state of the art num mod weld phenomena final...Post weld heat treatment to avoid higher resdiual stresses and reduce hydrogen content 25 N. Enzinger, H. Cerjak Brussels, 29.4.2009

Inst. f. Materials Science and Welding

State of the art in numerical modellingof weld phenomena

N. Enzinger, H. Cerjak

Graz University of Technology, Inst. for Materials Science and Welding,

Kopernikusg 24 8010 Graz AustriaKopernikusg. 24, 8010 Graz, Austria

1

N. Enzinger, H. Cerjak Brussels, 29.4.2009


Introduction

Wh i l i l ti ?• Why numerical simulation?• What is possible?

• Examples presented in M th ti l M d lli„Mathematical Modelling

of Weld Phenomena 8“• Actual examples from• Actual examples from

IWS at Graz University of Technology

• Summary and Conclusion

2



Why numerical simulation?

P i ti ti d ti i ti• Process investigation and optimization– Process parameters

Tool development– Tool development

• Improved understanding• Improved understanding

• Prediction of behaviour• Prediction of behaviour– Without experiments– Long term forecastLong term forecast

• Failure analysis

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Failure analysis


Investigated Processes

A W ldi• Arc Welding– TIG

Submerged arc welding– Submerged arc welding

• Laser Welding• Resistant Spot Welding

and arbitrary, complex• Resistant Spot Welding

• Cladding• Friction and Friction Stir Welding

pcombinationsto model total production• Friction and Friction Stir Welding

• Heat treatmentMachining

chain

• Machining• Forming

4



Investigated Materials

Al i i d it ll• Aluminium and its alloys

• Steel– Structural steel

Advanced high strength steels– Advanced high strength steels– Austenitic stainless steel

• Quartz Glass

• Polymers

5



Considered Phenomena

T t di t ib ti• Temperature distribution• Welding residual stresses and deformation

mac

ro

• Stresses during welding m

odel

ling

• Fluid flow in arc and weld pool• Vaporation

mes

o

scal

em

o

• Solidification

Mul

ti –

s

• Metallurgical effects and transformation• Damage (creep, cracking, …) m

icro

6



Scientific fields• Solid state physics and mechanics• Solid state physics and mechanics

– residual stresses and deformation– friction– damage model (creep fracture hot / cold cracking)damage model (creep, fracture, hot / cold cracking)

• Electromagnetism– arc processes– spot welding and arbitrary, p g

• Fluid flow– weld pool formation / weld pool shape

• Thermodynamics / kinetics

y,complexinteractionsby couplingy /

– microstructure– diffusion– phase transformation

• Heat transfer– heat input– cooling

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What to consider in simulation –What to consider in simulation –preliminary thoughts

A l t i t t i fl hi h b lt d iAnalyze most important influences, which can be altered in process, to consider proper modelling approach

M. Asadi and A.H. Kokabi. Numerical Modelling and Studying the Effects of

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Resistance Spot Welding Parameters on Tensile-Shear Strength in Automotive Sheets.


Modelling approachExecution Speed

Extrapolation quality

Theoretical model

Empirical modelNeural NetworkNeural NetworkRegression Analysis

Experimental Expense

D W i K H Ch i t d J K K i t C t C lib ti f Th l

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D. Weiss, K.H. Christensen and J.K. Kristensen. Computer Calibration of Thermal Welding Models. p. 469-484 in Mathematical Modelling of Weld Phenomena 8.


Typical approach in Numerical Modelling

onm

plifi

catio

Sim

• Validation: “solving the correct equation” g q• Verification: “solving the equation correctly”

− Discretisation (meshing, time steps)− Iteration (convergence criteria)

Programming and user errors

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− Programming and user errorsD. Radaj and L.-E. Lindgren. Verification and Validation in Computational Welding Mechanics


Time consuming

Model Half model Full model Full modelSize Medium LargeComplexity Simple Medium high

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C. Schwenk, M. Rethmeier and D. Weiss. Rapid Generation of Temperatur Fields for Simulation of Welding Distortions


Typical application of NN

D W i K H Ch i t d J K K i t C t C lib ti f Th l

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D. Weiss, K.H. Christensen and J.K. Kristensen. Computer Calibration of Thermal Welding Models. p. 469-484 in Mathematical Modelling of Weld Phenomena 8.


