Prediction of microstructure gradient distribution in machined surface induced by high speed machining through a coupled FE and CA approach

Surface integrity is the permanent pursuit of industries for decades, and microstructure is a key factor controlling physical and mechanical properties of machined surfaces. During machining, a complicated non-uniform distribution of deformation fields will be applied to machined surfaces, as a result, microstructure evolution will be significantly influenced. In this study, a coupled finite element (FE) and cellular automata (CA) approach is used to characterize and predict microstructure evolution during high-speed machining oxygen-free high-conductivity (OFHC) copper, where a unique material model is presented to describe both constitutive behaviors and microstructure evolution, and a mixed mechanism of continuous dynamic recrystallization (cDRX) and discontinuous dynamic recrystallization (dDRX) is adopted to show grain refinement and grain growth procedure under gradient distributed fields of strains, strain rates and temperatures in machined surfaces. A similar gradient distribution of grain sizes is obtained through both simulation and experimental results, which validates the predictive model and presents an in-depth understanding of microstructure evolution process during surface formation, and it shows the primary factors influencing the grain size distribution in sub-surface are cDRX-induced grain refinement and dDRX-induced grain growth. Moreover, the gradient distribution of microstructures in refined sub-surfaces could be used to explain mechanisms of sub-surface damage in the future.