chemical processing and design

Encyclopedia of
Chemical Processing and
Design: 69 Supplement 1

Rayford G. Anthony
John J. McKetta

Marcel Dekker, Inc.


Encyclopedia of
Chemical Processing
and Design
EDITOR

Rayford G. Anthony

SENIOR ADVISORY EDITOR

John J. McKetta

69

Supplement 1


Library of Congress Cataloging in Publication Data
Main entry under title:
Encyclopedia of chemical processing and design.
Includes bibliographic references.
1. Chemical engineering—Dictionaries 2.

Technical—Dictionaries. I. McKetta, John J.
II. Cunningham, William Aaron.
Tp9.E66
660.2′8′003
ISBN: 0-8247-2621-9

Chemistry,
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Contributors to Volume 69
Steve Chum, Ph.D. Research Fellow, The Dow Chemical Company, Polyolefins
Research, Freeport, Texas: Structure, Properties, and Applications of Polyolefins
Produced by Single-Site Catalyst Technology
Ray A. Cocco, Ph.D. Senior Specialist, The Dow Chemical Company, Midland,
Michigan: Circulating Fluidized Bed Reactors: Basic Concepts and Hydrodynamics
David M. Fishbach, P.E. Senior Consulting Engineer, Starfire Electronic Development & Marketing, Ltd., Bloomfield Hills, Michigan: Nanophase Materials in
Chemical Process
Avery N. Goldstein, Ph.D. Research Director, Starfire Electronics Development & Marketing, Ltd., Bloomfield Hills, Michigan: Nanophase Materials in
Chemical Process
Manfred Grove Senior Partner, Intermacom A.G., Technology Consultants,
Auerich, Switzerland: Introduction to the Selective Catalytic Reduction Technology
Dennis Hendershot Rohm and Haas Company, Bristol, Pennsylvania: Fundamentals of Process Safety and Risk Management
Trevor A. Kletz Process Safety Consultant, Cheshire, United Kingdom: Fundamentals of Process Safety and Risk Management
Fu-Ming Lee, Ph.D. Director of Technology, GTC Technology Corporation,
Houston, Texas: Recent Development of Extractive Distillation: A Distillation Alternative
Jim Makris Director, Chemical Emergency Preparedness and Prevention Office,
U.S. Environmental Protection Agency, Washington, D.C.: Process Safety and
Risk Management Regulations: Impact on Process Safety
M. Sam Mannan, Ph.D., P.E. Associate Professor of Chemical Engineering,
Mary Kay O’Connor Process Safety Center, Texas A&M University, College Station, Texas: Fundamentals of Process Safety and Risk Management; Process Safety
and Risk Management Regulations: Impact on Process Industry
Rajen M. Patel, Ph.D. Technical Leader, The Dow Chemical Company, Polyolefins Research, Freeport, Texas: Structures, Properties, and Applications of Polyolefins Produced by Single-Site Catalyst Technology
H. James Overman Dow Chemical Company, Freeport, Texas: Process Safety
and Risk Management Regulations: Impact on Process Industry
iii

iv

Contributors to Volume 69
Michael V. Pishko, Ph.D. Assistant Professor, Department of Chemical Engineering, Texas A&M University, College Station, Texas: Recent Advances in Biomaterials
Alan W. Weimer, Ph.D., P.E. Professor of Chemical Engineering, University
of Colorado, Boulder, Colorado: Effect of Pressure and Temperature in Bubbling
Fluidized Beds


CONTENTS OF VOLUME 69
Contributors to Volume 69

iii

Conversion to SI Units

vii

Bringing Costs up to Date

ix

Circulating Fluidized Bed Reactors: Basic Concepts and
Hydrodynamics
Ray A. Cocco

1

Effect of Pressure and Temperature in Bubbling Fluidized Beds

Alan W. Weimer

35

Fundamentals of Process Safety and Risk Management
M. Sam Mannan, Dennis Hendershot, and Trevor A. Kletz

49

Introduction to the Selective Catalytic Reduction Technology
Manfred Grove

94

Nanophase Materials in Chemical Process
Avery N. Goldstein and David M. Fishbach

150

Process Safety and Risk Management Regulations: Impact on
Process Industry
M. Sam Mannan, Jim Makris, and H. James Overman

168

Recent Advances in Biomaterials
Michael V. Pishko

194

Recent Development of Extractive Distillation: A Distillation
Alternative
Fu-Ming Lee

207

Structure, Properties, and Applications of Polyolefins Produced by
Single-Site Catalyst Technology
Rajen M. Patel and Steve Chum

