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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