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Cellular automaton modeling of dynamic recrystallization of Ni–Cr–Mo-based C276 superalloy during hot compression

Published online by Cambridge University Press:  16 July 2019

Chi Zhang
Affiliation:
School of Materials Science and Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China; and State Key Lab of Rolling Technologies and Automation, Northeastern University, Shenyang, Liaoning 110819, China
Xiaole Tang
Affiliation:
School of Materials Science and Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
Liwen Zhang*
Affiliation:
School of Materials Science and Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
Yan Cui
Affiliation:
School of Materials Science and Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
*
a)Address all correspondence to this author. e-mail: [email protected]
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Abstract

To simulate the effects of hot working parameters on microstructure and flow resistance during dynamic recrystallization (DRX) of a Ni–Cr–Mo-based C276 superalloy, a 2D mesoscopic model has been established using cellular automaton (CA) method. The isothermal hot compression tests were performed on a Gleeble 1500 thermal-mechanical simulator at the temperature range of 1273–1473 K and strain rate range of 0.001–5 s−1. The flow stress behaviors were then obtained and the microstructures of quenching specimen were observed after compression. Then the dislocation density evolution, nucleation and grain growth during hot compression were determined from experiments and integrated to the CA model. The topology of microstructure evolution and deformation resistance were calculated using the developed CA model and compared with the experimental ones. The CA simulation results show reasonable agreements with the experiments, implying the developed CA can capture the effects of processing parameters on the DRX behavior of C276 superalloy.

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Article
Copyright
Copyright © Materials Research Society 2019 

