Post on 26-Jun-2022
Xiaolu Yan
Department of Mechanical Science & Engineering
University of Illinois at Urbana-Champaign
CCC Annual ReportUIUC, August 19, 2015
Transient Thermo-fluid Model of
Meniscus Behavior and Oscillation
Mark Formation
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 2
Background
• Meniscus region controls many casting defects, such as:– Level fluctuations– Slag entrapment– Deep oscillation mark
• Many coupled phenomena occur,– melting powder, – oscillating mold, – steel flow with superheat, – re-solidified slag rim hitting
meniscus and pushing liquid slag into gap
– heat transfer through the gap and top slag layer,
– meniscus freezing,– overflow– Steel shell moving down Solidifying Steel
Shell
jet
entrainment
Coppermold
Resolidifiedslag
Oscillationmark
Slag rim
Slag powder
Liquid slag
Molten steel pool
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 3
Objectives
• Develop a transient thermo-fluid model of meniscus behavior and shell solidification
• Investigate mechanism of oscillation mark formation
• Predict during mold oscillation– Transient flow behavior of slag in meniscus region– Transient heat flux, temperature profile near
meniscus– Strand profile, shell thickness– Slag gap thickness, oscillation mark depth
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 4
MO
LD
MO
LD
MO
LD
MO
LDMeniscus freezing
Liquid Steel
Hook growth
Meniscus overflow
Liquid Steel
Liquid Steel
Liquid Steel
Hook tip fracture
Line of hook origin
New hook
Liquid flux
Shell growth
Liquid flux
Solid flux
Solid flux
Shell
Hook
Mechanisms of Hook & OM Formation –Overflow with hook
J. Sengupta, H. Shin, BG Thomas, et al, Met Trans B, 2006
Other mechanisms: “mini-sticker”; bending; overflow without hookthermal distortion
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 5
Hook – Overflow Animation Simulation result in current work
K. Thomas and BG Thomas, UIUC, 2010
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 6
Domain & modelling method
Slag
Steel
Mol
d
shell
Osc
illat
ion
• 2D simulation of a center slice through mold, gap, shell and liquid in the meniscus region
• K-ω SST turbulent CFD model to allow both turbulent flow in steel and laminar flow in slag and boundary layer
• Transient heat transfer• Solidification of slag rim by
increased specific heat and viscosity (temperature dependent functions)
• Solidification of steel by extracting latent heat and increasing viscosity and fixing shell velocity to casting speed
• VOF (volume of fluid) method to separate slag & steel phases
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 7
Equations
• � � ���� ���: � �� �
������ �
���
� ��
� �� � �� � ��
� �� �
������ �
���
� ��
� �� � �� � ��
• VOFmethod:1�%
� &%�% � ' ∙ &%�%)% � �*+ � , -. /% � -. %/
0
/12• Solidification:
: � � � �;<=�=�% � �;<=
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 8
Boundary conditionsPressure Inlet, P=0 Gauge
Mold Wall ConvectionTamb=40 >? � 45272D/-FG
Pressure Outlet
P=4500Pa
Insulated wall
Insulated wall
Velocity Inlet (steel)Mass inflow rate =outflow rate at pressure outlet,inflow superheat=3.5>
Insulated wall
Fix Temp ZoneWidth=5mmSuperheat=3.5>
Slag Solidification Zone Width=3mm
Slag
Steel
Casting speed=1.39m/min
Mol
d
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 9
Material property & casting condition
Unit value
Density GJ/-K 7000Specific heat M/�J ∙ G 700Conductivity D/- ∙ G 30Latent heat M/�J 2.72 N 10O
Solidus temperature > 1528.85Liquidus temperature > 1529.85
Unit value
Density GJ/-K 2500
Slag property
Unit value
Stroke -- 5.89Oscillation frequency RS 2.9Casting speed -/-TU 1.39Negative strip time V 0.12Theoretical pitch -- 8.01
Casting condition Steel property (ULC)
Slag-steel interfacial tension coefficient:WXY/-Z � 1.3 � 8.38 N 10[\ N X1803 � �XGZZ
0 0.05 0.1 0.15 0.2 0.25 0.3-3
-2
-1
0
1
2
3
Mol
d po
sitio
n (m
/s)
0 0.05 0.1 0.15 0.2 0.25 0.3-0.06
-0.04
-0.02
0
0.02
0.04
Time in one cycle (s)
Mol
d ve
loci
ty (
m/s
)
NST
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 10
Slag properties – spatial and temperature variation
0 200 400 600 800 1000 1200 1400 16000
0.5
1
1.5
2
2.5
3
Temperature (°C)
Sla
g C
on
du
ctiv
ity (
W/m
.k)
SolidifyingMelting
400 600 800 1000 1200 1400 160010
-1
100
101
102
103
104
105
Temperature (°C)
Sla
g v
isco
sity
(Pa.
s)
SolidifyingMelting
600 700 800 900 1000 11001000
1500
2000
2500
3000
3500
Temperature (°C)
Sla
g S
pe
cific
He
at,
Cp (
J/kg
.K)
Slag Solidification Zone
3mm
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 11
Fix solid steel shell velocity
• ADJUST UDF is used to fix steel shell velocity. It changes its value to casting speed at the beginning of each calculation iteration.
