Energy Balance Calculations in Metallurgical Processes Designing High Strength Aluminium Alloys for Aerospace Applications

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Energy Balance Calculations in Metallurgical Processes Designing High Strength Aluminium Alloys for Aerospace Applications Powered By Docstoc
					Designing High Strength
 Aluminium Alloys for
Aerospace Applications
Aluminium Alloys in Aerospace

                                     Airbus A340
Despite competition from other materials, Al alloys still
make up > 70% of structure of modern commercial airliner
Design Requirements

• Components must be
   – Lightweight
   – Damage tolerant
   – Durable (corrosion resistant)
   – Cost effective
• Requires careful balance of material
Critical Material Properties
Aluminium Alloys
• Pure aluminium has
   – Low density (rrelative Al=2.7, Fe=7.9)
   – Readily available (Al is 3rd most abundant element
     in Earth's crust)
   – Highly formable (FCC crystal structure)
   – Low strength and stiffness (EAl=70GPa,
   – Low melting point (Tm=660oC)
• Alloy with other elements to improve strength
  and stiffness - results in alloys with properties
  well matched to aerospace requirements
 Aerospace Al-Alloys
• Dominated by high strength wrought
• Two main alloy series in particular
  – 2xxx alloys (Al + Cu, Mg) UTS~500MPa
  – 7xxx alloys B + Mg, Zn, (Cu)) UTS~600MPa

     A                   E   Alloys used in typical wing structure

                     H        A) Slats - 2618          E) Spars / Ribs - 7010
             F                B) D-Nose Skins - 2024   F) Flap Support - 7175
                              C) Top Panel - 7150      G) Flap Track - 7075
 D                            D) Bottom Panel - 2024   H) Landing Gear - 2024
 Next Generation Aircraft


                                 Airbus A380 > 950 seats

Boeing sonic cruiser > Mach.95

• Next generation aircraft rely on advances
  in materials and assembly methods
• Weight reduction is critical
  – Alloy optimization
     • Increase strength and stiffness and/or reduce
       density whilst maintaining other properties
  – Assembly optimization
     • Reduce weight associated with joints between
Alloy Design
• Traditionally, alloy and process
  development largely by trial and error
  based on metallurgical experience
• Recently, emphasis has changed to
  designing alloys and processes to meet
  specific property goals
  – Improved understanding of relationships between
    processing, microstructure and properties
  – Development of models to predict alloy
    microstructure and performance
 Applications of Modelling
• Models on a range of length scales
  – Atomistic (nm)
    • Limited application as currently capable of dealing with
      only very small volumes of material
  – Microstructural (nm-mm)
    • Used to predict particle distributions, grain sizes etc.. as
      function of alloy chemistry and processing conditions,
      often coupled to microstructure-property models
  – Macro-scale (>mm)
    • Widely used to predict performance of components
      during processing and service as a function of average
      material properties and stress, strain, temperature....
 Modelling Examples
• Finite element modelling to optimize

  extrusion processing of aerospace Al-
• Thermodynamic modelling for the
  development of weldable aerospace

  aluminium alloys
• Precipitation kinetics modelling for
  optimization of dispersoid particles in
  7xxx alloys
Finite Element Modelling of Extrusion
The Extrusion Process
• Extrusion is widely used to produce
  aerospace components

    Ram      Billet     Die
           (Al alloy)
          Direct                       Indirect

•   Extruded shapes are often complex -
    design of die is critical
Die Design

• Die must be designed to ensure balanced
  metal flow to avoid bending of extrusion
• Die shape influences metal temperature-aim to
  avoid cold or hot spots
• Traditionally, die design based on past
  experience and modifications of existing dies
• Alternative: Use finite element methods to
  model extrusion process and identify and test
  new die designs
The Finite Element Method

                                    2D finite element mesh
                                    for an extrusion

• Divide billet/extrusion into small, connected
• Relate displacements/temperature changes in
  one element to those in surrounding elements
  using well established physical laws
Use of Finite Element Model
• Use commercially available FE package to
  model metal flow and temperature during
                 Modify design          Yes

                            Any problems?
New die design              U
                            • nbalanced metal flow          No
                            • xcess temperature variation

          Simulate extrusion process                      Make
                                                      prototype die
FE Model - Example Simulations

   Example Simulations in 2D and 3D
Weldable Aerospace Al-Alloys
Joining Aerospace Al-Alloys
• Mechanical fasteners (rivets) are still the most
  widely used method of joining airframe
• Riveted joints have a number of disadvantages