NN prediction of toughness

J.M. Vitek and S. Travis. Neural Network Design Options

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for Mechanical Property Modelling. p. 373-386 in Mathematical Modelling of Weld Phenomena 8


Limits of NN

J.M. Vitek and S. Travis. Neural Network Design Options

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for Mechanical Property Modelling. p. 373-386 in Mathematical Modelling of Weld Phenomena 8


Coupling of complex processes

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V. Robin, E. Feulvarch, I. Masters, X. Fan and D. Dry. A local Spotweld Model to predict Large Assembly Distortions


spot welding simulation …

M.F. Zaeh, L. Papadakis and W. Rauh. Realisation of the Virtual Process

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Chain Forming-Welding on Whole Assembled Automotive Body Components by Means of Shell Elements


… of previously deformed sheets

M.F. Zaeh, L. Papadakis and W. Rauh. Realisation of the Virtual Process

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Chain Forming-Welding on Whole Assembled Automotive Body Components by Means of Shell Elements


Leads to remarkable results

M.F. Zaeh, L. Papadakis and W. Rauh. Realisation of the Virtual Process Chain Forming-Welding on Whole Assembled

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Automotive Body Components by Means of Shell Elements


Special spot weld elements

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T. Heubrandtner and G. Rangger. Modelling of Plastic Deformation of a Spotweld Based on the Trefftz-Method.


Local global approachLocal global approach

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V. Robin, E. Feulvarch, I. Masters, X. Fan and D. Dry. A local Spotweld Model to predict Large Assembly Distortions.


benefits

D f ti b ti t d• Deformation can be estimated

• Tools such as clamping devices can be optimized

• Improved accuracy of final part by– Proper clamping

P iti f t ld– Position of spot welds– Minimize deformation

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Basic Model of GMAW Process - SimWeld

• Ohmic heating of electrode• Contact resistance• Anode heat flux into droplet• Heat diffusion• Evaporation heat losses• Electromagnetic forces• Surface tension• Plasma composition• Power source

characteristics• Voltage in anode, arc and

th dcathode• Temperature dependence

of material properties

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V. Pavlyk, O. Mokrov and U. Dilthey. Heat Source Modelling in GMA-Welding and its integration in Stress-Strain-Analysis.


Application of SimWeld Results in SysweldHeat source parameters Temperature fieldp p

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V. Pavlyk, O. Mokrov and U. Dilthey. Heat Source Modelling in GMA-Welding and its integration in Stress-Strain-Analysis.


Post weld heat treatment to avoid higherPost weld heat treatment to avoid higherresdiual stresses and reduce hydrogen content

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P. Wongpanya, Th. Boellinghaus and G. Lothongkum. Numerical Simulation of Hydrogen Removal Heat Treatment Procedures in High Strength Steel Welds


Hydrogen cracking in steelIncreased preheat temperatureIncreased preheat temperatureincreases resdiual stresses

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P. Wongpanya, Th. Boellinghaus and G. Lothongkum. Numerical Simulation of Hydrogen Removal Heat Treatment Procedures in High Strength Steel Welds


Production modelling of complex parts

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J. Goldak, J. Zhou, S. Tchernov and D. Downey. Designer Driven Analysis of Welded Structures II


Production modelling of complex parts

1. Ohji-Sudnik heat source model (instead of distributed heat source) weld pool h b di dshape can be predicted

2. Anisotropic non-convex i l ti it d lmicro-macro plasticity model

(instead of isotropic macro convex plasticity)

3. Monte Carlo synthetic microstructure model (instead of density Kirkaldyof density Kirkaldymicrostructure evolution model)

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J. Goldak, J. Zhou, S. Tchernov and D. Downey. Designer Driven Analysis of Welded Structures II


Overlay technique to reduce SCCOverlay technique to reduce SCC susceptibility

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S. Courtin and Ph.Gilles. Multipass Welding on a Dissimilar Metal Weld and Overlay Design.


reduction of computation costs - macrobead approachThe main features of the technique are:

One macrobead is defined per• One macrobead is defined per overlay layer

• Return to room or preheating temperature between twotemperature between two macrobeads,

• Thermal cycles similar to welding operation are just applied on theoperation are just applied on the extreme beads of the macrobead

• Residual Stresses are overestimatedResidual Stresses are overestimated

Results• Compressive stresses are introduced at inner diameterp• Overlay technique works up to 50% of wall thickness• Thicker overlays tend to introduce tensile stresses due to bending

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S. Courtin and Ph.Gilles. Multipass Welding on a Dissimilar Metal Weld and Overlay Design.


