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LABORATORY OF APPLIED THERMODYNAMICS Dr. Grigorios C. Koltsakis Aristotle University Thessaloniki Tutorial DOC & DPF modeling
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Microsoft PowerPoint - MODEGAT 2009 - Koltsakis presentation.ppt Fundamentals, basic model equations
Transport-reaction coupling
“3-dimensional” effects
Channel model
( ) ( )jsjgj
Substrate Ts, ρs, vs Washcoat
O2, N2, CO, HC, NOx O2, N2, CO2, H2O
Gas Tg, ρg, vg
(convection, exothermy)
profile at catalyst inlet, as function of flow
resistance
S r
T r
O2, N2, CO, HC, NOx O2, N2, CO2, H2O
Gas Tg, ρg, vg
( )
Temperature [°C]
E ff
Temperature [°C]
E ff
Temperature [°C]
E ff
Langmuir isotherm
D-R isotherm is applicable to multilayer adsorption in microporous solids (zeolites).
The equation of the DR isotherm gives the adsorbed mass as function of temperature and partial pressure.
A linear «driving force» is assummed to calculate the rates towards equilibrium.
β (affinity parameter)
k (rate constant)
The rate constant for desorption is an exponential function of temperature.
2
Not possible with a single HC species
Pontikakis et al. (2000) used 4 HC species
Toluene: fast oxidizing, less easily adsorbable
Propene: fast oxidizing, practically non-
100 150 200 250 300 350 400
Temperature [°C]
Temperature [°C]
Time [s]
0.00E+0
2.50E-4
5.00E-4
7.50E-4
1.00E-3
1.25E-3
1.50E-3
C o n c e n tr a ti o n
Inlet
Time [s]
a ti o n a
t o u tl e t
-1.0
0.0
1.0
e d H
Time[s]
H C
]
o C
0
50
100
150
200
250
300
350
400
450
Time[s]
H C
]
o C
Water condensation/evaporation effect on thermal response
0 100 200 300 400 500
Time [s]
Periphery, exp.
Periphery, cmp.
Pontikakis et al., CaPoC 5, 2000
Hysteresis (history) effect
0
10
20
30
40
50
60
70
80
90
100
60 100 140 180 220 260 300 340 380 420 460
T [°C]
io n e
ie n c y %
CO light off CO cool down NO light off NO cool down HC light off HC cool down
COCO
HCHC
NONO
Definitions
Random shape, segmentation
any flow distribution
“Mixed reactor”
( ) IvY
Extremely high species transfer rates inside the porous wall
Species equations
( ) IvY
Haralampous O. A., Koltsakis G. C.: Industrial & Engineering Chemistry Research, Vol.43, Issue 4, p. 875-883, 2004.
Inlet channel Wall Outlet channel
Species equations
inI YY =
Neglecting the convective species transfer from channel gas to surface
(not justified, especially in catalyzed applications)
Species equations
inI YY =
IfI YY ,=
Bissett E. J., Shadman F., AlChE Journal (Vol31, No5), p. 753, May 1985. ”0-d model”
Bissett E. J., Chemical Engineering Science Vol. 39, Nos 7/8, pp. 1233-1244 (1984). “1-d model”
Neglecting diffusion in the wall-flow direction
Energy equations
Energy equations
( ) Ip vTC ρ
( ) IIfpwIIadv TCvH ,, ρ=
( )− Ip vTC ρ
)(zTI
Haralampous O., Koltsakis G. C.: Chemical Engineering Science, Volume 57, Issue 13, July 2002, Pages 2345-2355.
Energy equations
( ) IIconvIconvreactwconv w
*
,
Bissett E. J., Chemical Engineering Science Vol. 39, Nos 7/8, pp. 1233-1244 (1984). “1-d model”
Koltsakis G. C., Stamatelos A. M., Ind. Eng. Chem. Res., 1997 Vol. 36 p. 4155-4165. “catalytic 1-d model, modified energy balance”
wIIf TT =,
Summary of model equations
( ) ( )jjsj
w
jw
w
S z
T k
LABORATORY OF APPLIED THERMODYNAMICS
Clean filter filtration modeling
wu pd
Does the unit-cell approach apply to wall-flow filter structure?
Semi-empirical cake formation modeling
0%
20%
40%
60%
80%
100%
C a k e f il tr
a ti o n e
ff ic
a ti o n e
ff ic
ff ic
0
10
20
30
40
50
60
70
80
90
100
Time [s]
ff ic
a s s [ g ]
Estimation of soot in the wall
depending on the wall structure
High Flow Rate (300 kg/h)
0
10
20
30
40
50
60
70
80
90
100
Time [s]
ff ic
a s s [ g ]
0
10
20
30
40
50
60
70
80
90
100
Time [s]
ff ic
a s s [ g ]
Estimation of soot in the wall
depending on the flow rate
Soot cake properties
Effect of pressure drop on porosity
Compressible soot cake modeling
Velocity [cm/s]
e n s it y [ k g /m
³]
Soot Mass [g/l]
Depth filtration of soot in the wall contributes strongly to pressure drop.
Pressure drop “hysteresis”
Soot Mass [g/l]
Depth filtration of soot in the wall contributes strongly to pressure drop.
Pressure drop “hysteresis”
Soot Mass [g/l]
Depth filtration of soot in the wall contributes strongly to pressure drop.
Pressure drop “hysteresis”
Soot Mass [g/l]
generatio n
After partial regeneration, oxidation of soot in the wall reduces pressure drop for same
Pressure drop “hysteresis”
Soot Mass [g/l]
generatio n
After partial regeneration, oxidation of soot in the wall reduces pressure drop for same
Pressure drop “hysteresis”
Soot Mass [g/l]
Incoming soot does not re-penetrate the wall. The correlation of pressure drop vs soot
Pressure drop hysteresis effect
Soot Mass [g/l]
dots: measurement
lines: simulation
Following an incomplete regeneration, the cake soot does not allow the incoming soot to-
penetrate the wall. The pressure drop correlation with soot loading changes dramatically.
Uncatalyzed soot oxidation reactions
1000/T [1/K]
a te
E=122±4 kJ/mole
NO2 is produced in the catalyzed wall
NO2 diffuses back to the soot layer
Soot density NO2 concentration
( ) ( )jjsj
w
jw
w
∑=

