent-air stream and the ‘fuel reactor’, where

the fuel combusted, produces a stream of hot combustion products. Heat exchangers are

employed to take the excess heat in these two streams to produce steam which is used to drive a

5

steam turbine for power generation. The now cooler combustion products consist of CO2 and

H2O. These are easily separated, and the CO2 can be sequestered directly. Current problems with

this technology consist of 1) a need for robust oxygen carriers that can survive harsh reactor

environments, 2) the development of efficient techniques for circulating/managing multiple

solids in the form of ash, fuel, and carrier solids and 3) the efficient recovery of heat from the

process. [7]

Finally, what this thesis focuses on, oxy-combustion inside of a new reactor design that

operates at higher pressures. Some goals of all oxy-combustion processes include: 1) having no

need for post-combustion flue-gas stream scrubbers, 2) the ability to operate at higher reactor

temperatures allowing for higher reactor efficiencies, and 3) lower capital costs in greenfield

designs. Unfortunately, economics, uncertainty in future regulation, fuel supply availability, and

other factors make greenfield designs a difficult commercial option. As a result, companies have

focused research on retrofit options like those above, rather than in complete power plant

redesigns [8]. Another negative for current oxy-combustion systems is their lower overall plant

efficiencies compared to standard coal-fired power plants [9]. The parasitic load from pre-

reactor, pure-oxygen-production units and from post-reactor CO2-compression units, is the

acknowledged main cause of the reduced efficiency. Despite current challenges, the U.S. DOE

has granted research funds to see if a demonstration reactor that operates at both higher

temperatures and higher pressures might be environmentally safe and as profitable, or more so,

than current coal-fired power plants [10]. Higher temperatures would translate to higher

efficiencies. Higher pressures would 1) cause any CO2 produced to require significantly less

energy to compress to a supercritical state than atmospheric CO2, 2) cause more moisture to stay

6

in the vapor phase allowing for greater heat recovery, and 3) lower capital costs since equipment

could be made smaller.

1.1.2 Oxy-Combustion Opportunities

A new pressurized oxy-combustion reactor will be explored to solve many of the issues

encountered by previous large-scale atmospheric oxy-combustion designs. The critical design

focus areas include:

• Materials that can withstand larger heat fluxes,

• Advanced burner designs that can better control flame length and shape,

• New strategies for recovering heat from a smaller reactor

• A pressurized dry feed system.

The first three bullet points result from an oxidizer stream that no longer contains N2. The lack of

N2 as a diluent causes a significant increase in flame temperatures calling for reactor construction

materials with higher melting points. To prevent hot spots and distribute the thermal load

throughout the reactor requires burner designs that can adjust flame shape and length as needed.

Additionally, the lack of N2 in the gas inlet stream causes the reactor volume needed to decrease

drastically (on the order of 80%). Since normal combustion reactor designs cover every square

inch of external reactor surface area with heat exchanging equipment there is a need for a much-

improved heat exchange system. Even after those bullet points are overcome, the capacity factor

(the average amount of power produced by a plant divided by its rated peak output) of this coal-

7

fired oxy-combustion plant must be high, roughly above 62% [11], to justify its usage over other

coal-fired power plant designs. Finally, the challenges mentioned just now are not the subject of

this thesis. They were included for some additional insight into the demonstration reactor that

will be constructed for the Department of Energy. The last of the challenges listed above as a

critical focus area, a pressurized feed system that can continuously feed dry, pulverized-coal to

the reactor, is the issue that this thesis assists in solving.

8

2 Coal Feed System

Historically coal has been fed to combustion reactors in a variety of manners. Feed

systems operated at atmospheric pressure, while troublesome, are well understood. Existing high

pressure feed systems, such as coal water slurries [12], are less well understood and do not fit the

needs of the planned pressurized oxy-combustor. Slurry injection reduces the ability to tailor

flame length and shape and lowers reactor efficiency. Some companies, such as Shell, have

developed alternate high-pressure, dry coal feed systems but, due to protected intellectual

property, have declined to share their technology in detail. Additionally, these systems are

composed of multiple lock hoppers that are operated in tandem, resulting in a pseudo-continuous

feed system, which is likely insufficient to aerodynamically stabilize a flame. Lock hopper

systems are high-maintenance and are usually limited in operating pressure [12]. So while this

system is a viable candidate for the new reactor design, it is not the first choice. Other

organizations, such as the Gas Technology Institute (GTI), have also developed high pressure,

dense phase transport systems [13] that are again, proprietary. Since current technologies are

either inappropriate for our application or are proprietary, a fluidized bed concept was chosen for

the new reactor’s feed system. Fluidized beds are a mature technology which have been used for

many years to continuously convey and/or circulate particles at atmospheric pressures. This well

understood technology was used to design and build a high-pressure feed system that could

continuously and smoothly deliver dry pulverized coal.

9

2.1 Technical Theory

A bench scale apparatus was built to understand what sources of uncertainty exist and

how to control them. This bench scale apparatus was not used to feed the final demonstration

reactor. To understand the bench scale apparatus and its purpose, fundamental concepts which

the bench scale apparatus was based upon are examined. Then parameters, some affected by, and

others unaffected by operating at high pressures, will be examined. Note, some of the parameters

explained were not used in the bench-scale system but are mentioned here for convenience if

they are needed later in the system that will be used to feed the demonstration reactor.

2.2 Fluidized Beds

Industrial fluidized beds are designed for a variety of purposes including: rapid heat

exchange via the flow of ‘cool’ solid particles through a hot system or ‘hot’ solid particles

through a cold system, efficient macro-scale mixing of solid-liquid or solid-gas systems,

obtaining high mass transfer rates between a carrier gas and system particles, and the contained

transport of particles from one point to another. A fluidized bed is a layer of solid particles

through which a liquid or a gas passes through fast enough to at least periodically suspend

individual particles. When suspended the “frictional force between particle and fluid just

counterbalances the weight of the particles” and “the vertical component of the compressive

force between adjacent particles disappears” [14]. Once suspended, a fluidized bed of solids acts

like a liquid. As gas velocities increase, the bed displays different behaviors called fluidization

regimes. During the first few fluidization regimes particles will mainly remain in the bed if no

10

openings below the bed surface are available for egress. Once the particles reach higher velocity

regimes, they become entrained and start to leave the bed through the bed surface. These

particles, once out of the bed, are conveyed in either dilute phase flow or dense phase flow.

Dilute phase flow refers to the less energy efficient, but faster movement, of solids when fully

entrained in the flow of conveying gas. Dense phase flow refers to the more energy efficient but

slower movement of any solids in ‘slugs’, or plugs of material, by conveying gas through

sections of a system. Conveying coal particles via dense phase flow, while more energy efficient,

would not give us the ability to make fine adjustments to the coal distribution entering the

reactor. Consequently, dense phase flow was not tested during this research.

2.3 Fluidization Regimes

Fluidization regimes are categories of behavior exhibited by a fluidized bed based on the

incoming velocity of the carrier gas. With increasing gas velocity, the commonly acknowledged

regimes are as follows: 1) minimum fluidization, 2) bubbling bed, 3) slugging bed 4) turbulent

bed, 5) fast fluidization, and 6) pneumatic transport. Each of these regimes has a minimum

‘threshold velocity’. These threshold velocities are important when designing any fluidized bed.

For consistency’s sake the equations displayed later in this chapter all came from “Circulating

Fluidized Bed Boilers” written by Basu and Frasier [15]. Additionally, all of the threshold

velocities shown in Figure 1 where calculated using those same equations. The ‘High Pressure’

line shows the superficial velocities at which a bed, inside of a 2-inch diameter vertical pipe and

under 20 atmospheres worth of pressure, switches regimes. The ‘Atmospheric’ line shows the

same information but for a bed at atmospheric pressure. Some regimes, or behaviors, do not

11

present themselves (such as the pneumatic transport regime for a bed under atmospheric

pressure) due to a variety of factors.

To begin, a packed bed is a bed of particles that are all at rest on top of one another. It

takes very little incoming carrier gas to change a packed bed into an incipiently fluidized bed, as

can be seen by the nonexistent packed bed bars in Figure 1. Note, that some packed beds do

require a higher, therefore ‘visible’ on the graph, incoming superficial gas velocity depending

mainly on the density and size distribution of the particles.

A packed bed becomes an incipiently fluidized bed once the velocity of the incoming gas

exceeds the minimum fluidization velocity. The now fluidized bed will expand and start

behaving like a liquid. To illustrate, if the fluidized bed’s container is tilted the surface of the bed

will remain level with the ground. If the container develops a hole, the bed particles will exit the

container at higher velocities if the hole is closer to the bottom of the container due to

‘hydrostatic pressure’.

Knowing at what velocity a packed bed will become a fluidized bed is key. According to

Basu and Fraser [15] the minimum fluidization velocity, 𝑢𝑢𝑚𝑚𝑚𝑚, can be found using the following

equation:

𝑑𝑑𝑝𝑝 𝑈𝑈𝑚𝑚𝑚𝑚 𝜌𝜌𝑔𝑔𝜇𝜇

= [ 𝐶𝐶12 + 𝐶𝐶2 𝐴𝐴𝐴𝐴]0.5 − 𝐶𝐶1 ( 1 )

where

𝐴𝐴𝐴𝐴 = 𝜌𝜌𝑔𝑔 �𝜌𝜌𝑝𝑝−𝜌𝜌𝑔𝑔� 𝑔𝑔 𝑑𝑑𝑝𝑝3

𝜇𝜇2( 2 )

12

Figure 1. Fluidization Regime Changes in a 2” Diameter Vertical Hopper with 50-micron (average diameter); 50 lb/ft3 (bulk density) coal and CO2 motivating gas

𝑑𝑑𝑝𝑝 is the particle diameter, 𝜌𝜌𝑔𝑔 is the density of the incoming gas, 𝜇𝜇 is the viscosity of the

incoming gas, 𝜌𝜌𝑝𝑝 is the density of the bed particles, 𝑔𝑔 is gravity, 𝐶𝐶1 is a constant equal to 27.2,

and 𝐶𝐶2 is a constant equal to 0.0408 [16].

As the velocity of the incoming carrier gas increases bubbles will begin to form inside of

the incipiently fluidized bed. Again, like the transition from packed beds to minimally fluidized

beds, it does not take a large increase in carrier gas velocity to move into the next regime (refer

to the small area of the orange bars in comparison to the other fluidization regimes). These

bubbles form because so much gas is trying to make its way through the bed that slipping

between the particles in smooth streams is no longer possible. Basu and Fraser [15] identified the

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Atmospheric

High Pressure

Superficial Velocity (m/s)

Packed Bed

Minimum Fluidization

Bubbling Bed

Slugging Bed

Turbulent - Start

Turbulent - Stable

Pneumatic Transport

13

‘minimum bubbling’ velocity, 𝑈𝑈𝑚𝑚𝑚𝑚 , at which beds full of particles between 30 and 100

micrometers will begin to see bubbles:

𝑢𝑢𝑚𝑚𝑚𝑚 = 2.07.716 𝐹𝐹 𝑑𝑑𝑝𝑝𝜌𝜌𝑔𝑔0.06 𝜇𝜇0.347 ( 3 )

where F is the mass fraction of particles less than 45 micrometers in diameter, 𝑑𝑑𝑝𝑝 is the mean

particle diameter in meters, 𝜌𝜌𝑔𝑔 is the density of the carrier gas in 𝑘𝑘𝑔𝑔𝑚𝑚3, and 𝜇𝜇 is the gas viscosity in

𝑘𝑘𝑔𝑔𝑚𝑚 𝑠𝑠

.

The bubbles will continue to grow as the velocity of the incoming carrier gas keeps

increasing. If a bed is sufficiently narrow and the velocity of the carrier gas sufficiently high,

then bubbles may grow large enough to stretch all the way across a bed forming a slug. Slugs can

lift all the particles trapped above them for a time before the weight of the bed above becomes

too great and the slug effectively dissipates and travels through the particles above it.

Mathematically slugs will only form if two things are found to be true. First,

𝐷𝐷𝑚𝑚𝑚𝑚𝑏𝑏𝑏𝑏 > 0.6 𝐷𝐷 ( 4 )

[17] where 𝐷𝐷𝑚𝑚𝑚𝑚𝑏𝑏𝑏𝑏 is the maximum stable bubble diameter and D is the bed diameter. Second,

𝑈𝑈𝑡𝑡2

𝑔𝑔 𝐷𝐷> 0.123 ( 5 )

[18] where 𝑈𝑈𝑡𝑡 is the terminal velocity of the average bed particle. The equation to calculate 𝑈𝑈𝑡𝑡

depends on the Reynold’s number of the system and is given later in this paper (Equations 14 –

16). If both conditions are met then the minimum slugging velocity, 𝑈𝑈𝑠𝑠𝑠𝑠, is found using

14

𝑈𝑈𝑠𝑠𝑠𝑠 = 𝑈𝑈𝑚𝑚𝑚𝑚 + 0.07 (𝑔𝑔 𝐷𝐷)0.5. ( 6 )

[19] If a bed is not circular then, for Equation 6 specifically, we adjust D to be

𝐷𝐷 = 4 (𝑏𝑏𝑎𝑎𝑎𝑎𝑏𝑏 𝑜𝑜𝑚𝑚 𝑠𝑠ℎ𝑏𝑏𝑝𝑝𝑎𝑎)(𝑝𝑝𝑎𝑎𝑎𝑎𝑝𝑝𝑚𝑚𝑎𝑎𝑡𝑡𝑎𝑎𝑎𝑎 𝑜𝑜𝑚𝑚 𝑠𝑠ℎ𝑏𝑏𝑝𝑝𝑎𝑎)

( 7 )

Note, slugging is usually both undesirable and hard to avoid. See how in Figure 1 the slugging

bed regime is the largest part of the Atmospheric line. Contrast that with how the slugging bed

regime’s portion is significantly reduced in size on the High Pressure line. If avoiding slugging is

desired operating at a higher pressure can be beneficial.

As the incoming carrier gas velocity increases, bubbles, and sometimes then slugs, will

form. Further increases in incoming carrier gas velocity will eventually cause bubbles to rapidly

cycle between coalescing and breaking up. If slugs had been forming, they will no longer form

due to the gas velocity being too high. Instead they will also revert to bubbles which will again,

rapidly coalesce and break up. The bed will expand even more than it did when it first became

fluidized and the surface of the bed will be increasingly less clear as activity at, and just

underneath the surface, becomes more and more violent. This rapidly changing bed will have

increasingly large pressure fluctuations within itself as the carrier gas velocity increases. At some

point the pressure fluctuations will peak and the carrier gas velocity that this occurs at is referred

to as 𝑢𝑢𝑐𝑐. Refer to Figure 2. This is the beginning of the transition from a bubbling, or slugging

bed, to a stable turbulent bed. A stable turbulent bed is fully realized when 𝑢𝑢𝑘𝑘 is reached. 𝑢𝑢𝑘𝑘

refers to the point where the decreasing pressure fluctuations occurring after 𝑢𝑢𝑐𝑐 level out.

15

Figure 2. Turbulent Bed Transitional Behavior [15]

Equations from [20] for 𝑢𝑢𝑐𝑐 and 𝑢𝑢𝑘𝑘 are given below.

𝑢𝑢𝑐𝑐 𝑑𝑑𝑝𝑝 𝜌𝜌𝑔𝑔𝜇𝜇

= 0.936 𝐴𝐴𝐴𝐴0.472 ( 8 )

𝑢𝑢𝑘𝑘 𝑑𝑑𝑝𝑝 𝜌𝜌𝑔𝑔𝜇𝜇

= 1.46 𝐴𝐴𝐴𝐴0.472 (𝐴𝐴𝐴𝐴 < 104) ( 9 )

𝑢𝑢𝑘𝑘 𝑑𝑑𝑝𝑝 𝜌𝜌𝑔𝑔𝜇𝜇

= 1.41 𝐴𝐴𝐴𝐴0.56 (𝐴𝐴𝐴𝐴 > 104) ( 10 )

Note, the 𝐴𝐴𝐴𝐴 used in Equations 8, 9, and 10 is the Archimedes number defined in Equation 2. In

Figure 1 note the difference between the size of the slugging, turbulent – start, and turbulent –

16

stable bars in the Atmospheric and High-Pressure lines. At higher pressures it is significantly

harder for bubbles to grow large enough to form slugs and the rapid break up and coalescence of

bubbles is hindered. Working at higher pressures should significantly impact whether certain

regimes are seen at all and how long those regimes are seen as incoming carrier gas velocity

increases.

Fast fluidized behavior is observed between turbulent behavior and pneumatic transport

behavior. Fast fluidized behavior cannot be seen or attained unless a bed is above the ‘transport

velocity’, 𝑢𝑢𝑡𝑡𝑎𝑎.

𝑢𝑢𝑡𝑡𝑎𝑎 = 1.45 𝜇𝜇𝜌𝜌𝑔𝑔 𝑑𝑑𝑝𝑝

𝐴𝐴𝐴𝐴0.484 20 < 𝐴𝐴𝐴𝐴 < 50,000 ( 11 )

Note here that the transport velocity is a threshold velocity for a given bed. Above the transport

velocity the bed will empty in some time period A. Below the transport velocity the bed will

empty in some time period B which is much greater in magnitude than time period A.