     Riveted joint           Welded joint
     Extra material required No extra material (less weight)
     Labour intensive        Process readily automated

•   Problem: Most high strength Al-alloys suitable
    for aerospace are considered unweldable
Difficulties with welding

• One of the major metallurgical problems
  preventing the widespread application of
  welding to aerospace Al-alloys is
  solidification cracking
                               Cracks arise when the
                               thermal stresses
                               generated during cooling
                               exceed the strength of the
                      250 mm   almost solidified metal
      7075 TIG Weld
Factors Influencing Solidification Cracking
1) Level of Thermal Stresses 2

2) Grain Structure of Fusion Zone 2
         - columnar grains vs equiaxed grains

3) Absolute Freezing Range         ?
         - alloys with a wide freezing range are susceptible to cracking

4) Freezing Range for Dendrite Cohesion ?
         - thought to occur at about 50-60% Solid (depend on grain structure)

5) Volume Fraction of Low Melting Point Eutectic Phases ?
         - if there is sufficient liquid at the end of solidification to flow around
           the dendrites, then any cracks might be healed

                 Thermodynamic Modelling
Thermodynamic Modelling
• For any alloy system, set of conditions and
  configuration of the components there will be an
  associated free energy
• Use computer models to calculate the free energy for
  complex systems (lots of elements) from data for
  simple systems (1,2 or 3 elements)
• Calculate the equilibrium (minimum free energy)
  configuration and hence phase diagrams for complex
   – Can be useful in the interpretation of real microstructures
• Calculate phase fractions and compositions for certain
  other well defined non-equilibrium problems
                            Simple Phase Diagrams
                  Even for simple 2xxx alloy (Al-Cu-Mg), need data for 3 binaries
                  and information about ternary phases
                  700                                                                                        700                                                                                                  1200

                  650          Al-Cu System (Al-Rich)
                                                                                                                              Al-Mg System (Al-Rich)                                                              1000
                                                                                                                                                                                                                                                     Cu-Mg System
                                                                   Liquid + -Al2Cu                          600
Temperature (C)

                                                                                           Temperature (C)
                  600                                                                                                                                                                                                           L + -Cu

                                                                                                                                                                                                Temperature (C)
                             Liquid + -Al                                                                   550
                                                                                                                                                                                                                  800                                             Liquid
                  550 -Al                                                                                   500                   Liquid + -Al
                                                                                                                                                                                                                  700    

                                                                                                             450       -Al                                                                                                              Liquid +
                  500                                                                                                                                                                                             600                  Laves - C15
                                                  -Al + -Al2Cu         -Al2Cu                             400                                                                  -AlMg                                                                                                   Liquid + Mg
                                                                                                                                                                                                                  500                                        L + CuMg2


                  450                                                                                                                                                                                                       -Cu
                                                                                                             350                        -Al + -AlMg

                                                                                                                                                                                                                  400    Laves - C15   Laves - C15                            CuMg2 + Mg
                  400                                                                                        300                                                                                                  300
                        0      10            20           30        40         50     60                           0          10          20         30                 40       50        60                            0             20            40                  60           80                 100
                                                      wt.% Cu                                                                                      wt.% Mg                                                                                                   wt.% Mg

                        Ternary Phases S - Al2CuMg, T - Mg32(Al,Cu)49, V - Al5Cu6Mg2, Q - Al7Cu3Mg6
                                                                                                                                                                               MTDATA predicted phase diagrams
         Real, commercial Al-alloys may contain > 10 alloying
         Success of thermodynamic models relies on availability of
         sufficient, high quality, thermodynamic data
  Solidification Microstructures
Solidification occurs rapidly under non-equilibrium
However, given certain assumptions, thermodynamic
calculations and the equilibrium phase diagram can still
be used to predict solidification microstructure
Scheil Solidication Model - Assumptions:                   Microstructure
(i) Local equilibrium exists at the                             Liquid
    solid/liquid interface
                                             Csol0              Cliq1
(ii) No diffusion in the solid phases          Csol1                 Cliq2
                                                 Csol2                    Cliq3
                                           T       Csol3
(iii) Uniform liquid composition
(iv) No density difference between             Solid
    solid and liquid

                                                                   % Solute
                      Predictions for Binary Al-Cu Alloy

                                              Freezing Range
Mass Phase Fraction

                      0.6                     fcc -Al
                      0.5          Eutectic
                      0.2    - Al2Cu