∂ ∂
− ∂

∑=

∂ ∂
− ∂

Haralampous O. A., Koltsakis G. C.: Industrial & Engineering Chemistry Research, Vol.43, Issue 4, p. 875-883, 2004.
O2 transfer from channel gas to soot surface
O2
Length [mm ]
C o
n c
e n
tr a
ti o
Wall flow
Due to concentration gradient, O2 is transferred from the axial flow to the soot layer and
increases local availability and reaction rates Haralampous O. A., Koltsakis G. C.: AIChE Journal, Vol. 50, No. 9, p. 2008, 2004
Importance of O2 transfer for the prediction of filter temperature
Ignoring O2 mass-transfer effects (diffusive-convective) leads to serious under-prediction
of peak temperatures
800
900
1000
1100
1200
1300
1400
Importance of O2 transfer for the prediction of filter temperature
Ignoring O2 mass-transfer effects (diffusive-convective) leads to serious under-prediction
of peak temperatures
800
900
1000
1100
1200
1300
1400
Importance of O2 transfer for the prediction of filter temperature
800
900
1000
1100
1200
1300
1400
Ignoring O2 mass-transfer effects (diffusive-convective) leads to serious under-prediction
of peak temperatures
Catalyzed DPF simulation
Uncoated DPF
“Axial” zoning
Better cold-start performance
Better passive regeneration
for catalyst zoning
65
70
75
80
85
90
95
100
105
Filter Length [mm]
]
F-DPF in F-DPF out R-DPF in R-DPF out Z-DPF in Z-DPF out
CO
zoned
high-PGM
low-PGM
high-PGM
low-PGM
zoned
Koltsakis, G. C., Dardiotis, C. K., Samaras, Z. C., Frey, M., Wenninger, G., Krutzsch, B., Haralampous, O. A., SAE 2008-01-0445, 2008
LABORATORY OF APPLIED THERMODYNAMICS
3-d DPF regeneration simulation Sources of “3-dimensionality”
t=50 s t=60 s t=70 s t=80 s t=90 s
S oo
t T
em pe
ra tu
re F
lo w
“3-d effects”
Heat losses, segmentation, asymmetric inlet temperature/flow, oval DPF geometry
Flow, soot and temperature distribution effects due to inlet cone shape
Temperature (°C)
t=48 s
t=100 s
t=140 s
t=180 s
t=500 s
Koltsakis, G. C., Samaras, Z. C., Echtle H., Chatterjee D.,Markou P., Haralampous O., SAE paper 2009-01-1280, 2009
Model validation – centerline channel
300
400
500
600
700
800
900
1000
Time [s]
Dots: Measurement, Lines: Model
Koltsakis G.C, Haralampous O. A, Margaritis N., Samaras Z. C., Vogt C.D., Ohara E., Watanabe Y., Mizutani T.:, SAE Transactions,, 2005
Stress analysis
Koltsakis et al., FAD Conference-2007 (LAT-IAV GmbH-Exothermia)
62
Time [s]
T e
m p
e ra
tu re