Simulation of dynamic recrystallization of a magnesium alloy with a cellular automaton method coupled with adaptive activation energy and matrix deformation topology

Abstract

The cellular automata (CA) model combining topological deformation and adaptive activation energy was successfully constructed to analyze the thermal dynamic recrystallization of the magnesium alloy (AZ61). The simulation datum shown that the recrystallization nucleation located on the grain boundary (GB) once the density of dislocation accumulated to specific value, and the result presents a typical characteristics i.e., repeated nucleation and growth. The simulation results agree well with the experimental results because the activation energy affects recrystallization by affecting nucleation rate.

Keywords

• az61 magnesium alloy
• cellular automaton
• adaptive activation energy
• deformation topology
• dynamic growth criterion