                              520 540 560 580 600 620 640 660 680 700
                                         Temperature (C)                 - Al2Cu          fcc -Al
                                                                        eutectic fcc -Al dendrites
Predictions for Ternary Al-Cu-Mg alloy
Predictions for 2xxx (Al-4.5Cu-1.5wt%) Mg alloy
                                                     TS                 DT
       Mass Phase Fraction

                             0.7                             fcc -Al
                             0.3                                    Liquid

                             0.2     S - Al2CuMg
                                    - Al2Cu
                                      470      490    510   530 550 570 590   610   630        650
                                                            Temperature (C)
   Ternary Eutectic Predicted at ~ 500ºC
                Prediction of Freezing Range
To reduce tendency for solidification cracking, need to
minimize absolute freezing range
Use thermodynamic model to predict freezing range
for different alloy compositions
                                                                                                               Effect of Mg
                                                                                                               content on freezing
 D T (Freezing Range of Eutectic)

                                                                                 Optimum                       range of eutectic in
                                                                                 composition                   Al-4.5Cu-x Mg alloy
                                    30                                           range


                                    15                               Ternary Eutectic
                                                                                            Saddle Point
                                                                       [ + S]
                                                                                              [ + S]
                                             Binary Eutectic
                                                 [ + ]

                                         0              0.5    1     1.5                2           2.5    3
                                                                   wt.% Mg
Value of Calculations
• Thermodynamic calculations suggest
  modifications to current alloy
  compositions to improve weldability
• Focus experimental investigation on
  promising compositions
  – Save both development time and cost
• New weld filler wires have been
  developed on the basis of these
  calculations and are now being tested
Modelling Dispersoid Precipitation in
    7xxx Aerospace Al Alloys
Prediction of Microstructure
• Thermodynamic calculations give an indication
  of likely phases but give no information about
   – How phase is distributed
     • Particle size, spacing and location
  – How microstructure changes as function of
     • Transformation of metastable phases
     • Evolution of volume fraction of phase and
       particle size distribution
• These factors depend onphase
  transformation kinetics and are critical in
  determining microstructure and hence
Kinetic Modelling

• Aim to predict key microstructural
  parameters as a function of alloy
  composition, temperature and time
• Difficult problem for aerospace Al-alloys
  due to complex microstructures and
  processing routes
  – Large number of possible phases evolving
  – Metal subjected to thermal cycling and
    complex deformation during processing
7050 Plate
Focus on one alloy (7050) and product (thick
hot rolled plate)
           Components machined from 7050
           alloy thick plate are widely used in
           load bearing applications e.g. wing

7050 composition specification
Processing Sequence - 7050 Plate

           Direct chill               Age

                                 Solution treat
           Homogenize            475oC, 1h
           ~475oC, 24h           spray quenched

                      Hot roll
                      20+ passes
              Microstructural Changes



              Cast   Homogenized   Rolled    Solutionized   Aged
            Al3Zr dispersoid particles in
            7050 after homogenization

• Fine Al3Zr dispersoid particles precipitate
  during homogenization of 7050
• Dispersoid particles are important for the
  control of grain structure during processing
  – Act to pin grain boundaries
Modelling Dispersoid Precipitation
• Effectiveness of dispersoids depends on
  their size, spacing and distribution
• Develop model for dispersoid
  precipitation and use to optimize
  homogenization treatment to give best
  dispersoid distribution
• To model dispersoid precipitation must
  account for both non-uniform distribution
  of Zr due to microsegregation during
  casting and Al3Zr precipitation kinetics
Schematic of Model
     Average                                    profile
  (depends on
 position in slab)

                       Local zirconium        Kinetics
Microsegregation     concentration (as a       Model
     Model           function of position
(MTDATA Scheil          within grain)
                                            Dispersoid size,
                                            number density,
                                            spacing and size
 Precipitation Kinetics
The precipitation of Al3Zr dispersoids is a diffusion
controlled phase transformation
Classically, precipitation of particles considered as
2-step process of nucleation and growth, followed
by coarsening
      Nucleation            Nucleation+growth          Coarsening
      Time = t1               t2                       t3

Clusters of Al, Zr atoms    Particles grow,     Small particles dissolve
form by random in matrix.   controlled by       at the expense of large
Stable clusters become      diffusion of Zr     particles to reduce total
particle nuclei                                 interfacial area
Kinetics Model
?   Time is divided into a large number of small
?   Growth, nucleation and coarsening allowed to
    occur concurrently governed by driving force
    and concentration gradients
?   At each step new particles nucleate and
    existing particles grow (or shrink) depending
    on local interfacial compositions
?   After each step, solute supersaturation in the
    matrix is recalculated and used for next step
• Nucleation rate (number of new particles
  formed/s) depends on
  – Thermodynamic driving force for formation
    of new phase
  – Diffusion rate (temperature)
  – Interfacial energy between nucleus and

