Optimisation of single crystal superalloy

homogenisation heat treatment

using DICTRA and MICRESS simulationsN. Warnken*, H. Larsson+, R. Reed*

* University of Birmingham

+ KTH Stockholm

Outline

• Bridgman processing of superalloys, overview

• Models

• Results on solidification and homogenisation

• Approach for the optimisation

• Outlook

Directional solidification of superalloys

The directional heat flux forces the crystals to grow in a given direction

As-cast Microstructure

as cast microstructure

single crystal Superalloy

γγγγ dendritesγγγγ’

Microstructure evolution during processing

Aged

CMSX4

As-cast

Homogenised

Microsegregation in the as-cast structure

Ni 13.0Al 10.5Cr 2.9Ta 2.6W

γ′ precipitation during cooling (CMSX4)

CMSX4 in the as-cast state, DICTRA simulationC. Walter et. al. Mat.Sci.Eng.A, 2004

Moving Boundary Problems

α γ

Maintain fixed interfacial width δδδδby adding convective fluxes

δ

1DFinite volume methodSemi-implicitCoupled to Thermo-calcImplemented in DICTRA

H. Larsson et.al.

• Diffuse Interface, expressed by the Phase-field Parameter φ:φ:φ:φ:

• Introduction of an orderparameter φ = f (x,t), which is a density function

for the phase distribution.

Phase Field Approach

MICRESS was used for the microstructure simulations

Material Process

Unit-Cell Approach

Experimental Single Crystal Superalloy

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

NP

(*)

400 600 800 1000 1200 1400 1600 1800

TEMPERATURE_KELVIN

THERMO-CALC (2007.06.05:14.16) :

DATABASE:USER

N=1., P=1E5,W(AL)=6E-2, W(CO)=3E-2, W(CR)=3E-2, W(MO)=2.5E-2, W(TI)=2.5E-3,

W(TA)=6.5E-2, W(W)=4.8E-2, W(RE)=6.2E-2, W(RU)=5E-2;1

1:T,NP(LIQUID)

2

2:T,NP(FCC_A1)

1

22

3

3:T,NP(GAMMA_PRIME)

2

3

4

4:T,NP(P_PHASE)

2

3

5

5:T,NP(MU_PHASE)

4

2

3

6

6:T,NP(HCP_A3)

5 4

2

3

654

1200

1250

1300

1350

1400

1450

Tem

pera

ture

, C

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Weight Fraction of Solid

THERMO-CALC (2007.06.05:14.21) :

DATABASE:USER

W(AL)=WAL, W(CO)=WCO, W(CR)=WCR, W(MO)=WMO, W(TI)=WTI, W(TA)=WTA, W(W)=WW,

W(RE)=WRE, W(RU)=WRU, P=1E5, N=1;

1

1: LIQUID

2

2: FCC_A1 LIQUID

2

3

3: FCC_A1 GAMMA_PRIME LIQUID

3

4

4: FCC_A1 GAMMA_PRIME LIQUID NIAL

5

5: FCC_A1 LIQUID NIAL

5

Results of the 1D model

Dashed – as-cast profileSolid – after 40000 s (~10 h)

Al Re

LDSX6

As-Cast

Al Co Cr

MoRu

Ta Ti W

Re

4500s

Al Co Cr

MoRu

Ta Ti W

Re

8375s

Al Co Cr

MoRu

Ta Ti W

Re

13743s

Al Co Cr

MoRu

Ta Ti W

Re

20343s

Al Co Cr

MoRu

Ta Ti W

Re

23943s

Al Co Cr

MoRu

Ta Ti W

Re

26643s

Al Co Cr

MoRu

Ta Ti W

Re

Homogenisation - γ′ fraction

2D Phase field

1D HomogenizationModel

Tem

pera

ture

[°C]

Tem

pera

ture

[°C]

Correlation microsegregation – incip. melting

Dendrite core Interdendritic

Concentration

Temperature

c0

cas-cast

Distance

Dendrite core InterdendriticDistance

c0

Tsol. co

Tsol core

Tsol interd

Cinterd.ccore

Tsol. co

Tsol core

Tsol interd

As-Cast

Correlation microsegregation – incip. melting

Dendrite core Interdendritic

Concentration

Temperature

c0

cas-cast

Distance

Dendrite core InterdendriticDistance

c0

Tsol. co

Tsol core

Tsol interd

Cinterd.ccore

Tsol. co

Tsol core

Tsol interd

Partially homogenised

Simulation of ”Optimised” homogenisation

• Target temperature Ttarget =Tsol(t)-10 [K]

• Maximum heating/cooling rate 4 K/min

• Input from simulation of solidification

Future Work

• Derivation of an optimised solution heat treatment

• Nucleation of γ′

• Including other phases in the simulation (i.e. NiAl)

• Influence of primary spacing on homogenisation

• Cross check with other simulations / experiments

• Alloy variation

• Speed up simulations