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CWJCR Advanced Scaling Techniques for the Modeling of Materials Processing Patricio F. Mendez Colorado School of Mines
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Advanced Scaling Techniques for the Modeling of Materials Processing

Jan 02, 2016

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Advanced Scaling Techniques for the Modeling of Materials Processing. Patricio F. Mendez Colorado School of Mines. Goals. For people less familiar with scaling will show how scaling is especially helpful for materials processes For people familiar with scaling - PowerPoint PPT Presentation
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Page 1: Advanced Scaling Techniques for the Modeling of Materials Processing

CWJCR

Advanced Scaling Techniques for the Modeling of Materials Processing

Patricio F. MendezColorado School of Mines

Page 2: Advanced Scaling Techniques for the Modeling of Materials Processing

2CWJCR

Goals

• For people less familiar with scaling– will show how scaling is especially helpful for materials

processes

• For people familiar with scaling– will show a new relationship that permits to automate part

of the scaling process

• The reasoning applies to almost all materials processes

• For clarity, I’ll use a particular welding problem as an example, but the approach is valid beyond welding

Page 3: Advanced Scaling Techniques for the Modeling of Materials Processing

3CWJCR

Materials Processes are “Multiphysics” and Coupled

• Welding example: free surface depression of weld pool. Can induce defects and lower productivity

Page 4: Advanced Scaling Techniques for the Modeling of Materials Processing

4CWJCR

Materials Processes are “Multiphysics” and Coupled

• Multiphysics in the weld pool (12)

weld pool

substrate

solidified metal

arc

electrode

Page 5: Advanced Scaling Techniques for the Modeling of Materials Processing

5CWJCR

Materials Processes are “Multiphysics” and Coupled

• Multiphysics in the weld pool– Inertial forces

weld pool

substrate

solidified metal

arc

electrode

Page 6: Advanced Scaling Techniques for the Modeling of Materials Processing

6CWJCR

Materials Processes are “Multiphysics” and Coupled

• Multiphysics in the weld pool– Inertial forces– Viscous forces

weld pool

substrate

solidified metal

arc

electrode

Page 7: Advanced Scaling Techniques for the Modeling of Materials Processing

7CWJCR

Materials Processes are “Multiphysics” and Coupled

• Multiphysics in the weld pool– Inertial forces– Viscous forces– Hydrostatic

weld pool

substrate

solidified metal

arc

electrode

gh

Page 8: Advanced Scaling Techniques for the Modeling of Materials Processing

8CWJCR

Materials Processes are “Multiphysics” and Coupled

• Multiphysics in the weld pool– Inertial forces– Viscous forces– Hydrostatic– Buoyancy

weld pool

substrate

solidified metal

arc

electrode

ghT

Page 9: Advanced Scaling Techniques for the Modeling of Materials Processing

9CWJCR

Materials Processes are “Multiphysics” and Coupled

• Multiphysics in the weld pool– Inertial forces– Viscous forces– Hydrostatic– Buoyancy– Conduction

weld pool

substrate

solidified metal

arc

electrode

Page 10: Advanced Scaling Techniques for the Modeling of Materials Processing

10CWJCR

Materials Processes are “Multiphysics” and Coupled

• Multiphysics in the weld pool– Inertial forces– Viscous forces– Hydrostatic– Buoyancy– Conduction– Convection

weld pool

substrate

solidified metal

arc

electrode

Page 11: Advanced Scaling Techniques for the Modeling of Materials Processing

11CWJCR

Materials Processes are “Multiphysics” and Coupled

• Multiphysics in the weld pool– Inertial forces– Viscous forces– Hydrostatic– Buoyancy– Conduction– Convection– Electromagnetic

weld pool

substrate

solidified metal

arc

electrode

J

BB

J×B

Page 12: Advanced Scaling Techniques for the Modeling of Materials Processing

12CWJCR

Materials Processes are “Multiphysics” and Coupled

• Multiphysics in the weld pool– Inertial forces– Viscous forces– Hydrostatic– Buoyancy– Conduction– Convection– Electromagnetic– Free surface