                                     Driving force

                                                      I/f energy
                                     increasing but
                                     diffusion rate

                   Nucleation rate                                 Nucleation rate
• Growth rate for each particle depends on
  – Concentration gradient ahead of particle
     • Equilibrium compositions from phase diagram
     • Particle size
  – Diffusion rate
                                                   Concentration profiles
                                  Zr in particle
               Zr concentration

                                                       Small particle

                                                       Large particle

                                      Zr in matrix at interface
                                      (depends on particles size)
Coarsening does not need to be modelled separately
but arises naturally from growth model in later stages
of precipitation
                          Early stages                               Late stages

                                                                      growing   shrinking
   Concentration Zr

                                              Concentration Zr
                      c                                          c

                      All particles growing      Large particles growing,
                                                 small particles shrinking
 Testing the Model
• First test model against experiment for a
  single initial Zr concentration
                                     of model

                                     experiment at
  Evolution of size
  distribution with time
  Effect of Zirconium Segregation
  • In practice, Zr concentration varies across a
    grain due to segregation during casting
  • Leads to non-uniform dispersoid precipitation
    during homogenization
                                    Low Zr

                                                           High Zr
 EDGE                     CENTRE
                                   Observed dispersoid distribution
Zr concentration after casting     after homogenization
Including Effect of Segregation
• To model Al3Zr distribution across a grain
  – Divide the distance from grain edge to
    centre into large number of elements
  – Model dispersoid evolution in each element
  – Allow zirconium redistribution by diffusion
    between elements
   Zr diffusing out of element           Zr diffusing into element
                      Zr concentration

                                                        Zr removed into
                                                        Al3Zr dispersoids

                                 Edge             Centre
Predicting Across a Grain

   Edge              Can the model reproduce
                     the observed behaviour?

Volume Fraction       Zr in solution     Mean radius

Centre       Edge   Centre        Edge Centre      Edge
Effect of Dispersoid Distribution
• Inhomogeneously distributed dispersoids
  are not best for control of grain structure
• In regions where there are few
  dispersoids, new grains can form
  (recrystallization) - this is undesirable

                  Structure after processing
                  New grains have formed and
                  partially consumed original
                  grains - this structure does
                  not give best properties
Optimizing Dispersoid Distribution

• Use model to determine optimum
  homogenization conditions to promote
  dispersoid precipitation in low Zr regions
• Aim is to reduce the formation of new
  (recrystallized) grains during processing
• For best recrystallization resistance, want
  a large number of small dispersoid
  particles, as uniformly distributed as
Model Predictions
Use model to investigate kinetics in detail

                          Temperature /oC


     Temperature /oC                        Time /h

To promote dispersoid nucleation in low Zr regions
need to hold at ~425oC
   Optimizing Homogenization
? BUT Homogenization temperature for 7050 is restricted

Need to
dissolve these                                                  Must avoid
phases during                                                   onset of melting

                                Homogenization range


? Model suggests that best temperature for precipitating
  dispersoids in low Zr regions lies below this range
Two Step Practice
? Two step homogenization practice may
  be of benefit
  ? Step 1: Hold at a temperature to precipitate
    optimum dispersoid distribution
  ? Step 2: Hold at final homogenization
? Model used to determine best conditions
  for step 1
  ? 5h Hold time at 430oC
? Test 2 step homogenization practice
Effect on Dispersoids

    Standard Homogenization   Two step treatment
Comparison of Recrystallization

  Standard Practice                 Hold + Homogenize Practice
  Recrystallized Fraction = 30.4%   Recrystallized Fraction = 14.0%

Two step homogenization practice, developed entirely by
computer modelling, is effective in significantly reducing the
fraction of recrystallization
Aerospace aluminium alloys are complex
materials, developed over a long period of time
by empirical experiment to meet industrial
In recent years, the understanding of the
metallurgical processes governing the
microstructure and properties of these alloys
has greatly increased
This has led to the development of models that
have practical application in the design of new
alloys and processes

• For provision of data and examples of FE
  and thermodynamic modelling
  – Dr Qiang Li, Birmingham University
  – Dr Andy Norman, Manchester Materials
    Science Centre
• Luxfer and Alcoa for funding some of this

Description: Energy Balance Calculations in Metallurgical Processes document sample