Modelling of Microstructure Changes During Hot Deformation Using Cellular Automata

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Modelling of Microstructure Changes During Hot Deformation Using Cellular Automata

The paper is focused on an application of the cellular automata (CA) method to description of microstructure changes in continuous deformation condition. The model approach consists of Cellular Automata model of microstructure development and the thermal-mechanical finite element (FE) code. Dynamic recrystallization phenomenon is taken into account in 2D CA model which takes advantage of explicit representation of microstructure, including individual grains and grain boundaries. Flow stress is the main material parameter in mechanical part of FE and is calculated on the basis of average dislocation density obtained from the CA model. The results obtained from the model were validated with the experimental data. In the present study, austenitic steel X3CrNi18-10 was investigated. The examination of microstructure for the initial and final microstructures was carried out, using light microscopy, transmission electron microscopy and EBSD technique. Compression forces were recorded during the tests and flow stresses were determined using the inverse method.

M.A. Miodownik, A review of microstructures computer models used to simulate grain growth and recrystallization in aluminum alloys, J. of Light Metals 2, 125-135 (2002).

R. Ding, X.Z. Guo, Coupled quantitative simulation of microstructural evolution and plastic flow during dynamic recrystallization Acta Mater. 49, 3163-3168 (2001).

R.L. Goetz, Z. Seetharaman, Modelling dynamic recrystallization using cellular automata, Scripta Mater. 38, 405-410 (1998).

Ch. Zheng, N. Xiao, D. Li, Y. Li, Microstructure prediction of the austenite recrystallization during multi-pass, Comp. Mat. Sci. 44, 507-514 (2008).

D. Kuc, J. Gawąd, M. Pietrzyk, Multiscale CAFE Modelling of Dynamic Recrystallization, Materials Science Forum 638-642, 2567-2572 (2010).

S. Das, E.J. Palmiere, I.C. Howard, CAFE: a tool for modeling thermomechanical processes. Proc conf. Thermomech. Processing: Mechanics, Microstructure and Control, Eds. E. J. Palmiere, M. Mahfouf, C. Pinna, Sheffield, 296-301 (2002).

J. Gawąd, D. Kuc, Application of Cellular Automata and Particle Swarm Optimization methods to identification of initial microstructure representation, Hutnik Wiadomości - Hutnicze 8, 568-600 (2009).

H. Mecking, U.F. Kocks, Kinetics of Flow and Strain-Hardening, Acta Metall. 29, 1865-1875 (1981).

W. Roberts, B. Ahlblom, A nucleation criterion for dynamic recrystallization during hot working Acta Metall. 29, 801-813 (1978).

F.J. Humphreys, A unified theory of recovery, recrystallization and grain growth, based on the stability and growth of cellular microstructures, Acta Mater. 45, 4231-4240 (1997).

H.J. Klaar, P. Schwaab, W. Österle, Ringversuch zur quantitativen Ermittlung der Versetzungsdichte im elektronen mikroskop, Prakt. Metallogr. 29, 3-25 (1992).

A.K. Head, P. Humble, L.M. Clarebrought, A.J. Morton, C.T. Forwood, Computed Electron Micrographs and Defect Identification; University of Melbourne, Australia (1973).

G. Niewielski, D. Kuc, Structure and properties of high - alloy hot deformed steels, Hadasik E. Schindler I. Plasticity of Metallic Materials, Publishers of the Silesian University of Technology, 199-221 (2005).

M. Pietrzyk, R. Kuziak, Problem of modelling of deformation materials properties in variable conditions, Computer Methods in Materials Science 2, 4, 227-258 (2002).

Archives of Metallurgy and Materials

The Journal of Institute of Metallurgy and Materials Science and Commitee on Metallurgy of Polish Academy of Sciences

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