Presentation was made at AIChE Particle Technology Forum as an Award Lecture. After a brief review of achievements of fluidization engineering over decades, a discussion is made on one of the latest issues for applications in material industries as well as for the improvements in reliability of many fluidization processes, i.e., granulation and defluidization issues. 2.1 Background For a long period, phenomena associated with agglomerating fluidization have been treated with complete empiricism and scientific lights were shed seldom on them. It was, however, natural because the basic intention of fluidization has long been the better gas and solid contacting and, accordingly, agglomeration has been only one of unwanted side effects, which, once technically avoided, tend to be forgotten. At the same time, knowledge on elementary processes that should be relevant to agglomerating fluidization, e.g., bubble characteristics, forces acting among fluidized particles, surface characteristics of solids etc., was only gradually established during the last decades. Defluidization/agglomeration issues are, however, quite significant in a majority of fluidization processes probably except for gas-to-gas catalytic processes. In polyolefin processes agglomeration due to softening of plastic particles in local hot spots should be avoided.　In a polyolefin reactor it has been confirmed by a DEM simulation of Kaneko et al. (1998) that a stable solid circulation does not help removing the heat of polymerization. Instead, a solid motion induced by the always-fluctuating bubbling action is necessary as shown in Fig. 3. Ash melting and agglomeration, which finally causes defluidization, limits the operating temperature and pressure of pressurized fluidized bed combustion (PFBC) or gasification (PFBG). Figure 4 shows the so-called "sinter eggs" formed in a FBC boiler that is close to those found in AEP Tidd PFBC. Sinter egg/grain formation is again experienced recently in a commercial scale PFBC in Japan.

1. Fluor Daniel Lectureship Award
Flour Daniel Lectureship Award
AIChE 2001 Annual Meeting,
AIChE 2001 Annual Meeting
Particle Technology Forum
November 2001
November 6, 2001, Reno, NV
New Developments through
New Developments through
Microscopic Reconstruction of the
Microscopic Reconstruction of the
Nature of Fluidized Suspensions
Nature of Fluidized Suspensions
Masayuki Horio
Tokyo U. A & T
Koganei, Tokyo

2. 1. Fluidization processes
previous developments and fundamental researches
2. Significance of agglomerating fluidization
2.1 Background 2.2 Potential of Binderless granulation
2.3 Size Determining Mechanism in Agglomerating
Fluidization
3. Further discussions on the size
determining mechanism
3.1 DEM simulation
3.2 Comparison of Major Forces in the context of I-H model
3.2.1 A case study on ZnO
3.2.2 Ash agglomeration in FBC
3.2.3 Additional remarks
4. Concluding remarks

3. coal, wastes,
biomass
FCC
coal
biomass catalytic catalytic
wastes cracking and bio
Gasificat- reactions
de-SOx,H2S,HCl ion
PP, PE
FBC olefin
power
Applications
polymeri
gen. zation
of
waste Fluidization iron ore hardening,
manage- reduction, annealing,
patenting,
ment Powd. M
OTHER: Portland Cement,
mixing, Si Ferrite, Ceramics,
mixing, Nanoparticles
separation, drying,
amusement, chlorina
healthcare agglom tion &
-eration, CVD
coatin’
food, pharmaceutical

4. Enos, J.L.,(1964)
Capacity in world total [%]
FCC
year
The first dramatic success of fluid catalytic cracking (FCC).
See how desruptive the FCC technology that time was to all
other technology options.

5. COMMERCIAL
Cat Reactors
FCC Incinera-
CFBC
tors
PP, CVD PFBC
PE;
R Si; AFBC
&
Spray
D Granu
lators
1930 1940 1950 1960 1970 1980 1990 2000
Major Fluidized Bed Process Developments

6. Advantages, particularly
1. high yield by uniform & stable temperature field
that cannot be obtained by any other
contact modes.
2. high heat transfer rate when solids or surface
are immersed.
3. good solid mixing and potential of handling
solids continuously
4. High energy efficiency and
resources utilization capability

7. Disadvantages
However, the advantages listed are closely related to the disadvantages of fluidization such as,
1. High back mixing, then low yields.
2. Poor gas-gas contact efficiency without high surface
area catalysts.
3. Highly erosive conditions to immersed surfaces and
high attrition conditions to bed particles because of high
particle collision frequency (essential for high heat
transfer rate).
4. High defluidization potential at high load conditions due
to agglomeration or clinkering.
5. Short residence time of fine particles and gas species
emitted from solids.
6. Low mixing intensity in the freeboard.

