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国际多尺度计算工程期刊

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ISSN 打印: 1543-1649

ISSN 在线: 1940-4352

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MODELING OF TWO-PHASE GRAIN STRUCTURE IN THE TITANIUM ALLOY TI-6AL-4V USING CELLULAR AUTOMATA

卷 12, 册 1, 2014, pp. 23-31
DOI: 10.1615/IntJMultCompEng.2014007094
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摘要

The static coarsening behavior of the alpha-beta titanium alloy Ti-6Al-4V during heat treatments is modeled using a probabilistic cellular automata model (CA). For this purpose the kinetics of grain growth is described via transformation probabilities which are determined by diffusion mechanisms at grain and phase boundaries. For temperature changes an algorithm is implemented which adjusts the fraction of alpha and beta phase to reach equilibrium phase values. Hence, the CA is capable of calculating grain coarsening as well as grain dissolution in the two-phase area during heating and isothermal treatments at forging temperature. For these calculations, an initial microstructure is used as input and it can be imported from either virtual created microstructures, real micrographs, or electron backscatter diffraction (EBSD) maps. The model output includes mean diameter, grain size distribution, and virtually simulated microstructures which can be easily compared with experimental micrographs. Examples showing a good correlation between the predicted microstructures and experimental results, as well as data from literature, are presented in this work. The successful implementation of this model will lead to predictions of behavior in other dual-phase alloys.

参考文献
  1. Boyer, R., Welsh, G., and Collings, E. W., Materials Properties Handbook: Titanium Alloys.

  2. Candic, M., Grain Structure Design of Hot Formed and Annealed Multi Phase Alloys.

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

  4. Gil, F. J. and Planell, J. A., Behaviour of normal grain growth kinetics in single phase titanium and titanium alloys. DOI: 10.1016/S0921-5093(00)00731-0

  5. Hamilton, C. H., Johnson, C. H., Richter, S. K., and Hoyt, J. J., Static grain growth in a microduplex Ti-6Al-4V alloy. DOI: 10.1016/S1359-6454(98)00341-3

  6. Hea, Y., Ding, H., Liu, L., and Shin, K., Computer simulation of 2D grain growth using a cellular automata model based on the lowest energy principle. DOI: 10.1016/j.msea.2006.05.070

  7. Homporova, P., Thermal History of Alpha Morphology in Titanium Alloy Ti-6Al-4V.

  8. Janssens, K. G. F., An introductory review of cellular automata modeling of moving grain boundaries in polycrystalline materials. DOI: 10.1016/j.matcom.2009.02.011

  9. Katzarov, I., Malinov, S., and Sha, W., Finite element modeling of the morphology of β to α phase transformation in Ti-6Al-4V alloy. DOI: 10.1007/s11661-002-0204-4

  10. Kozeschnik, E., MatCalc software version 5.42.

  11. Krumphals, A., Microstructure Modeling of the Alpha/Beta Titanium Alloy Ti-6Al-4V During Thermo Mechanical Treatment.

  12. Liu, Y., Baudin, T., and Penelle, R., Simulation of normal grain growth by cellular automaton. DOI: 10.1016/1359-6462(96)00055-3

  13. Lütjering, G. and Williams, J. C., Titanium.

  14. Raghavan, S. and Sahay, S. S., Modeling the grain growth kinetics by cellular automaton. DOI: 10.1016/j.msea.2006.09.023

  15. Semiatin, S. L., Brown, T. M., Goff, T. A., Fagin, P. N., Barker, D. R., Turner, R. E., Murry, J. M., Miller, J. D., and Zhang, F., Diffusion coefficients for modeling the heat treatment of Ti-6Al-4V. DOI: 10.1007/s11661-004-0250-1

  16. Sente Software, Ltd., JMatPro software version 6.2, Titanium alloys, UK, 2012.

  17. Walsoe de Reca, N. E. and Libanati, C. M., Self-diffusion in β-titanium and β-hafnium.

对本文的引用
  1. Barriobero-Vila Pere, Requena Guillermo, Buslaps Thomas, Alfeld Matthias, Boesenberg Ulrike, Role of element partitioning on the α–β phase transformation kinetics of a bi-modal Ti–6Al–6V–2Sn alloy during continuous heating, Journal of Alloys and Compounds, 626, 2015. Crossref

  2. Oberwinkler Bernd, On the anomalous mean stress sensitivity of Ti-6Al-4V and its consideration in high cycle fatigue lifetime analysis, International Journal of Fatigue, 92, 2016. Crossref

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