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References

Doherty, R.D., Hughes, D.A., Humphreys, F.J., Jonas, J.J., Jensen, D.J., Kassner, M.E., King, W.E., McNelley, T.R., McQueen, H.J., and Rollett, A.D.: Current issues in recrystallization: A review. Mater. Sci. Eng., A 238, 219 (1997).CrossRefGoogle Scholar
Zhang, H.B., Zhang, K.F., Jiang, S.S., and Lu, Z.: The dynamic recrystallization evolution and kinetics of Ni–18.3Cr–6.4Co–5.9W–4Mo–2.19Al–1.16Ti superalloy during hot deformation. J. Mater. Res. 30, 1029 (2015).CrossRefGoogle Scholar
Son, H.W., Jung, T.K., Lee, J.W., and Hyun, S.K.: Hot deformation characteristics of CaO-added AZ31 based on kinetic models and processing maps. Mater. Sci. Eng., A 695, 379 (2017).CrossRefGoogle Scholar
Liu, Y.H., Ning, Y.Q., Yao, Z.K., Li, Y.Z., Zhang, J.L., and Fu, M.W.: Dynamic recrystallization and microstructure evolution of a powder metallurgy nickel-based superalloy under hot working. J. Mater. Res. 31, 2164 (2016).CrossRefGoogle Scholar
Shang, X.Q., Cui, Z.S., and Fu, M.W.: A ductile fracture model considering stress state and Zener–Hollomon parameter for hot deformation of metallic materials. Int. J. Mech. Sci. 144, 800 (2018).CrossRefGoogle Scholar
Chen, M.S., Lin, Y.C., and Ma, X.S.: The kinetics of dynamic recrystallization of 42CrMo steel. Mater. Sci. Eng., A 556, 260 (2012).CrossRefGoogle Scholar
Chen, M.S., Li, K.K., Lin, Y.C., and Yuan, W.Q.: An improved kinetics model to describe dynamic recrystallization behavior under inconstant deformation conditions. J. Mater. Res. 31, 2994 (2016).CrossRefGoogle Scholar
Zhang, C., Zhang, L.W., Shen, W.F., Liu, C.R., Xia, Y.N., and Li, R.Q.: Study on constitutive modeling and processingmaps for hot deformation of medium carbon Cr–Ni–Mo alloyed steel. Mater. Des. 90, 804 (2016).CrossRefGoogle Scholar
Li, X.L., Li, X.L., Zhou, H.T., Zhou, X., Li, F.B., and Liu, Q.: Simulation of dynamic recrystallization in AZ80 magnesium alloy using cellular automaton. Comput. Mater. Sci. 140, 95 (2017).CrossRefGoogle Scholar
Chen, M.S., Yuan, W.Q., Lin, Y.C., Li, H.B., Zou, Z.H., Chen, M.S., Yuan, W.Q., Lin, Y.C., Li, H.B., and Zou, Z.H.: Modeling and simulation of dynamic recrystallization behavior for 42CrMo steel by an extended cellular automaton method. Vacuum 146, 142 (2017).CrossRefGoogle Scholar
Chen, F., Qi, K., Cui, Z.S., and Lai, X.M.: Modeling the dynamic recrystallization in austenitic stainless steel using cellular automaton method. Comput. Mater. Sci. 83, 331 (2014).CrossRefGoogle Scholar
Jiang, H., Yang, L., Dong, J.X., Zhang, M.C., and Yao, Z.H.: The recrystallization model and microstructure prediction of alloy 690 during hot deformation. Mater. Des. 104, 162 (2016).CrossRefGoogle Scholar
Xiao, N., Hodgson, P., Rolfe, B., and Li, D.: Modelling discontinuous dynamic recrystallization using a quantitative multi-order-parameter phase-field method. Comput. Mater. Sci. 155, 298 (2018).CrossRefGoogle Scholar
Li, J., Xu, H., Mattila, T.T., Kivilahti, J.K., Laurila, T., and Paulasto-Kröckel, M.: Simulation of dynamic recrystallization in solder interconnections during thermal cycling. Comput. Mater. Sci. 50, 690 (2010).CrossRefGoogle Scholar
Chen, F., Cui, Z.S., Liu, J., Chen, W., and Chen, S.J.: Mesoscale simulation of the high-temperature austenitizing and dynamic recrystallization by coupling a cellular automaton with a topology deformation technique. Mater. Sci. Eng., A 527, 5539 (2010).CrossRefGoogle Scholar
Shabaniverki, S. and Serajzadeh, S.: Simulation of softening kinetics and microstructural events in aluminum alloy subjected to single and multi-pass rolling operations. Appl. Math. Model. 40, 7571 (2016).CrossRefGoogle Scholar
Ding, R. and Guo, Z.X.: Coupled quantitative simulation of microstructural evolution and plastic flow during dynamic recrystallization. Acta Mater. 49, 3163 (2001).CrossRefGoogle Scholar
Ding, R. and Guo, Z.X.: Microstructural modelling of dynamic recrystallisation using an extended cellular automaton approach. Comput. Mater. Sci. 23, 209 (2002).CrossRefGoogle Scholar