Analytical thermal solution

speed up calculationtimes significantlytimes significantly

GTA-Welding250 Amps250 Amps12 Volt5 mm/s

V.A. Karkhin, P.N. Homich and V.G. Michailov. Models for Volume

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Heat Sources and Functional-Analytical Technique for Calculating the Temperature Fields in Butt Welding


FSW modelling

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P. Colegrove, H. Shercliff, J. Robson, N. Kamp, A. Sullivan and S. Williams. Integrated Process Modelling of Friction Stir Welding


Particle tracking – simulation andParticle tracking – simulation andexperimental verification by CT

P. Colegrove, H. Shercliff, J. Robson, N. Kamp, A. Sullivan and S. Williams. Integrated Process Modelling of Friction Stir Welding

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PhD Th. Weinberger


FSW

P di ti f t t fi ld k ll• Prediction of temperature field works well• Semi empirical modelling

• Future challange– Influence of parameters on final result– Physically based prediction of

• heat input (friction),heat input (friction), • microstructural development, • residual stresses

Defect prediction– Defect prediction– Tool wear

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Examples from current research at IWS

Si l ti f i t t l l ti i th HAZ f• Simulation of microstructural evolution in the HAZ ofa 9% Cr steel

• Modeling FSW considering a deformable tool

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Simulation of microstructural evolution in the HAZ of a 9% Cr steel

Chemical composition

41


PhD I. Holzer, IWS, TUGraz


Experimental Verification• Specimens for microstructural

investigations were produced on a GLEEBLE 1500

Experimental Verification

GLEEBLE 1500• Several specimens were exposed to

defined time-temperature sequences characterized by the peak temperature Tpy p p pand the t8/5 time

• For the microstructural characterisation the welding cycle characterised by T =1300°C and t =80s was selectedTP=1300 C and t8/5=80s was selected

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•The “as-received” conditionis characterised by theis characterised by thepresence of M23C6 an MXprecipitates.

•During welding (at T=TP) allprecipitates are dissolved.

•In the “as-welded” conditionsmall rod shaped precipitateswere present in thewere present in themicrostructure.

•During PWHT re-precipitationtakes place and theprecipitation state again ischaracterized by thepresence if M23C6 and MXprecipitatesprecipitates.

Characterisation of precipitate size

Electron microscopy was carried out at the Institute for Electron Microscopy

Characterisation of precipitate size

43


y yof Graz University of Technology using a Philips CM20.



Evolution of precipitate diameters during welding cycle and PWHT:

•During Welding (2) and in the as-welded“ condition ∑

∑∑∑ +

=⋅

=i

i ii

ii

i

iii

tdt

td

w

wdd

S l

Sample,

During Welding (2) and in the „as welded condition (3) no MX and M23C6 precipiates could be identified

•After PWHT (7) the size of MX and M23C6 reach similar values to the size in the „as-received“ condition (1)

∑∑+i ii

ii

i

dtwSample,

B. Sonderegger, Ultramicroscopy, 2006,106, 941-950condition (1)

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•Dissolution of M23C6 during austenitisationand re-precipitation during tempering

•Dissolution of all precipitate phases during

M23C6MXM Cwelding cycle and re-precipitation of M23C6

and MX precipitates during PWHTM3CM7C3

Database: MC_Steel.tdb (standard MATCALC)

45




Simulation resluts•After the heat treatment in the “as-received” condition the precipitates reach sizes of 70nm (M C ) and 27nm (MX)

M23C6MXM C(M23C6) and 27nm (MX)

•During the welding process (TP=1300°C) all precipitate phases dissolve

•After the PWHT the precipitates reach again

M3CM7C3

M23C6MXsizes of 45 nm (M23C6) and 11 nm (MX) MX

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FSW (deformable tool)

S. Khosa, T. Weinberger, N. Enzinger; Finite element analysis of material flow patterns in

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friction stir spot welding of AL6082-T6 using different process parameters and tool geometries - 5th International Conference (HEFAT) Sun City, South Africa (2007)


Boundary and Initial Conditions

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S. Khosa, T. Weinberger, N. Enzinger; Investigation of Thermomechanical Response of Work piece during Friction Stir Spot Welding (FSSW) – Proceedings of 3rd FSW Modeling and Flow Visualization Seminar. (2008), P. 97 - 102


Thermal ModelThermal Modeltssq f Δ

Δ== ητητ &

Pμτ = P.μτ =• Thermal Model

• Interfacial Heat Input D f ti l H t I tεσα &..=dq • Deformational Heat Input

• Interaction• Friction Co-efficient• Strain Rate & Resultant Stress

Energy InputLosses (Mechanical efficiency, Rad & Conv, Sound, etc)

