16 singh varun user-friendly model of heat transfer in...
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ANNUAL REPORT 2010ANNUAL REPORT 2010UIUC, August 12, 2010
User-friendly model of heat transfer in submerged entry nozzles duringsubmerged entry nozzles during
preheating, cool down and casting
Varun Kumar Singh, B.G. Thomas
Department of Mechanical Science and Engineering
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Lance C. Hibbeler • 1
Department of Mechanical Science and EngineeringUniversity of Illinois at Urbana-Champaign
Objectives
• Develop a user friendly spreadsheet based tool tol l t th h t t f ffi i t d flcalculate the heat transfer coefficients and flame
temperature during preheating of the nozzle.
D l f i dl d h t b d t l t• Develop a user friendly spreadsheet based tool tomodel the heat transfer in submerged entry nozzlesduring the three stages: preheat cool down andduring the three stages: preheat, cool down andcasting.
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 2
Model & computational domain
Model of Nozzle exposed to ambient
Gas
Molten SteelTundish
1. Preheat
2. Cool down
Nozzle Layers
Insulation layer
Gas Burner
Nozzle Insulation
AmbientAmbient
Ambient
Flux Submerged Entry Nozzle
Slide Gate (Flow Control)
Tundish Nozzle
Clog
3. Casting
Layers layer
Ambient
Nozzle Layers
Insulation layer
Solid Steel Clog
Liquid
Steel
Molten Steel
M d l f N l b d i l
Molten Steel Jet
Submerged Depth
Flux Submerged Entry NozzlePlane of Symmetry
Insulation Layer1. Preheat Ambient
Nozzle Layers
Insulation layer
Gas Burner
Model of Nozzle submerged in steel
Copper Mold
Solidifying Steel
Liquid Steel
Pool3. Casting
2. Cool down Ambient
Nozzle Layers
Insulation layer
Ambient
Molten Steel
NozzleLiquid
Molten Steel
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 3
Continuous Withdrawl
Solidifying Steel Shell
Nozzle Layers
Insulation layer
Liquid
Steel
Models Developed
• Flame Temperature Calculation Model
• Heat Transfer Coefficients Calculation Model
• Model for heat transfer in the refractoryModel for heat transfer in the refractory during the three stages: – preheatpreheat,
– cool down
casting– casting• Ambient slice
• Submerged sliceSubmerged slice.
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 4
Flame Temperature Calculation Model – Input PageCalculation Model Input Page
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 5
Calculation of Flame temperature and heat transfer coefficients
• User can select from the following gases as fuel: Methane, hydrogen,propane, natural gas, blast furnace gas and acetylene.propane, natural gas, blast furnace gas and acetylene.•The species considered are: CO2, O2, O, CO, H2O, N2, NO, OH, H, H2
• For natural gas and blast furnace gas, user can specify the percentageof various constituents (natural gas: mathane – 94%, ethane – 3%,propane – 1%, butane – 0%, CO2 – 1%, O2 – 0%, N2 – 1%)•Reactants temperature and pressure need to be entered.•The reaction is a constant pressure process.•The user can choose between excess air and oxygen enrichment.•The amount of excess air or air enrichment needs to be specified.•The flame temperature calculated for the above composition of naturalgas with 50% excess air was found to be 1510 °Cgas with 50% excess air was found to be 1510 °C.
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 6
Heat Transfer Coefficients
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 7
Heat Transfer Coefficients
• Free Convection to ambient:– The Churchill and Chu [1] equation for flow over a vertical flat plate is usedThe Churchill and Chu [1] equation for flow over a vertical flat plate is used
2
1 / 6
8 / 2 79 / 1 6
0 . 3 8 70 . 8 2 5
0 . 4 2 91P r
a v g
R aN u
= + + P r
• Forced Convection from flame:The Petukhov, Kirillov, and Popov [1] is used
[ ]1/ 2 2/3
( / 8) Re Pr1.07 12.7( /8) (Pr 1)
DfNu
f= + −
Th f d h t t f ffi i t l l t d t b 72 5 W/ 2K• The forced heat transfer coefficient was calculated to be 72.5 W/m2K. • The free heat transfer coefficient was calculated to be 7.6 W/m2K
• Sleicher and Rouse equation was used to calculate the forced
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 8
qconvection heat transfer coefficient from molten steel flowing on the inside of the nozzle.