8. In the case of Municipal Waste Incineration
1. The frequent and unpredictable variation of calorific value of waste
feed as well as the rapid preheating and incineration rates make it
difficult to adjust the air-to-fuel ratio at a stoichiometric air ratio as low as
1.2 of coal combustion. To avoid high PCDD/PCDF formation the air ratio
has to be as high as 2.0~2.5.  fuel pretreatment (RDF), slow
pyrolysis at low temperatures
2. Remaining volatiles have to be combusted in the freeboard but the
turbulent mixing in the freeboard is still not sufficient.  circulating
fluidized bed
3. The presence of chlorine makes it difficult to control the bed
temperature by in-bed tubes. Furthermore, the water spray method from
the top of the freeboard adopted sometimes brought high DXN emission.
 de-chlorination by CaCO3.
4. Alkali and chlorine compounds formed in the bed help to form
agglomerates.  de-chlorination, strict material balance

9. MSFB
1974 Battelle
Waste plastic Columbus Lab.
pretreatment
1970’s: Conoco
plant troubled
Sand 1980’s: Kurarey &
Idemitsu plants
RDF troubled.
machiie Limestone
Spec. of MSFB at
Kraray Co.
steam: 70t/h
8.92 MPa,
513C
fuel: coal
plastics
waste AC
MSFB born again
etc.
as a flexible energy recovery process

10. Expanded
Horizon of
New Technical Fluidization High
Demand
Challenges Processes but High
Risk
due to the
lack
New Scientific of
Knowledge
Challenges Expanded
Knowledge on
Fluidization
Phenomena
 Fluidization research has been aiming at new designs and new
process developments as other chemical engineering principles have.
 However, it has to develop phenomenological understanding of the
nature of fluidized suspensions because no other disciplines ever
more seriously encountered it.
Good Heritage of Fluidization Research

11. Nature and Art
Natural Science and
Engineering Science
The presence of column wall made
the analysis much easier
volcanic
cloud plateau
artificial
plant hail

12. ‘Turbulent’
‘ Turbulent ’
Dense
Dense Dilute
and
suspension
suspension ‘ Fast ’
suspension
suspension
Fluidization
turbulent fast bed
bed
pnewmatic
transport
A phase diagram of a FCC powder.
(Horio and Ito (1997); data: Hirama et al.)
For analogy with matters:
gas velocity u0 should correspond to temperature,
solid circulation flux Gs to pressure, and
particle volume flux p to density

13. Fluidization, matured ?
• Once only few professional peoples' business.
• Trough national projects since the 70s including CCT
and by the spread of fluidized bed sludge/waste
incinerators, fluidization has become popular in a
much wider professions.
• Unfortunately in Japan, the serious DXNs emission
from furnaces with poor temperature control by water
spraying made the term "fluidized bed" a little more
popular to people.
• Its application is widening even coming closer to
everyday life. A bed for a burned patient is an already
classical invention but recently a dry bathing system
for nursing an aged person (Yokogawa (1998)) has
been invented.

14. Still exist high hurdles for higher selectivity, lower
emissions and safer scale-up.
New applications once expected promising in the field of
materials processing have not yet achieved much
breakthrough except for pharmaceutical granulation and small
applications.
After the enthusiasm of circulating fluidization research in
the 80s, the most interesting, essential and highly
interdisciplinary research topics lie in
1) new contacting concept development including co-current
down-flowing suspensions in the downer to provide less
back mixing conditions in catalytic reactors and porous BM
for incineration and other gas-solid systems.
2) agglomerating fluidization including granulation and the
3) numerical simulation by DEM, DNS.
In today’s talk the agglomerating fluidization issues are
discussed with a wide perspective.

15. 2. SIGNIFICANT ASPECTS OF
AGGLOMERATING
FLUIDIZATION
For a long period, phenomena associated with agglomerating
fluidization have been treated completely empirically and
scientific lights were shed seldom on them.
It was, however, natural because the basic intention of
fluidization has long been the better gas and solid contacting
and, accordingly, agglomeration has been only one of
unwanted side effects, which, once avoided, tend to be
forgotten.
At the same time, knowledge on elementary processes that
should be relevant to agglomerating fluidization, e.g., bubble
characteristics, forces acting among fluidized particles,
surface characteristics of solids etc., was only gradually
established during the last decades.

