Designing High Strength Aluminium Alloys for Aerospace Applications

1. Designing High Strength Aluminium Alloys for Aerospace Applications H.Aourag

2. Aluminium Alloys in Aerospace Airbus A340 Despite competition from other materials, Al alloys still make up > 70% of structure of modern commercial airliner

3. Design Requirements • Components must be • Lightweight • Damage tolerant • Durable (corrosion resistant) • Cost effective • Requires careful balance of material properties

4. Critical Material Properties

5. 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, EFe=211GPa) • Low melting point (Tm=660oC) • Alloy with other elements to improve strength and stiffness - results in alloys with properties well matched to aerospace requirements

6. B C E A A) Slats - 2618 B) D-Nose Skins - 2024 C) Top Panel - 7150 D) Bottom Panel - 2024 E) Spars / Ribs - 7010 F) Flap Support - 7175 G) Flap Track - 7075 H) Landing Gear - 2024 H F G D Aerospace Al-Alloys • Dominated by “high strength” wrought alloys • Two main alloy series in particular • 2xxx alloys (Al + Cu, Mg) UTS~500MPa • 7xxx alloys (Al + Mg, Zn, (Cu)) UTS~600MPa Alloys used in typical wing structure

7. Next Generation Aircraft Bigger.... Airbus A380 > 950 seats ...Faster Boeing sonic cruiser > Mach.95

8. Goals • 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 components

9. 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

10. 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....

11. Modelling Examples Macro • Finite element modelling to optimize extrusion processing of aerospace Al-alloys • Thermodynamic modelling for the development of weldable aerospace aluminium alloys • Precipitation kinetics modelling for optimization of dispersoid particles in 7xxx alloys Micro

12. Finite Element Modelling of Extrusion

13. Direct The Extrusion Process • Extrusion is widely used to produce aerospace components Extrusion Billet Die Ram (Al alloy) Indirect Direct • Extruded shapes are often complex - design of die is critical

14. 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

15. The Finite Element Method 2D finite element mesh for an extrusion • Divide billet/extrusion into small, connected elements • Relate displacements/temperature changes in one element to those in surrounding elements using well established physical laws

16. Use of Finite Element Model • Use commercially available FE package to model metal flow and temperature during extrusion Modify design Yes • Any problems? • Unbalanced metal flow • Excess temperature variation New die design No Make prototype die Simulate extrusion process

17. FE Model - Example Simulations Example Simulations in 2D and 3D

18. Weldable Aerospace Al-Alloys

19. Riveted joint Extra material required Labour intensive • Problem: Most high strength Al-alloys suitable for aerospace are considered “unweldable” Joining Aerospace Al-Alloys • Mechanical fasteners (rivets) are still the most widely used method of joining airframe components • Riveted joints have a number of disadvantages Welded joint No extra material (less weight) Process readily automated

20. 250 mm 7075 TIG Weld 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 almost solidified metal

21. 2 2 2) Grain Structure of Fusion Zone - 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 Factors Influencing Solidification Cracking 1) Level of Thermal Stresses

22. 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 systems • Can be useful in the interpretation of real microstructures • Calculate phase fractions and compositions for certain other well defined non-equilibrium problems

23. Al-Cu System (Al-Rich) Al-Mg System (Al-Rich) Cu-Mg System Simple Phase Diagrams Even for simple 2xxx alloy (Al-Cu-Mg), need data for 3 binaries and information about ternary phases S - Al2CuMg, T - Mg32(Al,Cu)49, V - Al5Cu6Mg2, Q - Al7Cu3Mg6 Ternary Phases MTDATA predicted phase diagrams Real, commercial Al-alloys may contain > 10 alloying elements! Success of thermodynamic models relies on availability of sufficient, high quality, thermodynamic data