231

v



Conversion to SI Units

To convert from

To

Multiply by

acre
angstrom
are
atmosphere
bar
barrel (42 gallon)

Btu (International Steam Table)
Btu (mean)
Btu (thermochemical)
bushel
calorie (International Steam Table)
calorie (mean)
calorie (thermochemical)
centimeter of mercury
centimeter of water
cubit
degree (angle)
denier (international)
dram (avoirdupois)
dram (troy)
dram (U.S. fluid)
dyne
electron volt
erg
fluid ounce (U.S.)
foot
furlong
gallon (U.S. dry)
gallon (U.S. liquid)
gill (U.S.)
grain
gram
horsepower
horsepower (boiler)
horsepower (electric)
hundred weight (long)

hundred weight (short)
inch
inch mercury
inch water
kilogram force
kip
knot (international)
league (British nautical)
league (statute)

square meter (m 2 )
meter (m)
square meter (m 2 )
newton/square meter (N/m 2 )
newton/square meter (N/m 2 )
cubic meter (m 3 )
joule (J)
joule (J)
joule (J)
cubic meter (m 3 )
joule (J)
joule (J)
joule (J)
newton/square meter (N/m 2 )
newton/square meter (N/m 2 )
meter (m)
radian (rad)
kilogram/meter (kg/m)
kilogram (kg)
kilogram (kg)

cubic meter (m 3 )
newton (N)
joule (J)
joule (J)
cubic meter (m 3 )
meter (m)
meter (m)
cubic meter (m 3 )
cubic meter (m 3 )
cubic meter (m 3 )
kilogram (kg)
kilogram (kg)
watt (W)
watt (W)
watt (W)
kilogram (kg)
kilogram (kg)
meter (m)
newton/square meter (N/m 2 )
newton/square meter (N/m 2 )
newton (N)
newton (N)
meter/second (m/s)
meter (M)
meter (m)

4.046 ϫ 10 3
1.0 ϫ 10Ϫ10
1.0 ϫ 10 2
1.013 ϫ 10 5

1.0 ϫ 10 5
0.159
1.055 ϫ 10 3
1.056 ϫ 10 3
1.054 ϫ 10 3
3.52 ϫ 10Ϫ2
4.187
4.190
4.184
1.333 ϫ 10 3
98.06
0.457
1.745 ϫ 10Ϫ2
1.0 ϫ 10Ϫ7
1.772 ϫ 10Ϫ3
3.888 ϫ 10Ϫ3
3.697 ϫ 10Ϫ6
1.0 ϫ 10Ϫ5
1.60 ϫ 10Ϫ19
1.0 ϫ 10Ϫ7
2.96 ϫ 10Ϫ5
0.305
2.01 ϫ 10 2
4.404 ϫ 10Ϫ3
3.785 ϫ 10Ϫ3
1.183 ϫ 10Ϫ4
6.48 ϫ 10Ϫ5
1.0 ϫ 10Ϫ3
7.457 ϫ 10 2
9.81 ϫ 10 3

7.46 ϫ 10 2
50.80
45.36
2.54 ϫ 10Ϫ2
3.386 ϫ 10 3
2.49 ϫ 10 2
9.806
4.45 ϫ 10 3
0.5144
5.559 ϫ 10 3
4.83 ϫ 10 3

vii


viii

Conversion to SI Units

To convert from

To

Multiply by

light year
liter
micron
mil
mile (U.S. nautical)

mile (U.S. statute)
millibar
millimeter mercury
oersted
ounce force (avoirdupois)
ounce mass (avoirdupois)
ounce mass (troy)
ounce (U.S. fluid)
pascal
peck (U.S.)
pennyweight
pint (U.S. dry)
pint (U.S. liquid)
poise
pound force (avoirdupois)
pound mass (avoirdupois)
pound mass (troy)
poundal
quart (U.S. dry)
quart (U.S. liquid)
rod
roentgen
second (angle)
section
slug
span
stoke
ton (long)
ton (metric)
ton (short, 2000 pounds)

torr
yard

meter (m)
cubic meter (m 3 )
meter (m)
meter (m)
meter (m)
meter (m)
newton/square meter (N/m 2 )
newton/square meter (N/m 2 )
ampere/meter (A/m)
newton (N)
kilogram (kg)
kilogram (kg)
cubic meter (m 3 )
newton/square meter (N/m 2 )
cubic meter (m 3 )
kilogram (kg)
cubic meter (M 3 )
cubic meter (m 3 )
newton second/square meter (N ⋅ s/m 2 )
newton (N)
kilogram (kg)
kilogram (kg)
newton (N)
cubic meter (m 3 )
cubic meter (m 3 )
meter (m)
coulomb/kilogram (c/kg)

radian (rad)
square meter (m 2 )
kilogram (kg)
meter (m)
square meter/second (m 2 /s)
kilogram (kg)
kilogram (kg)
kilogram (kg)
newton/square meter (N/m 2 )
meter (m)