16. Defluidization velocity [m/s]
Polyolefin Process Coal
Uniform gas feeding Nonuniform gas feeding Gasification
particle temp. particle velocity particle temp. particle velocity
vector vector
t=9.1 sec t=8.2 sec
Fig. 5. Defluidization curves for different coal
3umf 3umf 3umf 2umf 2umf species in a pilot scale fluidized bed gasifier
15.7umf Circulation
eddies (Fujioka and Nagai (1988))
: Upward motion
: Downward motion
Starting
cast shot FB
Fines
taken up Combustion
1500F 87% reduction 1600F 87% reduction
Iron-oxide Experimental data from self nucleation tests
Wt pct Wt pct Wt pct
Reduction Size, mesh
US std
Starter
bed
first cycle
Final
bed
Final
bed less
Starter
beda
second cycle
Final
bed
Final
bed less
Starter
bedb
third cycle
Final
bed
Final
bed less
oversize oversize oversize
+20 32.1 42.3 44.6
-20+30 18.2 33.6 49.4 55.6 38.1 66.0 67.0 36.2 65.4
-30+40 45.1 18.3 27.0 30.0 12.5 21.7 22.0 10.1 18.2
-40 36.7 16.0 23.6 14.4 7.1 12.3 11.0 9.1 16.4
Significance of Agglomerating
Fluidization in almost all fluidized bed
processes

17. Puzzling Umf
increase for
fine powders
u [cm/sec]
[cm/sec]
Data by Sugihara(1966)
and
umfmf
correlation by Jimbo (1966)
g(rp -rff) 2 n2aF
umf= dp + 3pbm dp
18bm
[ Along with their efforts for
establishing Soc. Powder
CaCO3
Tech. Japan]
dp [mm]

18. Chronology
Green letters: fundamentals
1961 Davidson’s Bubble
1966 Jimbo, Sugihara’s umf issue left a question at least to Japanese
1973 Geldart’s Powder classification and ‘Group C’ for cohesive ones
197X Donsi-Massimila(75), Masters-Rietema(77): Cohesion force and
fluidized bed behavior
1985 Chaouki et al., Group C fluidization and agglomerate size (da)
prediction
1987 Kono et al.: Measurement of force acting on particles
1988 Morooka et al.: Energy balance model for da
1990 Pacek-Nienow: Fine & dense hardmetal powder fluidization
1991 Campbell-Wang: Particle pressure in a FB
1992 Nishii et al.: Pressure Swing Granulation
1993 Tsuji, Kawaguchi & Tanaka: DEM for Fluidized Bed
1998 Mikami, Kamiya & Horio: Numerical simulation of agglomerating FB
(SAFIRE)
Iwadate-Horio: Particle pressure / Force balance model to predict da

19. Spray granulation
moisture content of bed[%]
F RD
A: acetoaminophen
E: ethensamide
gas vel. yield d50 bulk density VC: ascorbic acid
A
E
VC
time
Fig. 8. Typical moisture content curves in spray granulation. Fig. 9. Effect of drug types on product size distribution of fluidized bed
(Aoki (1997)) spray granulation (Sunada et al. (1997)( F: free bubbling type, RD:
rotating distributor type)

20. ①Fluidization
Bag filter interval
15s
②Compaction 1s
interval
0 time[s] 7200
Gas tank
Compressor
0.41m
f0.108m
Compressor ①Fluidization ②Compaction
interval interval
(a) apparatus (b) operation
Pressure Swing Granulation
Nishii et al., U.S. Patent No. 5124100 (1992)
Nishii, Itoh, Kawakami,Horio, Powd. Tech., 74, 1 (1993)

21. ① bubbling period: pulse (in reverse flow period)
Bed expansion de- ① ②
agglomerates and
compaction, attrition
and solids revolution
make grains spherical. cake
Fines are separated
and re compacted on
the filter.
fines‘ entrainement
② filter cleaning &
bed expansion reverse flow period:
Cakes and fines are
bubbling returned to the bed
cleaning-up the filter, and
bed is compacted
distributor promoting
compaction agglomerates’ growth
and attrition and consolidation.
air (in bubbling period)
What happens in PSG?