24. Cliq1 Csol1 Cliq2 Csol2 Cliq3 Csol3 Solidification Microstructures Solidification occurs rapidly under non-equilibrium conditions However, given certain assumptions, thermodynamic calculations and the equilibrium phase diagram can still be used to predict solidification microstructure Microstructure Scheil Solidication Model - Assumptions: C0 (i) Local equilibrium exists at the solid/liquid interface (ii) No diffusion in the solid phases (iii) Uniform liquid composition (iv) No density difference between solid and liquid Liquid Csol0 T Solid % Solute

25. Freezing Range 1.0 0.9 0.8 0.7 fcc a-Al 0.6 Mass Phase Fraction Liquid Eutectic Reaction 0.5 0.4 0.3 0.2 q - Al2Cu 0.1 620 560 600 580 660 680 640 700 540 520 Temperature (C) Predictions for Binary Al-Cu Alloy q - Al2Cu eutectic fcc a-Al dendrites fcc a-Al eutectic

26. DT 1.0 0.9 0.8 0.7 fcc a-Al 0.6 Mass Phase Fraction 0.5 0.4 Liquid 0.3 0.2 S - Al2CuMg 0.1 q - Al2Cu 570 510 550 530 590 610 630 650 490 470 Temperature (C) Ternary Eutectic Predicted at ~ 500ºC Predictions for Ternary Al-Cu-Mg alloy Predictions for 2xxx (Al-4.5Cu-1.5wt%) Mg alloy TS TL

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

28. 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

29. Modelling Dispersoid Precipitation in 7xxx Aerospace Al Alloys

30. 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 time • Transformation of metastable phases • Evolution of volume fraction of phase and particle size distribution • These factors depend on phase transformation kinetics and are critical in determining microstructure and hence properties

31. 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 simultaneously • Metal subjected to thermal cycling and complex deformation during processing

32. 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 spars 7050 composition specification

33. Cast Direct chill Age Solution treat 475oC, 1h spray quenched Homogenize ~475oC, 24h Hot roll ~350-450oC 20+ passes reduction~70% Processing Sequence - 7050 Plate

34. Temperature RD 50nm Microstructural Changes Time Cast Homogenized Rolled Solutionized Aged

35. Dispersoids 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

36. 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

37. Schematic of Model Start Homogenization temperature/time profile Average zirconium concentration (depends on position in slab) Precipitation Kinetics Model Local zirconium concentration (as a function of position within grain) Microsegregation Model (MTDATA Scheil Model) Dispersoid size, number density, spacing and size distribution

38. 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 form by random in matrix. Stable clusters become particle nuclei Particles grow, controlled by diffusion of Zr Small particles dissolve at the expense of large particles to reduce total interfacial area

39. Kinetics Model • Time is divided into a large number of small steps • 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

40. I/f energy Nucleation rate Nucleation • 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 matrix Driving force increasing but diffusion rate decreasing Temperature Nucleation rate

41. Growth • 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 Small particle Large particle Zr concentration Zr in matrix at interface (depends on particles size) distance

42. Coarsening 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 c c Concentration Zr Concentration Zr All particles growing Large particles growing, small particles shrinking

43. Testing the Model • First test model against experiment for a single initial Zr concentration Comparison of model prediction and experiment at 500oC Number Size Evolution of size distribution with time

44. Edge Low Zr Dispersoid free zone High Zr Centre 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 EDGE CENTRE Observed dispersoid distribution after homogenization Zr concentration after casting

45. 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 removed into Al3Zr dispersoids Zr concentration Centre Edge

46. Centre Edge Centre Edge Centre Edge Predicting Across a Grain Can the model reproduce the observed behaviour? Edge Centre Mean radius Zr in solution Volume Fraction

47. 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

48. 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 possible

49. Model Predictions Use model to investigate kinetics in detail Growth Nucleation Temperature /oC Temperature /oC Time /h To promote dispersoid nucleation in low Zr regions need to hold at ~425oC

50. Homogenization range AA7050 Optimizing Homogenization Need to dissolve these phases during homogenization • BUT Homogenization temperature for 7050 is restricted Must avoid onset of melting • Model suggests that best temperature for precipitating dispersoids in low Zr regions lies below this range