Frictional HeatEnergy Input Frictional Heat

Deformational Heat

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S. Khosa, T. Weinberger, N. Enzinger; In Proceedings of 3rd FSW Modelling and Flow Visualization Seminar. (2008), P. 97 - 102


Material ModelsMaterial Models• Model Description

Material Model (Mises-Experimental)– Material Model (Mises-Experimental) (Temperature and Strain Rate Sensitive Data from Literature)

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After Spegarelli et al; Scripta Materilia49 (2003) 179-183


Rotational Speed

Downward Loads

Pin Profile

Process Parameters

Traverse Speed

Tool

Weld Location & Geometry

Conductivity

Material Properties

Base Material

Parameters

System Parameters

Tool Geometry

FSW Process

Backing Plate

Tool Material

Temperature Field

St Fi ld

Outputs

Velocity Profile

Stress Fields

Tool Deformations

Microstructure

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Profile Predictions S. Khosa: 5th IWS Internal Seminar, TU Graz, Austria - 2007


Model DevelopmentModel Development• Model Description

M h C t l (ALE)– Mesh Controls (ALE) • Lagrangian & Eulerian Formulation

Without ALE Step – 2

With ALE Step – 1Step – 2

Step – 1

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S. Khosa: 5th IWS Internal Seminar, TU Graz, Austria - 2007


Temperature Profile

Temperature (K)

Plunge Rate: 1.2 mm/s (72 mm/min)

Spindle Speed: 800 rpm

ALE mesh control with mass scaling

Material Model: Ideal Plastic

(SS 304)

Weinberger, T.; Khosa, S. U.; Führer, B.; Enzinger, N.: Analysis of tool wear and

54


failure mechanism during friction stir welding of steel. - in: Conference Proceedings 7th International Symposium ‘Friction Stir Welding’ . (2008) In Press


Results and DiscussionResults and Discussion

• Stir Zone Predictions

1200 RPMPlunge Rate: 72 mm/minMaterial: AA6082-T6

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S. Khosa, T. Weinberger, N. Enzinger; Investigation of Thermomechanical Response of Work piece during Friction Stir Spot Welding (FSSW) – Proceedings of 3rd FSW Modelling and Flow Visualization Seminar. (2008), P. 97 - 102


Results and DiscussionResults and Discussion

• Material Flow TrendsMaterial Flow Trends

1200 RPMPlunge Rate: 72 mm/minSheet Material: AA6082-T6 Tool: RigidTool: Rigid

Schneider, Nunes: Metal. & Mate. Trans. B 35B (2004) 777

Khosa, S. U.; Weinberger, T.; Enzinger, N.: Effect of energy input rate on the deformation behavior of AL 6082-T6 matrix during friction stir spot welding "Computer Technology in Welding and

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friction stir spot welding. – "Computer Technology in Welding and Manufacturing" - Cranfield University, Cranfield -UK (2008) In Press


Preliminary ResultsPreliminary Results

• Stress Profile

1600 RPMPlunge Rate: 72 mm/minSheet Material: SS 304Tool Material: Assumed WC-Co

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Tool Material: Assumed WC CoUnpublished Work: S. Khosa, T. Weinberger, N. Enzinger: IWS – TU Graz, Austria


Different Approaches and Aims

A i t• Accuracy improvement– More details (clamping, …)

Material model– Material model– Physical description (heat input due to friction)– Coupling of different phenomenap g p

vs. • faster calculation

– Phenomenalogical appraoch– Limited accuracy with still enough information– Large structure (real world problems)

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Summary and Conclusion

M t i l d t d d l i i l i t• Material data and model is a crucial point– Nowadays considering transformation is standard– Temperature (strain rate) dependance has to be considerede pe atu e (st a ate) depe da ce as to be co s de ed

• You have to know strength and limits of your approach, e.g.– Linear vs. quadratic finite elements formulation and stability

Transfereability of results from one mesh to another– Transfereability of results from one mesh to another– Accuracy / extrapolation

• Validation and Verification of simulation is absolutely necessary

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Thank you for your attention!Thank you for your attention!come and see more

9th International SeminarNumerical Analyses of Weldability

28 Sep - 30 Sep / Seggau Graz Austria

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Documents

state of the art num mod weld phenomena final...Post weld heat treatment to avoid higher resdiual stresses and reduce hydrogen content 25 N. Enzinger, H. Cerjak Brussels, 29.4.2009