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Modeling the recrystallization process using inverse cellular automata and genetic algorithms: Studies using differential evolution

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Title Modeling the recrystallization process using inverse cellular automata and genetic algorithms: Studies using differential evolution
 
Creator RANE, TD
DEWRI, R
GHOSH, S
MITRA, K
CHAKRABORTI, N
 
Subject computer-simulation
static recrystallization
heterogeneous nucleation
growth
kinetics
optimization
microstructures
aluminum
 
Description An inverse modeling approach was taken up in this work to model the process of recrystallization using cellular automata (CA). Using this method after formulating a CA model of recrystallization, differential evolution (DE), a real-coded variant of genetic algorithms, was used to search for the value of nucleation rate, providing an acceptable matching between the theoretical and experimentally observed values of fraction-recrystallized (X). Initially, the inverse modeling was attempted with a simple CA strategy, in which each of the CA cells had an equal probability of becoming nucleated. DE searched for the value of the nucleation rate yielding the best results for single-crystal iron at 550 degrees C. A good match could not be simultaneously achieved this way for the early stages of recrystallization as well as for the later stages. To overcome this difficulty, the CA grid was divided into two zones, having lower and higher probabilities of nucleation. This resulted in good correspondence between the predicted and experimental values of X for the entire duration of recrystallization. The introduction of a distribution in the probability of nucleation made the model even closer to the actual process, in which the probability of nucleation is often nonuniform due to nonuniformity in dislocation density as well as the presence of grain/interface boundaries.
 
Publisher ASM INTERNATIONAL
 
Date 2011-07-18T16:03:47Z
2011-12-26T12:50:42Z
2011-12-27T05:36:42Z
2011-07-18T16:03:47Z
2011-12-26T12:50:42Z
2011-12-27T05:36:42Z
2005
 
Type Article
 
Identifier JOURNAL OF PHASE EQUILIBRIA AND DIFFUSION, 26(4), 311-321
1547-7037
http://dx.doi.org/10.1361/154770205X56297
http://dspace.library.iitb.ac.in/xmlui/handle/10054/4975
http://hdl.handle.net/10054/4975
 
Language en