To cause fast fluidized behavior in a bed rather than skip directly to seeing pneumatic

transport behavior two main actions can be taken. First, after attaining pneumatic transport

velocity in the bed slowly increase the feed rate of solids to the bed. At some point single

particles can be observed to slip into the wake of other upwards traveling particles and due to the

reduced upward buoyant gas force, the first set of particles will fall and form clusters with the

second set of particles. These clusters will not remain for long but be torn apart by collisions

with other particle clusters and by the upward buoyant force of the carrier gas. If the solids feed

rate is increased the pressure drop across the bed will start to increase. At the ‘choking velocity’,

𝑢𝑢𝑐𝑐ℎ, the buoyant force of the gas will no longer be able to transport ever larger clusters and the

17

bed will enter the captive stages again. The choking velocity can be found by simultaneously

solving:

𝑈𝑈𝑐𝑐ℎ𝜖𝜖𝑐𝑐

= 𝑈𝑈𝑡𝑡 + �2 𝑔𝑔 𝐷𝐷 �𝜖𝜖𝑐𝑐−4.7−1� 𝜌𝜌𝑝𝑝2.2

6.81𝑏𝑏105 𝜌𝜌𝑔𝑔2.2 �0.5

( 12 )

𝐺𝐺𝑠𝑠 = (𝑈𝑈𝑐𝑐ℎ − 𝑈𝑈𝑡𝑡) (1− 𝜖𝜖𝑐𝑐) 𝜌𝜌𝑝𝑝 𝐷𝐷 < 0.3 𝑚𝑚 ( 13 )

where 𝜖𝜖𝑐𝑐 is the voidage at choking and 𝐺𝐺𝑠𝑠 is the solid circulation rate. Now that choking velocity

and transport velocity have both been introduced refer to Figure 3 below to better understand the

relationship between both velocities, captive stage behaviors, fast fluidization, and pneumatic

transport.

The second method for attaining fast fluidization behavior is to get above the pneumatic

transport velocity by a good margin and then slowly decrease the incoming carrier gas flowrate.

Fast fluidization behavior cannot always be seen depending on the average diameter, shape, and

density of the particles being transported along with the viscosity of the carrier gas and the size

of the column. Refer to Figure 4 to get a better idea of how these factorscan affect whether or not

one will see fast fluidization along with some of the other regimes. As a quick illustration: If you

increase the tube size you descend the y-axis of Figure 4. If you do not want to have slugging

occur in your fluidized bed, then increase the tube size.

Pneumatic transport behavior is simple. Once the incoming carrier gas has risen above

the terminal velocity and the solids feed rate is not above Line C in Figure 3 the bed will exhibit

pneumatic transport behavior. Particles will be entrained mostly as single particles and the bed

18

will empty within a finite amount of time if solids are not replenished. The faster the incoming

gas, the faster the bed will empty. The terminal velocity for spherical particles, 𝑈𝑈𝑡𝑡 is found using

Figure 3. Fast Fluidization Transitional Behavior [15]

Figure 4. Regime Transitions as a Function of Multiple Parameters [15]

19

𝑑𝑑𝑝𝑝 𝑈𝑈𝑡𝑡 𝜌𝜌𝑔𝑔𝜇𝜇

= 𝐴𝐴𝑎𝑎18

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑒𝑒′𝑠𝑠 𝐿𝐿𝐿𝐿𝐿𝐿 0 < 𝑅𝑅𝑒𝑒 < 0.4 ( 14 )

𝑑𝑑𝑝𝑝 𝑈𝑈𝑡𝑡 𝜌𝜌𝑔𝑔𝜇𝜇

= � 𝐴𝐴𝑎𝑎7.5

�0.666

𝐼𝐼𝐼𝐼𝑆𝑆𝑒𝑒𝐴𝐴𝑚𝑚𝑒𝑒𝑑𝑑𝐼𝐼𝐿𝐿𝑆𝑆𝑒𝑒 𝐿𝐿𝐿𝐿𝐿𝐿 0.4 < 𝑅𝑅𝑒𝑒 < 500 ( 15 )

𝑑𝑑𝑝𝑝 𝑈𝑈𝑡𝑡 𝜌𝜌𝑔𝑔𝜇𝜇

= � 𝐴𝐴𝑎𝑎0.33

�0.5

𝑁𝑁𝑒𝑒𝐿𝐿𝑆𝑆𝑆𝑆𝐼𝐼′𝑠𝑠 𝐿𝐿𝐿𝐿𝐿𝐿 500 < 𝑅𝑅𝑒𝑒. ( 16 )

The Atmospheric line in Figure 1 is not shown to have reached pneumatic transport within the

bounds of the graph. The High-Pressure line in Figure 1 does reach pneumatic transport and

stays in that regime thereafter. As the superficial velocity increases the time it takes particles to

arrive at their destination will decrease. Corrections for non-spherical particles exist but are not

covered here. Please refer to Appendix 1, pg 300 of Circulating Fluidized Bed Boilers [15].

2.4 Loop Seals

Loop seals are simple non-mechanical “valves”, often used in circulating fluidized beds,

which are well understood, robust, simple to construct, and inexpensive [21]. Generally,

engineers use loop seals when temperature or flowrate limitations rule out the use of a

mechanical valve. The purpose of a loop seal is to create a controlled blockage that allows an

area of high pressure to form on one side of the block. This high-pressure area, in conjunction

with carefully placed fluidization ports, causes circulation in the system.

By design two different types of behavior, or fluidization regimes, are present, one within

the loop seal and one directly after it. The following is an illustration of how a loop seal might be

20

used and references Figure 5. Within the loop seal, the circled portion of Figure 5, fluidization

ports inject

Figure 5. Example of a Circulating Fluidized Bed with a Loop Seal Circled [14]

gas at a velocity which will minimally fluidize the bed above it. This fluidized bed will then, due

to a pressure gradient within the system, be pushed over the edge of a weir inside the seal (Point

8 in Figure 5) and enter a region where different fluidization ports operate at a different, higher

21

velocity (Point 1). The higher velocity gas entering can do several things depending on how fast

it is entering. Regardless, the loop seal has done its job and allowed for particles to move from an

area of low pressure where particles are in one fluidization regime to a different area with a

higher pressure where particles are in a different fluidization regime.

22

3 Conveying Gas Parameters

It is clear from the discussion of fluidization regimes that the flowrate of the incoming

carrier gas is key to the proper operation of any fluidized bed. Operating a fluidized bed that is

not at atmospheric pressure but significantly higher, causes the density of the fluidizing gas to

increase. Additional, non-fluidization regime ‘gas parameters’ which were significant

considerations for the bench scale system and will impact the scaled-up system included saltation

velocity and pickup/entrainment velocity. In the literature, both the saltation and pickup

velocities have a variety of definitions. For this thesis the saltation velocity is the velocity at

which there is a minimum pressure drop for a given solids flow rate [22] and the pickup velocity

is the velocity at which coal particles that are initially at rest begin to roll/slide along the pipe

bottom or become entrained in the flow of CO2 [23, 24].

3.1 Saltation Velocity

The saltation velocity creates a condition where particles begin to fall out of entrainment

and settle at the bottom of the conveying channel. At first, as particles settle, the pressure drop in

the system will decrease. As the layer of particles on the bottom of the channel thickens ‘waves’

23

of particles can begin to form and travel down the length of the conveying line causing

increasing pressure pulses in the system. This is undesirable. Controlling the amount of coal

traveling down the pipe in each wave is incredibly hard and unpredictable system pressure

changes are bad. The saltation velocity, therefore, provides a minimum carrier gas velocity

below which we will not operate in the conveying sections of the feed system.

Jones et al. [25] examined the historical development of numerous correlations and

compared 8 of the more well-known saltation prediction correlations:

- Thomas 1962 RMS – 44% [26]

- Doig and Roper 1963 RMS – 90% [27]

- Zenz 1964 RMS – 54% [28]

- Rose and Duckworth 1969 RMS – 78% [29]

- Rizk 1973 RMS – 60% [30]

- Matsumoto et al I 1974 RMS – 60% [31]

- Matsumoto et al II 1975 RMS – 53% [32]

- Mewing 1976 RMS – 50%

Each correlation was evaluated by comparing the predicted saltation velocity to the measured

saltation velocity from 390 data sets gathered from various researchers [25]. Two conclusions

from this study were:

24

1) Thomas et al. had the lowest root mean square (RMS) relative error of about 44%

which made it the initial ‘recommended’ candidate for design purposes [25]. Thomas et

al.’s low RMS was likely due to their using a saltation mechanism as their correlation’s

theoretical foundation.

2) Both correlations from Matsumoto et al. [31, 32] were deemed the most accurate at

scaling up gathered data since very little accuracy was ‘sacrificed’ during scaling. This

was likely due to Matsumoto basing his correlations on dimensional analysis.

A paper developed by Geldart et al. [22] gave a separate viewpoint and conclusion.

Geldart et al. [22] considered what effects pressures up to 1200 psi, would have on the saltation

velocity when conveying fine coal. The steady and reliable conveying of fine coal at 300 psi is

what the current research project is trying to accomplish so this paper was of special interest. In

the paper Geldart et al. [22] compared multiple correlations and his own individually developed

correlation against data he had personally taken. He found that the Thomas et al. [26] and

Matsumoto [32] correlations were ‘generally too low’ in their predictions while the Zenz [28]

correlation was usually too high in its predictions. Geldart’s personal correlation, and that of

Rizk, were in good agreement with the empirically determined saltation values (right around

15% RMS relative error for both). For the purposes of this project, the Rizk and Geldart

correlations will be used to predict the saltation velocity since they were more accurate at

elevated pressures. The Rizk and Geldart correlations are Equation 17, Equation 18, and

Equation 19, respectively. A nomenclature defining variables is at the end of the thesis.

25

The correlation developed by Rizk for finding the saltation velocity, 𝑢𝑢𝑠𝑠, is given in

Equation 17:

𝑢𝑢𝑠𝑠 = �4 𝑀𝑀𝑠𝑠 10𝑎𝑎 𝑔𝑔𝑏𝑏2 𝐷𝐷−2+

𝑏𝑏2

𝜋𝜋 𝜌𝜌𝑔𝑔�

1𝑏𝑏+1

( 17 )

Where 𝑀𝑀𝑠𝑠 is the solids mass flowrate and the constants a and b are found by inputting the mean

particle size (surface area/volume) in Equation 18:

𝐿𝐿 = 1440 𝑑𝑑𝑚𝑚𝑎𝑎𝑏𝑏𝑚𝑚 + 1.96 𝑏𝑏 = 1100 𝑑𝑑𝑚𝑚𝑎𝑎𝑏𝑏𝑚𝑚 + 2.5 ( 18 )

Geldart and Ling developed a correlation for finding the total pressure drop required to

move fine coal at high pressures and then differentiated the correlation with respect to the

superficial gas velocity. It is useful to remember here that as velocity decreases in a conveying

pipe the pressure drop decreases to a minimum upon which further decreases in velocity cause an

increase in pressure drop. The velocity at which the minimum pressure drop is found is the

saltation velocity. Therefore when dΔ𝑃𝑃𝑡𝑡𝑑𝑑𝑢𝑢

= 0 the superficial velocity, 𝑢𝑢, in Equation 19 is equal to

the saltation velocity, 𝑢𝑢𝑠𝑠.

26

𝑑𝑑 Δ𝑃𝑃𝑡𝑡𝑑𝑑𝑢𝑢

= (2 𝐺𝐺𝑠𝑠) + �0.2765 𝜌𝜌𝑔𝑔0.75𝑢𝑢0.75𝜇𝜇𝑔𝑔075 �𝐿𝐿𝐷𝐷�1.25

� − �𝐾𝐾 𝐿𝐿 �𝐺𝐺𝑠𝑠𝐷𝐷�𝑚𝑚

�𝜇𝜇𝑔𝑔𝜌𝜌𝑔𝑔�0.4

1𝑢𝑢2� −

�𝐺𝐺𝑠𝑠 𝑔𝑔 𝐻𝐻𝑢𝑢2

+ 𝑚𝑚 𝐺𝐺𝑠𝑠2� ( 19 )

The superficial velocity used in Equation 19 is found by rearranging Equation 20 and solving for

𝑢𝑢. 𝑣𝑣𝑠𝑠 is the particle velocity, 𝑑𝑑𝑝𝑝 is the particle diameter and 𝜌𝜌𝑝𝑝 is the density of the particle.

𝑣𝑣𝑠𝑠 = 𝑢𝑢�1 − 0.0638 𝑑𝑑𝑝𝑝0.3 𝜌𝜌𝑝𝑝0.5 � ( 20 )

With these more accurate correlations the carrier gas velocities at which the system can be run at

will have a set lower bound, below which pipe blockages and undesirable loading distributions

are expected to occur.

3.2 Pickup Velocity

Just as there is a saltation velocity below which particles begin to deposit along the length of

a pipe there is a higher velocity which is required to pick up particles initially at rest called the

pickup velocity. Several parameters affect the pickup velocity. Cabrejos et al. [33] found the

pickup velocity to be proportional to: 𝜌𝜌𝑝𝑝34 , 𝑑𝑑𝑝𝑝

12 , 𝜌𝜌𝑔𝑔

−12 , 𝐷𝐷14 , and 𝜇𝜇𝑔𝑔 (the gas viscosity, 𝜇𝜇𝑔𝑔, has a

minimal impact). Knowing how the pickup velocity is related to these parameters gives bed

27

designers a better handle on the stability and efficiency of the system. The pickup velocity

therefore was a key parameter when looking for the pipe diameter and carrier gas velocities to

initially test at.

28

4 Other Considerations for Conveying

Dense-phase flow occurs when operating at velocities below the saltation velocity, the

velocity at which particles begin to fall out of entrainment. Dilute phase flow, or lean phase flow,

occurs when operating above the saltation velocity and all particles being conveyed are

suspended within the conveying gas. To design and efficiently operate a dilute-phase-conveying

high-pressure fluidized bed many papers were examined. Many of these papers covered dilute-

phase atmospheric systems but their contents were included in the previous sections of this

thesis. Even more of the examined papers were written about dense-phase high pressure systems.

Despite being written about dense-phase, and not dilute phase, systems, some of these papers

were found containing pertinent information. This information includes the broad categories of

system geometry and coal type. Within these broad categories there are additional ‘sub-

parameters’ that will be examined, including inclination angle and coal moisture content.

4.1 System Geometry

Fluidized beds operate best with minimal piping and/or bends. The amount of piping and

number/geometry of bends significantly impact the surface wear, possibility of clogging, and

pressure drop throughout a system.

29

Several authors developed correlations for bends and piping that cannot be eliminated. Geldart

and Ling’s correlation, made for dense phase conveying, strives to account for pressure loss due

to acceleration from rest, gas/pipe friction, solids/wall friction, any vertical heights in the system,

and bends of radius 0.3 m or more [34]. Geldart and Ling note that in dense phase flow the

solids/wall friction controls energy loss and the predicted pressure drop due to solids is related to

the inverse of the superficial velocity. They note that in dilute-phase flow the energy of the

particles is controlled by the gas velocity and pressure drop due to solids is directly related to

superficial gas velocity [34]. Another set of equations, gathered/developed by Zhou et al., also

looked at gas/pipe friction, solids/wall friction, and pressure drop due to bends [35]. Conclusions

by Zhou et al. that were still applicable to the bench scale system, and will be applicable to the

scaled up system, included that 1) as coal mean particle size decreases so does the pressure drop

across the system and 2) “solids-to-gas mass flow ratio and mean particle size have no obvious

effect on the friction factor.” [35]. In summary, correlations and papers developed for dense-

phase high-pressure conveying still hold general principles that apply to the proposed dilute-

phase high-pressure scaled up system. They support that pressure drop is controlled by the

superficial gas velocity and that the mean coal particle size will be a determining factor in the

pressure drop due to solids. These general principles, and all others discussed hereafter, will

form a fundamental basis for scaling up the bench scale system.

To minimize the amount of piping and number of bends required in a design horizontal

pipes can be inclined. As pipes are inclined, the pressure drop across the system steadily

increases until a certain angle is reached, after which the system pressure drop decreases. If

systems are operated with their pipes inclined at the system’s critical inclination angle, termed by

30

Hong et. al., they will receive energy efficiency gains [36]. Hong et al. examined the effect that

the angle of pipe inclination had on the in-system pressure gradient. A pressure gradient occurs

inside of pipes due to two main forces: 1) the gravitational force, dominant in horizontal pipes,

and 2) sliding bed frictional forces, dominant in vertical pipes. Vertical pipe pressure gradients

are usually higher than those in horizontal pipes. In horizontal pipes, it was observed that

pressure gradients would quickly increase as the angle of inclination increased between 0° and

60° [36]. Hong et al. found that somewhere between 60° and 90° pressure gradients began

decreasing as inclination angle increased (although they never got below the horizontal pressure

gradient). The max pressure gradient for the system examined by Hong et al. occurred at

approximately 60°. Although 60° was the critical inclination angle for Hong et al.’s system, it

was determined that a more general rule of thumb was needed. The lower the solids flow rate,

and therefore the lower the solids loading ratio, the higher the critical inclination angle. Based

upon published critical angles the system being designed is expected to have a critical inclination

angle somewhere between 65° and 85° [15]. Although the bench-scale apparatus that is

described later in this thesis did not incorporate any inclined angles, the feed system for the

demonstration reactor may in the future, especially if dense phase flow is desired and the feed

system is located at a lower elevation relative to the feed point on the reactor.