9.46 ϫ 10 15
0.001
1.0 ϫ 10Ϫ6
2.54 ϫ 10Ϫ6
1.852 ϫ 10 3
1.609 ϫ 10 3
100.0
1.333 ϫ 10 2
79.58
0.278
2.835 ϫ 10Ϫ2
3.11 ϫ 10Ϫ2
2.96 ϫ 10Ϫ5
1.0
8.81 ϫ 10Ϫ3
1.555 ϫ 10Ϫ3
5.506 ϫ 10Ϫ4
4.732 ϫ 10Ϫ4
0.10

4.448
0.4536
0.373
0.138
1.10 ϫ 10Ϫ3
9.46 ϫ 10Ϫ4
5.03
2.579 ϫ 10Ϫ4
4.85 ϫ 10Ϫ6
2.59 ϫ 10 6
14.59
0.229
1.0 ϫ 10Ϫ4
1.016 ϫ 10 3
1.0 ϫ 10 3
9.072 ϫ 10 2
1.333 ϫ 10 2
0.914


Bringing Costs up to Date
Cost escalation via inflation bears critically on estimates of plant costs. Historical
costs of process plants are updated by means of an escalation factor. Several published cost indexes are widely used in the chemical process industries:
Nelson Cost Indexes (Oil and Gas J.), quarterly
Marshall and Swift (M&S) Equipment Cost Index, updated monthly
CE Plant Cost Index (Chemical Engineering), updated monthly
ENR Construction Cost Index (Engineering News-Record), updated weekly
Vatavuk Air Pollution Control Cost Indexes (VAPCCI) (Chemical Engineering),
updated quarterly
All of these indexes were developed with various elements such as material

availability and labor productivity taken into account. However, the proportion
allotted to each element differs with each index. The differences in overall results
of each index are due to uneven price changes for each element. In other words,
TABLE 1 Chemical Engineering and Marshall and Swift Plant and Equipment Cost
Indexes since 1950
Year

CE Index

M&S Index

Year

CE Index

M&S Index

1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962

1963
1964
1965
1966
1967
1968
1969
1970
1971
1972

73.9
80.4
81.3
84.7
86.1
88.3
93.9
98.5
99.7
101.8
102.0
101.5
102.0
102.4
103.3
104.2
107.2
109.7
113.6

119.0
125.7
132.3
137.2

167.9
180.3
180.5
182.5
184.6
190.6
208.8
225.1
229.2
234.5
237.7
237.2
238.5
239.2
241.8
244.9
252.5
262.9
273.1
285.0
303.3
321.3
332.0

1973

1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997

144.1
165.4
182.4
192.1
204.1

218.8
238.7
261.2
297.0
314.0
316.9
322.7
325.3
318.4
323.8
342.5
355.4
357.6
361.3
358.2
359.2
368.1
381.1
381.7
386.5

344.1
398.4
444.3
472.1
505.4
545.3
599.4
659.6
721.3

745.6
760.8
780.4
789.6
797.6
813.6
852.0
895.1
915.1
930.6
943.1
964.2
993.4
1027.5
1039.2
1056.8

ix


x

Bringing Costs up to Date
TABLE 2 Nelson-Farrar Inflation Petroleum Refinery Construction Indexes since 1946
(1946 ϭ 100)

Date

Materials
Component

Labor
Component

Miscellaneous
Equipment

Nelson
Inflation
Index

1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964

1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991

100.0
122.4

139.5
143.6
149.5
164.0
164.3
172.4
174.6
176.1
190.4
201.9
204.1
207.8
207.6
207.7
205.9
206.3
209.6
212.0
216.2
219.7
224.1
234.9
250.5
265.2
277.8
292.3
373.3
421.0
445.2
471.3

516.7
573.1
629.2
693.2
707.6
712.4
735.3
739.6
730.0
748.9
802.8
829.2
832.8
832.3

100.0
113.5
128.0
137.1
144.0
152.5
163.1
174.2
183.3
189.6
198.2
208.6
220.4
231.6
241.9

249.4
258.8
268.4
280.5
294.4
310.9
331.3
357.4
391.8
441.1
499.9
545.6
585.2
623.6
678.5
729.4
774.1
824.1
879.0
951.9
1044.2
1154.2
1234.8
1278.1
1297.6
1330.0
1370.0
1405.6
1440.4
1487.7

