Simulation of Grain Refinement Induced by High-Speed Machining of OFHC Copper Using Cellular Automata Method

电子背散射衍射 材料科学 机械加工 动态再结晶 粒度 微观结构 晶粒生长 等轴晶 冶金 再结晶(地质) 应变率 复合材料 热加工 地质学 古生物学
作者
Jun Zhang,Xiang Xu,J.C. Outeiro,Hongguang Liu,Wanhua Zhao
出处
期刊:Journal of Manufacturing Science and Engineering-transactions of The Asme [ASME International]
卷期号:142 (9) 被引量:22
标识
DOI:10.1115/1.4047431
摘要

Abstract During high-speed machining (HSM), the microstructure of materials evolves with significant plastic deformation process under high strain rate and high temperature, which affects chip formation and material fracture mechanisms, as well as surface integrity. The development of models and simulation methods for grain refinement in machining process is of great importance. There are few models which are developed to predict the evolution of the grain refinement of HSM in mesoscale with sufficient accuracy. In this work, a cellular automata (CA) method with discontinuous (dDRX) and continuous (cDRX) dynamic recrystallization (DRX) mechanisms is applied to simulate the grain refinement and to predict the microstructure morphology during machining oxygen-free high-conductivity (OFHC) copper. The process of grain evolution is simulated with the initial conditions of strain, strain rate, and temperature obtained by finite element (FE) simulation. The evolution of dislocation density, grain deformation, grain refinement, and growth are also simulated. Moreover, cutting tests under high cutting speeds (from 750 m/min to 3000 m/min) are carried out and the microstructure of chips is observed by electron backscatter diffraction (EBSD). The results show a grain refinement during HSM, which could be due to the occurrence of dDRX and cDRX. High temperature will promote grain recovery and growth, while high strain rate will significantly cause a high density of dislocations and grain refinement. Therefore, HSM contributes to the fine equiaxed grain structure in deformed chips and the grain morphology after HSM can be simulated successfully by the CA model developed in this work.
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