22. Potential of binderless
granulation
•Particle strength: how much is
needed ?
•Weak granules help easy
tabletting, higer green density,
potential application to DPI
•Attrition reagglomeration
mechanism helps achieving
content uniformity

23. #30-2 #30-2 #16-2 #16-2
#30-1 #30-1 #16-1 #16-1
ZnO
#30-2 #30-1 #16-2 #16-1
500mm
Structure of PSG granules
Granules split by a needle show a core/shell structure.
(Horio et al., Fluidization X (2001))

24. original
PSG
granules
Cumulative weight [%]
PSG
granules slide
500mm
from ZnO gate
dp=0.57mm
after
1st fall
2nd fall
3rd fall
Particle size [10-6m]
PSG granules: weak but strong enough!
Change in PSD of PSG granules in realistic conditions

25. 1mm 1mm 1mm
No. 2 No. 3 No. 4
100
Cumulative size distribution [v%]
80 d p,sv [mm]
No. 2 7.48
60 No. 3 4.95
No. 4 4.79
40 No. 5 4.14
1mm 1mm 1mm No. 6 3.71
20 No. 7 2.58
No. 5 No. 6 No. 7
0
0 10 20 30 40 50
Product Powders Primary particle size [mm]
Original Powders
Fig. 4 Size distributions of primary particles
PSG Microphotographs of PSG granules offound possible for
Fig. 6 from lactose lactose
dp<3mm Tkakno et al. (1998)

26. Lactose 3
Granule size: 0.355～0.5mm
0.01
Ethensamide Lactose
Load[gf]
2
force [N]
1E-3
1
Lactose
1E-4
0
40 80 120 160 200 1 10
displacement [mm]
100
Displacement[μm]
(a) photo image (b) particle compression (c) close-up of
test elastic behavior
Characteristics of PSG granules

27. Applications
•Hard metal cutting tool manufacturing
and other PM materials
•Ceramic and other materials
•Pharmaceutical agglomeration and
DPI (dry powder inhalation) etc.

28. feed compositions
powd. dp(WC) WC Co wax*
x10-6m %wt %wt %wt
1 1.5 93.0 7.0 0.5
2 6.0 85.0 15.0 0.5
Powder 1 Powder 2 Powder 3 3 9.0 77.0 23.0 0.5
dp(cobalt)=1.3-1.5x10-6m
*) Tmp(wax)=330K
preparation:
1. grinding 2.5hr
2. vacuum drying
PSG:
Agglomerate 1 Agglomerate 2 Agglomerate 3 Dt=44mm
charge=150g
u0=0.548 m/s
Hard Metal Application P(TANK)=0.157 MPa
SEM images of feeds and product granules total cylces=64
Nishii et al., JJSocPPM(1994)

29. Transverse rupture strength [N/mm2]
PSG
method
PSG
method
convent-
ional
method
Co content [wt%] Co content [wt%]
Application to hard metal industry (Nishii et al., JJSPPM(1994))
Improved strength of sintered bodies

30. 500mm
L : E=1 : 1
500mm
Co-agglomeration L : E=0 : 1
of lactose and ethensamide
CH2OH O
H O H
C-NH2
CH2OH H
OH H OCHCH3
2
OH O O OH
H H OH
OH H
H H
H OH ･H2O
10mm 10mm
Lactose Ethenzamide

31. 100
Concentration of Ethenzamide 1000mm
Granule Sample : 10mg
in Product Granules [%]
80 500mm
60
250mm
40
UV
20 absorbance:
300nm
0
0 20 40 60 80 100
Average Mass Concentration of
Ethenzamide in Feed [%]
Chemical Uniformity of PSG
granules

32. Size Determining Mechanism
in Agglomerating Fluidization
2.1 Background
2.2 Potential of Binderless
granulation
2.3 Size Determining
Mechanism in Agglomerating
Fluidization

33. difference, P
difference, P
B D B’ C’ D’
C
A A’
pressure
pressure
E’ mf,a u
superficial gas velocity, u0 superficial gas velocity, u0
A B C A B’ C’ D’ E’
D
left: a completely uniform and rigid bed; right: a realistic bed
A thought experiment of fluidization
of cohesive powders

