Outline - HZG€¦ · •Friction stir welding of dissimilar alloys •Grain structure and texture evolution during FSW/FSP •Microstructure and property modelling for FSW/FSP Manchester

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Microstructure and Property Modellingof Aerospace Aluminium Alloy FrictionStir WeldsJoe RobsonSchool of MaterialsUniversity of [email protected]

Light Alloys for Environmentally Sustainable Transport

2nd IPSUS Meeting, Berlin, 12th June 2008

Outline

• FSW activities at Manchester• Modelling overview• Microstructure and strength models• Model calibration and validation• Model application

– parametric analysis of welding variables– extension to other alloys

• Summary

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FSW Activities at Manchester• Friction stir spot welding• Friction stir welding of aluminium alloy plate

for armour applications• Friction stir processing of cast aluminium

alloys• Friction stir welding and processing of

magnesium alloys• Friction stir welding of dissimilar alloys• Grain structure and texture evolution during

FSW/FSP• Microstructure and property modelling for

FSW/FSPManchester FSW machineCrawford-Swift Powerstir 320(25kW machine, 0-2000RPM 50kNX,Y force, 100kN downforce)

Model Overview• A complete physical model for FSW requires

integration of several sub-model components

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?Alloy, T, ε, ε….

Precipitate size,number, distribution,dislocation density,grain structure,texture…

Model Components• Process model

– Coupled 2-D flow and 3-D thermalmodel [Colegrove and Shercliff]

– Thermal profile predictions outputto microstructure model

• Microstructure model– Numerical model based on classical

theory– Predicts particle size distribution for

various precipitate populations

• Properties model– Classical strengthening model– Empirical toughness model– Predicts yield strength and

toughness

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Examples of Weld Microstructures

• AA7449 FSW, 20mm thick in 40mm plate, Triflat tool

parent HAZ TMAZ nugget

Microstructural Detail

• Nugget

• HAZ

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Model Representation

• heterogeneousnucleation

• enhanced diffusion• collector plate effect

PFZGB zone Grain interior zone

• heterogeneousnucleation– dispersoids– dislocations

• homogeneousnucleation

• locally depleted soluteconcentration

• no strengtheningprecipitates

Kinetic Model• Classical model based on Kampmann and Wagner numerical

(KWN) method• Stepwize prediction of particle evolution• Particle evolution tracked in GB, PFZ, and grain interior zones• Solute exchange between zones

Precipitate radius

Num

ber d

ensi

ty

Matrixprecipitates

Precipitateson

dislocationsPrecipitates on

dispersoids

Precipitate radius

Time step Δt:

• Nucleation

• Growth

• Coarsening

• Dissolution

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Phases Modelled• Main strengthening phases in 7xxx

– η’ metastable MgZn2

• Grain interior

– η equilibrium MgZn2

• Grain interior• Grain boundaries

• Natural ageing– Final GP zone fraction

Full particle sizedistribution, f(t)KWN model

Volume fraction(final)JMatPro

Thermodynamics• JMatPro: precipitate solvus compositions (Mg and Zn)• Gibbs-Thomson equation: curvature compensated composition• Flux balance equation for Mg & Zn: fixes precipitate interface

composition

CZn

CMgCr

growthStochiometric

line

Fluxequality

C0

Cr,t0

Equilibrium solvus(JMatPro)

Curvaturecompensated solvus(f(r))

Ppt interfacecomposition

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Particle Nucleation, Growth, Coarsening andDissolution

particleradius, r

Num

ber

of p

artic

les

in c

lass

, N

r*

particlesshrinking

particlesgrowing

New nucleiJΔt particles

growth/dissolution ofparticles in each size class

r

r

CC

CC

r

D

dt

dr

!