1533.3

100.0
114.2
122.1
121.6
126.2
145.0
153.1
158.8
160.7
161.5
180.5
192.1
192.4
196.1
200.0
199.5
198.8
201.4
206.8
211.6
220.9
226.1
228.8
239.3
254.3
268.7
278.0
291.4

361.8
415.9
423.8
438.2
474.1
515.4
578.1
647.9
622.8
656.8
665.6
673.4
684.4
703.1
732.5
769.9
797.5
827.5

100.0
117.0
132.5
139.7
146.2
157.2
163.6
173.5
179.8
184.2
195.3

205.9
213.9
222.1
228.1
232.7
237.6
243.6
252.1
261.4
273.0
286.7
304.1
329.0
364.9
406.0
438.5
468.0
522.7
575.5
615.7
653.0
701.1
756.6
822.8
903.8
976.9
1025.8
1061.0
1074.4
1089.9

1121.5
1164.5
1195.9
1225.7
1252.9


Bringing Costs up to Date

xi

TABLE 2 Continued

Date

Materials
Component

Labor
Component

Miscellaneous
Equipment

Nelson
Inflation
Index

1992
1993

1994
1995
1996
1997

824.6
846.7
877.2
918.0
917.1
923.9

1579.2
1620.2
1664.7
1708.1
1753.5
1799.5

837.6
842.8
851.1
879.5
903.5
910.5

1277.3
1310.8
1349.7
1392.1

1418.9
1449.2

the total escalation derived by each index will vary because different bases are
used. The engineer should become familiar with each index and its limitations
before using it.
Table 1 compares the CE Plant Index with the M&S Equipment Cost Index.
Table 2 shows the Nelson-Farrar Inflation Petroleum Refinery Construction Indexes since 1946. It is recommended that the CE Index be used for updating total
plant costs and the M&S Index or Nelson-Farrar Index for updating equipment
costs. The Nelson-Farrar Indexes are better suited for petroleum refinery materials,
labor, equipment, and general refinery inflation.
Since
C B ϭ C A (B/A) n

(1)

Here, A ϭ the size of units for which the cost is known, expressed in terms of
capacity, throughput, or volume; B ϭ the size of unit for which a cost is required,
expressed in the units of A; n ϭ 0.6 (i.e., the six-tenths exponent); C A ϭ actual
cost of unit A; and C B ϭ the cost of B being sought for the same time period as
cost C A .
To approximate a current cost, multiply the old cost by the ratio of the current
index value to the index at the date of the old cost:
C B ϭ C A I B /I A

(2)

Here, C A ϭ old cost; I B ϭ current index value; and I A ϭ index value at the date
of old cost.
Combining Eqs. (1) and (2),

C B ϭ C A (B/A) n (I B /I A )

(3)

For example, if the total investment cost of plant A was $25,000,000 for 200million-lb/yr capacity in 1974, find the cost of plant B at a throughput of 300
million lb/yr on the same basis for 1986. Let the sizing exponent, n, be equal to
0.6.
From Table 1, the CE Index for 1986 was 318.4, and for 1974 it was 165.4.
Via Eq. (3),


xii

Bringing Costs up to Date
TABLE 3 Vatavuk Air Pollution Control Cost Indexes (VAPCCI). First Quarter 1994
ϭ 100.0 (index values have been rounded to the nearest tenth).
Control Device

1994
(Avg.)

1995
(Avg.)

1996
(Avg.)

Carbon adsorbers
Catalytic incinerators
Electrostatic precipitators

Fabric filters
Flares
Gas absorbers
Mechanical collectors
Refrigeration systems
Regenerative thermal oxidizers
Thermal incinerators
Wet scrubbers

101.2
102.0
102.8
100.5
100.5
100.8
100.3
100.5
101.4
101.3
101.3

110.7
107.1
108.2
102.7
107.5
105.6
103.0
103.0
104.4

105.9
112.5

106.4
107.0
108.0
104.5
104.9
107.8
103.3
104.4
106.3
108.2
119.8

C B ϭ C A (B/A) n (I B /I A )
ϭ 25.0 (300/200) 0.6 (318.4/165.4)
ϭ $61,200,000
Table 3 shows the Vatavuk Air Pollution Control Cost Indexes (VAPCCI) since
1994. For details, see the Vatavuk Air Pollution Control Cost Indexes article in
volume 61.
Editor’s note: For a more thorough explanation of updating costs, see the article, ‘‘Tower Cost Updating’’ in volume 58.

