Simulation of dynamic recrystallization for aluminium alloy 7050 using cellular automaton

Shi-quan Huang , You-ping Yi , Chao Liu

Journal of Central South University ›› 2009, Vol. 16 ›› Issue (1) : 18 -24.

PDF
Journal of Central South University ›› 2009, Vol. 16 ›› Issue (1) : 18 -24. DOI: 10.1007/s11771-009-0003-9
Article

Simulation of dynamic recrystallization for aluminium alloy 7050 using cellular automaton

Author information +
History +
PDF

Abstract

The prediction of microstructure evolution plays an important role in the design of forging process. In the present work, the cellular automaton (CA) program was developed to simulate the process of dynamic recrystallization (DRX) for aluminium alloy 7050. The material constants in CA models, including dislocation density, nucleation rate and grain growth, were determined by the isothermal compress tests on Gleeble 1500 machine. The model of dislocation density was obtained by linear regression method based on the experimental results. The influences of the deformation parameters on the percentage of DRX and the mean grain size for aluminium alloy 7050 were investigated in details by means of CA simulation. The simulation results show that, as temperature increases from 350 to 450 °C at a strain rate of 0.01 s−1, the percentage of DRX also increases greatly and the mean grain size decreases from 50 to 39.3 μm. The mean size of the recrystallied grains (R-grains) mainly depends on the Zener-Hollomon parameter. To obtain fine grain, the desired deformation temperature is determined from 400 to 450 °C.

Keywords

aluminium alloy 7050 / dynamic recrystallization / cellular automaton

Cite this article

Download citation ▾
Shi-quan Huang, You-ping Yi, Chao Liu. Simulation of dynamic recrystallization for aluminium alloy 7050 using cellular automaton. Journal of Central South University, 2009, 16(1): 18-24 DOI:10.1007/s11771-009-0003-9

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

KuglerG., TurkP.. Modeling the dynamic recrystallization under multi-stage hot deformation [J]. Acta Materialia, 2004, 51(15): 4659-4668

[2]

LanY. J., LiD. Z.. Mesoscale simulation of ferrite transformation form deformed austenite during continuous cooling in a C-Mn steel using a cellular automaton method [J]. Acta Materialia, 2005, 53(4): 991-1003

[3]

GoetzR. L., SeetharamanV.. Modeling dynamic recrystallization using cellular automata [J]. Scripta Materialia, 1998, 38(6): 405-413

[4]

ZhangJ.-h., HuangB.-y., HeY.-h., ZhouK.-c., MengL.-ping.. Physical simulation of hot deformation of TiAl based alloy [J]. Journal of Central South University of Technology, 2002, 9(2): 73-76

[5]

RollettA. D., LutonM. J., SrolovizeD. J.. Microstructure simulation of dynamic recrystallization [J]. Acta Metall Mater, 1992, 40(1): 43-55

[6]

PezakP., LutonM. J.. A monte carlo study of the influence of dynamic recovery on dynamic recrystallization [J]. Acta Metal Mater, 1993, 41(1): 59-71

[7]

PezakP.. A monte carlo study of influence of deformation temperature on dynamic recrystallization [J]. Acta Metall Mater, 1995, 43(3): 1279-1291

[8]

DingR., GuoZ. X.. Coupled quantitative simulation of microstructural evolution and plastic flow during dynamic recrystallization [J]. Acta Materialia, 2001, 49(16): 3163-3175

[9]

XiaoH., XuY.-c., YanY.-hong.. Cellular automaton method for simulation of dynamic recrystallization process with consideration of grains deformation [J]. China Mechanical Engineering, 2005, 16(24): 2245-2249

[10]

JinW.-z., WangL., LiuX.-hua.. Modeling of cellular automaton method in the simulation of recrystallization [J]. Materials for Mechanical Engineering, 2005, 29(10): 10-13

[11]

EstrinY.Unified constitutive laws of plastic deformation [M], 1996, London, Academic Press

[12]

XiaoN.-m., ZhengC.-wu.. A simulation of dynamic recrystallization by coupling a cellular automaton method with a topology deformation technique [J]. Computational Materials Science, 2008, 41(3): 366-374

[13]

YI You-ping, YANG Ji-hui, LIN Yong-cheng. Flow stress constitutive equation of 7050 aluminium alloy during hot compression [J]. Journal of Materials Engineering, 2007(4): 20–22. (in Chinese)

[14]

YiY.-p., FuX., CuiJ.-d., ChenH.. Prediction of grain size for large-sized aluminium alloy 7050 forging during hot forming [J]. Journal of Central South University of Technology, 2008, 15(1): 1-5

[15]

XuN.-g., JiangH.. TEM and HRTEM study of influence of thermal cycles with stress on dynamic recrystallization in Ti46Al8Nb1B during creep [J]. Micron, 2008, 39(8): 1210-1215

[16]

RichertM., StuweH. P.. Work hardening and microstructure of AlMg5 after severe plastic deformation by cyclic extrusion and compression [J]. Materials Science and Engineering, 2003, 335(2): 180-185

[17]

ChenH.-q., CaoC.-xiao.. Hot deformation mechanism and microstructure evolution of TC11 titanium alloy in β field [J]. Transactions of Nonferrous Metals Society of China, 2008, 18(5): 1021-1027

[18]

DerbyB.. The dependence of grain size on stress during dynamic recrystallization [J]. Acta Metal Mater, 1991, 39(5): 955-962

[19]

DerbyB.. Dynamic recrystallization: the steady state grain size [J]. Scripta Metal Mater, 1992, 27(11): 1581-1585

AI Summary AI Mindmap
PDF

132

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/