4.2 Coal Type

A significant consideration in the design of a fluidized bed system is whether a material

can be conveyed in dense-phase flow or dilute-phase flow. Dense-phase flow occurs when

operating at velocities below the saltation velocity, the velocity at which particles begin to fall

31

out of entrainment. Particles which cease to be fully entrained will begin to form ‘slugs’ while

still being conveyed along the pipe. This conveying method can be desirable as it takes less

energy to operate at lower carrier gas inlet velocities and wear on the pipe wall decreases.

Whether dense-phase conveying is possible was previously predicted using the median particle

size and density. Deng et al. convincingly showed that mean particle size and the particle size

distribution are better deterministic factors [37]. Their tests showed that some materials were not

able to be conveyed in dense-phase flow even though correlations based on the particle size and

density suggested they should be. Similarly, materials which should not have been able to be

conveyed in dense-phase flow based upon median particle size and density, were conveyed in

dense-phase flow. Deng et al. [37] grouped materials first by their mean particle size and then by

their particle size distributions and a pattern emerged that fit the data. Fine powders (D50 < 70

micron), or materials that had a high number of fines in them, could be conveyed in fluid-like

dense-phase flow (likely due to air retentiveness). If low-velocity slug flow was desired, then a

narrow size distribution (D90/D10 < 2.5) was required. Materials with a small number of fines,

those that didn’t fit either of the other two criterium, required high gas inlet velocities to move

and could not be conveyed below their saltation velocity. These coarse materials had to be

conveyed in dilute-phase flow.

Another significant consideration is the moisture content of a coal. Liang et al. found that

in general, the flowability of a coal decreases as moisture content increases. More specifically he

and others found that the mass flow rate decreases with increasing moisture content in the range

from 3.24% to 8.18% [38]. From the same report Liang et al. also notes that the pressure drop

across the system increases as the moisture content increases [38]. These conclusions are most

32

likely due to the cohesive forces that develop between large and small particle agglomerations.

Particle agglomerations are created when there is enough moisture present that surface tension

draws particles together. In a different paper Liang et al. found that if moisture content and

operating parameters were kept constant then flowability increased as particle size decreased

[39]. Additionally, if moisture content got below 1%, conveying stability decreased rather than

increased [39]. Liang et al. explained these last two points by examining the electrostatic charge

that particles pick up during conveying. If too little moisture was present then the electrostatic

charge of a particle would dominate whether the particle formed agglomerations, stuck to the

wall, or interacted with other particle trajectories strangely. As moisture content increased above

1% a particle’s electrostatic charge would begin to move more easily across the particle in

general, from one particle to another, and from one particle to the wall. This meant that charge

stopped being the dominating force while moisture content had not yet reached a point where

cohesive forces became a problem. From about 6% moisture content and onwards cohesive

forces began to dominate how particles would interact instead. In summary, coal flowability is

maximized when particles are fine and they have an external moisture content between 1% and

8%.

33

5 Apparatus

An experimental system was developed that allowed operators to determine the effects of

system pressure (300 psi) on fluidization inlet/outlet flowrates and conveying line velocity. With

the system pressurized to 300 psi different fluidization inlet and outlet flowrate combinations can

be tested to characterize pressure fluctuations occurring during the conveying process, the rate

coal can be transported from the hopper to the primary filter point, and the distribution of coal

between the primary/secondary filter points. From this information operators may understand 1)

the fluidization regime behavior occurring in the hopper and 2) the general correlation between

coal mass flowrate and fluidization inlet/outlet flowrates at high pressure. The apparatus, shown

in Figure 6, was built by Jacob Tuia and Landon Nutall.

Note that in Figure 6 there are five flowrates that are of special interest throughout the

paper that for the sake of convenience have been assigned alphabetic designations.

- Hopper Fluidization Inlet (A)

- Conveying Line Fluidization Inlet (B)

- Hopper Fluidization Outlet (C)

- System Exit Coal Flowrate (D)

- Hopper Exit to Conveying Line (E)

34

Figure 6. Experimental Apparatus

35

Figure 7. Physical Experimental Apparatus Setup

5.1 Materials of Construction

The primary piece of equipment within the apparatus was the hopper. It consisted of a 2-

inch diameter, 1.5-foot-tall piece of Schedule 80 carbon steel pipe with NPT threads on both

ends. It was placed vertically in order to act as a vessel which could be filled with coal.

At the bottom of the hopper were a series of fittings consisting of a 2-inch diameter tee, a

2-inch diameter nipple, a 2-inch to 1-inch diameter bell reducer, a 1-inch diameter nipple, and a

1-inch to ¼-inch diameter bell reducer. The tee was made of Class 3000 low temperature steel

36

with FNPT threads on both ends (operating pressure: 3,000 psi). The nipple was Schedule 40

galvanized steel with MNPT threads on both ends (operating pressure: 500 psi). Both bell

reducers were made of Class 300 malleable iron and had FNPT threads (operating pressure:

1,500 psi). The 1-inch diameter nipple was made of Schedule 160 galvanized steel and had

MNPT threads (operating pressure: 900 psi). Directly after the series of fittings was a Swagelok

all-welded stainless steel ¼ in-line filter (SS - 4W2 - 2) with MNPT threads on both ends that

could filter particles down to 2 microns. Its purpose was to filter any coal from flowing back

through subsequent quick connects and along a corrugated flexible metal hose connecting the

mass flow controller (MFC) to the system. Connected to the Swagelok in-line filter was a

Swagelok stainless steel ¼-inch instrumentation quick connect stem (SS - QC4 - D - 4PF) with

integrated valve that had FNPT threads (operating pressure: 3,000 psi). Mated with the stem was

a stainless steel ¼-inch instrumentation quick connect body with integrated valve that had FNPT

threads (operating pressure: 3,000 psi). This allowed for easy coupling and decoupling of the

corrugated flexible metal hose from the hopper allowing for easy access into the bottom of the

hopper for cleaning purposes. The ¼-inch in diameter, 2-foot in length, corrugated flexible metal

hose was made of 316 stainless steel, the braid around the hose was 304 stainless steel, and the

fittings at either end of the hose were carbon steel with MNPT threads. The hose had a max

working pressure of 2400 psi.

At the top of the system, directly attached to the 2-inch diameter pipe acting as the

hopper, was a 2-inch in diameter Class 300 galvanized malleable iron wye fitting with FNPT

threads in all openings (operating pressure: 1,500 psi). To cap and then suspend the system

from, a 2-inch in diameter Class 3000 316 stainless steel hex head plug with MNPT threads

37

(operating pressure: 3,000 psi) was screwed directly into the vertical branch of the wye fitting. A

carbon steel eye nut was welded onto the top of the hex plug. Screwed into the branching side of

the wye fitting was a Class 300 galvanized steel 2-inch diameter MNPT to ½-inch diameter

FNPT hex bushing (operating pressure: 1,500 psi). Into that fitting a black forged steel ½-inch

diameter MNPT to ¼-inch diameter FNPT bushing (operating pressure: 3,000 psi) was placed.

Finally, a Swagelok stainless steel ¼-inch quick connect stem (SS - QF4 – S - 4PM) with MNPT

threads was inserted into the black forged steel bushing. This series of fittings leading out of the

branching side of the wye led to the secondary filter through another length of corrugated

flexible metal hose (described at the end of the paragraph directly above) via a Swagelok

stainless steel ¼-inch quick connect body (SS - QF4 - B - 4PF) with FNPT threads. Both

Swagelok quick connects had a 3,000 psi operating pressure at room temperature. This branching

construction was used so that the hopper could be filled through the branching side of the wye

while still being suspended from the vertical side of the wye. Disconnecting the quick connects

on the branching side of the wye, unscrewing the black forged steel bushing, and then inserting a

funnel allowed for quick access for loading the hopper with minimal physical disruption to the

system.

Conveying sections made up of ¼-inch Class 3000 304 stainless steel tees and elbows,

Schedule 80 black steel seamless nipples, and ¼-inch Schedule 80 carbon steel piping connected

the hopper to the primary filter. Both the primary and secondary filter were bought from

McMaster.com and were steel filter bag housings (5168K251) 4.5-inches in diameter and 19-

inches tall that could be easily accessed through top mounted removable covers secured using

three built-in eyebolts. Inside of the filter housings were high purity fabric filter bags

38

(9844K411) that could filter particles down to 1 micron. These bags were replaced every 7-9

experiments. After the primary filter a 316 stainless steel 1-inch diameter MNPT to ¼-inch

diameter FNPT bushing led to another Swagelok in-line filter which kept any excess coal from

getting into the inner workings of the control valve. The control valve was a 306 stainless steel

globe cast body which had a linear response, trim size O, 0.003 max Cv, needle valve inside and

¼-inch FNPT connections outside. An air to open, side mounted, 4 – 20 mA digital

SRD991smart positioner allowed for electronic PID control over the pressure within the system.

Opto 22, an instrumentation controls software package, was used to receive flowrate information

and to send signals controlling the percent opening of the valve.

Series 626 pressure transmitters bought from Dwyer.com were mounted at 3 different

positions, 2 within the conveying section between the hopper and primary filter and one directly

after the primary filter. They had a ¼-inch MNPT system connection, a 0 – 500 psi measurement

range, and 0.25% full scale accuracy piezo-resistive sensor. Opto 22 was used to receive system

pressure measurements. In-line Swagelok filters were placed before each one in the conveying

section to make sure that no coal disabled sensitive systems or exhaust into the lab. Two relief

valves, one in the conveying section right next to the pressure transmitter and the other next to

the pressure transmitter directly after the primary filter, provided intrinsic safety in case of a

blockage somewhere in the system. The relief valves were Swagelok 316 stainless steel ¼-inch

MNPT incoming ¼-inch FNPT outgoing proportional low-pressure relief valves with Buna-N

seals (SS - RL3M4F4 - BU). Different spring packages allowed for different ranges at which the

relief valve would activate. In this case both relief valves were outfitted with Swagelok Blue

Spring kits that ranged from 50 – 350 psig.

39

The whole system was suspended from two points: one at the top of the primary filter and

the second was an eyenut at the top of the hopper. Both points had load cells from LCM Systems

between them and their hardpoint mounts on the ceiling. The load cell between the primary filter

and its hardpoint mount was a STA-7 Low Range S type tension and compression load cell rated

for 50 kg. The same type of load cell but rated for 25 kg was placed between the top of the

hopper and its hardpoint mount. Opto 22 recorded the load cell’s measurements 30 times a

second at a minimum.

From the secondary filter a 1-inch to ¼-inch reducing bushing led to a ¼-inch nipple that

led to a ¼-inch FNPT brass manual needle valve (operating pressure: 600 psi). This valve

controlled pressure by limiting fluidizing gas passing through the bed and leaving through the

secondary filter. A Dwyer flowmeter calibrated for air with measurement markings from 20-200

SCFH was mounted on the outside of the needle valve so that monitoring of the fluidization

outlet could take place. Flowrates through the Dwyer flowmeter were set using the manual

needle valve and checked at regular intervals during the test to ensure constant fluidization outlet

flowrates.

Finally, fluidizing gas could enter the system through two points: through the bottom of

the hopper (fluidization inlet A) or through a point in the conveying sections (dilution inlet B).

Two Teledyne HFC-203L mass flow controllers regulated the amount of incoming CO2 gas.

Both operated best with an upstream pressure of 400 psig and a downstream pressure between

300 – 350 psig. Both had a max operating pressure of 500 psig and required a 24 VDC power

supply. Opto 22 received flowrate information and sent signals for the required flowrates.

Solenoid valves were placed between the K cylinders providing CO2 to the system and the two

40

MFC’s. These solenoid valves were made of 303 stainless steel, had ¼-inch FNPT connections,

operating pressure of 3,000 psi, and required 120 VAC to open. Fluidizing gas, once through the

system, could only leave through the fluidization outlet, the control valve, or through one of the

two emergency relief valves. All four of the exits had ¼-inch MNPT to ¼-inch tube adapters that

allowed heavy wall construction ¼-inch PFA tubing with a burst pressure of 1550 psi to be

attached to the system. CO2 exiting the system was vented outside through the attached tubing.

5.2 System Adjustments

The operating team focused only on what impact fluidization inlet A and its interaction

with fluidization outlet C would have on controlling a dilute-phase high-pressure conveying

system. This occurred because the MFC originally attached to the dilution inlet B had to be taken

offline for cleaning at the beginning of the testing process. The length of time needed for

cleaning the second MFC caused the operating team to go ahead with testing despite only having

one MFC. Note, pressurization of the system always had to occur through the dilution inlet rather

than the fluidization inlet in order to prevent coal from prematurely flowing out of the hopper

which would have skewed test results. The fluidization inlet MFC was connected to both inlets to

facilitate pressurization of the system once the MFC connected to the dilution inlet was taken

offline. A tee was connected to the outlet of the fluidization inlet MFC. A brass bodied Schedule

80 ball valve was placed on each of the open tee fitting ends. A corrugated flexible metal hose

was connected to each ball valve. One hose led to the fluidization inlet A and the other to the

dilution inlet B.

41

5.3 System Fuel

Pittsburgh 8 coal was the primary coal used in the system during the main test set. It had

a particle size distribution where 70% by mass was smaller than 200 mesh and less than 1% by

mass was larger than 50 mesh. The median particle diameter was 50 microns and the moisture

content was about 6% by mass. This coal did not have strong electrostatic charge interactions,

nor overly strong cohesive forces affecting its flowability and was conveyed using dilute-phase

flow.

When the primary coal supply was temporarily depleted during the main test set a

secondary coal, Illinois 6, was found. It had within 5%, the same average particle size

distribution, particle diameter, and moisture content as Pittsburgh 8. It was deemed that the data

from tests conducted with Illinois 6 could be analyzed with the Pittsburgh 8 data without adding

additional error.

After the main test set a secondary test set was conducted to compare the conveyability of

Sufco 2010 to Sufco 2016. Note, their moisture contents differed by 2% while their particle

diameters were roughly the same at 50 micron.

5.4 Intended Operating Regimes

The system was operated by first loading the hopper with dry, pulverized coal through

the branching side of the wye fitting at the top of the hopper. To run as long as possible, while

still leaving room for bed expansion, the system was loaded to just above where the wye fitting

began to branch. This meant that 2 lbs on average were loaded into the hopper. Once loaded, the

42

1-inch to ¼-inch bushing and the quick connect stem were replaced so that the secondary filter

could be reattached to the system. At this point the fluidization outlet C was opened to a preset

point which would only allow that experiment’s desired fluidization outlet flowrate to leave.

Once the system was sealed, aside from the fluidization outlet, the Opto 22 data recording

software was started, the control valve PID control loop was started, and the system was

pressurized up to 300 psi through the dilution inlet via the fluidization inlet MFC. After the

system reached its target pressure the dilution inlet ball valve was shut while the fluidization

inlet ball valve was opened. The fluidization inlet MFC was set to whatever fluidization inlet A

flowrate was desired for that test and the system was left to run. Once 5 minutes had passed

where coal was no longer moving from the hopper to the primary filter shutdown procedures

were initiated. The fluidization inlet MFC was set to 0 kg/hr, after which the fluidization inlet

solenoid was closed. The control valve PID loop was shut down and the control valve was set to

2% open. The system was allowed to slowly lose pressure through the control valve and through

the, still open, fluidization outlet C. Once the system was completely de-pressurized it was lifted

onto a rack so both filters could be examined. The secondary filter was disconnected via the

quick connect mounted to branching side of the wye fitting while the primary filter was simply

opened. Coal was removed, weighed, and disposed off from both filters. The primary filter was

closed, the secondary filter closed and then reconnected to the system, the control valve opened

fully, and then CO2 was ran through the system at the highest MFC setting possible. This system

‘flush’ was intended to remove the majority of any coal left in the bottom of the hopper (due to

the outlet from the hopper to the conveying section being 3 inches above the top of the first bell

reducer) and in the conveying sections. Once flushed, both filters were opened again, coal was

removed, weighed, and discarded, and both filters were closed and reattached to the system. The

43

system was removed from its rack and an ‘empty system’ weight was recorded. The system was

then ready to be filled again so another test could be conducted.

5.5 Quantities of Interest

Five parameters were measured and recorded during the operation of the system shown in

Figure 6: system pressure, fluidization inlet (A) and outlet (C) flowrates, the force exerted by the

‘hopper side’ of the system, and the force exerted by the ‘primary filter side’ of the system.