• When a cell satisfies:– Temperature <�;<=-0.1K– VOF fraction of steel > 0.8
Fix: ] _̂ � 0^̀ � 1.39-/-TU � abV�TUJVc
• Case 1: only adjust bottom of shell (y < 88mm)• Case 2: applied to whole domain (including shell
tip in meniscus region)
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 12
Steel shell viscosity
• Plasticity dominates solid steel mechanical behavior near solidus temperature
• Stress depends more on strain rate than strain
• Viscosity is appropriate to describe its mechanical behavior
• Current model only uses viscosity ~10Kdb ∙ V to avoid convergence issues with the real viscosity (that is 10\ Nhigher)
1480 1490 1500 1510 1520 1530 154010
-3
10-2
10-1
100
101
102
103
Temperature (°C)
Ste
el v
isco
sity
(P
a.s
)
(1489, 1e3) (1528.85,5e2)
(1529.85,6.3e-3)liquidus
solidus
• Case 1: Only has 10Kdb ∙ Vviscosity in meniscus region
• Case 2: In addition, uses Adjust function to fix velocity, effectively making viscosity infinite
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 13
Steel shell viscosity - theory
e̅.X1/VZ � 0.1gh0
gh � ijX�cbZkl ∙ �XGZ
300[O.OF
∙ 1 � 1000e̅ mkl � 13678 N ca�o [p.pOOq
U � 1.617 N 10[\ N � G � 0.06166 [2- � �9.4156 N 10[O N � G � 0.349501 Temperature
(K)
Pct Carbon
(%)
Von-Mises
Strain
Rate (1/s)
Viscosity
(Pa.s)
1800 0.001 0.01 4 N 10r
1800 0.001 0.1 6.8 N 10q
1800 0.001 1 1.15 N 10q
1800 0.01 0.01 3.5 N 10r
1800 0.1 0.01 3.1 N 10r
s � t_`e._`
� 23kl ∙ �XGZ
300[O.OF 1
e̅. 10u̅. 20
kl � 13678 N ca�o [p.pOOqU � 1.617 N 10[\ N � G � 0.06166 [2
Li C & BG Thomas, Met Trans B, 2004
Constitutive equations for delta-ferrite
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 14
Modeling Procedure
1. Initialize phase fraction distribution (slag vs steel) with Bikerman Eqn.
2. Flow-only transient simulation to smooth phase interface (meniscus shape)
3. Thermal-only steady state simulation to establish temperature field and form initial shell
4. Coupled flow-thermal transient simulation with no mold oscillation to establish flow field
5. Fully coupled transient simulation for 8 cycles (case 1) and 2 cycles (case 2)
1 cycle of simulation takes 1 day on 6 core PC
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 15
Viscosity Solution @7.25s
X (mm)Y
(m
m)Y (
mm
)
X axis elongated to show close up of gap
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 16
Velocity – case 1
• Domain at corner of NF• Flow entering domain is
form secondary recirculation zone, with velocityv 0.3-/V, carrrying 3.5> superheat
• Generates tertiary recirculation zone in corner
• Far-field flow pattern relatively stable (for 2.5s = 8 cycles)
• far-field surface waves
Video
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 17
Temperature – case 1
• Slag rim near meniscus represented by 1000C contour
• slow thermal response of mold
Video
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 18
Temperature in gap – case 1
• X axis expanded
• Note: solid layer on mold wall;
• nonlinear temperature gradient across gap due to fluid flow
• Slag gap grows, (from shell tip down)
Video
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 19
Initial solidification & OM formation – case 1
• During 8-cycle (2.5s) simulation: two occurrences of overflow happen at 7.5s and 7.9s
• As the simulation goes on meniscus cool down and freeze, changes to bending behavior
• Bending is due to viscosity 10\ times smaller and ADJUST function not in use at meniscus Video
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 20
Initial solidification & OM formation – case 2
• Duration 2 cycles• Shell is rigid after
solidification (turning blue)• Overflow happens when
mold has maximum speed upward
• Small hook forms (even with no undercooling)
• Smaller slag gap compared to bending mechanism
Video
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 21
1 mm 0
Side view (of section)
Entrapped bubble
Curved hook
Oscillation Marks and Hooks
Hook depth
OM
OM depth
J. Sengupta, H. Shin, BG Thomas, et al, Acta Mat., 2005
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 22
Shell & slag gap profile – case 1
X (mm)
Y(m
m)
20 22 240
20
40
60
80
100
X (mm)
Y(m
m)
20 22 240
20
40
60
80
100
Time: 10.135 sX (mm)
Y(m
m)
20 22 240
20
40
60
80
100
X (mm)
Y(m
m)
20 22 240
20
40
60
80
100
X (mm)
Y(m
m)
20 22 240
20
40
60
80
100
Video
• X axis expanded• The ADJUST
function is capable of keeping OM shape, but still allows too much movement
• Slag gap gets wider as simulation goes on
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 23
Predicted strand surface profile along the strand