john j. mcketta


Encyclopedia of
Chemical Processing
and Design
69

Circulating Fluidized Bed Reactors:
Basic Concepts and Hydrodynamics

Introduction
Circulating fluidized beds (CFBs) consist of two basic designs, as shown in Fig. 1.
One design involves a fast-fluidized bed where high gas velocities convey a substantial amount of solids to one or more cyclones. The separated particles are fed
back to the fluidized bed using a standpipe. The second basic design uses a riser
to convey solids to one or more cyclones. The separated particles are fed to an
optional fluidized bed and then back to the riser. Solids flow rates can be controlled
using nonmechanical L- and J-valves or using a mechanical slide valve.
The large-scale commercial realization of CFBs occurred in the early 1940s,
although some coal gasification was done in a fluidized bed as early as 1926 [1].
With the increased demand for gasoline during World War II, major efforts were
underway to develop reactors to crack petroleum feedstocks into usable fuels more
productively than the moving bed or snake reactors (i.e., the Houndry Process)
used at that time. The result was a fluidized catalyst cracker (FCC), where high
catalyst circulation rates allowed a balance between the exothermic burning of
coke on the catalyst in the regenerator and the endothermic hydrocracking of petroleum in the reactor. The continuous circulation or regeneration of catalyst provided
fresh catalyst for petroleum cracking and thereby resulted in high sustainable productivities. With the addition of a stripping section after the reactor, even higher
yields were obtained. The addition of steam, CO 2, or other inerts would remove
the product from and around catalyst particles flowing toward the regenerator.
Today, the evolution of the FCC unit has results into several basic designs, as
shown in Fig. 2.
In 1960, circulating fluidized beds contributed to another breakthrough process
for the petroleum and chemical industry. Standard Oil of Ohio (SOHIO) developed
a fluidized-bed reactor for the ammoxidation of propene to acrylonitrile. Previous
technology was done in tube-and-shell fixed-bed reactors. However, the high heat

of reaction of 160 kcal/mol limited the economic feasibility of those units. The
high heat transfer characteristic of fluidized-bed reactors made them ideal for the
production of acrylonitrile. Today, nearly all large-scale acrylonitrile plants are
based on the SOHIO design, with capacities up to 180,000 tons per year [4].
The greatest challenge in developing the SOHIO process was in the management of backmixing. The inherent hydrodynamics of fluidized beds, where solids
and, to a lesser extent, gas circulate from the top of the bed to the bottom, then
to the top again, would have a deleterious effect on acrylonitrile selectivity. To
overcome backmixing, SOHIO developed sieve trays to compartmentalize the gas
flow in the fluidized-bed reactor to resemble a more plug-flow characteristic [5].
In 1979, SOHIO redesigned the acrylonitrile reactor to more of a ‘‘tube-and-shell’’
fluidized-bed unit [6], as shown in Fig. 3.
1


2

Circulating Fluidized Bed Reactors

FIG. 1 Basic design of circulating fluidized beds.

FIG. 2 Typical FCC units based on the designs of (a) Standard Oil Development, (b) UOP, (c) Kellogg, and (d) Exxon. (Adapted from Refs. 2 and 3.)


Circulating Fluidized Bed Reactors

3

FIG. 3 Two-dimensional schematic of the SOHIO acrylonitrile processes. (Adapted from Ref. 5.)

During the late 1970s and early 1980s oil crisis, circulating fluidized beds found

applications in coal combustion. The high-heat-transfer capabilities of these reactors resulted in lower operating temperatures, thereby reducing NO x and SO 2
emissions. In addition, the high gas velocities resulted in significant turbulence,
which provided uniform temperatures in the combustor. With the surplus of oil
starting in the late 1980s, fluidized-bed combustors became economically less attractive. As of the early 1990s, only Dynergy (via the Destec process) and Lurgi
and Ahlstrom are practicing this technology [7].
Today, circulating fluidized beds are used in a wide array of chemical processes, as shown in Table 1. With fluidized beds having the unique distinction of
excellent heat transfer and continuous in situ regeneration, the economic attractiveness of processing thermally sensitive chemicals or using catalysts that require
TABLE 1 Some Fluidized and Circulating Fluidized Bed Reactor Processes
Product
Acrolynitrile
Aniline
Chloromethanes
Goal gasification
Hydrocyanic acid
Maleic anhydride
Maleic anhydride
Maleic anhydride
Perchlorethlyene
Phthalic anhydride
Polyethylene
Synthesis gas
Vinyl chloride

