Cellular Automata Modeling of Grain Coarsening and Refinement during the Dynamic Recrystallization of Pure Copper

Abstract

In this study, a cellular automata technique was developed to simulate a dynamic recrystallization process of pure copper. Moore's neighboring rule was applied with partial fraction and time step control in the current approach to represent the grain growth kinetics more accurately. The cellular automata model developed in this study was applied to a simulation of the dynamic recrystallization of pure copper during hot deformation and compared with the experimental flow stresses and grain sizes determined from hot compression tests for validation. The predicted results were in reasonably good agreement with the experimental results. The grain coarsening and refinement phenomena were also investigated in detail. Finally, the effects of the process parameters on the microstructure and flow stress were investigated from various simulation results.

Strain energy limitations in Monte Carlo Potts modeling of grain growth

“…Both hybrid models gave JMAK predicted recrystallization kinetics, however JMAK predictions involve homogeneous nucleation and are very idealized. Matching JMAK predictions under idealized conditions is good for model verification, but recrystallization is a heterogeneous process so JMAK kinetics rarely coincide with real materials [9]. Deviating from the JMAK predictions is a necessity when modeling real materials.…”

“…Utilization of pure MCP [7,8] to model recrystallization has waned in favor of CA [9,10] including a few MCP/CA [11,12] hybrid models. The disaffection likely originates from literature reports indicating that MCP cannot model strain energy driven grain growth as well as CA [11,1].…”

Modelling multiple cycles of static and dynamic recrystallisation using a fully implicit isotropic material model based on dislocation density

“…Monte Carlo Potts [23,25], cellular automaton (CA) [21,43], phase eld (PF) models [10,39,53], vertex or front-tracking [38,54] as well as level set methods [7,22]. In terms of recrystallisation model developments linked to dislocation density based mechanical response models, Lee and Im [36] coupled a CA model to a Kocks Mecking (KM) [32,33] type dislocation density based model formulation. Takaki et al [49] also recently linked a multi-PF dynamic recrystallisation model to macroscopic mechanical response using J 2 ow theory.…”

Cellular Automaton Simulation for the Effects of Uneven Distribution of Dislocation Density and Small-Sized Precipitated Particles on Dynamic Recrystallization

“…Goetz and Seetharaman [8] first applied CA method to simulate the DRX features such as the necklace type of microstructures at high strain rates and its kinetics obeying the JMAK equation. Then, many researchers have been focused on DRX simulation based on the CA method [9][10][11][12][13][14][15]. However, the investigation with regard to the effects of precipitated particles on DRX is little.…”

“…If information on microstructure development during DRX is simultaneously required, the models with adequate temporal and spatial resolution are needed. Therefore, numerical models, such as Q state Monte Carlo (MC) [5,6], phase field (PF) [7] and cellular automaton (CA) [8][9][10][11][12][13][14][15] have been proposed to simulate DRX. Compared with MC and PF method, the CA method is used more because of its more flexible and adaptable to temporal and spatial scale.…”