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A hardness prediction model considering grain size effect for ferrite steel

机译:考虑晶粒尺寸影响的铁素体钢硬度预测模型

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Hardness is frequently used as an index to evaluate the mechanical properties of manufactured parts. Prediction of hardness distribution is beneficial to the optimisation of process parameters. For polycrystalline materials, the grain size has significant influence on hardness. In this paper, a hardness prediction model for ferrite steel was established by taking the grain size effect into consideration. The influence of grain size and effective strain on the hardness evolution during cold forming processes was investigated based on both experiments and simulations. The results proved that initial hardness, hardness coefficient and hardening exponent are all significantly affected by the grain size, i.e., they all decrease with the increase in grain size. The model proposed was validated to be capable of predicting the hardness distribution in cold forgings with different initial grain sizes.
机译:硬度通常用作评估制造零件机械性能的指标。硬度分布的预测有利于工艺参数的优化。对于多晶材料,晶粒尺寸对硬度有重要影响。本文考虑了晶粒尺寸效应,建立了铁素体钢硬度预测模型。基于实验和模拟,研究了晶粒尺寸和有效应变对冷成形过程中硬度演变的影响。结果证明,初始硬度,硬度系数和硬化指数均受晶粒尺寸的显着影响,即,它们都随晶粒尺寸的增加而降低。所提出的模型经验证能够预测具有不同初始晶粒尺寸的冷锻件的硬度分布。

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