Process

Developer

Propene ammoxidation
Nitrobenzene hydrogenation
Cat. oxidaton of methane

Oxidation
Ammono-dehydrogenation
Butane oxidation
Butane oxidation
Butene oxidation
Chlorination
Naphthalene oxidation
Ethlyene polymerization
Fisher–Tropsch
Ethylene chlorination,
oxychlorination

SOHIO
BASF, Cyanamid, Lonza
Asahi Glass
Winkler
Shawinigan
Alusuisse & Lummus (Alma Process)
DuPont
Mitsubishi
Diamond Shamrock
Badger/Sherwin-Williams
Union Carbide (Unipol)
SASOL, Kellogg
Ethyl, Hoechst, Mitsui, Toatsu, Monsanto


4

Circulating Fluidized Bed Reactors

frequent regeneration are more realized. Once the obstacles of backmixing, mass
transfer, and attrition have been addressed, these reactors often set the standards
in reactor design.

Basic Concepts
As the gas velocity through a bed of solids increases, the bed undergoes several
regimes, as shown in Fig. 4. At first, the gas velocity is insufficient to fluidize
the particles and the bed remains fixed. With increasing velocity and under ideal
conditions, the fixed bed expands smoothly and uniformly. Particles move in a
limited fluidlike fashion and the bed pressure drop becomes constant. At this point,
the bed is commonly referred to as undergoing minimum fluidization.
Further increases in gas velocity results in further bed expansion and particles
appear to freely move throughout the bed. The gas permeates through the bed
without the formation of bubbles. This regime is referred to as smooth fluidization
and is only observed for Geldart Group A powders (see Appendix A). These powders require noticeably higher gas velocities to promote the formation of gas bubbles after minimum fluidization. In contrast, Group B powders begin bubbling
shortly after minimum fluidization. Group C powders, being cohesive, may even
show signs of bubbling prior to minimum fluidization; however, this is usually the
result of channeling.
The onset of bubbles in the fluidized bed is commonly referred to as bubbling
fluidization. Here, gas bubbles form at or near the distributor and grow to a maximum bubble size as they propagate through the bed. The top of the fluidized bed
is still well defined, as it was in the minimum and smooth fluidization regimes.
The pressure drop across the bed is still constant, on average, but starts exhibiting
large, but regular, fluctuations with time.
As the gas velocity continues to increase, the top of the bed becomes less
defined. Large amounts of particles are ejected into the freeboard region above
the bed. Concurrently, sizeable regions of voidage and particle clusters are seen

FIG. 4 Various fluidization regimes with increasing superficial gas velocity.

Circulating Fluidized Bed Reactors

5

in the bed itself. For Group A and B powders, this transition from the bubbling
fluidized-bed regime is called the onset of turbulent fluidization. Group C and D
powders may show a slugging behavior prior to the turbulent fluidization regime.
During fast fluidization, the gas velocity is sufficient enough that the surface
of the bed can no longer be discerned. Particle density is still higher at the bottom
of the unit compared to the top, suggesting that some sort of bed exists. Particle
clusters and streamers are readily observed and, in some cases, a core–annulus
radial variation in particle density begins to take shape. Particle entrainment is high
and the total disengagement height may be well beyond the physical dimensions of
the fluidized-bed unit. To overcome the losses of particles due to entrainment,
cyclones may be used to capture entrained particles and recirculate them back into
the bed.
At very high gas velocities, nearly all the particles are entrained from the bed.
This regime is commonly referred to as pneumatic conveying. In this regime, axial
variation in particle density is no longer observed, except maybe in entrance and
exit regions. Radial variation in particle density can vary dramatically and range
from a core–annulus profile to a uniform profile. For dense systems, clusters and
streamers are readily observed.
Thus, for gas–solid systems, increases in the gas velocity results in dramatic
and sometimes sharp transitions in the hydrodynamics. In the design of fluidized
beds, it is crucial that one knows the fluidized regime that will exist at operating
conditions. The simple transition from one regime to another can have significant
impacts on reaction, heat transfer, attrition, and entrainment rates. For circulating
fluidized beds, where several regimes may exist in a single unit (i.e., from conveying in the riser to a bubbling fluidized-bed regime in the regenerator), knowledge of the fluidization regimes is paramount.
In order to gain better understanding of these regimes, the methodology used
to determine the onset of each fluidization regime is discussed in the following

sections. Keep in mind that most of the correlations are empirical and may not
fully represent every system. With the cost of these units running in the tens of
millions of dollars for large-scale plants, experimental validation of the expected
regimes is critical when designing these processes.

