1. University of Cambridge Department of Materials Science and Metallurgy
Modelling The Microstructure and Mechanical Properties of Austempered Ductile Cast Iron By
Miguel Angel Yescas-Gonzalez

2. Grey cast iron Ductile cast iron
CHEMICAL COMPOSITION OF CAST IRON: Fe C Si Mn P S Mg val
Only in Ductile
iron
Grey cast iron
No addition of Mg or Ce
Tensile strength: MPa
Elongation: 0 %
Ductile cast iron
Addition of cerium
or magnesium to induce
nodularisation of graphite
Tensile strength: MPa
Elongation: 3-20 %

3. Microstructure of Ductile irons

4. Austempered ductile cast iron (ADI)
A further improvement of ductile cast iron is obtained with an
isothermal heat treatment named austempering
1. Austenitising between 850 and 950 C
typically for 60 min.
2. Quenching into a salt or oil bath at a
temperature in the range C
usually between 0.5 and 3 hours
3. Cooling to a room temperature

5. Mechanical properties
STRENGTH : equal to or greater than steel
ELONGATION : maintain as cast elongation while double the strength of quenched and tempered ductile iron
TOUGHNESS : better than ductile iron and equal to or better than cast or forged steel
FATIGUE STRENGTH : equal to or better than forged steel.
DAMPING : 5 times greater than steel.

6. R. Elliott, 1988

7. Economical advantages and applications
ADI has excellent castability, it is possible to obtain near-net shape castings even of high complex parts.
ADI is cheaper than steel forgings
ADI has a weight saving of 10%
Gears
Automotive industry

8. Processing window g a g r g a r + + Carbide
The bainitic transformation in ductile iron can be described as two stage reaction:
Sage I: Austenite decomposition to bainitic ferrite and carbon enriched austenite g a + g r
Sage II: Further austenite decomposition to ferrite and carbide g a +
Carbide r

9. Closed processing window

10. Microstructure of ADI Bainite Retained austenite Martensite Carbide
Pearlite

11. Fe-3.5C-2.5Si-0.55Mn-0.15Mo Element Cell boundary Close to graphite

12. homogenised at 1000 C for 3 days
Austempered at 350 C for 64 min

15. Variables for modelling include:
C, Mn, Si, Mo, Ni, Cu,
Austenitising temperature and time
Austempering temperature and time V g
= a + b (%C) + c (%Mn) V g
= a + b (%C) + c(%Mn) + d (%C x %Mn) V g
= sin (%C) + tanh (%Mn)

16. C T Mn A
INPUT
C x W c
Mn x W Mn
HIDDEN
sum
OUTPUT V g

17. Modelling with neural networks
Hyperbolic tangents
a) three different hyperbolic tangents functions
b) combination of two hyperbolic tangents

18. Modelling with neural networks
DATABASE
(Experimental data)
Microstructural model
for volume fraction of
retained austenite
(V )
Input
variables
Output
or target g h
= tanh (S w x + q ) i ij j i j

20. Error bars

28. Physical Model for Retained Austenite

33. Babu etal. 1993

38. 40 mm