Properties of mixture of gases in combustion productsp
ni iy λλ
• Thermal conductivity of the mixture of gases is calculated using Saxena and Mason [3]:
λ
1
1
i im n
ij ij
j
y
y A=
=
λ =
Where = the thermal conductivity of the gas mixture
[ ]
mλWhere = the thermal conductivity of the gas mixture= the thermal conductivity of pure i
= mole fractions of component i and jiλ
,i jy y
21 / 2 1 / 41 ( / ) ( / )M M + η η 1 / 2 1 / 4
1 / 2
1 ( / ) ( / )[ 8 ( 1 / ) ]
i j j i
i ji j
M MA
M M
+ η η =+
j ij i i j
MA A
M
η=j i i j
i jMη
Where are the viscosities of pure i and j respectively
And are the molecular weights of pure i and j
jη,iη
,iΜ jΜ
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 9
i j
• Thermal diffusivity, kinematic viscosity, density and specific heat are calculated using the particle mixture rule.
Heat Transfer Model for the refractory – Main Pagerefractory Main Page
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 10
Heat Transfer Model for the refractory – Featuresrefractory Features
• User can enter the number of layers he wants in the model.
• Each layer can have different thickness and ydifferent number of nodes.
• The user can choose at what times theThe user can choose at what times the results have to be plotted.
• User can select the nodes where the results• User can select the nodes where the results are to plotted.
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 11
Heat transfer model – assign refractory propertiesrefractory properties
• The table gets populated based on the number of layers entered by the modelentered by the model.
• User can select which material should be assigned to each layer by choosing from the drop down menu (which get
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 12
automatically populated to show all the materials in the excel file)
Governing Equation and finite difference equation for interior nodesq
I f
AmbientGas Burner
• Heat conduction equation in cylindrical co–ordinates [1]
Inner surface refractory layer
Insulation layer
Bulk refractory layer
Outer surface refractory layer
i+1ii-1
q y [ ]
1p
T TC kr
t r r r
∂ ∂ ∂ρ =∂ ∂ ∂
• Using Taylor series [1] expansion the equation is discretized
2
2pT T
rr r
T kC
t r ∂ ∂+ ∂ ∂
∂ρ =∂
2
2
1 T T
r r r
Tt
∂ ∂+ ∂ ∂
∂ = α∂
• Using Taylor series [1] expansion, the equation is discretized as:
11 1 1 1
2
212
n n n n n n ni i i i i i iT T T T T T
r r r
Tt
++ − + − − − − ++ Δ Δ
= αΔ
21 1 1 1 nT
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 13
11 12 2 2
21 1 1 12 2
nn n n n i
i i i i
TT T t T T
r r r r r r r+
+ −
+ Δ + + − − Δ Δ Δ Δ Δ = α
Finite Difference Equations (Side nodes with convection))
1 2Inner surface
AmbientGas Burner
B lk f
• Heat balance on side half cell gives:
Side Half CellInner surface refractory layer
Insulation layer
Bulk refractory layer
Outer surface refractory layer
T T∂ ∂2 2 1 1pV kA hA T
T TC
t r− ⏐ + Δ ⏐∂ ∂ρ =
∂ ∂
( )1
1
2 2
n n n nni i i i
ambient ipT T Tr r r
k r hr T Tr
TC
t
++ − −Δ Δ + + − Δ
ρ =Δ
( )1 12 22
n nn n ni i
i i ambient ip
T Tt r thrT T r T T
r r r r rC+ + −αΔ Δ Δ + + + − Δ Δ Δ
=ρ
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 14
Finite Difference Equations (Interface Nodes))
Inner surface
AmbientGas Burner
B lk f tinterface
1p
T TC kr
t
∂ ∂ ∂ρ =∂ ∂ ∂
Inner surface refractory layer
Insulation layer
Bulk refractory layer
Outer surface refractory layer
interfacei i+1i-1
p t r r r
ρ∂ ∂ ∂
1
1/2 2 1/2 1/2 1 1/21n n
i ii i i i
ip
T T Tr k r k
r r
TC
t rr
+
+ + − −− ∂ ∂ ⏐ − ⏐ ∂ ∂
ρ =Δ Δ
11 1
2 12 21n n n n n n
i i i i i i
ip
T T T T Tr rr k r k
r r
TC
t rr
++ − − − −Δ Δ + − − Δ Δ
ρ =Δ Δ i
12 1 1 1( ) ( )n n n n n n
i i i i i i
r rT T r T T r T T
t+ Δ Δ + α + − − α − − Δ= 2 1 1 12 ( ) ( )
2 2i i i i i ii
T T r T T r T Tr r + −+ α + α Δ
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 15
Steel Shell Solidification Model
• Enthalpy formulation of the transient 1-D heat conduction equation is solved:equation is solved:
1H Tkr
t r r r
∂ ∂ ∂ρ =∂ ∂ ∂
• Top row temperatures:
i pourT T= p
• Top row enthalpies [2]:
* *int pourTH C T L
= + inti p pour f
solidus
H C T LT
= +
where Lf is the latent heat of fusion.