!=

"

distance

com

posi

tion

cβ

crc

Strength Model

• K, M, α , ρd from literature/calibration

Friction stress in Al(~10MPa)

Solid solutioncontribution

Dislocationcontribution

Particlecontribution

solute remaining in matrix

dislocation density

solid solution contribution

dislocation contribution

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Particle Strengthening

obstacle strength depends on RFor particle shearing (R<Rtrans)

obstacle strength is constantFor particle bypassing (R>Rtrans)

slip plane

before after

dislocationline

before after

particle shearing particle bowing

Particle sizedistribution

Inputs and Outputs

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Model Calibration Parameters• Calibrated model parameters (ppt

evolution model)– Interfacial energy of η and η’– GB diffusion coefficient of Mg– Critical radius for η’ to η transformation

• Calibration experiments devised tolimit number of varying parameterse.g.– During reversion treatment of 7449AA from a

known T7 condition (containing only η), γη isthe only fitting parameter

– Adjust γη to fit data from in-situ isothermalheating SAXS measurements [M. Nicolas]

0

2

4

6

8

10

12

14

10 100 1000

Time (s)

Avera

ge r

ad

ius (

nm

) 200oC225oC250oC

Model Predictions AA7449• Model tested by making predictions for well

characterized AA7449 FSW– 20mm thick half penetration weld, Triflat tool, 215RPM,

95mm/min, initial underaged (TAF) temper

0 3 6 9 12 15 18 21

17mm0.5

5

10

• Modelling– 3 depths: 0.5mm, 5mm and 10mm– 10 positions across the weld from 3mm to

30mm distance from weld centre– PWHT: T6 (12h @ 120°C) and T7 (12h

@ 160°C)

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Predictions: Nugget

η'η

Thermal cycle Matrix

Grain boundary Ppt Strengthening

Comparison with Experiment

• Microstructure

0

10

20

30

40

50

60

70

0 10 20 30 40 50

Distance from weld center (mm)

Avera

ge r

ad

ius (

nm

)

Model-5mm-FSW

Model-0.5mm-FSW

7449TAF-FSW (TEM)

Model-10mm-FSW

5mm

η in the matrix

• Strength/hardness

• Example comparison ofpredictions and– TEM– Hardness measurement

0

100

200

300

400

500

600

700

800

0 50 100 150 200

Measured Hardness

Pre

dic

ted

Yie

ld S

tren

gth

(MP

a)

0.5mm as welded

10mm as weldedNA weld

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Model Applications

• Parametric analysis of weld processvariables

• Extrapolation to other 7xxx alloys

Parametric Analysis• Model allows welding parameters to be systematically

varied and effect on microstructure and strength predicted• Example application: explore effect of rotation and

advance speed variation

4mm

8mm

6.1mm

20.3mm

rotation speed: 50-1000 RPM

advance speed: 50-300 mm/minAA7449-T6

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Thermal predictions

Peak temperature in nugget Thermal cycles for the same peaktemperature for 3 advance speeds

230mm min-1

150mm min-1

100mm min-1

Microstructure: Nugget

• Advance speed has strong effect on precipitation during post weldcooling

• At slow advance speeds, extensive reprecipitation of η is predicted onpost weld cooling

• Effect on strength depends on size of reprecipitated particles

Matrix ηslow weld speed

Matrix ηfast weld speed

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Microstructure: HAZ

• Fraction and size of η in HAZ increases as advance speed slows• Results in reduction in strength minimum

Slow Fast

Fraction and size of η in matrix (HAZ)

Strength Predictions

Predicted strength profile as afunction of advance speed (nonatural ageing) [RS=800RPM]

Predicted minimum strength (HAZ)

Strength recovery due to finereprecipitation during PWcooling

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Extrapolation to other Alloys• Model can be applied to similar 7xxx alloys and

different initial tempers without recalibration

• Model currently being adapted for application to2xxx, 6xxx alloys

7449-TAF 7050-T74 7150-T6

Future Directions• Extending model to latest generation Al-alloys

(e.g. 2198 Al-Li)– Challenge due to uncertainties in thermodynamic data

• Coupling precipitation model to recrystallizationand dislocation generation models– More accurate predictions for TMAZ, HAZ

• Incorporating additional property models– Fracture toughness (in progress)– Corrosion performance

• Experimental validation over wider range ofconditions

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Summary• Coupled process-microstructure-strength

developed for FSW of AA7xxx• Examples of model application demonstrated• Ongoing developments include

– extending to 2xxx and 6xxx alloys– fracture toughness prediction

• Future directions include– Extending to latest generation Al-Li alloys– Incorporating effects of deformation & recrystallization

on precipitate evolution in TMAZ, nugget– Extending property predictions– Model validation for wide range of conditions

Acknowledgements

• Engineering and Physical Sciences ResearchCouncil, UK

• Airbus• Alcan• Hugh Shercliff, Cambridge University; Paul

Colegrove, Cranfield University