System pressure was measured to 1) verify that the system was pressurized to the desired test

pressure and 2) to monitor for blockages. The fluidization inlet (A) and outlet (C) flowrates were

monitored to determine what fluidization regime the system was operating in and so that

correlations between A, C, and the resultant coal mass flowrate D could be developed. Lastly,

the forces exerted by both sides of the system during any one test were used in the calculation of

that test’s coal mass flowrate. A static force model was developed using the spatial location and

mass of each component of the apparatus and provided a calculated value for the force on each

load cell. After calibration, the left-hand load cell in Figure 6 output the weight of the hopper and

its contents in lbs mass. Similarly, the right-hand load cell in Figure 6 output the weight of the

primary filter and its contents in lbs mass. Prior to using coal in an actual test, load cell

calibration was performed by hanging known weights from a load cell, recording the voltage

outputs, and graphing lbs vs voltage. Lines of best fit were passed through the points on the

graph and the line equation found was input into Opto22 to convert ‘forces exerted on a single

load cell’ into ‘lbs hung from said load cell’. Equations 21 and 22 correspond to left and right

load cells (LC’s) respectively.

44

𝑙𝑙𝑏𝑏𝑠𝑠 ℎ𝐿𝐿𝐼𝐼𝑔𝑔𝐼𝐼𝐼𝐼𝑔𝑔 𝑓𝑓𝐴𝐴𝑆𝑆𝑚𝑚 𝑙𝑙𝑒𝑒𝑓𝑓𝑆𝑆 𝐿𝐿𝐶𝐶 = (0.54933 ∗ 𝐿𝐿𝑒𝑒𝑓𝑓𝑆𝑆 𝐿𝐿𝐶𝐶 𝑣𝑣𝑆𝑆𝑙𝑙𝑆𝑆𝐿𝐿𝑔𝑔𝑒𝑒) − 0.47522 ( 21 )

𝑙𝑙𝑏𝑏𝑠𝑠 ℎ𝐿𝐿𝐼𝐼𝑔𝑔𝐼𝐼𝐼𝐼𝑔𝑔 𝑓𝑓𝐴𝐴𝑆𝑆𝑚𝑚 𝐴𝐴𝐼𝐼𝑔𝑔ℎ𝑆𝑆 𝐿𝐿𝐶𝐶 = (0.54917 ∗ 𝑅𝑅𝐼𝐼𝑔𝑔ℎ𝑆𝑆 𝐿𝐿𝐶𝐶 𝑣𝑣𝑆𝑆𝑙𝑙𝑆𝑆𝐿𝐿𝑔𝑔𝑒𝑒) − 0.26989 ( 22 )

Numerous tests were performed to determine if simply adding weight to the system beneath each

load cell would be registered as the correct weight under the correct load cell. Additionally, tests

were done to see at what weight the load cell would show significant error, more than 5%, in the

reported weight versus the actual weight. Refer to Appendix 1 to obtain details. Once a known

weight of coal was loaded into the hopper the weight of the empty hopper was subtracted from

the new left-hand load cell reading to verify the weight of the newly added coal. As fluidization

and entrainment of coal occurred, a calculation block inside of Opto22 used Equations 21 and 22

to convert load cell voltages to mass readings and then converted said mass readings into

instantaneous coal mass flowrates many times a second. An internal timer inside of Opto22

timestamps each piece of information that is recorded. Coal mass flowrates are then found via

Equation 23.

𝐶𝐶𝑆𝑆𝐿𝐿𝑙𝑙 𝑚𝑚𝐿𝐿𝑠𝑠𝑠𝑠 𝑓𝑓𝑙𝑙𝑆𝑆𝐿𝐿𝐴𝐴𝐿𝐿𝑆𝑆𝑒𝑒 = (𝑐𝑐𝑜𝑜𝑏𝑏𝑠𝑠 𝑤𝑤𝑎𝑎𝑝𝑝𝑔𝑔ℎ𝑡𝑡 𝑏𝑏𝑡𝑡 𝑡𝑡𝑝𝑝𝑚𝑚𝑎𝑎 𝐴𝐴 − 𝑐𝑐𝑜𝑜𝑏𝑏𝑠𝑠 𝑤𝑤𝑎𝑎𝑝𝑝𝑔𝑔ℎ𝑡𝑡 𝑏𝑏𝑡𝑡 𝑡𝑡𝑝𝑝𝑚𝑚𝑎𝑎 𝐵𝐵)(𝑡𝑡𝑝𝑝𝑚𝑚𝑎𝑎 𝐴𝐴−𝑡𝑡𝑝𝑝𝑚𝑚𝑎𝑎 𝐵𝐵) ( 23 )

45

Objects above 0.05 lbs placed on the left load cell had an error under 5%. The resolution of the

scheme used was somewhat low considering only about 2 lbs of coal were moved during each

individual test. Additionally, the right load cell gave errors on the order of 10% and above rather

than 5%. This was due to the usage of a less sensitive load cell to suspend the primary filter

which was roughly three times the weight of the hopper.

5.6 Opto 22

The apparatus had several devices that were continuously outputting data and/or needed

to be controlled by a computer. These devices included: the control valve maintaining the system

pressure, the three pressure transmitters monitoring system pressure, the two load cells the

system was suspended from, the fluidization inlet MFC, and the fluidization inlet solenoid valve.

Hardware and software from Opto 22, a company that specializes in manufacturing process

control and automation products, was used to accomplish both data acquisition/recording and

automated control of the system. A SNAP – PAC – R1 motherboard with 8 input/output (I/O)

modules slotted into it took care of processing system input/output. A DC Power Supply took

incoming 120 VAC and output 24 VDC which powered the R1 motherboard and its attendant

modules. Individual modules took the VDC power supplied to them and transformed it into mA,

mV, or VDC depending on whatever was needed by the device that I/O module was connected

to. Many of the modules had multiple channels giving one module the capability to connect to

multiple devices of the same type. Note that the scale for communications between modules and

devices was linear and set by the user. For example, if during module setup the user set 4-mA to

46

14.7 psi and 20-mA to 500 psi, then a 10-mA signal from the device would cause the module to

output a value of 181.988 psi.

Figure 8. Physical Opto 22 Setup

Table 1. Opto 22 Control Scheme Modules

Figure 8 Module # Opto 22 Module Type Purpose

3 SNAP - AILC Analog Input Receive mV signal from left load cell

4 SNAP - AILC Analog Input Receive mV signal from right load cell

2 SNAP - AIMA - 8 Analog Input Receive 4 - 20 mA signal from all 3 pressure transmitters

7 SNAP - AIMA - 8 Analog Input Receive 4 - 20 mA signal from control valve

47

Table 1 - Continued

Figure 8 Module # Opto 22 Module Type Purpose

1 SNAP - AOA - 23 - iSRC Analog Output Send 4 - 20 mA signal to control valve

5 SNAP - AIV - 4 Analog Input Receive 0 - 5 VDC signal from both MFC's

48

6 Method

Matrix 1 in Table 2 displays the conditions for testing, whose purpose was to determine a

flowrate, or set of flowrates, which would move 13.61 kg coal/hr from the hopper to the primary

filter (representing the reactor in future systems). Therefore, for the first set of conditions within

this matrix, the fluidization inlet port (A) was fixed at a point just high enough for coal to start

moving and then increased each consecutive test. The dilution inlet port (B) was only used to

pressurize the system as was explained earlier in the Apparatus section of this thesis. The

fluidization outlet port (C) was kept closed for the entirety of the first set of fluidization inlet

flowrates. The second set of conditions within this first test matrix was where the fluidization

inlet port (A) was again increased from a low mass flowrate on upwards. The dilution inlet port

(B) was kept closed and the fluidization outlet was kept at a constant 0.771 kg CO2/hr. Finally,

the last set of conditions was where the fluidization inlet port (A) started off as low as possible

while the fluidization outlet port (C) was kept constant at 1.538 kg CO2/hr. Again, the dilution

inlet was kept closed. The fluidization inlet flowrates in all three condition sets within Matrix 1

were chosen evenly spaced out with the hope that any action, such as changing fluidization

regimes, would be caught immediately or be obvious upon analyzing the recorded data.

49

Table 2. Test Matrix 1 – Varying A for 3 Different C’s

Fluidization Inlet - A (kg/hr)

Fluidization Outlet - C

(kg/hr)

E = A - C (kg/hr)

Coal Used

Pressure (kPa)

1.85

0

1.85

Pitt

sbur

gh 8

2067

.86

2.44 2.44

2.98 2.98

3.64 3.64

4.22 4.22

4.87 4.87

1.84

0.771

1.07

2.43 1.66

2.75 1.99

2.99 2.22

3.37 2.6

3.69 2.92

4.26 3.49

4.88 4.11

5.45 4.68

2.46

1.538

0.92

2.8 1.26

3.35 1.81

3.64 2.1

4.25 2.71

50

Table 2 - Continued

Fluidization Inlet - A (kg/hr)

Fluidization Outlet - C

(kg/hr)

E = A - C (kg/hr) Coal Used Pressure

(kPa)

4.83 1.538

3.29 Pittsburgh 8 2067.86

5.45 3.91

The second test matrix, shown in Table 3, gave conditions for testing if a linear

relationship existed between E (fluidization inlet flowrate A – fluidization outlet flowrate C) and

coal mass flowrate D ,or not. It was expected that there would be a linear relationship between E

and D. What E that should be used was based upon a recommendation of 2.9 kg CO2/hr, which

came from the computational flow dynamics modeling group working with the design team.

Between fluidization inlet and outlet flowrates, the outlet flowrates tended to be the limiting

factor since they were unable to go above a certain point without rendering the system unable to

maintain pressure (at high C flowrates CO2 tended to leave through the fluidization outlet rather

than through the system and out the control valve). Fluidization inlet flowrates (A) were chosen

by adding the fluidization outlet value to the recommended E value. Note that the coal in Matrix

2 was different from the coal used in Matrix 1. This is because the supply of drum-stored

Pittsburgh 8 was exhausted right before all the testing in Matrix 1 was complete. The change in

coal used was deemed not significant since the size distribution and moisture content of Illinois 6

was close to the size distribution and moisture content of drum-stored Pittsburgh 8.

51

A third test matrix shown in Table 4 was used to look at which coal out of Sufco 2010

and Sufco 2016 gave more reliable results. At the time, these two coals were the main two coals

which were going to be available from suppliers that Dr. Fry and others trusted. The fluidization

outlet of 0.771 kg CO2/hr was chosen as it seemed to have lower error associated with its

resulting coal mass flowrates. The fluidization inlet was varied around the 4 kg CO2/hr point

because previous matrices had seen a significant number of tests at that inlet flowrate result in

the desired 13.61 kg coal/hr.

Table 3. Test Matrix 2 – Constant E

Fluidization Inlet - A (kg/hr)

Fluidization Outlet - C

(kg/hr)

E = A - C (kg/hr)

Coal Used

Pressure (kPa)

5.53 2.59

2.9

Illin

ois 6

2067

.86

4.92 1.97

4.59 1.67

4.27 1.39

3.97 1.08

3.66 0.8

3.36 0.51

52

Table 4. Test Matrix 3 - Testing Different Sufco Coals

Fluidization Inlet - A (kg/hr)

Fluidization Outlet - C

(kg/hr)

E = A - C (kg/hr)

Coal Used

Pressure (kPa)

4.99

4.22 Sufc

o 20

10

2067

.86 3.13 2.36

Sufc

o 20

16

3.75 2.98

4.38 3.61

4.68 3.91

5.02 4.25

Throughout the testing process there were some results that complicated the analysis

which required consideration. Tuning the parameters in the Opto 22 control scheme was ongoing

throughout the testing and provided valuable insight shared later in this work. The impacts of

coal moisture were significant. Some few tests were done with Black Thunder 1 (moisture

content: 19.42%) as the coal used and very quickly (within 10 tests) it was known that high

moisture content coals would simply not convey reliably or smoothly.

53

7 Safety

Multiple hazards were presented with the operation of the apparatus described in Figure

6. They included:

1) possible asphyxiation in the testing room due to CO2 buildup from leaks,

2) an apparatus rupture while pressurized up to 350 psi, and

3) a deflagration of spilled or leaked pulverized coal.

Each of the hazards listed had associated safety measures in place to minimize the danger

involved in operating the apparatus. These measures included:

1.1) exhaust lines ran directly outside from the control valve and both relief valves,

1.2) gas monitoring devices were operational in the testing room,

2.1) pressure transmitters were placed to detect pressure buildups in the system,

2.2) fail-closed solenoid valves were placed between each CO2 cylinder and the system,

2.3) an Opto 22 emergency shutdown procedure would run if pressure exceeded 350 psi,

2.4) spring operated pressure relief valves would open at 375 psi,

54

3.1) 2-micron filters placed on all exits from the system,

3.2) careful control of all ignition sources within the testing room, and

3.3) the careful cleaning of the room after every 5 tests.

All tests were ran after all operators were outside of the testing room. Access to the room was

kept to a bare minimum while tests were being ran. Only periodic checks to make sure the

fluidization outlet C was constant and to use ball valves to switch CO2 flow from pressurizing

through the dilution inlet to fluidization through the fluidization inlet were allowed.

55

8 Results

8.1 Coal Flow vs. Fluidization Flow

The data presented below are focused on the fluidization state of the hopper and how it

affects the smoothness and reliability of the solids conveyed. Figure 9 – Figure 19 were

generated from the data taken during Test Matrix 1 shown in Table 2.

Data taken during individual test runs allowed for the calculation of instantaneous

and overall average coal flowrates. The overall average coal flowrate for each individual test run

was what we used to draw conclusions later. Figure 9 - Figure 11 are three examples out of

hundreds of tests and are meant to showcase how overall average coal flowrates were

determined.

Figure 9 displays individual load cell readings recorded by Opto 22 over the course of

Test 50. Note, that the x-axis in Figure 9 consists of ‘Opto Data Points’. Opto 22 was

programmed to take a datum every second while the fluidization mass flow controller had a

positive flowrate going through it. Noise from the mass flow controller caused Opto 22 to not

take a datum every second but only nearly every second. Fortunately, Opto 22 also recorded the

times at which it took each datum which allowed us to still get an accurate flowrate. To illustrate:

The hopper initially had 1.2 kg of coal inside of it but lost some coal after a brief hiccup where

the system fluidization inlet was opened around when Opto 22 took its 30th data point. After the

56

fluidization inlet opened the hopper still had 1.1 kg of coal inside of it at a time of

10:14:48. This mass steadily dropped to 0.5 kg of coal over the course of roughly 130 data points

or 160 seconds. From 10:17:28 and onwards the mass in the hopper stayed constant. Therefore,

the coal flowrate for Test 50 was 0.6 kg coal/160 seconds or about 13.5 kg coal/hr. This ‘Test 50

average flowrate’ then became an individual datum for Round Three of Figure 16.

Figure 9. Test 50 Data A=4.23 kg/hr CO2; C=1.54 kg/hr CO2

Figure 10 is included here to show a test run that was used but may have introduced some

error into the end results which may not be readily apparent. Figure 10 displays all the recorded

Opto 22 data points for Test 70. The process that was used to summarize data in Figure 9 was

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 50 100 150 200 250

Coal

in H

oppe

r (k

g)

Opto Data Points (~ seconds)

57

used to summarize the data in Figure 10. There was 0.82 kg of coal in the hopper at 12:50:02, or

the 55th datum. There was 0.19 kg of coal in the hopper at 12:54:06, the 291st datum. The coal

flowrate for this test was determined to be 9.3 kg coal/hr. This test became a datum in Round

Two of Figure 14.

Figure 10. Test 70 Data A=2.63 kg/hr CO2; C=0.77 kg/hr CO2

Figure 11 was included to show a test run that was NOT included. Figure 11 had no

discernible slope from some starting hopper weight to some ending hopper weight. It also had no

discernible ending hopper weight. For these reasons the conditions that Test 113 was run at were

run again and the results shown in Figure 11 were removed. Other tests throughout Matrix 1 and

Matrix 2 testing were thrown out but only when we either 1) could not maintain the conditions of

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 50 100 150 200 250 300 350 400

Coal

in H

oppe

r (k

g)

Opto Data Points (~s)

58

the test consistently (system pressure at 300 psi for test duration, fluidization inlet non constant,

etc) and/or 2) could not see a discernible movement of coal from the hopper to the primary filter.

The second circumstance was not a case where data that did not support our expected conclusion

was just ignored. All data was kept from every test. Tests that looked like Figure 11 or had

similar issues made up less than 7% of all tests ran and were always accompanied by odd system

pressure fluctuations and/or mass flow controller issues.

Figure 11. Test 113 Data A=2.46 kg/hr CO2; C=Closed

Now that the method for summarizing individual test runs has been shown, further results

can be shown. Figure 12 and Figure 13 are different ways of presenting the same set of data. This

data was taken while at the following conditions:

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 200 400 600 800 1000 1200

Coal

in H

oppe

r (k

g)

Opto Data Points (~s)

59

- Fluidization Inlet (A) = varied from 1.75 kg CO2/hr to 4.75 kg CO2/hr

- Dilution Inlet (B) = 0 kg CO2/hr

- Fluidization Outlet (C) = 0 kg CO2/hr (0 % open)

- System Pressure = 2068.43 kPa

Figure 12 shows the individual datum taken while the fluidization inlet was varied, and the

fluidization outlet was maintained closed throughout. Figure 13 shows datum, taken at the same

fluidization inlet flowrate, averaged and displayed with standard deviation error bars. All tests in

Figure 12 and Figure 13 were performed using the same coal, Pittsburgh 8.