weld pool

substrate

solidified metal

arc

electrode

Page 13: Advanced Scaling Techniques for the Modeling of Materials Processing

13CWJCR

Materials Processes are “Multiphysics” and Coupled

• Multiphysics in the weld pool– Inertial forces– Viscous forces– Hydrostatic– Buoyancy– Conduction– Convection– Electromagnetic– Free surface– Gas shear

weld pool

substrate

solidified metal

arc

electrode

Page 14: Advanced Scaling Techniques for the Modeling of Materials Processing

14CWJCR

Materials Processes are “Multiphysics” and Coupled

• Multiphysics in the weld pool– Inertial forces– Viscous forces– Hydrostatic– Buoyancy– Conduction– Convection– Electromagnetic– Free surface– Gas shear– Arc pressure

weld pool

substrate

solidified metal

arc

electrode

Page 15: Advanced Scaling Techniques for the Modeling of Materials Processing

15CWJCR

Materials Processes are “Multiphysics” and Coupled

• Multiphysics in the weld pool– Inertial forces– Viscous forces– Hydrostatic– Buoyancy– Conduction– Convection– Electromagnetic– Free surface– Gas shear– Arc pressure– Marangoni

weld pool

substrate

solidified metal

arc

electrode

Page 16: Advanced Scaling Techniques for the Modeling of Materials Processing

16CWJCR

Materials Processes are “Multiphysics” and Coupled

• Multiphysics in the weld pool (12)– Inertial forces– Viscous forces– Hydrostatic– Buoyancy– Conduction– Convection– Electromagnetic– Free surface– Gas shear– Arc pressure– Marangoni– Capillary weld pool

substrate

solidified metal

arc

electrode

Page 17: Advanced Scaling Techniques for the Modeling of Materials Processing

17CWJCR

Materials Processes are “Multiphysics” and Coupled

Hydrostatic

Buoyancy

Electromagnetic

Free surface

Capillary

Gas shear

Arc pressure

Marangoni

Inertial forcesViscous forces

ConductionConvection

Page 18: Advanced Scaling Techniques for the Modeling of Materials Processing

18CWJCR

Materials Processes are “Multiphysics” and Coupled

Hydrostatic

Buoyancy

Electromagnetic

Free surface

Capillary

Gas shear

Arc pressure

Marangoni

Inertial forcesViscous forces

ConductionConvection

Page 19: Advanced Scaling Techniques for the Modeling of Materials Processing

19CWJCR

Materials Processes are “Multiphysics” and Coupled

Hydrostatic

Buoyancy

Electromagnetic

Free surface

Capillary

Gas shear

Arc pressure

Marangoni

Inertial forcesViscous forces

ConductionConvection

Page 20: Advanced Scaling Techniques for the Modeling of Materials Processing

20CWJCR

Materials Processes are “Multiphysics” and Coupled

Hydrostatic

Buoyancy

Electromagnetic

Free surface

Capillary

Gas shear

Arc pressure

Marangoni

Inertial forcesViscous forces

ConductionConvection

Page 21: Advanced Scaling Techniques for the Modeling of Materials Processing

21CWJCR

Materials Processes are “Multiphysics” and Coupled

Hydrostatic

Buoyancy

Electromagnetic

Free surface

Capillary

Gas shear

Arc pressure

Marangoni

Inertial forcesViscous forces

ConductionConvection

Page 22: Advanced Scaling Techniques for the Modeling of Materials Processing

22CWJCR

Materials Processes are “Multiphysics” and Coupled

Hydrostatic

Buoyancy

Electromagnetic

Free surface

Capillary

Gas shear

Arc pressure

Marangoni

Inertial forcesViscous forces

ConductionConvection

Page 23: Advanced Scaling Techniques for the Modeling of Materials Processing

23CWJCR

Materials Processes are “Multiphysics” and Coupled

Hydrostatic

Buoyancy

Electromagnetic

Free surface

Capillary

Gas shear

Arc pressure

Marangoni

Inertial forcesViscous forces

ConductionConvection

Page 24: Advanced Scaling Techniques for the Modeling of Materials Processing

24CWJCR

Disagreement about dominant mechanism

• Experiments cannot show under the surface• Numerical simulations have convergence