34. Comparison of previous model concepts
Authors Model External force/energy Cohesion force/energy Comments
FGa Fpp
Chaouki
[ ]
FGa = Fpp No bubble
FGa = p d a3
hwd p
hw
et al. Fpp =
2 1+ 8 2 3 hydrodynamic
r ag
6 16 p
effects included.
Force balance Hr
van der Waals force
gravity force ≒drag force
between primary particles
No bubble
v=u mf Etotal =(Ekin+Elam ) Esplit
hydrodynamic
Etotal=(Ekin+Elam ) h w (1- a)d a2
Morooka Elaminer =3pmu mfd a2 Esplit =
effects included.
=Esplit shear
322 If 3m umf <hw (1-a)
et al. Ekinetic =mu mf 2/2 Etotal  ad p /(32pd p  a),
Energy balance energy required to negative d a is
laminar shear + kinetic force
break an agglomerate obtained.
expansion Fcoh,rup
Fexp = Fcoh,rup exp = - Ps Bed expansion
force caused by
p Db rag(-Ps)d a2 Had a(1- a)
bubble Fexp = Fcoh,rup = bubbles is
Iwadate-Horio 2n k 242 equated with
Force balance cohesive rupture
force.
bed expansion force cohesive rupture force

35. 4 4
expansion expansion
3 2Ps 3
Ps Ps 2Ps
rp(1-)gD b rp(1-)gDb
2 2
Ps =-1/4
=2p/3 -1/2 =0.639p -1/4 bubble A
1 -3/4 -1/8 1 -1/2 -1/8 2,000
-3/4 Ps = -1/20 b
-1 -1/20 -0.843 a c
0 0 -4
dp/dz=1.31×10 [Pa/m]
b
0 1,500
b
0
3/2 1,306
z/R
1/20
z/R
-1 -1
P[Pa]
5/4 1/20
5/4 1 1,000 gas pressure
3/4 1 1/2
1/8 1/8 3
-2 1/2 3/4 -2 1/4 dp/dt=-5.44×10 [Pa/s]
1/4
500 particle pressure
-3 -3
d
compaction compaction
-4 -4 0
0 1 2 3 4 0 1 2 3 4 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
x/Rb x/Rb time[s]
(a) two dimensional bed (b) three dimensional bed
Fig. 17 Normal stress distribution around a bubble; left: theoretical predictionfor 2D and 3D single isolated bubble; right: experimental
verification (Horio, Sugaya and Iwadate. (1998))
Particle pressure around a Davidson’s bubble

36. agglomerating
fluidization unstable point The critical condition
1E-4
stable point B
Hada(1- a)
1E-5
Fcoh,rup=
24 2 A C
log F[N]
1E-6
log F[N]
saddle point
1E-7
fluidized
1E-8
pDbra g da2  is reduced to
Fexp= 2 nk
1E-9
modify Fexp
3E-5 1E-4 3E-4 1E-10
1E-6 3E-6 1E-5 3E-5 1E-4 3E-4 1E-3 3E-3
3E-6 1E-5 1E-3 3E-3
log d a[m] log d [m] a
Ps* defluidization ( u0=umfa)
(a) Force balance and two solutions (b) Critical agglomerate size
Force balance to determine agglomerate
size
I-H model (Powder Technol., 1998)

37. Two difficulties in I-H model
1. particle-particle attraction force ?
2. agglomerates grow while bubbles
are absent ?
4
expansion agglomerating
3 fluidization unstable point The critical condition
2Ps
Ps rp(1-)gDb 1E-4
2
stable point B

1E-5
=0.639p -1/4 Fcoh,rup H ad a(1- a)
=
1 -1/2 -1/8 24  e2
A C
 da
1
E-6
log F[N]
forc
log F[N]
-3/4 Ps = -1/20 ture F coh,ru
p
-0.843 rup
on
1
E-7
0 esi e fluidized saddle point
coh rc
b
0 2
fo
on da
1
E-8
3/2
ns
i  pDbra g d a2   is reduced to
z/R
-1
1/20 pa Fexp= p
ex F ex modify Fexp
1
E-9
5/4 -
2-
nk -
1 1/2
5 - - 1 - - 3 -
1/8
3/4 -2 1/4 3 -6
E 15
E-
3E5
3E-5 1 -4
E4
E 3E4
3E-4
1
E-3 3E-3
1 10
E-
1E6
1E-6 3E6
3E-6 1
E-5 3 -5
E5
E 1 -4
E4
E 3E
E-4 1
E3
E-3 3E-3
log d a[m] log d a[m]
Ps* defluidization ( u0=umfa)
-3
compaction
(a) Force balance and two solutions (b) Critical agglomerate size
-4
0 1 2 3 4
x/R b
( b) three dimensional bed