Data presented in Figure 14 and Figure 15 were taken while at the following conditions:

- Fluidization Inlet (A) = varied from 1.75 kg CO2/hr to 5.5 kg CO2/hr

- Dilution Inlet (B) = 0 kg CO2/hr

- Fluidization Outlet (C) = 0.771 kg CO2/hr (15 % open)

- System Pressure = 2068.43 kPa

Figure 14, similar to Figure 12, shows the individual datum taken while the fluidization inlet was

varied and the fluidization outlet was maintained 15% open throughout. Figure 15, like Figure

13, shows datum, taken at the same fluidization inlet flowrate, averaged and displayed with

standard deviation error bars. All tests in Figure 14 and Figure 15 were performed using the

same coal, Pittsburgh 8.

60

Figure 12. Coal (Pittsburgh 8/Illinois 6) Flowrate (D) vs CO2 Flowrate (A) when Fluidization Outlet (C) = 0 kg CO2/hr (Replicates)

Figure 13. Coal (Pittsburgh 8/Illinois 6) Flowrate (D) vs CO2 Flowrate (A) when Fluidization Outlet (C) = 0 kg CO2/hr (Aggregate with Error Bars)

0

10

20

30

40

50

60

0 1 2 3 4 5 6

Coal

Flowr

ate

(kg/

hr)

CO2 Flowrate (kg/hr)

Round One

Round Two

Round Three

Round Four

0

5

10

15

20

25

30

35

40

45

50

0 1 2 3 4 5 6

Coal

Flowr

ate

(kg/

hr)

CO2 Flowrate (kg/hr)

61

Figure 14. Coal (Pittsburgh 8) Flowrate (D) vs CO2 Flowrate (A) when Fluidization Outlet (C) = 0.77 kg CO2/hr (Replicates)

Figure 15. Coal (Pittsburgh 8) Flowrate (D) vs CO2 Flowrate (A) when Fluidization Outlet (C) = 0.77 kg CO2/hr (Aggregate with Error Bars)

0

5

10

15

20

25

30

35

40

0 1 2 3 4 5 6

Coal

Flowr

ate

(kg/

hr)

CO2 Flowrate (kg/hr)

Round One

Round Two

Round Three

Round Four

0

5

10

15

20

25

30

35

40

0 1 2 3 4 5 6

Coal

Flowr

ate

(kg/

hr)

CO2 Flowrate (kg/hr)

62

Figure 16 and Figure 17 testing conditions were as follows:

- Fluidization Inlet (A) = varied from 2.5 kg CO2/hr to 5.5 kg CO2/hr

- Dilution Inlet (B) = 0 kg CO2/hr

- Fluidization Outlet (C) = 1.538 kg CO2/hr (30 % open)

- System Pressure = 2068.43 kPa

Figure 16 shows the individual datum taken while the fluidization inlet was varied, and the

fluidization outlet was maintained 30% open throughout. Figure 17 shows datum, taken at the

same fluidization inlet flowrate, averaged and displayed with standard deviation error bars. All

tests in Figure 16 and Figure 17 were performed using the same coal, Pittsburgh 8.

Figure 18 displays the combined data originally shown in Figure 13, Figure 15, and Figure

17. Observations using Figure 18 follow:

- As the fluidization outlet (C) percent open increased it took an increased fluidization inlet

(A) flowrate to achieve the same resultant coal mass flowrate (D)

- Lower amounts of error were present for the fluidization inlet flowrates of 3.5 kg CO2/hr

and below when the fluidization outlet (C) was set at 0.771 kg CO2/hr

- As the fluidization outlet (C) percent open increased there was lower amounts of error

overall, more error was present when C was closed than when C was open to 1.5 kg

CO2/hr

63

Figure 16. Coal (Pittsburgh 8/Illinois 6) Flowrate (D) vs CO2 Flowrate (A) when Fluidization Outlet (C) = 1.54 kg CO2/hr (Replicates)

Figure 17. Coal (Pittsburgh 8/Illinois 6) Flowrate (D) vs CO2 Flowrate (A) when Fluidization Outlet (C) = 1.54 kg CO2/hr (Aggregate with Error Bars)

0

5

10

15

20

25

0 1 2 3 4 5 6

Coal

Flo

wra

te (k

g/hr

)

CO2 Flowrate (kg/hr)

Round One

Round Two

Round Three

Round Four

0

5

10

15

20

25

0 1 2 3 4 5 6

Coal

Flo

wra

te (k

g/hr

)

CO2 Flowrate (kg/hr)

64

Figure 19 displays the coal mass flowrate as a function of a parameter, E. E, shown in

Figure 6, is the mass flowrate that leaves the column through the conveying exit. A mathematical

expression for E is A – C, or fluidization inlet – fluidization outlet. Observe the ‘collapse’ of the

lines shown in Figure 18 into basically one line in Figure 19. This line indicates that as E

increases the coal mass flowrate (D) will increase. With this empirically derived relationship the

coal mass flowrate could be roughly predicted based upon what fluidization inlet flowrates (A)

are used and their corresponding fluidization outlet flowrates (C).

Figure 18. All Aggregates with Error Bars (Pittsburgh 8/Illinois 6)

Figure 20 and Figure 21 were generated from data recorded during Test Matrix 2 shown

in Table 3. E was kept constant at 2.858 kg CO2/hr during these tests. Note that Test 115 – Test

149 were the tests that went into generating Figure 20 and Figure 21. As will be noted in the

0

5

10

15

20

25

30

35

40

45

50

0 1 2 3 4 5 6

Coal

Flo

wra

te (

kg/h

r)

CO2 Flowrate (kg/hr)

Closed

C = 0.771 kg/hr

C = 1.538 kg/hr

65

discussion of Figure 22 the large amounts of error between data points in both figures may have

been due to the bottom of the hopper not being cleaned until Test 142. The expected behavior, a

flat horizontal line, is not especially apparent.

Figure 19. Relationship between conveying exit flowrate and overall coal mass flowrate (Pittsburgh 8/Illinois 6)

0

5

10

15

20

25

30

35

40

45

50

0 1 2 3 4 5 6

Coal

Flo

wra

te (k

g/hr

)

E = A - C (kg/hr)

Closed

C = 0.8 kg/hr

C = 1.5 kg/hr

66

Figure 20. Coal (Pittsburgh 8/Illinois 6) Flowrate (D) vs CO2 Flowrate (A) while Hopper Conveying Exit (E) = 2.858 kg CO2/hr (Replicates)

Figure 21. Coal (Pittsburgh 8/Illinois 6) Flowrate (D) vs CO2 Flowrate (A) while Hopper Conveying Exit (E) = 2.858 kg CO2/hr (Aggregate with Error Bars)

0

5

10

15

20

25

30

35

0 1 2 3 4 5 6

Coal

Flo

wra

te (k

g/hr

)

CO2 Flowrate (kg/hr)

Round One

Round Two

Round Three

Round Four

0

5

10

15

20

25

30

35

0 1 2 3 4 5 6

Coal

Flo

wra

te (k

g/hr

)

CO2 Flowrate (kg/hr)

67

Figure 22 was generated from data taken during Test Matrix 3 shown in

Table 4. Sufco 2010 coal was being tested to see what kind of flowability it had under similar

conditions to what Pittsburgh 8 had been put through in Test Matrix 1. Fluidization inlet A was

varied while fluidization outlet C was kept constant at 0.77 kg CO2/hr. The dilution inlet B was

kept closed. No comment can be made about the large amount of error shown in Figure 22. Data

was taken for Sufco 2016 as well under the same A, B, and C conditions but it is incomplete.

Sufco 2016 testing was discontinued once it was found out that no Sufco 2016 was available for

purchase.

Figure 22. Sufco 2010 Coal Flowrate (D) vs CO2 Flowrate (A) when Fluidization Outlet (C) = 0.77 kg CO2/hr (Aggregate with Error Bars)

-20

-10

0

10

20

30

40

50

60

0 1 2 3 4 5 6

Co

al F

low

rate

(kg

/hr)

CO2 Flowrate (kg/hr)

68

8.2 Other Impacting Factors

During the data taking process various parameters outside of the fluidization inlet and outlet

flowrates were observed to also have an impact on the fluidization state of the hopper.

Additionally, during the subsequent analysis of the data taken interesting trends with regards to

the fluidization state of the hopper were found. These parameters and trends included:

- Trend: That atmospheric correlations predicted fluidization regime changes near where

anomalies in the data taken showed up consistently

- Parameter: The amount of moisture present in the coal being used

- Trend: Coal distribution to the two filter points was different than what might have been

expected

- Parameter: The presence of debris that were millimeters in diameter directly above the

fluidization inlet point

- Parameter: The usage of Opto tuning parameters other than those that have a direct

physical analogue

8.2.1 Operating Regime Transitions

Using correlations developed for fluidized beds at atmospheric conditions from

Circulating Fluidized Bed Boilers: Design and Operations by Basu and Fraser [15], we

calculated where fluidization regime changes were expected occur. These were plotted in Figure

23 along with the coal mass flowrate (D) as a function of the fluidization inlet flowrate (A) with

varying fluidization outlet flowrates (C). In Figure 24 the same expected fluidization regime

69

changes were plotted except the data displayed is for when E is held constant at 2.858 kg CO2/hr

(background data in Figure 24 is the same as displayed in Figure 19). Two regime changes,

minimum fluidization and bubbling, fell within a reasonable x-axis frame of reference and they

are the vertical lines depicted in Figure 23 and Figure 24. Figure 25 displays all of the

fluidization regime changes that apply to our system presented in Basu and Fraser’s [15] book.

Observe that the change in slope that occurs in all 3 of the different fluidization outlet trendlines

happen to fall within a 1 kg CO2/hr area of each other and also happen to be very near where an

atmospheric correlation predicts a fluidization regime change into a bubbling bed.

Figure 23. CFBB Fluidization Regimes when E varies - Zoomed In

Not shown in Figure 23, Figure 24, or Figure 25 is the threshold velocity at which a correlation

developed by Geldart and Abrahamsen [40] predicted the transition from incipiently fluidized to

0

5

10

15

20

25

30

35

40

45

50

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

Coal

Flo

wra

te (k

g/hr

)

CO2 Flowrate (kg/hr)

Closed

C = 0.8 kg/hr

C = 1.5 kg/hr

Min. Fluidization

Bubbling

70

bubbling bed would be. Using Equation 24, shown below, the bubbling bed velocity was

predicted to be at 16.68 m/s. This is 8 times the threshold velocity shown in Figure 23, Figure 24,

Figure 24. CFBB Fluidization Regimes when E = 2.858 kg CO2/hr - Zoomed In

and Figure 25. With two different empirically determined correlations you get two very different

predictions for the same threshold velocity. A large margin of error therefore exists for the

prediction of regime threshold velocities. This translates to uncertainty to which velocity the

fluidization may develop into a bubbling regime. We believe this regime change is responsible

for or a contributing factor towards the slope change in all of Test Matrix 1’s data.

𝑢𝑢𝑚𝑚𝑚𝑚 = 2300 𝜌𝜌𝑔𝑔0.13 𝜇𝜇0.52 exp�0.72 𝑃𝑃45𝜇𝜇𝑚𝑚� ( 24 )

0

5

10

15

20

25

30

35

40

45

50

0 1 2 3 4 5 6

Coal

Flowr

ate

(kg/

hr)

E = A - C (kg/hr)

Closed

C = 0.8 kg/hr

C = 1.5 kg/hr

Min. Fluidization Bubbling

71

𝑃𝑃45𝜇𝜇𝑚𝑚 is the mass fraction of particles smaller than 45 micron.

All of the data reported in Figure 23, Figure 24, and Figure 25 display an interruption in

the slope of the coal flow vs. fluidization flow curve. It is our hypothesis that this change in slope

is due to a fluidization regime change into a bubbling bed. The predicted fluidization regime

change detailed in Figure 23, Figure 24, and Figure 25 does not perfectly align with the observed

change in slope, although it is close. However, it is important to remember that the predicted

regime change points were found using correlations developed leveraging data from systems that

were operated at atmospheric conditions. Additionally, the distance of 3 inches, between the

fluidization inlet (A) and the ‘hopper exit to the conveying line’ (E) might not have been long

enough to allow for fully developed fluidized bed behavior to develop.

Figure 25. CFBB Fluidization Regimes - Zoomed Out

0

5

10

15

20

25

30

35

40

0 5 10 15 20 25 30 35 40 45

Coal

Flowr

ate

(kg/h

r)

CO2 Flowrate (kg/hr)

Closed

C = 0.8 kg/hr

C = 1.5 kg/hr

Terminal

SluggingBubbling

Min. Fluidization Turbulent

- Start

Turbulent- Stable

Transport

72

8.2.2 Coal Moisture Content

Throughout the data taking process different coals were used. Some coals exhibited

different behavior in the hopper from other coals despite being subjected to the same conditions

system wide. From the literature survey and Dr. Fry’s prior experience it was quickly determined

that the moisture content of the different coals was likely responsible. Table 5 shows each coal

that was used and its moisture content. The compositions detailed in Table 5 were determined by

putting a known coal sample weight into an oven and baking it for one hour at 107 degrees

Celsius. The oven conditions were recommended by a different research team who used the oven

to dry out coal regularly. Afterwards, the sample was weighed, and the difference between pre-

and post-baking was attributed to water.

Table 5. Moisture Content of Different Coals

Coal Average Moisture Content (%, mass)

Pittsburgh 8 (Bag) 0.98

Sufco 10 4.32

Pittsburgh 8 (Drum) 5.51

Illinois 6 6.09

Sufco 16 6.18

Black Thunder 19.42

73

Figure 26 shows the coal mass flowrate (D) as a function of the fluidization inlet mass

flowrate (C) while the fluidization outlet mass flowrate was kept constant at 15% open (0.771 kg

CO2/hr) for two different coals with different moisture contents.

Figure 26. Coal Moisture Content Impact, Coal Flowrate (D) vs CO2 Flowrate (A) while Fluidization Outlet (C) = 0.77 kg CO2/hr

Using Table 5, in conjunction with Figure 26, shows that coals with a high moisture content,

such as Black Thunder 1, do not fluidize or convey well. Not shown but supported by literature

and by test data is that coals with a moisture content below 2% are also hard to fluidize and

convey due to electric charge. Ideally, coals with a moisture content between 2% and 7% fluidize

and convey the best.

0

5

10

15

20

25

30

35

40

0 1 2 3 4 5 6

Coal

Flo

wra

te (k

g/hr

)

CO2 Flowrate (kg/hr)

Pittsburgh 8 (Drum) - 5.51%

Black Thunder 1 - 19.42%

74

Note that Table 5 and Figure 26 were generated from data developed during the

execution of the test matrices shown in Table 2, Table 3, and Table 4.

8.2.3 Final Coal Distribution

Figure 27 shows the percentage of coal moved to the secondary filter as a function of the

fluidization inlet flowrate with varying fluidization outlet flowrates. Observe the spread with

regards to fluidization outlet flowrate specifically. As the fluidization outlet flowrate is increased

the spread increases. There may be a correlation between the spread of the percentage moved to

the secondary filter and the fluidization regime which the tests were taken at. On the other hand,

there may be a relationship between the increasing amount of particulate matter present in the

bottom of the hopper as testing went on. Reiterating from above, the C = closed data set had

most of its points taken while there was the greatest amount of foreign debris in the bottom of the

hopper. This scenario would naturally lead to less coal being moved to the harder to reach

secondary filter compared to the much more easily reached primary filter. Also, the points with

the most spread, when C = 1.538 kg CO2/hr, were taken when there was the smallest amount of

foreign debris in the bottom of the hopper. Most importantly though, the amount of coal moved

to the secondary filter can seemingly be minimized with a C flowrate of 0.771 kg CO2/hr.

75

Figure 27. Percentage of Coal Moved to Secondary Filter

8.2.4 Bed Debris

Certain disturbing trends began to show themselves over the course of the first 100 tests that

made up Test Matrix 1 (shown in Table 2). The system pressure would not remain constant

throughout some tests no matter what strategies were employed to govern the control valve.

Additionally, coal mass flowrates found under the same system conditions at the beginning of

the 100 tests sometimes varied greatly from those found near the end of the 100 tests. After

various troubleshooting schemes 4 pieces of rusted metal, several mm in length, along with

multiple smaller pieces, were found at the bottom of the hopper directly on top of the fluidization

inlet point. Prior to Test 142 no effort had been made to check to see if any type of foreign

material accumulation had been taking place. Most likely these pieces of rust were contributing

0

5

10

15

20

25

0 1 2 3 4 5 6

% C

oal M

oved

to S

econ

dary

Bag

hous

e

CO2 Flowrate (kg/hr)

C = Closed

C = 0.771 kg/hr

C = 1.538 kg/hr

76

to lower and more erratic coal mass flowrates (D). Two things to note then: 1) The error bars

shown in Figure 12 - Figure 17 were probably heavily influenced by the presence, or lack, of

debris above the fluidization inlet. Very little debris was present for Figure 16 and Figure 17

tests since most were done much earlier than Test 142. This helps explain the lower error

displayed in those two figures. Figure 12 and Figure 13 had most of their tests done closest to

Test 142. This probably helps explain the high amount of error in these figures compared to

Figure 14 - Figure 17. 2) Tests were ran after Test 142 to find out the magnitude of the effect that

debris above the fluidization inlet could have on the coal mass flowrate (D). Figure 28 was the

result. At CO2 mass inlet flowrates lower than 4 kg CO2/hr there seems to be a greater degree of

correspondence between pre- and post-cleaning trendlines. After 4 kg CO2/hr the rate at which

the post-cleaning trendline increases seems to grow much faster than the pre-cleaning rate does.

