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International Journal for Multiscale Computational Engineering
インパクトファクター: 1.016 5年インパクトファクター: 1.194 SJR: 0.554 SNIP: 0.82 CiteScore™: 2

ISSN 印刷: 1543-1649
ISSN オンライン: 1940-4352

International Journal for Multiscale Computational Engineering

DOI: 10.1615/IntJMultCompEng.v7.i5.10
pages 381-393

Microstructure Evolution Modeling during and after Deformation in 304 Austenitic Stainless Steel through Cellular Automaton Approach

N. Yazdipour
Centre for Material and Fibre Innovation, Deakin University, Geelong, Victoria 3217, Australia
P. D. Hodgson
Centre for Material and Fibre Innovation, Deakin University, Geelong, Victoria 3217, Australia
C. H. J. Davies
Department of Materials Engineering, Monash University, Victoria 3800, Australia

要約

A 2D cellular automaton approach was used to simulate microstructure evolution during and after hot deformation. Initial properties of the microstructure and dislocation density were used as input data to the cellular automaton model. The flow curve and final grain size were the output data for the dynamic recrystallization simulation, and softening kinetics curves were the output data of static and metadynamic recrystallization simulations. The model proposed in this work considered the effect of thermomechanical parameters (e.g., temperature and strain rate) on the nucleation and growth kinetics during dynamic recrystallization. The dynamic recrystallized microstructures at different strains, temperatures, and strain rates were used as input data for static and metadynamic recrystallization simulations. It was shown that the cellular automaton approach can model the final microstructure and flow curve successfully in dynamic recrystallization conditions. The postdeformation simulation results showed that the time for 50% recrystallization decreases with increasing strain for a given initial grain size and that dynamic recrystallization slows the postdeformation recrystallization kinetics compared to a model without dynamic recrystallization.

参考

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  9. Ding, R., and Guo, Z. X., Microstructural modeling of dynamic recrystallisation using an extended cellular automaton approach. DOI: 10.1016/S0927-0256(01)00211-7

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