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 16
Steel Shell Solidification Model
• Enthalpy of interior nodes:
11 12 2 2
Δ 1 1 1 1 2ρ Δ 2 Δ Δ 2 Δ Δ
n n n n ni i i i i
k tH H T T T
r r r r r r r+
+ − + + + − −
=
1 1Δ 2 Δ ΔΔ Δ 2 Δ
2 n nn n n i ii i steel i
T Tt k t rH H T T r
h+ + − + − + + =
• Enthalpy of side nodes with convection:
Δ Δ 2 Δρ ρi i steel ir r r r
• After the enthalpy has been calculated the temperatures are then calculated i [2]
min ,max ,i fii sol
p p
H LHT T
C C
− =
using [2] :
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 17
Validation of Steady State Aspect of the Model
• Compared the results of the simulation when it reaches steady state with analytical Solution.
Governing equation for Analytical solution [1]:• Governing equation for Analytical solution [1]:
01 Tkr
r r r =
∂ ∂∂ ∂ Tflame
r
• Heat flux through the nozzle is calculated using:
r r r ∂ ∂hflame, T1
z
ln( / )1 1flame ambient
o i
flame i ambient o
T Tq
r r
h r k h r
−=
+ +
hambient, T2
Tambient
Refractory, kir orT , r
• Finally, the temperatures in the nozzle are : f
1 flame
qT T
h r= −
i or r t= −
q r
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 18
fflame ih r
2 ambientambient o
qT T
h r= +
1 lni
q rT T
k r
= −
Simulation conditions for validation of steady state aspect of the model
Label Symbol Value Units
Outer Radius of Refractory ro 67.5 mm
Bulk Refractory Wall Thickness t29.5 mm
Initial Nozzle TemperatureTintital 27* °C
Ambient Temperature T 27 °CTambient 27 C
Flame Temperature Tflame 1460 °CInternal Convection heat transfer
Coefficient (Forced) hflame 50 W/(m2K)
External Convection heat transfer Coefficient (Free)
hambient 7.3 W/(m2K)
Thermal ConductivityK 18.21 W/m-K
Specific Heat Cp 804* J/kg-Kp p g
Density ρ 2347 kg/m3
Stefan Boltzman's Constantσ 5.67E-8
Emmissivity ε 0.96
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 19
* Parameters required by transient simulation method
Validation – Steady state aspect of the model
• The results of the simulation are in good agreement with that of the analytical solution
Single Layer, No radiation Single Layer, with radiationg y , g y ,
Four Layers, No radiation Four Layers, with radiation
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 20
Validation of transient aspect of the model
• Compare the results of the simulation with that of the lumped thermal heat capacity model.
• System undergoing a transient thermal response to a heat transfer process has a nearly uniform temperature and small differences of temperature within the system can be ignored.
Th d l i lid l if th Bi t b (hL/k) 0 1• The model is valid only if the Biot number (hL/k) < 0.1
• The governing equation is [1]
( )p e
dTVC hA T T
dtρ = − −p edt
• To solve this equation, one initial condition is required:
t=0: T=To.
