Simulation on dynamic recrystallization behavior of AZ31 magnesium alloy using cellular automaton method coupling Laasraoui–Jonas model

Liu, Xiao; Li, Luoxing; He, Fang; Zhou, Jia; Zhu, Biwu; Zhang, Liqiang

doi:10.1016/s1003-6326(13)62786-7

Cited by 45 publications

(33 citation statements)

References 20 publications

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“…They stated that the CA model can simulate the nucleation and growth kinetics of dynamically recrystallized grains in hot working process. Besides these advantages, this method could not consider solely the effects of the process parameters on DRX and the relationship between the nucleation sites and the distribution of dislocation density (Liu et al 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Since it is difficult and time consuming to investigate experimentally the microstructure of weld, numerical simulations could be very applicable in different manufacturing processes (Liu et al 2013;Wang et al 2010). In terms of microstructure modeling, various approaches such as the cellular automaton (CA), the Monte Carlo model, and the phase field model have been developed to simulate microstructural evolution during processes (Liu et al 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Discrete spatial and temporal evolution of complex systems via applying local or global deterministic or probabilistic transformation rules to the location of a lattice is the main algorithm of the CA method. Many researchers have shown that CA offers a computationally efficient framework for simulation of microstructural evolution (Liu et al 2013).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Microstructural simulation of friction stir welding using a cellular automaton method: a microstructure prediction of AZ91 magnesium alloy

Asadi

Givi

Akbari

2015

Int J Mech Mater Eng

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Background: Recently, some researchers have simulated FSW using FEM and studied the influence of process parameters and tool geometry on material flow, welding force, and temperature and strain distributions during friction stir processing. Additionally, in terms of microstructure modeling, various approaches such as the Cellular Automaton (CA) model have been developed to simulate microstructural evolution during plastic deformation processes. Method: In this work, a finite element model (FEM) is established to study the microstructure evolution during friction stir welding (FSW) of AZ91 magnesium alloy. To this aim, first, the hot compression tests at different temperatures and strain rates were carried out to achieve the flow stress curves. Then, the hardening parameter, the recovery parameter and the strain rate sensitivity were calculated according to flow stress results and using the Kocks−Mecking model. Next, a continuum based thermo-mechanically coupled rigid-viscoplastic FEM model was proposed in Deform-3D software to simulate the FSW of AZ91 magnesium alloy. To evaluate microstructure of the weld zone a model is proposed based on the combination of Cellular Automaton and Laasraoui-Jonas models.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Microstructural simulation of friction stir welding using a cellular automaton method: a microstructure prediction of AZ91 magnesium alloy

Asadi

Givi

Akbari

2015

Int J Mech Mater Eng

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“…Ding and Guo (2002) simulated the microstructure evolution of DRX during hot compression forming process of Ti-6Al-4V alloy by combining the classic metallurgy principle with CA method. Liu et al (2013) simulated the evolution of dislocation density and microstructure during DRX process of hot compression of AZ31 magnesium alloy by coupling the CA method with the Laasraoui-Jonas model (LJ model). Jiang et al (2012Jiang et al ( , 2013 and Zhang et al (2013) simulated and predicted the microstructure evolution, dislocation density, flow stress and grain size of NiTi shape memory alloy during hot compression deformation based on cellular automaton.…”

Section: Research Status Of Microstructure Evolution Simulationmentioning

confidence: 99%

The classification and a review of hot power spinning of difficult-to-deform metals

Xia

Zhu

Cheng

et al. 2017

IJMPT

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Abstract:The plastic deformation of the difficult-to-deform metal at room temperature is very difficult due to the poor plasticity and large deformation resistance. Heating is an effective method to increase the material plasticity and decrease the forming forces. In this paper, the classification of the hot power spinning is proposed based on the heating methods, and the characteristics of the flame heating, laser heating, electromagnetic induction heating and hot gas convection heating methods are compared and analysed in detail. The research status of the macro forming quality during hot power spinning of the difficult-to-deform metal, especially the reasons and the preventing measures of the spinning defects, such as surface bulge, surface crack, surface pileup and surface peeling, is reviewed and discussed comprehensively. The research status of metallographic experimental analysis, microstructure involution simulation and mechanical properties of spun parts of the difficult-to-deform metal is summarised, and the main methods used for microstructure evolution simulation are compared. Finally, the research trend to realise the integrated controlling of the macro forming quality and microstructure of the hot spun part of the difficult-to-deform metal is put forward. The classification and a review of hot power spinning 213Keywords: difficult-to-deform metal; hot power spinning; macro forming quality; microstructure and property; forming defect.Reference to this paper should be made as follows: Xia, Q., Zhu, N., Cheng, X. and Xiao, G. (2017) Ningyuan Zhu is a PhD student in School of Mechanical and Automobile Engineering, South China University of Technology. He works on metal spinning technology, further investigations on the integrated control of the precision and the properties of difficult-to-deform metal during hot power spinning.Xiuquan Cheng is a Professor in Department of Aircraft Maintenance Engineering, Guangzhou Civil Aviation College. He research interests include plastic forming theory, method, technology and machine.Gangfeng Xiao is a PhD student in School of Mechanical and Automobile Engineering, South China University of Technology. He works on metal spinning technology, further investigations on the microstructure, properties and plastic deformation mechanism of nanomaterial of spinning, further investigations on the microstructure, properties and plastic deformation mechanism of nanomaterial.

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“…), then its neighbors will follow as well. Each cell consists of four main state variables, including the crystal orientation variable, the dislocation density variable, one order parameter variable and one fraction variable [8][9][10][11].…”

Section: Cellular Automata Modelmentioning

confidence: 99%

Influence of Strain Rate on Dynamic Recrystallization Behaviors of a Near-Titanium Alloy During Isothermal Hot-tensile Deformation:Experimental and Simulative Investigation.

Peng¹,

Hao²,

Cheng³

et al. 2016

Proceedings of the 2nd Annual International Conference on Advanced Material Engineering (AME 2016)

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Abstract. Dynamic recrystallization (DRX) behaviors of a near-α titanium alloy during isothermal hot-tensile tests were investigated with finite element simulation and electron backscattered diffraction (EBSD) test. The results show that the DRX behavior of the alloy is strongly sensitive to the strain rate, i.e., the average grain size increases with the decrease in strain rate, and the predicted average grain size of recrystallized grains with finite element method (FEM) based on cellular automata (CA) modeling are in good agreement with the experimental results by EBSD.

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Simulation on dynamic recrystallization behavior of AZ31 magnesium alloy using cellular automaton method coupling Laasraoui–Jonas model

Cited by 45 publications

References 20 publications

Microstructural simulation of friction stir welding using a cellular automaton method: a microstructure prediction of AZ91 magnesium alloy

Microstructural simulation of friction stir welding using a cellular automaton method: a microstructure prediction of AZ91 magnesium alloy

The classification and a review of hot power spinning of difficult-to-deform metals

Influence of Strain Rate on Dynamic Recrystallization Behaviors of a Near-Titanium Alloy During Isothermal Hot-tensile Deformation:Experimental and Simulative Investigation.

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