Figure 28 was developed using all of the data that went into developing Figure 16 and Figure 17,

along with 18 additional tests.

From all the tests conducted we know that debris will collect over time in the bottom of

the bed and from Figure 28 we know that it will cause considerable error. Therefore, the

demonstration reactor’s feed system bed bottom will be designed with regular cleanings in mind

to prevent bed debris from clogging the the system fluidization inlet.

8.2.5 Control Parameters

The inability to maintain the system pressure at 300 psig +/- 5 psig was another source of

error in the findings above. At first, while the system was new and without accumulation of any

77

sort, the Gain and Tune I parameters were enough to control the system. Adding needed

hardware, accumulation of coal in system nooks and crannies, the time delay involved in the

control valve responding from 0% open to any other percentage open, and the control valve’s

tendency to close entirely as soon as it hit 1% open presented challenges to finely tuned control

of the system pressure over time.

Figure 28. Hopper Bottom Cleaning, Coal Flowrate (D) vs CO2 Flowrate (A) when Fluidization Outlet (C) = 1.54 kg CO2/hr

Time was taken to discover and implement control schemes that would control the

system after new hardware was added and regular cleanings of the system addressed the first two

control issues mentioned earlier. To fix the control valve issues though, further investigation into

0

5

10

15

20

25

30

35

40

0 1 2 3 4 5 6

Coal

Flo

wra

te (

kg/h

r)

CO2 Flowrate (kg/hr)

Pre-Cleaning

Post-Cleaning

78

Opto 22 was undertaken. While looking through the miscellaneous details section of the Opto

PID controller, additional parameters originally meant to control physical feed forward systems

were found. Through trial and error, it was discovered that the FF and TuneFF parameters

worked in conjunction to dampen noise in the system and shift semi-stable system pressure

behavior up and down around the setpoint. These two additional parameters, despite a lack of

feed forward hardware to interface with, allowed system operators to more fully compensate for

the control valve time delay and prevent system noise from closing the control valve at an

inopportune moment. Table 6 shows the desired system pressure (setpoint) and the set

fluidization inlet mass flowrate. The Gain, Tune I, Tune D, FF, and TuneFF parameters were all

experimented with beforehand and Table 6 shows the final iterations in the Opto 22 tuning

process and what the results were for said iterations. Span was a variable built into Opto and it is

contained in Table 6 and the Appendices because it changed between 0.294118 and 0.331331 at

different intervals. Span data was included so others would know that Span changes and how it

changed for previous Opto 22 PID controller users.

Table 6. Opto Tuning Parameters

Setpoint (psig)

CO2 Flowrate (kg/hr)

Gain Tune I

Tune D Span FF Tune

FF Results

300 4 0.275 0.2 0 0.294118 0 0 289 - 322 psi

oscillation with 30 sec period

79

Table 6 - Continued

Setpoint (psig)

CO2 Flowrate (kg/hr)

Gain Tune I

Tune D

Span FF Tune FF

Results

300 4 0.275 0.2 0 0.294118 0.26 1 Steady at 284 psi

300 4 0.275 0.45 0 0.294118 0.22 1 293 - 295 psi oscillation with 4

minute period and 3 overshoots

300 4 0.275 0.30 0 0.294118 0.22 1 Steady at 291 - 292 psi

300 4.5 0.275 0.28 0 0.294118 0.22 1 Steady at 292 psi

Note, that all these issues were encountered in a bench-scale system. Therefore, small

PID changes which lead to small valve changes were easily able to have large consequences in

system. In a larger scale system, such as the one that will be built, those same sized PID and

valve changes will cause considerably smaller effects. This is beneficial since we will be able to

1) not have to worry as much about noise or small adjustments inducing significant error and 2)

control the demonstration reactor’s feed system more accurately.

Note that Figure 28 and Table 6 were generated from data taken during the test matrices

shown in Table 2, Table 3, and Table 4.

.

80

9 Conclusions

The purpose of this work was to understand how to smoothly and reliably feed dry

pulverized coal to an advanced high pressure oxy-combustion reactor using fluidized bed

technology and loop seals. A bench scale system was constructed and models were assembled

from literature to assist in analyzing the data generated by this system. Correlations, made from

observations discussed above, are presented below. These correlations will be grouped into three

separate categories based on the physical part of the system each corresponds too. The categories

are fluidization outlet (C), fluidization inlet (A), and coal/system conveyability.

As the fluidization outlet (C) percent opening increased:

1) It took an increased fluidization inlet (A) flowrate to achieve the same coal mass flowrate

(D)

2) The standard deviation of coal mass flowrates obtained at the same fluidization inlet

flowrates decreased. The likely reason for this has to do with the fluidization regime the

system was operated in.

3) The standard deviation in the percentage of coal moved to the secondary filter decreased

at first and then increased. In general, the greater the percent opening of the fluidization

outlet, the greater the flowrate carrying coal leaving through the fluidization outlet, rather

than entraining particles and exiting through the conveying exit, E.

81

Based on these observations a higher fluidization outlet percent opening would be beneficial

because operators could more effectively predict how much coal would move overall and at what

rate the coal would enter the reactor. To achieve the desired 13.6 kg coal/hr with a higher

fluidization outlet percent opening, a proportionally higher flowrate of motivating gas would be

required. This would correspond with higher long-term operating costs. Normally, this would be

undesirable but the demonstration reactor’s feed system being built will require significant

amounts of dilution CO2 to be added to the system anyways. Additionally, a greater percentage

of the total coal moved would move towards the fluidization outlet and the large-scale secondary

filter rather than the demonstration reactor. This would also correspond to higher operating costs.

Future operators would need to optimize between repeatability and operating cost.

For most systems the fluidization inlet flowrate is a key parameter in determining what

fluidization and conveying behaviors will be exhibited. This system was no exception. During

each of the fluidization inlet flowrate data sets ran at a single fluidization outlet flowrate, there

was a point below which standard deviation decreased. This point was roughly 3.5 kg CO2/hr for

all three fluidization outlet flowrates tested. For the closed fluidization outlet data set, the change

in error was particularly significant. Below 3.5 kg CO2/hr the standard deviation was 5.8 and

above it the standard deviation was 10.6. A slightly less dramatic change was seen with

fluidization outlet of 0.771 kg CO2/hr. Below the point the average standard deviation was 1.4

while above it the average standard deviation was 6.1. For the 1.538 kg CO2/hr fluidization outlet

flowrate the average standard deviation before 3.5 kg CO2/hr was 2.1 while above it the average

standard deviation was 1.8. There is some doubt about the validity of the 2.1 average standard

deviation associated with the 1.538 kg CO2/hr though as there were only two data points

82

available for the fluidization inlet flowrate of 2.5 kg CO2/hr. Without further testing it was

unknown whether that high coal mass flowrate could be excluded or not. Based on this

information it would be advantageous to operate at fluidization inlet flowrates below 0.0119 m/s.

In a 2-inch pipe 0.0119 m/s is the superficial velocity that corresponds to the fluidization inlet

mass flowrate of 3.5 kg CO2/hr. Operating at or below 0.0119 m/s would also correspond to

operating in the minimum fluidization regime rather than the bubbling fluidization regime.

Resulting coal mass flowrate predictability would increase, operating costs would decrease, and

solids degradation would be kept to a minimum.

Two other issues also affect the choice fluidization inlet flowrate in a larger scale system:

the presence of foreign debris in the bottom of the hopper and the fluidization regime which the

hopper is being operated in. The presence of foreign debris caused interesting behavior to be

observed. Below 0.0135 m/s (4 kg CO2/hr) it appears that, although there is still a discrepancy

between the clean hopper and ‘dirty’ hopper coal mass flowrates, the discrepancy is much

smaller than that between flowrates above 0.0135 m/s. Although multiple simple solutions exist

to prevent and/or eliminate any discrepancy (filtering the coal before it goes into the hopper,

opening the hopper and cleaning it periodically, etc) these solutions require extra time, additional

equipment, and/or special design considerations. From the behavior examined above, if it is

desired, the system can be run ‘dirty’ at fluidization inlet flowrates below 0.0135 m/s and the

resulting coal mass flowrates should be, at the outside, 110% of what they would have been if

the hopper were kept clean. Admittedly, this is not a great percentage, but it is a better one than

would be found not long after crossing the 0.0135 m/s demarcation. The last and most significant

of all the correlations observed and developed throughout this work is the fluidization regime

83

which the hopper is being operated in. Vastly different behavior will be exhibited by the system

depending on which fluidization regime is sought after. Correlations developed for atmospheric

pressure systems predicted that the bubbling velocity, where a system goes from a raised bed to a

bed that has growing bubbles traveling through it, was near where our system had a clear change

in slope for all three trendlines found. It is believed that, due to this system being operated at 20

atm rather than a single atmosphere, the bubbling velocity shifted to the right of where the

atmospheric correlations predicted it would be. Therefore, all the recorded data was taken

directly before and immediately after the bubbling regime began. This insight lends itself to

explaining why there was less standard deviation in the resulting coal mass flowrates when the

fluidization inlet was below 0.119 m/s. It is likely that the system did not yet have bubbles

traveling throughout the hopper disrupting smooth flow exiting through the conveying exit, E.

This lack of bubbles meant that less coal left through the conveying exit but what did leave left

more regularly over the course of several runs. It is recommended that the system is operated

either above or below the bubbling velocity. This can be achieved by changing the fluidization

inlet by itself or in conjunction with the fluidization outlet. Note that even if the fluidization

outlet is opened, if the fluidization inlet is reduced, the resulting system might still be within the

regime change region. Additionally, the bed dimensions can also be changed to keep the system

from operating inside of the bubbling regime transition.

I have two recommendations based on coal conveyability and system characteristics.

From the Results section it is recommended that a coal with a moisture content between 3% and

6% be used. This choice will greatly aid in giving rise to a linear coal mass flowrate vs inlet CO2

mass flowrate trendline with minimal amounts of error compared to coals with the wrong

84

moisture content. Again, from the Results section, it is recommended that future operators using

Opto to regulate system control valves remember they can use the FF and TuneFF parameters to

dampen noise and compensate for time delays upon opening from 0%.

In summary, there are four main recommendations being put forward that should aid in

the design of a feed system that will smoothly and reliably feed coal to the advanced high

pressure oxy-combustion demonstration reactor. First, operate with the fluidization outlet around

15% open (0.771 kg CO2/hr or 0.005 m/s). This will keep error to a minimum while maximizing

the amount of motivating energy being obtained from the incoming CO2 gas. Second, operate

with the fluidization inlet set to a mass flowrate of roughly 0.119 m/s. This should allow for the

system to deliver the desired 13.6 kg coal/hr while staying outside of the bubbling regime change

over zone. Third use a coal that has a moisture content between 3% and 6%. Finally, if there is

an issue, future operators can, as a last resort, change the diameter of the hopper. A larger

diameter hopper will indirectly shift the velocities at which fluidization regimes change and at

which behaviors examined above manifest. All of these recommendations are subject to change

based upon the fact that the hopper height and diameter will be changed rather dramatically in

the future.

85

Nomenclature

𝐷𝐷 = 𝐼𝐼𝐼𝐼𝑆𝑆𝑒𝑒𝐴𝐴𝐼𝐼𝐿𝐿𝑙𝑙 𝑝𝑝𝐼𝐼𝑝𝑝𝑒𝑒𝑙𝑙𝐼𝐼𝐼𝐼𝑒𝑒 𝑑𝑑𝐼𝐼𝐿𝐿𝑚𝑚𝑒𝑒𝑆𝑆𝑒𝑒𝐴𝐴 (𝑚𝑚) 𝑑𝑑𝑝𝑝 = 𝑝𝑝𝐿𝐿𝐴𝐴𝑆𝑆𝐼𝐼𝑝𝑝𝑙𝑙𝑒𝑒 𝑑𝑑𝐼𝐼𝐿𝐿𝑚𝑚𝑒𝑒𝑆𝑆𝑒𝑒𝐴𝐴 (𝑚𝑚)

𝑑𝑑𝑚𝑚𝑎𝑎𝑏𝑏𝑚𝑚 = 𝑚𝑚𝑒𝑒𝐿𝐿𝐼𝐼 𝑝𝑝𝐿𝐿𝐴𝐴𝑆𝑆𝐼𝐼𝑝𝑝𝑙𝑙𝑒𝑒 𝑠𝑠𝐼𝐼𝑠𝑠𝑒𝑒 (𝑠𝑠𝑢𝑢𝐴𝐴𝑓𝑓𝐿𝐿𝑝𝑝𝑒𝑒𝑣𝑣𝑆𝑆𝑙𝑙𝑢𝑢𝑚𝑚𝑒𝑒

) (𝑚𝑚)

𝑔𝑔 = 𝐿𝐿𝑝𝑝𝑝𝑝𝑒𝑒𝑙𝑙𝑒𝑒𝐴𝐴𝐿𝐿𝑆𝑆𝐼𝐼𝑆𝑆𝐼𝐼 𝑑𝑑𝑢𝑢𝑒𝑒 𝑆𝑆𝑆𝑆 𝑔𝑔𝐴𝐴𝐿𝐿𝑣𝑣𝐼𝐼𝑆𝑆𝑔𝑔 �𝑚𝑚2

𝑠𝑠� 𝐺𝐺𝑠𝑠 = 𝑠𝑠𝑆𝑆𝑙𝑙𝐼𝐼𝑑𝑑𝑠𝑠 𝑚𝑚𝐿𝐿𝑠𝑠𝑠𝑠 𝑓𝑓𝑙𝑙𝑢𝑢𝑓𝑓 �

𝑆𝑆𝑔𝑔𝑚𝑚2 𝑠𝑠

�

𝐻𝐻 = 𝑣𝑣𝑒𝑒𝐴𝐴𝑆𝑆𝐼𝐼𝑝𝑝𝐿𝐿𝑙𝑙 𝑑𝑑𝐼𝐼𝑠𝑠𝑆𝑆𝐿𝐿𝐼𝐼𝑝𝑝𝑒𝑒 (𝑚𝑚) 𝐾𝐾 = 𝑝𝑝𝑆𝑆𝐼𝐼𝑠𝑠𝑆𝑆𝐿𝐿𝐼𝐼𝑆𝑆

𝐿𝐿 = 𝑝𝑝𝐼𝐼𝑝𝑝𝑒𝑒 𝑙𝑙𝑒𝑒𝐼𝐼𝑔𝑔𝑆𝑆ℎ (𝑚𝑚) 𝑀𝑀𝑠𝑠 = 𝑠𝑠𝑆𝑆𝑙𝑙𝐼𝐼𝑑𝑑𝑠𝑠 𝑚𝑚𝐿𝐿𝑠𝑠𝑠𝑠 𝑓𝑓𝑙𝑙𝑆𝑆𝐿𝐿𝐴𝐴𝐿𝐿𝑆𝑆𝑒𝑒 �𝑆𝑆𝑔𝑔𝑠𝑠�

𝐼𝐼 = 𝐼𝐼𝑢𝑢𝑚𝑚𝑏𝑏𝑒𝑒𝐴𝐴 𝑆𝑆𝑓𝑓 𝑏𝑏𝑒𝑒𝐼𝐼𝑑𝑑𝑠𝑠 𝑃𝑃 = 𝑝𝑝𝐴𝐴𝑒𝑒𝑠𝑠𝑠𝑠𝑢𝑢𝐴𝐴𝑒𝑒 (𝑃𝑃𝐿𝐿)

𝑢𝑢 = 𝑠𝑠𝑢𝑢𝑝𝑝𝑒𝑒𝐴𝐴𝑓𝑓𝐼𝐼𝑝𝑝𝐼𝐼𝐿𝐿𝑙𝑙 𝑔𝑔𝐿𝐿𝑠𝑠 𝑣𝑣𝑒𝑒𝑙𝑙𝑆𝑆𝑝𝑝𝐼𝐼𝑆𝑆𝑔𝑔 �𝑚𝑚𝑠𝑠�

𝑢𝑢𝑠𝑠 = 𝑠𝑠𝑢𝑢𝑝𝑝𝑒𝑒𝐴𝐴𝑓𝑓𝐼𝐼𝑝𝑝𝐼𝐼𝐿𝐿𝑙𝑙 𝑠𝑠𝐿𝐿𝑙𝑙𝑆𝑆𝐿𝐿𝑆𝑆𝐼𝐼𝑆𝑆𝐼𝐼 𝑣𝑣𝑒𝑒𝑙𝑙𝑆𝑆𝑝𝑝𝐼𝐼𝑆𝑆𝑔𝑔 �𝑚𝑚𝑠𝑠�

Δ𝑃𝑃𝑡𝑡 = 𝑆𝑆𝑆𝑆𝑆𝑆𝐿𝐿𝑙𝑙 𝑝𝑝𝐴𝐴𝑒𝑒𝑠𝑠𝑠𝑠𝑢𝑢𝐴𝐴𝑒𝑒 𝑑𝑑𝐴𝐴𝑆𝑆𝑝𝑝 𝐿𝐿𝑝𝑝𝑝𝑝𝐴𝐴𝑆𝑆𝑠𝑠𝑠𝑠 𝑆𝑆ℎ𝑒𝑒 𝑠𝑠𝑔𝑔𝑠𝑠𝑆𝑆𝑒𝑒𝑚𝑚 �𝑁𝑁𝑚𝑚2�

𝜇𝜇𝑔𝑔 = 𝑔𝑔𝐿𝐿𝑠𝑠 𝑣𝑣𝐼𝐼𝑠𝑠𝑝𝑝𝑆𝑆𝑠𝑠𝐼𝐼𝑆𝑆𝑔𝑔 �𝑆𝑆𝑔𝑔 𝑚𝑚𝑠𝑠

� 𝜌𝜌𝑔𝑔 = 𝑔𝑔𝐿𝐿𝑠𝑠 𝑑𝑑𝑒𝑒𝐼𝐼𝑠𝑠𝐼𝐼𝑆𝑆𝑔𝑔 �𝑆𝑆𝑔𝑔𝑚𝑚3�

𝜌𝜌𝑝𝑝 = 𝑝𝑝𝐿𝐿𝐴𝐴𝑆𝑆𝐼𝐼𝑝𝑝𝑙𝑙𝑒𝑒 𝑑𝑑𝑒𝑒𝐼𝐼𝑠𝑠𝐼𝐼𝑆𝑆𝑔𝑔 �𝑘𝑘𝑔𝑔𝑚𝑚3�

86

Appendix 1 Load Cell Calibration

Before the load cells obtained from LCM Systems could be used they needed to be

calibrated. The voltages which the load cells output needed to be matched to different weights. 6

different objects of known weight were hung from the load cells and the resulting voltages

recorded. Figure 0000 and Figure 0000 are graphical depictions of the data contained in Table

0000. Trendline equations and R2 values were found for both graphs. Note that both graphs had

an R2 value above 0.99. The trendline equations were used inside of an Opto22 computational

block to transform the voltage signals from the load cells automatically into weights.

