Computational algorithms for simulating the grain structure formed on steel billets using cellular automaton and chaos theories

A. Ramírez-López , G. Soto-Cortés , J. González-Trejo , D. Muñoz-Negrón

International Journal of Minerals, Metallurgy, and Materials ›› 2011, Vol. 18 ›› Issue (1) : 24 -34.

PDF
International Journal of Minerals, Metallurgy, and Materials ›› 2011, Vol. 18 ›› Issue (1) : 24 -34. DOI: 10.1007/s12613-011-0395-z
Article

Computational algorithms for simulating the grain structure formed on steel billets using cellular automaton and chaos theories

Author information +
History +
PDF

Abstract

The development of some computational algorithms based on cellular automaton was described to simulate the structures formed during the solidification of steel products. The algorithms described take results from the steel thermal behavior and heat removal previously calculated using a simulator developed by present authors in a previous work. Stored time is used for displaying the steel transition from liquid to mushy and solid. And it is also used to command computational subroutines that reproduce nucleation and grain growth. These routines are logically programmed using the programming language C++ and are based on a simultaneous solution of numerical methods (stochastic and deterministic) to create a graphical representation of different grain structures formed. The grain structure obtained is displayed on the computer screen using a graphical user interface (GUI). The chaos theory and random generation numbers are included in the algorithms to simulate the heterogeneity of grain sizes and morphologies.

Keywords

continuous casting / solidification / grain growth / algorithms / computer simulation

Cite this article

Download citation ▾
A. Ramírez-López, G. Soto-Cortés, J. González-Trejo, D. Muñoz-Negrón. Computational algorithms for simulating the grain structure formed on steel billets using cellular automaton and chaos theories. International Journal of Minerals, Metallurgy, and Materials, 2011, 18(1): 24-34 DOI:10.1007/s12613-011-0395-z

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Ivasishin O.M., Shevchenko S.V., Vasiliev N.L. 3D Monte-Carlo simulation of texture-controlled grain growth. Acta Mater., 2003, 51, 1019.

[2]

Flemings M.C. Solidification Processing, 1974 New York, McGraw Hill 288 Book Co.

[3]

Lan C.W., Chang Y.C., Shih C.J. Adaptive phase field simulation of non-isothermal free dendritic growth of a binary alloy. Acta Mater., 2003, 51, 1857.

[4]

Holm E.A., Miodownik M.A., Rollett A.D. On abnormal subgrain growth and the origin of recrystallization nuclei. Acta Mater., 2003, 51, 2701.

[5]

Mishra S., DebRoy T. Measurements and Monte Carlo simulation of grain growth in the heat-affected zone of Ti-6Al-4V welds. Acta Mater., 2004, 52, 1183.

[6]

Lan Y.J., Li D.Z., Li Y.Y. Modeling austenite decomposition into ferrite at different cooling rate in low-carbon steel with cellular automaton method. Acta Mater., 2004, 52, 1721.

[7]

Yoshioka H., Tada Y., Hayashi Y. Crystal growth and its morphology in the mushy zone. Acta Mater., 2004, 52, 1515.

[8]

Tong M., Li D., Li Y.Y. Modeling the austenite-ferrite diffusive transformation during continuous cooling on a mesoscale using Monte Carlo method. Acta Mater., 2004, 52, 1155.

[9]

Zhang L., Zhang C.B., Wang Y.M., Wang S.Q., Ye H.Q. A cellular automaton investigation of the transformation from austenite to ferrite during continuous cooling. Acta Mater., 2003, 51, 5519.

[10]

McAfee R., Nettleship I. The simulation and selection of shapes for the unfolding of grain size distributions. Acta Mater., 2003, 51, 4603.

[11]

Wang W., Lee P.D., McLean M. A model of solidification microstructures in nickel-based superalloys: predicting primary dendrite spacing selection. Acta Mater., 2003, 51, 2971.

[12]

Feng W., Xu Q., Liu B. Microstructure simulation of aluminum alloy using parallel computing technique. ISIJ Int., 2002, 42(7): 702.

[13]

Yee K., Hong C.P. Stochastic modeling of solidification grain for structures of Al-Cu crystalline ribbons in planar flow casting. ISIJ Int., 1997, 37(1): 38.

[14]

Shin Y.H., Hong C.P. Modeling of dendritic growth with convection using a modified cellular automaton model with a diffuse interface. ISIJ Int., 2002, 42(4): 359.

[15]

Zhu M.F., Hong C.P. A modified cellular automaton model for the simulation of dendritic growth in solidification of alloys. ISIJ Int., 2001, 41(5): 436.

[16]

Zhu M.F., Kim J.M., Hong C.P. Modeling of globular and dendritic structure evolution in solidification of an Al-7mass%Si alloy. ISIJ Int., 2001, 41(9): 992.

[17]

Suwa Y., Saito Y., Onodera H. Phase field simulation of grain growth in three dimensional system containing finely dispersed second-phase particles. Scripta Mater., 2006, 55, 407.

[18]

Fadden S. M., Browne D.J. Meso-scale simulation of grain nucleation, growth and interaction in castings. Scripta Mater., 2006, 55, 847.

[19]

Randle V., Rios P.R., Hu Y. Grain growth and twinning in nickel. Scripta Mater., 2008, 58, 130.

[20]

Schwartz A.J., King W.E., Kumar M. Influence of processing method on the network of grain boundaries. Scripta Mater., 2006, 54, 963.

[21]

Liu D.R., Guo J.J., Wu S.P., Su Y.Q., Fu H.Z. Stochastic modeling of columnar-to-equiaxed transition in Ti-(45-48 at%) Al alloy ingots. Mater. Sci. Eng. A, 2006, 415, 184.

[22]

Ramírez-López A., Soto-Cortés G., Palomar-Pardavé M., et al. Computational algorithms to simulate the steel continuous casting. Int. J. Miner. Metall. Mater., 2010, 17(5): 596.

[23]

Ramírez-López A., Aguilar-López R., Palomar-Pardavé M., et al. Simulation of the heat transfer in steel billets during continuous casting. Int. J. Miner. Metall. Mater., 2010, 17(4): 403.

[24]

Ramírez-López A., Aguilar-López R., González-Trejo J., et al. Simulation factors of the steel continuous casting. Int. J. Miner. Metall. Mater., 2010, 17(3): 267.

AI Summary AI Mindmap
PDF

102

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/