problems with a very deformed free surface

Proposed explanations for very deformed weld pool• Ishizaki (1980): gas shear, experimental• Oreper (1983): Marangoni, numerical• Lin (1985): vortex, analytical• Choo (1991): Arc pressure, gas shear, numerical• Rokhlin (1993): electromagnetic, hydrodynamic,

experimental• Weiss (1996): arc pressure, numerical

Page 25: Advanced Scaling Techniques for the Modeling of Materials Processing

25CWJCR

Scaling of a high current weld pool• Goals:

– Identify dominant phenomena:• gas shear? Marangoni? electromagnetic? arc pressure?

– Relate results to process parameters• materials properties, welding velocity, weld current

– Estimate characteristic values:• velocity, thickness, temperature

thickness

velocity

Page 26: Advanced Scaling Techniques for the Modeling of Materials Processing

26CWJCR

Scaling of a high current weld pool• Governing equations (9):

U

z’

xz

Page 27: Advanced Scaling Techniques for the Modeling of Materials Processing

27CWJCR

Scaling of a high current weld pool• Boundary Conditions:

at free surface at solid-melt interface

far from weld

free surface

solid-melt interfacefar from weld

Page 28: Advanced Scaling Techniques for the Modeling of Materials Processing

28CWJCR

Scaling of a high current weld pool• Variables and Parameters

– independent variables (2)

– dependent variables (9)

– parameters (18)

from other models, experiments

with so many parameters Dimensional Analysis is not effective

Page 29: Advanced Scaling Techniques for the Modeling of Materials Processing

29CWJCR

Classical Scaling Approach

1. Scale variables and differential expressions

2. Assume a set of dominant driving forces

3. Normalize equations

4. Solve for the unknown terms

5. Verify self-consistency

6. If not self-consistent, return to 3.

Roughly, this is the approach suggested by Dantzig and Tucker, Bejan, Kline, Denn, Deen, Sides, Chen, Astarita, and more

Page 30: Advanced Scaling Techniques for the Modeling of Materials Processing

30CWJCR

Classical Scaling Approach

unknown characteristic values (9):

Page 31: Advanced Scaling Techniques for the Modeling of Materials Processing

31CWJCR

Classical Scaling Approachgoverning equation

Page 32: Advanced Scaling Techniques for the Modeling of Materials Processing

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Classical Scaling Approachgoverning equation

scaled variables

OM(1)

Page 33: Advanced Scaling Techniques for the Modeling of Materials Processing

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Classical Scaling Approachgoverning equation

scaled variables

OM(1)normalized equation

output inputinput

Page 34: Advanced Scaling Techniques for the Modeling of Materials Processing

34CWJCR

Classical Scaling Approach

output inputinput

two possible balances

B1

Page 35: Advanced Scaling Techniques for the Modeling of Materials Processing

35CWJCR

Classical Scaling Approach

output inputinput

two possible balances

B1 B2

Page 36: Advanced Scaling Techniques for the Modeling of Materials Processing

36CWJCR

Classical Scaling Approach

output inputinput

two possible balances

B1 B2

balance B1 generates one algebraic equation:

Page 37: Advanced Scaling Techniques for the Modeling of Materials Processing

37CWJCR

Classical Scaling Approach

output inputinput

two possible balances

B1 B2

balance B1 generates one algebraic equation:

balance B2 generates a different equation:

Page 38: Advanced Scaling Techniques for the Modeling of Materials Processing

38CWJCR

Classical Scaling Approach

output inputinput

two possible balances

B1 B2

balance B1 generates one algebraic equation:

balance B2 generates a different equation:

self-consistency: choose the balance that makes the neglected term less than 1

Page 39: Advanced Scaling Techniques for the Modeling of Materials Processing

39CWJCR

Classical Scaling Approachtwo possible balances

balance B1 generates one algebraic equation:

balance B2 generates a different equation:

self-consistency: choose the balance that makes the neglected term less than 1

TWO BIG PROBLEMS FOR MATERIALS PROCESSES!

Page 40: Advanced Scaling Techniques for the Modeling of Materials Processing

40CWJCR

Classical Scaling Approachtwo possible balances

balance B1 generates one algebraic equation:

balance B2 generates a different equation:

self-consistency: choose the balance that makes the neglected term less than 1

TWO BIG PROBLEMS FOR MATERIALS PROCESSES!

?

??

?

?

1 equation2 unknowns

1 equation3 unknowns

1. Each balance equation involves more than one unknown

Page 41: Advanced Scaling Techniques for the Modeling of Materials Processing

41CWJCR

Classical Scaling Approach

1. Each balance equation involves more than one unknown

2. A system of equations involves many thousands of possible balances

two possible balances

balance B1 generates one algebraic equation:

balance B2 generates a different equation:

self-consistency: choose the balance that makes the neglected term less than 1

TWO BIG PROBLEMS FOR MATERIALS PROCESSES!

Page 42: Advanced Scaling Techniques for the Modeling of Materials Processing

42CWJCR

Scaled equations (9)

all coefficients are power lawsall terms in parenthesis expected to be OM(1)

Page 43: Advanced Scaling Techniques for the Modeling of Materials Processing

43CWJCR

Scaled BCs (6)

Boundary conditions

Page 44: Advanced Scaling Techniques for the Modeling of Materials Processing

44CWJCR

Iterative process

• Simple scaling approach involves 334098 possible combinations

• There are 116 self-consistent solutions– there is no unicity of solution– we cannot stop at first self-consistent solution– self-consistent solutions are grouped into 55

classes (1- 6 solutions per class)

Page 45: Advanced Scaling Techniques for the Modeling of Materials Processing

45CWJCR

Automating iterative process

• Power-law coefficients can be transformed into linear expressions using logarithms

• Several power law equations can then be transformed into a linear system of equations

• Normalizing an equation consists of subtracting rows

Page 46: Advanced Scaling Techniques for the Modeling of Materials Processing

46CWJCR

Matrix of Coefficients

9 equations

6 BCs

one row for each term of the equation

Page 47: Advanced Scaling Techniques for the Modeling of Materials Processing

47CWJCR

9 equations

6 BCs

one row for each term of the equation

18 parameters 9 unknown charact. values

Page 48: Advanced Scaling Techniques for the Modeling of Materials Processing

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Calculation of a Balance1. select 9 equations2. select dom. input

Page 49: Advanced Scaling Techniques for the Modeling of Materials Processing

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Calculation of a Balance1. select 9 equations2. select dom. input3. select dom. output

Page 50: Advanced Scaling Techniques for the Modeling of Materials Processing

50CWJCR

Calculation of a Balance1. select 9 equations2. select dom. input3. select dom. output4. build submatrix of

selected normalized outputs

18 parameters 9 unknown charact. values

[No]P’ [No]S 9x9

Page 51: Advanced Scaling Techniques for the Modeling of Materials Processing

51CWJCR

Calculation of a Balance

18 parameters 9 unknown charact. values

[No]P’ [No]S 9x9

Page 52: Advanced Scaling Techniques for the Modeling of Materials Processing

52CWJCR

Calculation of a Balance

18 parameters 9 unknown charact. values

[No]P’ [No]S 9x9

Page 53: Advanced Scaling Techniques for the Modeling of Materials Processing

53CWJCR

Calculation of a Balance

18 parameters 9 unknown charact. values

[No]P’ [No]S 9x9

incompatible

power law estimation

Page 54: Advanced Scaling Techniques for the Modeling of Materials Processing

54CWJCR

Calculation of a Balance

incompatible

power law estimation

9 unknowns 18 parametersMatrix [S]