0 10 20 30 40 50 60 70 80 90 100 110 120
-2
0
2M
old
Pos
ition
(m
m)
0 10 20 30 40 50 60 70 80 90 100 110 1200.6
0.8
1
1.2
1.4
1.6
1.8
2
Ys: Distance along the shell (strand) (mm)
Gap
thic
knes
s (m
m)
@10.13 s (9.79s + 1 cycle)@ 9.79 s@ 9.44 s (9.79s - 1 cycle)
Theoretical pitch: 8.01mmPredicted pitch average: 7.82mmStandard deviation: 0.94mm
All lines at same position along shell surface (i.e. in shell frame of reference) �; � 0 means far field meniscus @ 9.79s
Difference between 3 lines shows the non-physical movement of the shell due to viscosity being 10\ times smaller
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 24
Heat flux at mold hot face
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 25
Thermocouple locations
• Due to insufficient heat in meniscus region, mold temperature is constantly dropping during simulation
• In order to extract the temperature fluctuation due to oscillation, the TC temperature history is fitted to a cubic function, which captures the cooling trend.
• A modified temperature is then acquired by subtracting the cubic function
#1 #2
#3 #4
#5 #6
#7 #8
#9 #10
#11 #12
7
0
-6
-12
-18
-25
Distance (mm) above meniscus
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 26
Thermocouple #1temperature fluctuations
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
110
112
114
116TC#1, x=15
Y L
oca
tion
(m
m)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10110
110.05
110.1
110.15
Mod
ifie
dT
emp
era
ture
( °C
)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
100
105
110
Time (s)
Ra
wT
emp
era
ture
( °C
)
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 27
Thermocouple #2temperature fluctuation
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
110
112
114
116TC#2, x=18.5
Y L
oca
tion
(m
m)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
116.7
116.8
116.9
117
Mod
ifie
dT
emp
era
ture
( °C
)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
105
110
115
Time (s)
Ra
wT
emp
era
ture
( °C
)
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 28
Thermocouple #3temperature fluctuation
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
104
106
108
110TC#3, x=15
Y L
oca
tion
(m
m)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10129.3
129.4
129.5
Mod
ifie
dT
emp
era
ture
( °C
)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
115
120
125
Time (s)
Ra
wT
emp
era
ture
( °C
)
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 29
Thermocouple #4~0.3C temperature fluctuations
Near Hot face; at far field meniscus
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
104
106
108
110TC#4, x=18.5
Y L
oca
tion
(mm
)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10138.5
138.6
138.7
138.8
Mod
ifie
dT
em
per
atu
re ( °
C)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10120
125
130
135
Time (s)
Raw
Te
mp
erat
ure
( °C)
NST
NST
NST
NST
NST
NST
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 30
Thermocouple #5temperature fluctuation
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 1096
98
100
102
TC#5, x=15
Y L
oca
tion
(m
m)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10155.25
155.3
155.35
155.4
Mod
ifie
dT
emp
era
ture
( °C
)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
135
140
145
150
155
Time (s)
Ra
wT
emp
era
ture
( °C
)
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 31
Thermocouple #6temperature fluctuation
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 1096
98
100
102
TC#6, x=18.5
Y L
oca
tion
(m
m)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10171.2
171.4
171.6
Mod
ifie
dT
emp
era
ture
( °C
)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
150
160
170
Time (s)
Ra
wT
emp
era
ture
( °C
)
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 32
Thermocouple #7temperature fluctuation
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 1090
92
94
96
TC#7, x=15
Y L
oca
tion
(m
m)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10176.45
176.5
176.55
176.6
Mod
ifie
dT
emp
era
ture
( °C
)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10150
160
170
Time (s)
Ra
wT
emp
era
ture
( °C
)
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 33
Thermocouple #8temperature fluctuation
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 1090
92
94
96
TC#8, x=18.5Y
Lo
catio
n (
mm
)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
197.1
197.2
197.3
Mod
ifie
dT
emp
era
ture
( °C
)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
170
180
190
Time (s)
Ra
wT
emp
era
ture
( °C
)Near Hot face; 12 mm below field meniscus
