ArcelorMittal Research June 2008

Optimization of lubrication and cooling in cold rolling

from 17 mars to 12 September 2008

- RFCS Optcoolub -

Tutor: NGO Quang Tien

Project leader : Nicolas LEGRAND

03/09/10

2

Presentation

• Name : BOULECHFAR Kamal

• Age: 26

• Nationality : Moroccan.

• Engineering school: Polytechnic School of the University of Orleans - Polytech’Orléans. “numerical simulation of mechanics “

• Graduation : DUT Thermal-Energy Engineering.

• My aim objective: Researches engineer in energetic-mechanics.

03/09/10

3

Internship : Background

This internship is carried out under the project Optcoolub

Optimize cooling systems in cold rolling in order to reduce water

consumption.

Make better lubrication on cold rolling mills

03/09/10

4

Internship : involvement

Analysis and optimization of lubricationand cooling system in cold rolling

The second aim is: Study of 13 roll cooling trials to understand cooling mechanism in roll

and strip ( HTC, Flux, T°).

Brno collaboration.Propose an optimum mill cooling configuration and confirm by pilot

trials ARsa.

The primary aim is : Developing / completing a modeling of cooling system : simulator Avilès

HTCs ( coolant-strip and coolant-roll )Rheology

Identify actions increasing the efficiency of cooling

03/09/10

5

The primary aim :

Developing / completing a modeling cooling system :

simulator Avilès

1) HTCs

2) Rheology

03/09/10

6

Advantage:It takes into account:

the parameters: , and νf(T)

influence of speed V

Thermal simulator: HTC(x) strip-coolant

)(Tk f

Stand n

wipingroll

Stand n+1

work roll work roll

HTC(x)

strip

x

x

Stand n

wipingroll

Stand n+1

work roll work roll

HTC(x)

strip

x

x

Improvement Heat Transfer Coefficient of strip-coolant interface along mill interstand

Current situation

3 Pr..

...)(L

VkC

x

Lxh

ff

EM

ν=

Weakness:It does not take into account:

Strip temperature

The water flow “explicitly”.

)Pr(T

Not Adapted for high temperatures of strip

Forced convection:

03/09/10

7

Thermal simulator: HTC(x)

What happen in a high strip temperature “Typically Ts >100°C at least “ ?

20°C 300°C

Problem

the material-coolant interface: vapor ,HTC The first appearance of bubbles

promotes the exchange of heat.

Higher the temperature higher the agitation of water “convection"

03/09/10

8

Thermal simulator: HTC(x)

Improvement When T°<100° : natural convection When T°>100° : Hodgson model

Weakness: “ to verify”It does not take into account:

influence of speed V

Advantage:It takes into account:

Strip temperature

The water flow.

example of strip temperature evolution

Evolution of HTC and Temperature along the strip

5000

15000

25000

35000

45000

55000

65000

75000

85000

95000

0.01 0.11 0.21 0.31 0.41

X(m) strip

HT

C

60

80

100

120

140

160

180

200

220

240

Te

mp

eratu

re °C

HTC coupling Hodgson and currentmodel

current model in simulator

surface temperature

03/09/10

9

Thermal simulator: Rheology

Current situation

Strip heat transfers in the roll bite:

strip plastic yield stress

( ) ( ) ECeBA xDxx +−+= − )(

0 1 εεσWe use the SMATCH law

Weakness: “ to verify”Does not take into account

The strain rate

Temperature

Plastic deformation Frictional heat Heat conduction

03/09/10

10

Thermal simulator: Rheology

Problem : the graphics show that strip rheology depends on the strain rate

We made those experiences for 3 steel grades of AVILES.

To validate the LUCY-BALISTIK model.

Influence of speedOur experiment

Influence of temperatureLiterature data

03/09/10

11

Thermal simulator: Rheology

Advantage predicting precisely the evolution of metal hardness along the rolling mill

Improvement

Integrate LUCY-BALISYIK model in our simulator:

03/09/10

12

Second aim is:

Study of 13 roll cooling trials to understand cooling

mechanism in roll and strip ( HTC, Flux, T°).

Propose an optimized mill cooling configuration and

confirm by pilot trials ARsa.

03/09/10

13

Conditions defined for realization at stand #4 of Aviles TDM2

Brno has characterized 13 roll cooling configurations for Optcoolub project

03/09/10

14

Method of operating results

S∂

Heat flux variation as a function of time

A specific program was developed to extractFlux and temperature measured under thedirect spray during the tests.