Page 55: Advanced Scaling Techniques for the Modeling of Materials Processing

55CWJCR

Calculation of a Balance

9 unknowns 18 parametersMatrix [S]

Page 56: Advanced Scaling Techniques for the Modeling of Materials Processing

56CWJCR

Self consistency

• can be checked using matrix approach

• checking the 334098 combinations took 72 seconds using Matlab on a Pentium M 1.4 GHz

secondary terms submatrices of normalizedsecondary terms

Page 57: Advanced Scaling Techniques for the Modeling of Materials Processing

57CWJCR

Scaling resultsμm50cK100cT

m/s 1cU

c=

36

m

Uc

c

c

2/12 cc UD

kqT ccc

cc UDU 2

Page 58: Advanced Scaling Techniques for the Modeling of Materials Processing

58CWJCR force dominant

force drivinggroups essdimensionl provide termsSecondary

Scaling results

1.00

0.34

0.08

0.07

0.06

0.03

0.03

0.03

7.E

-05

3.E

-04

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

arc

pres

sure

/ vi

scou

s

elec

trom

agne

tic

/ vis

cous

hydr

osta

tic

/ vis

cous

capi

llar

y / v

isco

us

Mar

ango

ni /

gas

shea

r

buoy

ancy

/ vi

scou

s

gas

shea

r / v

isco

us

conv

ecti

on /

cond

ucti

on

iner

tial

/ vi

scou

s

diff

.=/d

iff.

plasma shear causes crater

Page 59: Advanced Scaling Techniques for the Modeling of Materials Processing

59CWJCR

Summary

• Materials processes are “Multiphysics” and “Multicoupled”

• Scaling helps understand the dominant forces in materials processes

• Several thousand iterations are necessary for scaling

• The “Matrix of Coefficients” and associate matrix relationships help automate scaling

Page 60: Advanced Scaling Techniques for the Modeling of Materials Processing

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Page 61: Advanced Scaling Techniques for the Modeling of Materials Processing

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Approaches to the high current weld pool problem

• Experimental

Ishizaki, 1962,1980. Hammer blow, water droplets. Savage 1978, blank shot

Shimada, 1982

Force Balance:

Lin and Eagar, 1985

Savage, 1979

Adonyi, 1992

… and many more

very depressed weld pool become a “film”

Page 62: Advanced Scaling Techniques for the Modeling of Materials Processing

62CWJCR

Approaches to the high current weld pool problem

• Numerical

Kumar A, Zhang W, DebRoy T, JOURNAL OF PHYSICS D, 2005

Lee, Welding Journal, 1997

Chen, 1998

Kim, Welding Journal, 1992

Tsai, Int. J. Num. Meth. Fluids, 1989Zacharia, Welding Journal, 1988

Most numerical models based on recirculating flows

Wei and Giedt, Welding Journal 1985

Page 63: Advanced Scaling Techniques for the Modeling of Materials Processing

63CWJCR

Approaches to the high current weld pool problem

• Scaling: Focused on recirculating flowsOreper & Szekely, J. Fluid Mech.

1984, TWR 1986

DebRoy & David

Rev. Modern Phys

1995

Rivas & Ostrach,

Int. J. Heat Mass Transfer

1992

Chakraborty & Dutta

STWJ, 1992

No velocity BL

No thermal BL

Velocity BL

No thermal BL

Velocity BL

Thermal BL

T, R, D come from numerical calculations, experiments

T comes from scaling, R, D from numerical calculations, experiments