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
CHEMICAL COMPOSITION OF CAST IRON:
Fe
C
Si
Mn
P
S
Mg
val.
3.5
2.5
0.25
0.038
0.015
0.05
Grey cast iron
No addition of Mg or Ce
Tensile strength: 150-400 MPa
Elongation: 0 %
Ductile cast iron
Addition of cerium
or magnesium to induce
nodularisation of graphite
Tensile strength: 350-800 MPa
Elongation: 3-20 %
Only in
Ductile
iron
Microstructure of Ductile irons
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 450 - 250 C
usually between 0.5 and 3 hours
3. Cooling to a room temperature
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.
R. Elliott, 1988
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
Processing window
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 + gr
Sage II: Further austenite decomposition to ferrite and carbide
g
r
a +
Carbide
Closed processing window
Microstructure of ADI
¥ Bainite
¥ Retained
austenite
¥ Martensite
¥ Carbide
¥ Pearlite
Element Cell boundary
Mn
1.73
Si
1.75
Mo
0.60
Close to graphite
0.40
2.45
0.07
Element Cell boundary
Mn
0.81
Si
2.31
Mo
0.16
Fe-3.5C-2.5Si-0.55Mn-0.15Mo
Close to graphite
0.57
2.49
0.12
o
homogenised at 1000 C for 3 days
Austempered at 350 C for 64 min
Variables for modelling include:
C, Mn, Si, Mo, Ni, Cu,
Austenitising temperature and time
Austempering temperature and time
Vg = a + b (%C) + c (%Mn)
Vg = a + b (%C) + c(%Mn) + d (%C x %Mn)
Vg = sin (%C) + tanh (%Mn)
TA
C
Mn
INPUT
C x Wc
Mn x W Mn
HIDDEN
sum
OUTPUT
Vg
Modelling with neural networks
Hyperbolic tangents
a) three different hyperbolic tangents functions
b) combination of two hyperbolic tangents
Modelling with neural networks
NEURAL NETWORKS
DATABASE
(Experimental data)
Input
variables
Output
or target
h i = tanh (S wij x j + qi )
j
Microstructural model
for volume fraction of
retained austenite
(Vg )
Error bars
Physical Model for Retained Austenite
Babu etal. 1993
40 mm