38. 3
Ff
2.5
Load [mPa]
2
1.5
Grain compression test and
1
0.5
typical force displacement
0
0 50 100 150
Displacement [mm]
200 responses
(a) Example of fr actur e tensile str ength mesur ement
A : Elastic and plastic
deformation
Ff
B : Elastic brittle fracture
Ff
CCD
C :Plastic deformation
Ff
Then,particle-to-particle
cohesion force was
(b) Types of mesur ements determined by Rumph Eq.

39. 1E-3 1E-3
No. 4 No. 5
F exp 1.4E-3
1
1E-4 1E-4 F exp
=
F coh,rup
F coh,rup Lactose
F[N]
F[N]
77
1.2E-3
1
.05
2
=
1E-5 1E-5 ZnO
.15
al =0
al =0
L:E=7:3
ti c
ti c
cri
1E-6 1E-6
1E-3
cri


dobs=677mm dobs=788mm L:E=1:1
dcalc=621mm dcalc=723mm
[m]
1E-7 1E-7
1 10 100 1000 10000 1 10 100 1000 10000 L:E=3:7
a,calc
d a [ m m] d a [ m m] 8E-4
1E-3
1E-3
No. 6 No. 7
6E-4
d
1E-4
F exp F exp
F coh,rup 1E-4 F coh,rup
F[N]
1
1
=
=
4E-4
08
F[N]
1E-5
2
.08
.15
1E-5
al =0
al =0
ti c
ti c
1E-6
2E-4
cri
1E-6
cri


dobs=607mm dobs=373mm
dcalc=726mm dcalc=667mm
1E-7
1 10 100 1000 10000 1E-7
d a [ m m]
1 10 100
d a [ m m]
1000 10000
0E+0
0E+0 4E-4 8E-4 1.2E-3
2E-4 d a,obs [m] 1E-3
6E-4 1.4E-3
Comparison of model predictions with
observed data
Agglomerate size determination by I-H Fig. 13 Agglomerate size determination (PSG:2hr, pre-sieving by 16mesh)
model (Takano et al. Powd. Tech.,accepted,2001; Lactose;
PSG:2hrs, presieving by 16 mesh)

40. 500
Median diameter [10-6m] Median diameter [10- 600
Median diameter [10-
adsorption at: 293K, 293K,
p(adsorbate): 4kPa 4kPa
400 500
No effect: desorbed
during PSG
6m]
6m]
300 400
0 3 6 9 12 0 3 6 9 12 Notes: At 573K all
Absorption time [h] Absorption time [h] hydroxyl groups
Median diameter [10-6m]
500 on TiO2 are
500 eliminated
573K, 573K, (Morimoto, et al.,
13.3kPa 13.3kPa Bull. Chem. Soc.
400 JPN, 21, 41(1988).
400 Highest heat of
immersion at 573K
300 (Wade &
No effect ?? Hackerman, Adv.
Chem. Ser., 43, 222,
200 300 (1964))
0 3 6 9 12 0 3 6 9 12
Absorption time Absorption time [h]
(a) C2H5OH
[h]
(b) NH4OH
heat treatment:at p<13.3Pa
523K, for 6 hrs
adsorption:
bed= f150x10mm
Further possibility of size modification of PSG in a 0.03m3 vacuum
dryer
granules (from TiO2 (0.27x10 m) ) by heat and -6 PSG: charge=0.0333 kg
surface treatment 50%
u0=0.55 m/s RH: 40-
fluidiz.:15 s comp.: 1 s
Nishii & Horio (Fluidization VIII, 1996) total cycles=450

41. 3. Further discussions on the size
determining mechanism
3.1 DEM simulation
3.2 Comparison of Major Forces in the
context of I-H model
3.2.1 A case study on ZnO
3.2.2 Ash agglomeration in FBC
3.2.3 Additional remarks