Jaeger, J.D., Solas, D., Fandeur, O., Schmitt, J.H., and Rey, C.: 3D numerical modeling of dynamic recrystallization under hot working: Application to Inconel 718. Mater. Sci. Eng., A 646, 33 (2015).CrossRefGoogle Scholar
Han, F., Chen, R.Q., Yang, C.H., Li, X.M., and Wang, D.C.: Cellular automata simulation on dynamic recrystallization of TA16 alloy during hot deformation. Mater. Sci. Forum 849, 245 (2016).CrossRefGoogle Scholar
Chen, M.S., Yuan, W.Q., Li, H.B., and Zou, Z.H.: Modeling and simulation of dynamic recrystallization behaviors of magnesium alloy AZ31B using cellular automaton method. Comput. Mater. Sci. 136, 163 (2017).CrossRefGoogle Scholar
Zhang, T., Lu, S.H., Wu, Y.X., and Gong, H.: Optimization of deformation parameters of dynamic recrystallization for 7055 aluminum alloy by cellular automaton. Trans. Nonferrous Met. Soc. China 27, 1327 (2017).CrossRefGoogle Scholar
Zhang, C., Zhang, L.W., Shen, W.F., Xu, Q.H., and Cui, Y.: The processing map and microstructure evolution of Ni–Cr–Mo-based C276 superalloy during hot compression. J. Alloys Compd. 728, 1269 (2017).CrossRefGoogle Scholar
Zhang, C., Zhang, L.W., Shen, W.F., Li, M.F., and Gu, S.D.: Characterization of hot deformation behavior of hastelloy C-276 using constitutive equation and processing map. J. Mater. Eng. Perform. 24, 149 (2015).CrossRefGoogle Scholar
Mecking, H. and Kocks, U.F.: Kinetics of flow and strain-hardening. Acta Metall. 29, 1865 (1981).CrossRefGoogle Scholar
Zhang, Y., Tian, B., Volinsky, A.A., Chen, X., Sun, H., Chai, Z., Liu, P., and Liu, Y.: Dynamic recrystallization model of the Cu–Cr–Zr–Ag alloy under hot deformation. J. Mater. Res. 31, 1275 (2016).CrossRefGoogle Scholar
Huang, K. and Logé, R.E.: A review of dynamic recrystallization phenomena in metallic materials. Mater. Des. 111, 548 (2016).CrossRefGoogle Scholar
Sakai, T., Nagao, Y., Ohashi, M., and Jonas, J.J.: Flow stress and substructural change during transient dynamic recrystallization of nickel. Met. Sci. J. 2, 659 (2013).Google Scholar
Madej, L., Sitko, M., Legwand, A., Perzynski, K., and Michalik, K.: Development and evaluation of data transfer protocols in the fully coupled random cellular automata finite element model of dynamic recrystallization. J. Comput. Sci. 26, 66 (2018).CrossRefGoogle Scholar
Popova, E., Staraselski, Y., Brahme, A., Mishra, R.K., and Inal, K.: Coupled crystal plasticity-Probabilistic cellular automata approach to model dynamic recrystallization in magnesium alloys. Int. J. Plast. 66, 85 (2015).CrossRefGoogle Scholar
Liu, Y.X., Lin, Y.C., Li, H.B., Wen, D.X., Chen, X.M., and Chen, M.S.: Study of dynamic recrystallization in a Ni-based superalloy by experiments and cellular automaton model. Mater. Sci. Eng., A 626, 432 (2015).CrossRefGoogle Scholar
Mateusz, S. and Lukasz, M.: Development of dynamic recrystallization model based on cellular automata approach. Key Eng. Mater. 622–623, 617 (2014).Google Scholar
Poliak, E.I. and Jonas, J.J.: A one-parameter approach to determining the critical conditions for the initiation of dynamic recrystallization. Acta Mater. 44, 127 (1996).CrossRefGoogle Scholar
Zener, C. and Hollomon, J.H.: Effect of strain rate upon plastic flow of steel. J. Appl. Phys. 15, 22 (1944).CrossRefGoogle Scholar
Liu, Y.X., Lin, Y.C., and Zhou, Y.: 2D cellular automaton simulation of hot deformation behavior in a Ni-based superalloy under varying thermal-mechanical conditions. Mater. Sci. Eng., A 691, 88 (2017).CrossRefGoogle Scholar
Xia, Y.N., Zhang, C., Zhang, L.W., Shen, W.F., and Xu, Q.H.: A comparative study of constitutive models for flow stress behavior of medium carbon Cr–Ni–Mo alloyed steel at elevated temperature. J. Mater. Res. 32, 1 (2017).CrossRefGoogle Scholar
Kugler, G. and Turk, R.: Modeling the dynamic recrystallization under multi-stage hot deformation. Acta Mater. 52, 4659 (2004).CrossRefGoogle Scholar
Chen, F., Cui, Z.S., Ou, H.A., and Long, H.: Mesoscale modeling and simulation of microstructure evolution during dynamic recrystallization of a Ni-based superalloy. Appl. Phys. A 122, 889 (2016).CrossRefGoogle Scholar