Table A.1 - 1 Load Cell Voltage for Specific Weights

Object Actual Weight (kg)

Voltage (mV)

Left LC (25 kg)

Right LC (50 kg)

Nothing 0 0 0

Eyenut and Carabiner 0.117 2.6 0.1

Dustpan 0.5 3.1 0.3

87

Table A.1 - 1 Load Cell Voltage for Specific Weights - Continued

Object Actual Weight (kg)

Voltage (mV)

Left LC (25 kg)

Right LC (50 kg)

300 mm Adjustable Wrench 0.6 3.2 0.4

1-1/4 Wrench 0.75 3.3 0.4

Large Adjustable Wrench 3.95 5.8 1.7

Large Pipe Wrench 4.75 6.5 2.1

Figure A.1 - 1 25 kg Left Load Cell Calibration Curve

y = 0.8082x + 2.6465R² = 0.9977

0

1

2

3

4

5

6

7

0 1 2 3 4 5

Volta

ge (m

V)

Weight (kg)

88

Figure A.1 - 2 50 kg Right Load Cell Calibration Curve

y = 0.4231x + 0.0695R² = 0.9967

0

0.5

1

1.5

2

2.5

0 1 2 3 4 5

Volta

ge (m

V)

Weight (kg)

89

Appendix 2 Load Cell Accuracy

To test the accuracy, or the sensitivity, of the load cells obtained from LCM Systems

various weights were placed on two separate locations throughout the apparatus. Coal will reside

in either the hopper or the primary filter so these were the chosen test locations. 7 objects,

ranging in weight from 0.02 lbs to 1.4 lbs, were placed at these locations. The weight range was

chosen after calculating the volume of the hopper and noting that only about 3 lbs of coal could

be stored inside of it. Figure 3 contains the results gathered. The column labelled “Mass (lbs)”

refers to the actual weight of the object. “Load Cell Avg” refers to the average of load cell

readings taken over the course of several seconds after the placement of the object on the hopper

or the filter housing. The “Calculated Mass” column refers to the mass which was calculated

when the average of an empty location’s load cell readings were subtracted from the number

recorded in the “LC Avg” column. The “% Error” for each object was calculated using Equation

5.

� 𝐶𝐶𝑏𝑏𝑠𝑠𝑐𝑐𝑢𝑢𝑠𝑠𝑏𝑏𝑡𝑡𝑎𝑎𝑑𝑑 𝑀𝑀𝑏𝑏𝑠𝑠𝑠𝑠−𝐾𝐾𝑚𝑚𝑜𝑜𝑤𝑤𝑚𝑚 𝑀𝑀𝑏𝑏𝑠𝑠𝑠𝑠𝐾𝐾𝑚𝑚𝑜𝑜𝑤𝑤𝑚𝑚 𝑀𝑀𝑏𝑏𝑠𝑠𝑠𝑠

� ∗ 100 = % 𝐸𝐸𝐴𝐴𝐴𝐴𝑆𝑆𝐴𝐴 (A.2)

90

Table A.2 - 1 Error for Weight of Objects on Hopper

Hopper

Object Mass (lb) L. Cell Avg. Calc. % Error

Screw 0.024 25.314 0.012 49.5

Vial 0.016 25.306 0.004 77.8

Nipple 0.054 25.353 0.051 4.53

Eyenut 0.047 25.335 0.033 30.4

Hex Plug 0.481 25.797 0.495 2.79

394.08 g 0.869 26.183 0.881 1.41

618.72 g 1.364 26.679 1.377 0.95

Table A.2 - 2 Error for Weight of Objects on Primary Filter Point

Primary Filter Point

Object Mass (lb) L. Cell Avg. Calc. Mass % Error

Screw 0.024 38.992 0.041 72.5

Vial 0.016 38.979 0.027 67.7

Nipple 0.054 38.997 0.046 14.9

Eyenut 0.047 39.009 0.057 22.7

Hex Plug 0.481 39.375 0.423 12

394.08 g 0.869 39.728 0.776 10.7

618.72 g 1.364 40.192 1.24 9.08

91

A few things of note:

1) The % error recorded for many of the objects is not below the desired 5% which most

engineers hold as a good minimum standard.

2) 4 out of 7 of the objects placed on the hopper did fall below the 5% mark while none

of the objects placed on the filter housing had errors below 5%

To explain point 1 bear in mind that the resolution for the 25-kg load cell model being used is in

the 0.01 lb range. Therefore, we are operating at the limits of the resolution offered by this load

cell model. We note that the nipple placed on the hopper did have a percent error below that of

5% so it is possible to resolve objects on that scale. Also, fidelity increases as the weights being

placed become heavier. We are fully aware that this error will perpetuate throughout our coal

mass flowrate calculations. Further research into more accurate load cells and alternative

methods for calculating weight are being explored right now. To explain point 2 the reader

should bear in mind that there are quite a few heavier objects on the filter housing side of the

apparatus in comparison to the hopper side. It is harder to see small objects placed on the filter

housing side compared to when they are placed on the hopper side. The data backs this

conclusion up. Even in the 1 lb mass range we are getting into the less than 5% error range so we

believe that resolution is satisfactory even on the filter housing side provided that data taking is

meticulous and the analysis undertaken later is careful.

92

Appendix 3 MFC Impact on Load Cell Readings

A concern was brought up about if the flexible metal hoses used to convey CO2 between

the mass flow controllers and the CO2 injection ports on the apparatus would have some effect

on the measurements taken by the load cells, especially as CO2 flowrates were changed during

experimentation. During shakedown tests mass flow controllers manipulated CO2 flowrates

through their entire range and load cell changes were minimal. Data is being taken and graphed

to supplement this appendix in the future.

93

Appendix 4 C = Closed Raw Data

Test # A (kg/hr) C (kg/hr) D (kg/hr)18 1.814369 0 7.94053599 1.831174 0 8.783199105 1.879372 0 14.18507111 1.85909 0 7.61754427 2.379284 0 9.64978798 2.439003 0 19.24419

104 2.464021 0 13.21509110 2.465068 0 21.5625819 2.721554 0 7.94617297 3.045382 0 23.50257

103 3.066181 0 26.08895109 3.070998 0 27.2964530 3.585464 0 13.3900596 3.658671 0 29.51155102 3.66901 0 22.91802108 3.66154 0 23.6952720 4.082331 0 16.3293395 4.25358 0 18.27265

101 4.281879 0 27.71385107 4.280372 0 42.0285732 4.812906 0 22.0365194 4.860918 0 30.14645

100 4.904644 0 27.12261106 4.908854 0 52.18721

94

Appendix 4.1 Summarized Raw Data

Average CO2

Flowrate (kg/hr)

Average Coal

Flowrate (kg/hr) E (kg/hr)

St. Dev of Coal

Flowrate (kg)

1.846001 9.631587 1.846001 3.075172.436844 15.91791 2.436844 5.4626312.976028 21.20853 2.976028 8.9820943.643671 22.37872 3.643671 6.6757674.224541 26.0861 4.224541 11.733954.87183 32.87319 4.87183 13.30375

95

Appendix 4.2 C = Closed Raw Coal Loading/Movement Data

Test #

1. Movedto

Primary (kg)

2. Movedto

Secondary (kg)

3. MovedPost-

Flushing (kg) 1 + 2 + 3

Loaded Before

Experiment (kg)

Percent Moved

% Moved to

Primary

% Moved to

Secondary18 0.652999 0.008 0.134 0.794999 0.9549989 83.24607 82.13836 1.006289399 0.765 0.012 0.127 0.904 0.9659988 93.58189 84.62389 1.3274336105 0.482 0.001 0.261 0.744 0.843999 88.15176 64.78495 0.1344086111 0.7 0.024 0.157 0.881 0.9259989 95.1405 79.45516 2.724177127 0.812999 0.013 0.086 0.911999 0.8849989 103.0508 89.14474 1.425438698 0.833 0 0.091 0.924 0.9339989 98.92945 90.15152 0

104 0.741 0 0.113 0.854 0.9219989 92.62484 86.76815 0110 0.503 0.214 0.236 0.953 0.850999 111.986 52.78069 22.45540419 0.708999 0 0.149 0.857999 0.870999 98.50746 82.63403 097 0.494999 0.0779999 0.294 0.866999 0.9019989 96.11973 57.09343 8.9965398

103 0.832 0.016 0.086 0.934 0.9499989 98.31591 89.07923 1.7130621109 0.519 0.025 0.163 0.707 0.9309989 75.93994 73.40877 3.536067930 0.832999 0.012 0.033 0.877999 0.9069989 96.80265 94.87472 1.366742696 0.578999 0.1249999 0.167 0.870999 0.9189989 94.77693 66.47532 14.35132102 0.597 0.068 0.185 0.85 0.9259989 91.79277 70.23529 8108 0.792 0.002 0.054 0.848 0.872999 97.13643 93.39623 0.235849120 0.710999 0.002 0.138 0.850999 0.8949989 95.0838 83.54877 0.235017695 0.604999 0.2339997 0.189 1.027999 0.9029989 113.8427 58.85214 22.762646

101 0.809 0 0.046 0.855 0.9449989 90.4763 94.61988 0107 0.502 0.057 0.286 0.845 0.8919989 94.73105 59.40828 6.745562132 0.758999 0.004 0.053 0.815999 0.7889991 103.4221 93.01471 0.490196194 0.694999 0.033 0.195 0.922999 0.9589989 96.24609 75.29794 3.5752979

100 1.182 0.057 0.253 1.492 0.7479991 199.4655 79.22252 3.8203753106 0.655 0.006 0.201 0.862 0.8849989 97.40125 75.98608 0.6960557

96

Appendix 5 C = 0.77 kg CO2/hr Raw Data

Test # A (kg/hr) C (kg/hr) D (kg/hr)21 1.814369 0.76918654 2.2264069475 1.886899 0.76918654 2.8704064576 1.814369 0.76918654 3.788527393 1.829377 0.76918652 2.3799928229 2.379284 0.76918654 5.6805206273 2.441923 0.76918654 5.8422697374 2.450581 0.76918654 6.716478392 2.436084 0.76918652 9.6417227144 2.781511 0.76918654 6.7331958370 2.759195 0.76918654 9.3809615372 2.737333 0.76918654 11.238417791 2.741954 0.76918652 7.4176822123 2.721554 0.76918654 10.288207266 3.096002 0.76918654 10.770405768 3.104262 0.76918654 8.7199912690 3.034914 0.76918652 8.3838022139 3.401943 0.76918654 12.534353664 3.352981 0.76918654 11.551487265 3.402561 0.76918654 11.475637589 3.331135 0.76918652 9.7700757428 3.585464 0.76918654 11.421088862 3.818297 0.76918654 14.778039463 3.676822 0.76918654 23.027682688 3.661284 0.76918652 8.8635305725 4.082331 0.76918654 7.5713638461 4.364603 0.76918654 23.475804760 4.338379 0.76918654 17.65122587 4.26594 0.76918652 15.566396659 4.923387 0.76918654 18.659964633 4.812906 0.76918654 16.068857657 4.764307 0.76918654 31.370702358 5.056389 0.76918654 25.154500186 4.855466 0.76918652 18.48040141 5.443108 0.76918654 36.018723455 5.474266 0.76918654 27.923146356 5.421658 0.76918654 33.365442885 5.469693 0.76918654 24.3773512

97

Appendix 5.1 C = 0.771 kg CO2/hr Summarized Raw Data

Average CO2

Flowrate (kg/hr)

Average Coal

Flowrate (kg/hr) E (kg/hr)

St. Dev of Coal

Flowrate (kg)

1.836254 2.816333 1.065254 0.7039162.426968 6.970248 1.655968 1.8381972.754998 8.692564 1.983998 2.0346752.989183 9.540602 2.218183 1.1666073.372155 11.33289 2.601155 1.1480513.685467 14.52259 2.914467 6.1656614.262813 16.0662 3.491813 6.5784144.882491 21.94689 4.111491 6.2543725.452181 30.42117 4.681181 5.252593

98

Appendix 5.2 C = 0.771 kg CO2/hr Raw Coal Loading/Movement Data

Test #

1. Movedto

Primary (kg)

2. Movedto

Secondary (kg)

3. MovedPost-

Flushing (kg) 1 + 2 + 3

Loaded Before

Experiment (kg)

Percent Moved

% Moved to

Primary

% Moved to

Secondary21 0.708999 0.011 0.132 0.851999 0.86099898 98.9547 83.21596 1.291079875 0.613999 0.024 0.244 0.881999 0.84999899 103.7647 69.61451 2.721088476 0.749999 0.008 0.083 0.840999 0.91899891 91.51251 89.17955 0.951248593 0.657999 0.017 0.147 0.821999 0.88299895 93.09173 80.04866 2.068126529 0.758999 0 0.077 0.835999 0.87899895 95.10808 90.78947 073 0.593999 0.027 0.184 0.804999 0.83599901 96.29187 73.78882 3.354037374 0.560999 0.01 0.28 0.850999 0.73899912 115.1556 65.92244 1.175088192 0.714999 0.062 0.134 0.910999 0.97499884 93.4359 78.48518 6.80570844 0.666999 0.038 0.143 0.847999 0.95299887 88.98216 78.65566 4.481132170 0.619999 0.013 0.203 0.835999 0.86699897 96.42445 74.16268 1.555023972 0.523999 0.019 0.371 0.913999 0.88399895 103.3937 57.33042 2.078774691 0.752999 0.029 0.098 0.879999 0.98499883 89.3401 85.56818 3.295454523 0.778999 0.07 0.032 0.880999 0.80799904 109.0347 88.42225 7.945516566 0.600999 0.087 0.186 0.873999 0.90299893 96.78848 68.7643 9.954233468 0.565999 0 0.319 0.884999 0.88699895 99.77452 63.9548 090 0.571999 0.086 0.239 0.896999 0.840999 106.6587 63.76812 9.587513939 0.851999 0 0.022 0.873999 0.93099889 93.87755 97.48284 064 0.780999 0.038 0.06 0.878999 0.87599896 100.3425 88.85097 4.323094465 0.592999 0.055 0.203 0.850999 0.88199895 96.48526 69.68273 6.462984789 0.574999 0.001 0.175 0.750999 0.84899899 88.45701 76.56458 0.133155828 0.768999 0.016 0.095 0.879999 0.93099889 94.52202 87.38636 1.818181862 0.777999 0.067 0.077 0.921999 0.93799888 98.29424 84.38178 7.266811363 0.762999 0.011 0.062 0.835999 0.89399894 93.5123 91.26794 1.315789588 0.590999 0.028 0.24 0.858999 0.86399897 99.4213 68.80093 3.259604225 0.694999 0 0.148 0.842999 0.93999888 89.68085 82.44365 061 0.625999 0.056 0.222 0.903999 0.93699889 96.47812 69.24779 6.194690360 0.631999 0.028 0.172 0.831999 0.87399896 95.19451 75.96154 3.365384687 0.413 0.046 0.301 0.759999 0.78299907 97.06258 54.34211 6.052631659 0.806999 0.024 0.071 0.901999 0.93299889 96.67738 89.46785 2.660753933 0.728999 0.019 0.078 0.825999 0.87799896 94.07745 88.25666 2.300242157 0.664999 0.015 0.185 0.864999 0.9209989 93.91965 76.87861 1.73410458 0.784999 0.022 0.082 0.888999 0.91999891 96.63043 88.30146 2.474690786 0.563999 0.006 0.143 0.712999 0.76699909 92.95958 79.10238 0.841514341 0.658999 0.032 0.115 0.805999 0.84799899 95.04717 81.76179 3.970223355 0.603999 0.121 0.203 0.927999 1.00099881 92.70729 65.08621 13.03879356 0.673999 0.029 0.179 0.881999 0.91499891 96.39344 76.41723 3.287981985 0.613999 0.003 0.125 0.741999 0.80099905 92.63421 82.74933 0.4043127

