博士生刘弘光研究成果发表在最具影响力期刊Materials & Design
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发布时间：2020-09-09
发布时间：2020-09-09
文章标题：博士生刘弘光研究成果发表在最具影响力期刊Materials & Design
内容：
博士生刘弘光在课题组前面研究的基础上，提出了一种有限元与元胞自动机的耦合算法，用于高速加工OFHC铜时的表面微观组织演变行为，该方法的提出对实现零件表面性能的主动预测又进了一步。论文摘要和全文见下文：
https://www.sciencedirect.com/science/article/pii/S0264127520306687
Prediction of microstructure gradient distribution in machined surface induced by high speed machining through a coupled FE and CA approach. Materials & Design, 2020, 109133.
【摘要】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 and cellular automata 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.