Minimum and Smooth Fluidization
As a gas permeates through a fixed or packed bed, the pressure drop can be described by the Ergun equation [8]:
(1 Ϫ ε bp )2µu g
(1 Ϫ ε bp )ρ g u 2g
∆P
g c ϭ 150
ϩ
1.75
L
ε 3bp (Φd p ) 2
ε 3bp (Φd p ) 2

(1)

With increasing gas velocity, the bed reaches a point where the drag force exceeds
the force of gravity on the particles. The particles become mobile and the bed
becomes fluidized. The gas velocity at the onset of this type of fluidization is
referred to as the minimum fluidization velocity or u mf. Assuming that the weight


6

Circulating Fluidized Bed Reactors
of the particles in the fluidized bed corresponds to ∆P/L, the Ergun equation can
be written as

΂

΃

1.75 d p u mf ρ g
ε 3mf Φ
µ

2

ϩ

΂

΃

150(1 Ϫ ε mf ) d p u mf ρ g
d 3 gρ (ρ Ϫ ρ g )
ϭ p g 2s
3
2
ε mf Φ
µ
µ

(2)

or
150(1 Ϫ ε mf )

1.75 2
Re p,mf ϩ
Re p,mf ϭ Ar
ε 3mf Φ
ε 3mf Φ 2

(3)

where the Archimedes number, Ar, is defined as

Ar ϭ

d 3pgρ g (ρ s Ϫ ρ g )
µ2

(4)

and Re p is the particle Reynolds number having the expression

Re p,mf ϭ

d p u mf ρ g
µ

(5)

Equation (3) can be written as a quadratic with the coefficients K 1 and K 2 having
the form
K 1 Re 2p,mf ϩ K 2 Re p, mf ϭ Ar

(6)

By solving for Re p, mf, Eq. (6) can be rewritten as

Re p, mf ϭ

΄΂ ΃ ΂ ΃΅ Ϫ ΂2KK ΃
K1
2K 2

2

ϩ

Ar
K1

0.5

1

(7)

2

where the particle Reynolds number at minimum fluidization is a simple function
of the Archimedes number and two constants (K 1 /2K 2 and 1/K 1 ).
Many correlations for the minimum fluidization velocity are based on Eq. (7)

Circulating Fluidized Bed Reactors

7

TABLE 2 K1 and K2 Values for Eq. (7)
Reference
Wen and Yu [9]
Richardson [10]
Saxena and Vogel [11]
Bubu et al. [12]
Grace [13]
Chitester et al. [14]

K2 /2K1

1/K1

33.7
25.7
25.3
25.3
27.2
28.7

0.0408
0.0365
0.0571
0.0651
0.0408
0.0494

Comments
For fine particles
Dolomite at high temperature and pressure

For large particles

Source: Adapted from Ref. 7.

for the constants K 1 /2K 2 and 1/K 1. These constants are presented in Table 2 for
a wide range of studies. For typical Geldart Group A powder, the constants of
Wen and Yu are most often used. However, these correlations are specific to a
group of particles with common characteristics and may not represent a less-thanideal particle morphology and texture.
The minimum fluidization velocity can be experimentally determined by measuring the pressure drop across a bed of particles with increasing superficial gas
velocity. For smooth, round, and noncohesive particles, the pressure drop increases
linearly with gas velocity until the minimum fluidization velocity is reached. With
further increases in the gas velocity, the pressure drop remains constant. Hence,
the minimum fluidization velocity is the intersection of the linearly increasing line
with the constant-pressure-drop line.
Figure 5–8 demonstrate the results of such an experiment. Figure 5 is the
pressure-drop curve for alumina particles with a mean particle diameter of 60 µm
in a 4.5-in.-inner diameter fluidized bed unit. The minimum fluidization velocity
for these particles was determined to be 6.5 cm/min. When measuring the minimum fluidization velocity, less scatter in the data is obtained from larger or higher
beds. The scatter in Fig. 5 suggests that perhaps a higher bed should have been
used. The diameter of the fluidized bed used in this type of experiment is also

FIG. 5 Minimum fluidization curve for smooth and round alumina particles, d p,ave ϭ 60 µm.