42. The DEM simulation stands in between the two-fluid model (TFM) and
the direct Navier-Stokes simulation (DNS). DEM takes care of all distinct
particles and collisions. In the TFM particles are treated as a continuum
having a constitutive characteristics, which is derived based on stochastic
mechanics. In the DNS each particle should be surrounded by quite a few
finer grids to simulate fluid motion, as precisely as the particle scale, based
on the first principle.
Initiated by Candall and Struck (1979) DEM is now widely utilized in
many researchers of particulate materials. However, the concept of
DEM was applied to fluidized bed only recently by Tshuji et al. (1993).
Since it has been the author's belief that a simulation model has to be
able to deal with trouble making phenomena such as agglomeration,
where particle deformation may be maintained by bond formation, the
soft sphere model that allows multiple collisions and agglomerate
formation with reasonable complication was thought to be the right way
to go.
We have been developing models to take care of realistic situations in
chemical engineering. We also organized a research consortium with R-
Flow corporation, a software company in Japan, for a three year project
(1997-2000) to study the industrial needs and theoretical investigation.
Now we can be sure about the present limitation of DEM.

43. COMBUSTION Spray Agglomerating AGGLOMERATION
Granulation/Coating Fluidization
FB
w/ Immersed Ash
Tubes : Melting
FB of Particles w/
Pressure Effect I-H
Solid Bridging van der Waals
Rong-Horio 1998 Tangential
2000 FB w/ Interaction
Kuwagi-Horio Lubrication
Immersed Iwadate-Horio Effect
1999
Coal/Waste Tubes 1998
Kuwagi-Horio
Combustion Parmanently
Rong-Horio 2000
in FBC Wet FB
1999
Mikami,Kamiya,
SAFIRE Horio
DEM forAgglomerating FBs 1998
Particle-Particle Mikami-Horio 1996
Single Char Heat Transfer Dry-Noncohesive Bed
Combustion Rong-Horio Tsuji et al. 1993
Natural Phenomena
in FBC 1999
Rong-Horio OTHER
1999
Olefine Scaling Law
Polymerization Structure of for DEM
PP, PE Emulsion Phase Computation Low Reynolds
Kajikawa-Horio Simulation
Kaneko et al.
1999 Kajikawa-Horio 2000～
2001
Catalytic Reactions
LARGE SCALE
CHEMICAL REACTIONS FUNDAMENTAL SIMULATION

44. dp=100mm, rp=3700kg/m3
u0=0.1m/s, Ha=1.0×10-19J
0.411s 0.430s 0.450s 0.469s 0.489s
High particle normal stress right below a bubble
(Kuwagi-Horio(2001))

45. dp=100mm, rp=3700kg/m3
u0=0.1m/s, Ha=1.0×10-19J
0.460s 0.462s 0.464s 0.467s
0.469s 0.472s 0.474s
Close look at agglomerates (blue ones) in
the region above a bubble

46. Agglomerate: Fcoh>Frep, max
Collision: Fcoh<Frep, max
*
Non-cohesive Ha=0.4x10-19J Ha=1.0x10-19J Ha=2.0x10-19J
Kuwagi-Horio(2001)
Numerically determined agglomerates

47. High voltage DC power source (0-9kV)
100 static bed height: 200mm
fluidizing velocity: 0.4m/s
Filter
% collection [wt%]
80 voltage: ±0～9kV
fluidization time: 5min
175
60 Ground electrode
Aluminium
electrode 40
entrained Positive electrode
particles
150 10 20 Bag filter
200
490mm
0
0 2 4 6 8 10
)(
)(
Positive voltage [kV]
2D Fluidized bed
(a) Appaaratus (b) Results for ZnO agglomerate entrained from the bed (dp=0.78mm, da=337mm)
Fig. 22
qa=2.310-15C for a 50mm granule, and
1.610-11C/kg
Determination of particle charge by
parallel electrode method

48. r1 From Kelvin’s theory
r2 r2=[-3+(9+8brp)]/2b
rp b=(RTrL/M)ln(1/RH)
For primary particles: Flb,pp=pr2(1+r2/r1)
For agglomerates:Flb,aa=pr2a(1+r2a/r1a)
r1a
r2a
ra
Liquid bridge force