Solving the equation, the temperature at any time,t can be calculated from:Solving the equation, the temperature at any time,t can be calculated from:
( / )phA VC te
o e
T Te
T T− ρ− =
−
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 21
where To is the initial surface temperature, Te is the ambient temperature.
Simulation Parameters – Validation of transient aspect of the modelp
Label Symbol Value Units
Outer Radius of Refractory ro 67.5 mmOuter Radius of Refractory ro 67.5 mm
Bulk Refractory Wall Thickness t29.5 mm
Initial Nozzle TemperatureTintital 1100 °C
Ambient Temperature Tambient 27 °C
External Convection heat transfer Coefficient (Free) hambient 7.3 W/(m2K)Coefficient (Free) ambient
Thermal ConductivityK 1000 W/m-K
Specific Heat Cp 804 J/kg-K
Density ρ 2347 kg/m3
Stefan Boltzman's Constantσ 5.67E-8
Emmissivity ε 0.96Emmissivity ε 0.96
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 22
Comparison of Results of lumped model and transient simulation
• The results of the simulation are in good agreement with that of the lumped thermal heat capacity model
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 23
Output page of the tool
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 24
Comparison with measurements (inside heat transfer coefficient = 72 W/m2-K))
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 25
Comparison with measurements (inside heat transfer coefficient = 18 W/m2-K, emissivity = 0.5)
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 26
Parametric Study
Parameters Highest Temperature Difference in temp. between inner and outer
surface
Forced Convection = 72 W/m2-K, emissivity = 0.5
920 °C 90 °C
Forced Convection = 18 W/m2-K, emissivity = 0.5
585 °C 30 °C
Thermal Conductivity is 954 °C 150 °Chalved
Emissivity increased to 0.9
850 °C 100 °C
Specific Heat is doubled 954 °C 100 °C
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 27
Conclusions
• The temperature in the inner surface of the nozzle reached 900 °C after a preheat time of 2 hours If the inside heat900 C after a preheat time of 2 hours. If the inside heat transfer coefficient is reduced to 18 W/m2-K the temperature in the inner surface of the nozzle is 585 °C. Results from
i l i l ti t h th f i t f thinumerical simulation match those of experiments for this case.
• The tool can be used to predict the temperatures in theThe tool can be used to predict the temperatures in the nozzle during different stages of preheat, cool down and casting.
Th l b d l l h fl d• The tool can be used to calculate the flame temperature and heat transfer coefficients for different fuels and varying composition.
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 28
p
• Air entrainment should be decreased, because excess air reduces the flame temperature.
References
1. Incropera, F.P., and Dewitt, P.D., 2002, Fundamentals of Heat and Mass Transfer, John Wiley and Sons, New York.Mass Transfer, John Wiley and Sons, New York.
2. Thomas, B.G. and B. Ho, "Spread Sheet Model of Continuous Casting," Journal of Engineering for Industry, ASME, New York, NY, Vol. 118, No. 1, 1996, pp. 37-44.No. 1, 1996, pp. 37 44.
3. Poling, B.E., O’Connell J.M., and Prausnitz, J.M., 2001, The Properties of Gases and Liquids, McGraw-Hill, New York.
4 Moran J M and Shapiro H N 2004 Fundamentals of Engineering4. Moran, J.M., and Shapiro, H.N., 2004, Fundamentals of Engineering Thermodynamics, John Wiley and Sons, New York.
5. Report on “Modeling of Tundish Nozzle Preheating” by J. Mareno and B G ThomasB.G. Thomas.
University of Illinois at Urbana-Champaign • Metals Processing Simulation Lab • Varun Kumar Singh • 29
Acknowledgementsg
• Continuous Casting Consortium Members(ABB A l Mitt l B t l C LWB(ABB, Arcelor-Mittal, Baosteel, Corus, LWB Refractories, Nucor Steel, Nippon Steel, Postech, Posco ANSYS-Fluent)Posco, ANSYS Fluent)
• Rob Nunnington LWB Refractories• Rob Nunnington, LWB Refractories
University of Illinois at Urbana-Champaign • Mechanical Science & Engineering • Metals Processing Simulation Lab • Lance C. Hibbeler • 30