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 34
Thermocouple #9temperature fluctuation
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 1084
86
88
90
TC#9, x=15
Y L
oca
tion
(m
m)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10193.35
193.4
193.45
Mod
ifie
dT
emp
era
ture
( °C
)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
170
180
190
Time (s)
Ra
wT
emp
era
ture
( °C
)
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 35
Thermocouple #10temperature fluctuation
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 1084
86
88
90
TC#10, x=18.5
Y L
oca
tion
(m
m)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10216.9
217
217.1
Mod
ifie
dT
emp
era
ture
( °C
)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10180
190
200
210
Time (s)
Ra
wT
emp
era
ture
( °C
)
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 36
Thermocouple #11temperature fluctuation
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
78
80
82
84TC#11, x=15
Y L
oca
tion
(m
m)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10207.45
207.5
207.55
207.6
Mod
ifie
dT
emp
era
ture
( °C
)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
180
190
200
Time (s)
Ra
wT
emp
era
ture
( °C
)
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 37
Thermocouple #12temperature fluctuation
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
78
80
82
84TC#12, x=18.5
Y L
oca
tion
(m
m)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
233.2
233.3
233.4
Mod
ifie
dT
emp
era
ture
( °C
)
8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10
200
210
220
230
Time (s)
Ra
wT
emp
era
ture
( °C
)
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 38
Slag temperature near meniscusat x=21mm, y=106mm
X (mm)20.9999 20.9999 21 21 21
106
106
106
106
106
106
106
106
106
2602402202001801601401201008060
TemperatureMold (C)
X (mm)20.9999 20.9999 21 21 21
106
106
106
106
106
106
106
106
106
X (mm)20.9999 20.9999 21 21 21
106
106
106
106
106
106
106
106
106
X (mm)20.9999 20.9999 21 21 21
106
106
106
106
106
106
106
106
106
X (mm)20.9999 20.9999 21 21 21
106
106
106
106
106
106
106
106
106
1531.851530.851529.851528.85150014001300120011001000900
TemperatureSteel&Slag (C)
Steel Solidus1528.85 C
Time: 6.774715 sSolution Time (s)
Tem
pera
ture
(C)
7 7.5 8 8.5 9 9.5 10
600
700
800
900
1000
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 39
Shear stress at mold hot face
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 40
Slag consumption for 7 cycles
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35-0.1
-0.05
0
0.05
0.1
Time in one cycle (s)
Sla
g flo
w (
kg/m
.s)
InstantaneousConsumptionMeanConsumption
Cycle # 1 2 3 4 5 6 7 Average
Mean Consumption Xw m∙;⁄ Z 2.3 4.6 2.2 2.3 3.8 3.8 5.3 3.5
NST
Average consumption 3.5 g/ms
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 41
Conclusion - modelling
• New thermal-fluid VOF model of mold, slag, powder, solidifying steel shell, and gap has been developed to investigate initial solidification
• Model can predict oscillation mark formation, with different mechanisms (both bending and overflow) according to different material property (steel viscosity)
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 42
Conclusion – OM mechanism
• Low viscosity steel (nonphysical) - Bending mechanism– OM forms when mold at lowest position– Wider meniscus gap, causing lower meniscus heat flux and less mold TC
temperature variations– Very wide contoured OM shape – Slag consumption profile similar to previous work, but average consumption is
low– Nonphysical because frozen meniscus would break under so much bending
• Rigid steel viscosity - Overflow mechanism– Rigid shell (moving downward) combined with meniscus movement exceeds – Occurs when mold has maximum speed going up– OM shape is shallower than that from bending mechanism– Seems physically reasonable– We expect higher meniscus heat flux, larger TC temperature fluctuation.
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 43
Future work
• Eliminate the cooling trend by improving powder surface inlet boundary condition
• Improve realism of shell behavior at meniscus by increasing viscosity (if possible) or fine tune the ADJUST function zone
• Validate with more measurements• Parametric studies
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Xiaolu Yan • 44
Acknowledgments
• Continuous Casting Consortium Members(ABB, AK Steel, ArcelorMittal, Baosteel, JFE Steel Corp., Magnesita Refractories, Nippon Steel and Sumitomo Metal Corp., Nucor Steel, Postech/ Posco, SSAB, ANSYS/ Fluent)