8

Circulating Fluidized Bed Reactors

FIG. 6 Minimum fluidization curve for smooth and round alumina particles, d p,ave ϭ 60 µm, with
increasing and decreasing gas velocities.

critical to obtaining accurate data. For Geldart Group A powders, bed diameters
less than 3 in. can result in experimental data that are influenced by frictional
effects at the wall. For the coarser Group B powders, the minimum diameter is
much larger.
Figure 6 shows two pressure drop versus superficial gas velocity curves for
the same particles used in Fig. 5. The black data points are the pressure drop with
increasing gas velocity and the gray data points are the subsequent pressure-drop
measurements with decreasing gas velocities. For round, smooth, and noncohesive
particles, the two curves should overlap each other, as shown in Fig. 6. However,
for irregular, rough, or cohesive particles, a hysterisis effect is typically observed.
This is obvious in Fig. 7 for rough and irregularly shaped alumina particles with

FIG. 7 Minimum fluidization curve for rough alumina particles, d p,ave ϭ 92 µm.


Circulating Fluidized Bed Reactors

9

FIG. 8 Minimum fluidization curve for cohesive iron catalyst particles, d p,ave ϭ 68 µm.

a mean particle diameter of 92 µm. This resulted in higher solid shear forces during
fluidization such that the pressure drop is dependent on previous conditions or is
path dependent. Figure 8 shows the pressure-drop curve for a catalyst supported

on alumina with a mean particle diameter of 68 µm. Here, it is almost impossible
to detect the minimum fluidization velocity. High cohesive forces result in a fluidized bed prone to channeling. Each peak or spike in Fig. 8 is the result of another
channel achieving fluidization while the majority of the bed remains fixed. This
behavior is typically of Group C powders.

Bubbling Fluidization
As discussed earlier, beds with Group A powders pass from minimum fluidization
to smooth fluidization to bubbling fluidization with increasing gas velocity. Group
B and D powders exhibit bubbling fluidization at the onset of minimum fluidization. Oddly enough, gas bubbles in all fluidized beds behave similarly to gas bubbles in low-viscosity liquids [7]. Large gas bubbles are typically spherical on top
and flattened or even inverted on the bottom; smaller bubbles tend to be completely
spherical. As in liquid systems, gas bubbles in fluidized beds can coalesce into
larger bubbles or split into smaller bubbles, depending on bed conditions. Also,
as gas bubbles approach the top of a fluidized bed, they collapse such that solids
are propagated into the freeboard region. Higher pressures or temperatures result
in a decrease in the maximum bubble size (due to changes in the gas physical
properties) and tend to make fluidization smoother [1].
The minimum velocity for bubble formation is referred to as the minimum
bubbling velocity or U mb. For Geldart Group A and C powders, Abrahamsen and
Geldart [15] proposed that the minimum bubbling velocity can be calculated from


10

Circulating Fluidized Bed Reactors
0.52
u mb
2300ρ 0.13
g ug
ϭ 0.8
exp(0.72P 45 µm ) in SI units

u mf
d p,ave (ρ s Ϫ ρ s )0.93

(8)

This expression is based on observations that the minimum bubble velocity is
strongly dependent on P 45 µm, the probability of finding a particle with a diameter
less than 45 µm. For calculations where less information regarding the system is
known, Eq. (8) can be simplified into the form
u mb

΂΃

ρ
ϭ 33d p g
µg

0.1

in SI units

(9)

For Geldart Group B and D powders, the minimum bubbling velocity is near the
minimum fluidization velocity. Thus, the onset of fluidization and the formation
of gas bubbles nearly coincide and
u mb ϭ u mf

(10)

As gas bubbles rise through the fluidized bed, the bubble size increases until a
maximum or equilibrium size is achieved, provided that the bed is high enough.
For Group A and B powders, Davidson and Harrison [16] proposed that the maximum stable bubble size can be determined from
d b,max ϭ

2u t
g

(11)

where u t is the terminal free-fall velocity of the particle (see Appendix B). Geldart
[1] found that Eq. (11) provided a better fit to experimental data if an effective
diameter, d′p, was used to calculate the terminal velocity [i.e., u t ϭ f(d′p )]. The
effective diameter is defined as
d′p ϭ 2.7d p

(12)

For Group D powders, the maximum stable bubble size is so large that in realistic
fluidized-bed applications the bubbles size is restricted by the bed diameter.

Turbulent Fluidization
Further increases in the gas velocity result in a slugging or turbulent fluidized bed.
If the bed diameter is small and the bed is sufficiently high, the fluidized bed will
slug before entering the turbulent fluidization regime. For Group A, B, and D
powders, slugging is basically the result of a bubble diameter that exceeds about
two-thirds the bed diameter. The wall stabilizes the bubble such that almost the
entire bed is translated up to the top of the bed or even higher. Group C powders
may also exhibit slugging behavior even in large-diameter beds due to the cohesive
forces. Thus, the larger and more cohesive the particles or the smaller the bed

diameter, the higher the probability of a bed exhibiting slugging. For these cases,