99

Appendix 6 C = 1.528 kg CO2/hr Raw Data

Test # A (kg/hr) C (kg/hr) D (kg/hr)77 2.440599 1.538373 1.228883

112 2.475644 1.538373 6.73908542 2.721554 1.538373 4.02130343 2.721554 1.538373 3.25280224 2.721554 1.538373 5.0182878 3.039538 1.538373 4.02723337 3.340658 1.538373 4.57078554 3.303661 1.538373 4.81548653 3.386587 1.538373 7.62035279 3.365007 1.538373 5.95175831 3.585464 1.538373 10.5250652 3.666978 1.538373 10.7025951 3.655125 1.538373 9.19496680 3.665519 1.538373 6.59745150 4.228194 1.538373 13.8047936 4.213771 1.538373 12.0347149 4.265991 1.538373 14.2797181 4.272133 1.538373 16.0390348 4.799039 1.538373 16.7181234 4.812906 1.538373 17.9486547 4.832355 1.538373 18.1394882 4.865926 1.538373 12.9075146 5.443108 1.538373 16.5055438 5.443108 1.538373 18.5022845 5.457698 1.538373 19.8863383 5.47178 1.538373 16.92056

100

Appendix 6.1 C = 1.538 kg CO2/hr Summarized Raw Data

Average CO2

Flowrate (kg/hr)

Average Coal

Flowrate (kg/hr) E (kg/hr)

St. Dev of Coal

Flowrate (kg)

2.458121 3.983984 0.920121 3.8963012.80105 4.079904 1.26305 0.723615

3.348978 5.739595 1.810978 1.6944523.643272 9.255018 2.105272 1.8951484.245022 14.03956 2.707022 1.6462154.827556 16.42844 3.289556 2.4303345.453924 17.95368 3.915924 1.549253

101

Appendix 6.2 C = 1.538 kg CO2/hr Raw Coal Loading/Movement Data

Test #

1. Movedto

Primary (kg)

2. Movedto

Secondary (kg)

3. MovedPost-

Flushing (kg) 1 + 2 + 3

Loaded Before

Experiment (kg)

Percent Moved

% Moved to

Primary

% Moved to

Secondary77 0.435999 0.0839999 0.34 0.859999 0.9229989 93.17443 50.69767 9.7674419

112 0.314 0.035 0.428 0.777 0.9349989 83.1017 40.41184 4.504504542 0.654999 0.014 0.138 0.806999 0.801999 100.6234 81.16481 1.734820343 0.582999 0.0799999 0.195 0.857999 0.9129989 93.9759 67.94872 9.324009324 0.637999 0.014 0.19 0.841999 0.822999 102.3086 75.77197 1.662707878 0.454999 0.027 0.346 0.827999 0.861999 96.05568 54.95169 3.260869637 0.586999 0.1429998 0.122 0.851999 0.8969989 94.98328 68.89671 16.78403854 0.683999 0.0779999 0.098 0.859999 0.9079989 94.71366 79.53488 9.069767453 0.685999 0.1039999 0.098 0.887999 0.9119989 97.36842 77.25225 11.71171279 0.461999 0.0439999 0.33 0.835999 0.867999 96.31336 55.26316 5.263157931 0.735999 0.007 0.074 0.816999 0.9119989 89.58333 90.08568 0.856793152 0.658999 0.0829999 0.132 0.873999 0.9319989 93.77682 75.40046 9.496567551 0.632999 0.0869999 0.129 0.848999 0.876999 96.8073 74.5583 10.2473580 0.501999 0.0709999 0.309 0.881999 0.8999989 98 56.9161 8.049886650 0.562999 0.2319997 0.189 0.983999 1.0289988 95.62682 57.21545 23.57723636 0.687999 0.0859999 0.103 0.876999 0.8869989 98.8726 78.44926 9.806157449 0.614999 0.0799999 0.14 0.834999 0.829999 100.6024 73.65269 9.580838381 0.491999 0.014 0.313 0.818999 0.8959989 91.40625 60.07326 1.709401748 0.619999 0.0989999 0.106 0.824999 0.8879989 92.90541 75.15152 1234 0.660999 0.0669999 0.155 0.882999 0.875999 100.7991 74.85844 7.58776947 0.553999 0.1089999 0.201 0.863999 0.9009989 95.89345 64.12037 12.61574182 0.518999 0.021 0.286 0.825999 0.855999 96.49533 62.83293 2.542372946 0.708999 0.021 0.131 0.860999 0.8859989 97.17833 82.34611 2.439024438 0.710999 0.1569998 0.085 0.952999 0.9659989 98.65424 74.60651 16.47429245 0.581999 0.0619999 0.277 0.920999 0.9629989 95.63863 63.19218 6.731813283 0.613999 0.042 0.173 0.828999 0.842999 98.33926 74.06514 5.066345

102

Appendix 7 E = 2.92 kg CO2/hr Raw Data

Test # A (kg/hr) C (kg/hr) D (kg/hr)115 5.51 2.59 29.51116 4.90 1.97 20.79117 4.60 1.67 14.39

118.2 4.28 1.38 17.78119 3.98 1.08 18.46120 3.68 0.79 19.58121 3.38 0.51 18.04122 5.48 2.59 32.32123 4.95 1.97 24.49

124.2 4.61 1.67 30.11125.2 4.28 1.38 24.13126 3.97 1.08 23.03127 3.65 0.79 16.12128 3.36 0.51 16.36145 5.53 2.59 25.53144 4.88 1.97 16.26146 4.56 1.67 19.33143 4.25 1.38 14.94147 3.95 1.08 18.34148 3.67 0.79 14.22149 3.35 0.51 15.53136 5.58 2.59 23.56137 4.95 1.97 15.25138 4.58 1.67 18.20139 4.25 1.38 27.26140 3.95 1.08 18.55141 3.64 0.79 17.31142 3.35 0.51 18.25

103

Appendix 7.2 E = 2.92 kg CO2/hr Summarized Raw Data

Average CO2

Flowrate (kg/hr)

Average C (kg/hr)

Average Coal

Flowrate (kg/hr)

St. Dev of Coal

Flowrate (kg)

Average E (kg/hr)

5.53 2.59 27.73 3.93 2.944.92 1.97 19.20 4.27 2.944.59 1.67 20.51 6.74 2.924.26 1.38 21.03 5.66 2.883.97 1.08 19.60 2.29 2.893.66 0.79 16.81 2.24 2.873.36 0.51 17.05 1.32 2.85

104

Appendix 7.3 E = 2.92 kg CO2/hr Raw Coal Loading/Movement Data

Test #

1. Movedto

Primary (kg)

2. Movedto

Secondary (kg)

3. MovedPost-

Flushing (kg) 1 + 2 + 3

Loaded Before

Experiment (kg)

Percent Moved

% Moved to

Primary

% Moved to

Secondary115116 0.55 0.08 0.16 0.80 0.91 87.38 69.72 10.43117 0.52 0.19 0.10 0.81 0.86 93.98 63.67 23.89

118.2 0.00 0.00 0.59 0.59 0.88 67.05 0.00 0.00119 0.70 0.18 0.05 0.93 0.90 102.54 75.00 19.72120 0.43 0.21 0.25 0.88 0.88 100.00 48.30 23.36121 0.58 0.01 0.24 0.82 0.90 90.94 69.99 0.97122 0.77 0.02 0.10 0.89 0.91 98.02 86.55 2.02123 0.55 0.13 0.13 0.81 0.91 89.13 68.35 16.13

124.2 0.43 0.13 0.29 0.85 0.87 97.59 50.47 15.65125.2 0.59 0.20 0.05 0.84 0.85 99.17 70.56 23.84126 0.00 0.00 0.71 0.71 0.82 86.18 0.00 0.00127 0.47 0.07 0.28 0.82 0.98 83.84 57.32 8.17128 0.32 0.12 0.42 0.86 0.82 104.39 37.15 13.67145 0.43 0.23 0.24 0.91 0.92 99.13 47.52 25.91144 0.63 0.10 0.12 0.85 0.92 93.00 74.27 11.75146 0.49 0.20 0.20 0.88 0.92 96.61 55.77 22.17143 0.42 0.31 0.13 0.86 0.92 94.32 49.02 35.69147 0.53 0.01 0.33 0.87 0.92 94.97 60.87 1.04148 0.54 0.12 0.21 0.87 0.92 94.75 62.51 13.38149 0.52 0.17 0.17 0.86 0.92 94.43 60.65 19.21136 0.48 0.22 0.20 0.90 0.96 93.37 53.39 24.42137 0.00 0.28 0.44 0.72 0.92 78.52 0.00 38.33138 0.71 0.03 0.15 0.89 1.02 87.37 79.48 3.25139 0.09 0.30 0.51 0.91 0.57 160.67 10.21 33.26140 0.72 0.08 0.10 0.90 1.03 87.44 80.51 8.57141 0.51 0.26 0.10 0.88 0.83 105.29 58.40 30.17142 0.49 0.27 0.14 0.89 0.85 104.93 54.92 29.64

105

Appendix 8 Sufco 2010 Raw Data

Test # A (kg/hr) C (kg/hr) D (kg/hr)187 3.10 0.77 3.83191 3.13 0.77 13.42204 3.14 0.77 3.77188 3.69 0.77 6.86192 3.74 0.77 20.35205 3.76 0.77 18.26189 4.38 0.77 12.35193 4.38 0.77 11.40190 4.99 0.77 33.13194 4.99 0.77 12.18

106

Appendix 8.2 Sufco 2010 Summarized Raw Data

Average CO2

Flowrate (kg/hr)

Average Coal

Flowrate (kg/hr)

St. Dev of Coal

Flowrate (kg)

3.13 7.00 12.243.73 15.15 16.364.38 11.88 1.484.99 22.66 32.67

107

Appendix 8.3 Sufco 2010 Raw Coal Loading/Movement Data

Test #

1. Movedto

Primary (kg)

2. Movedto

Secondary (kg)

3. MovedPost-

Flushing (kg) 1 + 2 + 3

Loaded Before

Experiment (kg)

Percent Moved

% Moved to

Primary

% Moved to

Secondary187191 0.52 0.39 0.15 1.07 1.05 101.91 48.92 36.83204 0.28 0.38 0.32 0.99 0.83 118.73 28.51 38.62188 0.09 0.39 0.23 0.71 0.94 75.96 12.10 55.13192 0.50 0.39 0.14 1.03 1.09 94.52 48.50 38.07205 0.40 0.30 0.23 0.94 1.00 93.89 43.18 32.20189193 0.22 0.39 0.14 0.75 1.11 67.75 29.12 52.39190 0.35 0.42 0.28 1.05 1.11 94.49 33.81 39.64194 0.28 0.33 0.13 0.75 0.73 102.18 37.33 44.67

108

Appendix 9 Clean Hopper Raw Data

Test # A (kg/hr) C (kg/hr) D (kg/hr)155 3.07 1.54 5.25160 3.12 1.54 2.71153 3.50 1.54 20.75164 3.52 1.54 12.71156 3.69 1.54 14.02161 3.63 1.54 18.61150 3.95 1.54 17.57151 4.00 1.54 19.52152 4.16 1.54 17.98163 4.11 1.54 12.05165 4.21 1.54 14.59166 4.14 1.54 9.11168 4.14 1.54 10.15154 4.27 1.54 26.26157 4.24 1.54 28.05158 4.95 1.54 35.97162 4.76 1.54 35.44

109

Appendix 9.2 Clean Hopper Summarized Raw Data

Average CO2

Flowrate (kg/hr)

Average Coal

Flowrate (kg/hr)

St. Dev of Coal

Flowrate (kg)

1.40 1.81 0.811.59 7.59 2.581.66 7.40 1.471.80 8.41 0.631.88 6.09 1.711.93 12.32 0.572.20 16.20 0.17

110

Appendix 9.3 Clean Hopper Raw Coal Loading/Movement Data

Test #

1. Movedto

Primary (kg)

2. Movedto

Secondary (kg)

3. MovedPost-

Flushing (kg) 1 + 2 + 3

Loaded Before

Experiment (kg)

Percent Moved

% Moved to

Primary

% Moved to

Secondary155 0.55 0.12 0.28 0.95 0.90 104.99 57.66 12.57160 0.53 0.20 0.18 0.91 0.85 106.93 58.24 21.98153 0.47 0.19 0.12 0.79 0.85 92.70 60.23 24.14164 0.49 0.33 0.10 0.92 0.98 93.80 53.52 35.97156 0.56 0.03 0.28 0.87 0.90 96.22 64.32 3.46161 0.53 0.23 0.25 1.00 0.98 101.83 52.50 22.55150 0.55 0.10 0.18 0.83 0.91 90.97 65.98 12.11151 0.52 0.07 0.25 0.85 0.84 100.71 61.82 8.16152 0.65 0.02 0.09 0.77 0.91 84.40 85.29 2.73163 0.60 0.05 0.28 0.93 1.02 91.00 64.30 5.05165 0.51 0.26 0.15 0.92 0.93 98.82 55.22 28.48166 0.56 0.20 0.20 0.96 0.96 100.00 58.34 20.93168 0.56 0.05 0.29 0.90 0.94 95.96 62.31 5.54154 0.66 0.09 0.08 0.84 0.84 98.82 79.28 11.14157 0.48 0.00 0.39 0.87 1.04 83.64 55.58 0.00158 0.51 0.25 0.16 0.91 0.90 101.22 55.69 26.91162 0.58 0.03 0.28 0.90 0.93 97.08 64.40 3.89

111

Appendix 10 Black Thunder Raw Data

Test # A (kg/hr) C (kg/hr) D (kg/hr)173 3.47 0.77 10.77

174 Tune 3.38 0.77 6.42174 4.03 0.77 6.71

176.2 4.09 0.77 7.33175 4.67 0.77 8.24177 4.69 0.77 9.08179 5.31 0.77 7.03

112

Appendix 10.1 Black Thunder Summarized Raw Data

Average CO2

Flowrate (kg/hr)

Average Coal

Flowrate (kg/hr)

St. Dev of Coal

Flowrate (kg)

3.43 8.60 3.074.06 7.02 0.434.68 8.66 0.595.31 7.03

113

Appendix 10.2 Black Thunder Raw Coal Loading/Movement Data

Test #

1. Movedto

Primary (kg)

2. Movedto

Secondary (kg)

3. MovedPost-

Flushing (kg) 1 + 2 + 3

Loaded Before

Experiment (kg)

Percent Moved

% Moved to

Primary

% Moved to

Secondary173 0.48 0.00 0.31 0.79 0.84 93.91 60.99 0.25

174 Tune 0.53 0.03 0.30 0.87 0.81 107.28 61.22 3.80174 0.39 0.36 0.07 0.83 0.85 96.96 47.65 43.67

176.2 0.57 0.06 0.15 0.78 0.97 80.37 73.52 7.46175 0.59 0.16 0.13 0.88 0.96 91.88 66.59 18.23177 0.34 0.43 0.11 0.88 0.91 97.04 38.46 48.64179 0.64 0.10 0.10 0.84 0.89 94.71 76.13 12.00

114

Appendix 11 Coal Moisture Content Raw Data

CoalPre-Heat

(g)Post-Heat

(g) Moisture %Average

Moisure %6.14 5.03 18.083.70 3.00 18.922.84 2.30 19.012.81 2.27 19.222.83 2.21 21.982.18 1.76 19.314.98 4.67 6.207.21 6.74 6.552.20 2.05 6.826.09 5.74 5.754.95 4.67 5.663.78 3.57 5.566.44 6.37 1.094.78 4.72 1.372.60 2.58 1.116.30 6.24 0.955.39 5.34 0.939.03 8.95 0.895.48 5.42 1.093.63 3.60 0.833.75 3.73 0.535.03 4.74 5.804.05 3.82 5.683.14 2.96 5.876.46 6.11 5.426.72 6.35 5.513.90 3.71 4.875.52 5.20 5.803.87 3.66 5.432.48 2.35 5.245.68 5.43 4.465.60 5.35 4.396.43 6.17 4.166.02 5.76 4.366.06 5.80 4.283.78 3.62 4.266.32 5.91 6.476.85 6.42 6.266.13 5.74 6.335.62 5.28 6.085.06 4.76 5.974.54 4.27 5.915.41 5.07 6.276.79 6.37 6.244.74 4.45 6.12

4.32

6.18

Sufco 10

Sufco 16

Pittsburgh 8 (Bag)

Pittsburgh 8 (Drum)

0.98

5.51

6.09Illinois 6

Black Thunder 19.42

115

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