This paper reports on one part of a research project supported by NSF, which aims at developing a multi-scale methodology for systematic microstructure prediction in thermo-mechanical processing of metals. Based on combining mesoscopic microstructure models with macroscopic process formulations, the methodology is expected to provide universally applicable and accurate microstructure prediction capabilities. Cellular Automata (CA) models have been widely used in scientific studies of various microstructural phenomena. This paper discusses the modeling of the static recrystallization phenomenon by employing a regular CA algorithm. The recrystallization processes of single-phase systems under different nucleation conditions are simulated followed by the recrystallization kinetics analysis for 200 × 200 two-dimensional lattice. The performed simulations of static recrystallization confirm that the recrystallized volume fractions are time dependent. Furthermore, the simulated microstructures validate the following Johnson-Mehl-Avrami-Kolmogorov (JMAK) model according to which the recrystallized volume fraction is a sigmoidal function of time, and their evolution matches the JMAK equation with the expected exponents.

Volume Subject Area:
Fluids Engineering
Topics:
Algorithms, Modeling, Recrystallization, Mesoscopic systems, Metals, Nucleation (Physics), Simulation, Thermomechanical treatment
1.
Saetre
T. O.
,
Hunderi
O.
,
Nes
E.
,
1986
, “
Computer simulation of primary recrystallization microstructures: the effects of nucleation and growth kinetics
,”
Acta Metallurgica
,
34
(
6
), pp.
981
–
987
.
2.
Marthinsen
K.
,
Lohne
O.
, and
Nes
E.
,
1989
, “
Development of recrystallization microstructures studied experimentally and by computer simulation
,”
Acta Metallurgica
,
37
(
1
), pp.
135
–
145
.
3.
Humphreys
F. J.
,
1992
, “
Modelling mechanisms and microstructures of recrystallization
,”
Materials Science and Technology
,
8
(
2
), pp.
135
–
143
.
4.
Humphreys
F. J.
,
1992
, “
Network model for recovery and recrystallization
,”
Scripta Metallurgica et Materialia
,
27
(
11
), pp.
1557
–
1562
.
5.
Weygand
D.
,
Brechet
Y.
and
Lepinoux
J.
,
1999
, “
Zener pinning and grain growth: a two-dimensional vertex computer simulation
,”
Acta Materialia
,
47
(
3
), pp.
961
–
972
.
6.
Hesselbarth
H. W.
, and
Gobel
I. R.
,
1991
, “
Simulation of recrystallization by cellular automata
,”
Acta Metallurgica et Materialia
,
39
(
9
), pp.
2135
–
2143
.
7.
Marx
V.
,
Reher
F. R.
, and
Gottstein
G.
,
1999
, “
Simulation of primary recrystallization using a modified three-dimensional cellular automaton
,”
Acta Materialia
,
47
(
4
), pp.
1219
–
1230
.
8.
Ding
R.
, and
Guo
Z. X.
,
2001
, “
Coupled quantitative simulation of microstructural evolution and plastic flow during dynamic recrystallization
,”
Acta Materialia
,
49
, pp.
3163
–
3175
.
9.
Liu
Y.
,
Baudin
T.
, and
Penelle
R.
,
1996
, “
Simulation of normal grain growth by cellular automata
,”
Scripta Materialia
,
34
(
11
), pp.
1679
–
1683
.
10.
Geiger
J.
,
Roosz
A.
, and
Barkoczy
P.
,
2001
“
Simulation of grain coarsening in two dimensions by cellularautomaton
,”
Acta Materialia
,
49
, pp.
623
–
629
.
11.
Chen
L.
,
1995
, “
A novel computer simulation technique for modeling grain growth
,”
Scripta Metallurgica et Materialia
,
32
(
1
), pp.
115
–
120
.
12.
Fan
D.
,
Geng
C.
, and
Chen
L.
,
1997
, “
Computer simulation of topological evolution in 2-D grain growth using a continuum diffuse-interface field model
,”
Acta Materialia
,
45
(
3
), pp.
1115
–
1126
.
13.
Fan
D.
,
Chen
L.
, and
Chen
S. P.
,
1997
, “
Effect pf grain boundary width on grain growth in a diffuse-interface field model
,”
Materials Science and Engineering A
,
238
, pp.
78
–
84
.
14.
Rollett
A. D.
, and
Raabe
D.
,
2001
, “
A hybrid model for mesoscopic simulation of recrystallization
,”
Computational Materials Science
,
21
, pp.
69
–
78
.
15.
Humphreys, F. J., and Hatherly, M., 1995, “Recrystallization and Related Annealing Phenomena,” Pergamon.
16.
Doherty
R. D.
,
Hughes
D. A.
,
Humphreys
F. J.
,
Jonas
J. J.
,
Jensen
D. J.
,
Kassner
M. E.
,
King
W. E.
,
McNelley
T. R.
,
McQueen
H. J.
, and
Rollett
A. D.
,
1997
, “
Current issues in recrystallization: a review
,”
Materials Science and Engineering A
,
238
, pp.
219
–
274
.
17.
Ye
W.
,
Gall
R. L.
, and
Saindrenan
G.
,
2002
, “
A study of the recrystallization of an IF steel by kinetics models
,”
Materials Science and Engineering A
,
332
, pp.
41
–
46
.
18.
Yu
Q.
, and
Esche
S. K.
,
2003
, “
Three-dimensional grain growth modeling with a Monte Carlo algorithm
,”
Materials Letter
,
57
, pp.
4622
–
4626
.
19.
Yu
Q.
, and
Esche
Sven K.
,
2003
, “
A Monte Carlo algorithm for single phase normal grain growth with improved accuracy and efficiency
,”
Computational Materials Science
,
27
, pp.
259
–
270
.
20.
Yu
Q.
, and
Esche
Sven K.
,
2002
, “
Modeling of grain growth kinetics with Read-Shockley grain boundary energy by a modified Monte Carlo algorithm
,”
Materials Letters
,
56
, pp.
47
–
52
.
21.
Miodownik
M. A.
,
2002
, “
A review of microstructural computer models used to simulate grain growth and recrystallization in aluminum alloys
,”
Journal of Light Metals
,
2
, pp.
125
–
135
.
22.
Avrami
M.
,
1939
, “
Kinetics of phase change. I
,”
Journal of Chemical Physics
,
7
, pp.
1103
–
1112
.
23.
Avrami
M.
,
1940
, “
Kinetics of phase change. II
,”
Journal of Chemical Physics
,
8
, pp.
212
–
224
.
24.
Avrami
M.
,
1941
, “
Kinetics of phase change. III
,”
Journal of Chemical Physics
,
9
, pp.
177
–
184
.
25.
Srolovitz
D. J.
,
Grest
G. S.
,
Anderson
M. P.
and
Rollett
A. D.
,
1988
, “
Computer simulation of recrystallization - II heterogeneous nucleation and growth
,”
Acta Metall.
36
, pp.
2115
–
2128
.
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