Variation de flux et de température en fonction de temps

0

20

40

60

80

100

120

140

21950 22000 22050 22100 22150 22200 22250 22300 22350 22400

Température en (°C)

Pa

s d

e t

em

ps

0

200

400

600

800

1000

1200

1400

Flu

x c

ylin

dre

en

kW/m

²

temperaturePhi

study area

S∂ S∂ S∂

Time

Tem

pera

ture

03/09/10

15

Flux en fonction de la tmpérature Moyenne de surface de cylindre

0

500

1000

1500

2000

2500

0 50 100 150 200 250

Température moyenne de surface (°C)

flu

x (k

w/m

²)

Phi(T)

Logarithmique(Phi(T))

AV13-4

)(THTC

)(Tϕ

Evolution of Flux and HTC with a temperature of the cylinder

HTC mesuré et HTC Loi en fonction de la température moyenne de surface de cylindre

0

5000

10000

15000

20000

25000

0 50 100 150 200 250 300

Température moyenne de surface cyl °C

HT

C (

w/m

²K)

HTCmoy w /m ²K

Flux dependency to roll surface temperature is higher

03/09/10

16

Results with our analysis

Results with Brno analysis ±500: 13- 12- 8- 6 - 11

HTC average for each configuration “ position 4” at Twater = 0°c

Results obtained with Brno analysis

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

AV1

AV2

AV3

AV4

AV5

AV6

AV7

AV8

AV9

AV10

AV11

AV12

AV13

HT

C m

oy

en

ne

+- 200

+- 500

Results with Brno analysis ±200: 13- 6- 8- 12 - 9

Configuration common among all tests: 13-6-12

HTC average for each configuration

0

2000

4000

6000

8000

10000

12000

HT

C (

w/m

²K)

AV

4-1

AV

4-2

AV

4-3

AV

4-4

AV

4-5

AV

4-6

AV

4-7

AV

4-8

AV

4-9

AV

4-1

0

AV

4-1

1

AV

4-1

2

AV

4-1

3

HTC moyenne pour chaque essai position 4

HTC moyenne

03/09/10

17

)(Tϕ

If we use the flux as an indicator of the efficiency of cooling, somme differences in the classification are obtained(compared to classification with HTC)

However, we can conclud that config. N°6 is a good configuration as already concluded by Brno

Average flux for each configuration

0

200

400

600

800

1000

1200

1400

1600

1800

Flu

x m

oy

(w/m

²)

AV

4-1

AV

4-2

AV

4-3

AV

4-4

AV

4-5

AV

4-6

AV

4-7

AV

4-8

AV

4-9

AV

4-10

AV

4-11

AV

4-12

AV

4-13

Mean heat Flux for each test. Sensor n°4

Phi moyenne

03/09/10

18

-300 -250 -200 -150 -100 -50 0 50 100 150 200 250 300

Position [mm]

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

1333.3

Liq

uid

lev

el [

l/m

in.m

]

Liquid level (VK=32.30%) Mean value (994.41 l/min.m)

Roll surface

Valeurs de HTC et Phi en fonction de la position du capteur sur la largeur

HT

C (

W/m

²°C

)

ou

P

hi (

10.k

W/m

²)

phi a 100°C

HTC à 100°C

N°13

Uniformity of HTC with distribution of flow

Conclusions : globally, when the flow is strongly heterogeneous, the HTC seems heterogeneous also,but HTC does not follow irregularities of the flow

Valeurs de HTC et Phi en fonction de la position du capteur sur la largeur

0

2000

4000

6000

8000

10000

12000

-250 -200 -150 -100 -50 0 50 100 150 200

HT

C (

W/m

²°C

) o

u P

hi (1

0.k

W/m

²)

-225

-150

-100

-50

0

50

100

150

HTC w/m²°C

03/09/10

19

Conclusion

1er aim : thermal simulator

Improvement of inter-stand heat transfer model

The rheology experiments have been done

2nd aim : optimized mill cooling configuration

Analysis of 13 roll cooling trials.

Experiment planning has been done.

03/09/10

20

In Progress……..

• Achievement of simulator• The second aim:

# To find out an optimized mill cooling configuration “pilot experiment” .

Comparison of 6 roll cooling configurations:

1test with HTRC 6 test with nozzles

The test plan : ready

Monitoring and analysis of tests : begin next week

Synthesis of testes and conclusion: next weeks