49. mm,
ZnO 0.57 u0=0.351m/s, column diam.=0.3m
0.1
1E-3 F
FvW (with deformation) exp
1E-5
FvW0
Force [N]
1E-7
1E-9
Fgravity
1E-11 Fcapillary;RH=0.6
1E-13
Fstatic electric.
1E-15
1E-17
1E-6 1E-5 1E-4 1E-3 0.01
da [m]
Force comparison for ZnO

50. Liquid bridge curvature from bridge
volume VL
VL/(pda3)=1.5(r1a/ra)2[1- (r1a/ra)(1+2/ (r1a/ra))1/2sin-1[1/(1+ (r1a/ra))]
Karita PFBC 10bar 870C
sinter grain: a=0.2
bed height: 3.3m
bed width: 11.3m
=0.35 N/m (Novok et al. (1995)),
=0.0515

51. T=870 ｰC, d p =900 mm, Surface
tension=0.4N/m, Ha=1410-20 J/ Db,p=10atm
10
0.1 Db,p=1atm
Force [N], Db [m]
1E-3 Flb,pp
1E-5 Flb,a
1E-7
FvdW
1E-9
1E-11
FG Fexp,p=10atm
1E-13
Fexp,p=1atm
1E-15
1E-17
1E-6 1E-5 1E-4 1E-3 0.01
Solids size [m]
Force comparison for a
PFBC/AFBC conditions

52. 2D DEM results: dp=200mm,
T=1273K, u0=0.26m/s
3 micro contact points smooth surface 9 micro contact points
Case of Metal Sintering
steel shots deposit growth
vs. surface roughness
Kuwagi-Horio 2000

53. CONCLUDING REMARKS
1. Secrets of Fluidization have been unveiled almost by the 60 yrs
endeavor and fluidization should now be no more a risky
technology.
2. We are coming close to the comprehensive knowledge of
fluidization: Bubbling, turbulent, fast to pneumatic; Adhesion
effects and agglomerating fluidization; Scaling law and Numerical
simulation.
3. More challenge to invent a new reactor concept that provides a
longer but uniform gas species' residence time and equal events
for all particles.
4. Challenge for materials process developments based on the
thermal uniformity of fluidized beds, but guaranteeing the
uniformity of events for individual particles in the mass. The
development should be from its beginning.
5. More emphasis on education / continuing education needed; in
addition to fundamental research and high-tech developments,
social/everyday applications should be encouraged.

54. DEM: problems to be Solved
The problems of DEM in view of its future application to real large scale
computation are coming out from its essential intermediate nature
between TFM and DNS. At this moment millions of particles of uniform
sizes can be dealt with a fast machine by say a week of computation but if
we are simulating a bed of f2m and 4m high containing say 1mm particles
we have roughly 10 billion particles. Accordingly, it is necessary to invent
a new method that allows us to bypass the tedious collision computations.
Another difficulty is relevant to how to overcome the assumption of
uniform particles. If we introduce particle size distribution, we are forced
to do 3D computation although 3D computation itself was already done by
Mikami (1998). In the computation of distributed particle size systems,
however, we are facing the limitation of the simple fluid cell treatment and
tend to introduce subgrids to take care, for instance, the segregation of
particles in a cell, small particle motion around a large article surface etc.
The third difficulty originates from the present formulation of collision
with the assumption of spherical smooth surface particles. The surface
characteristics are found very much significant even in our simple model
of surface roughness in iron particle sintering (Kuwagi et al. (1999)). More
realistic look into the collision, lubrication and friction phenomena is
needed.

55. REMAINING MOUNTAINS IN DEM
SIMULATION
Collision formulation: particle shape, surface roughness, plastic
deformation, attrition, lubrication force, attraction and repulsion forces
Effect of particle distribution in a gas cell: local clustering
effect on pressure gradient
Particle size distribution: shielding effect of particles in the up-
stream; Local clustering and adhesion
Gas boundary layer and wake around a particle: Boundary
layer during a collision; Gas wake shedding behind a particle; Gas-gas
reaction modeling; freeboard modeling
Particle-to-particle heat transfer: Boundary layer modification
during collision; transient effects etc.
Long distance interaction forces: Collision and static electricity
charging;
Large scale computation: minimum 100million particles
Realistic process modeling: heat & mass transfer, erosion,
attrition, agglomeration, gas-solid reaction, gas-gas reaction