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Intelligent Heat Treating: Simulation of the Ferritic Nitriding Process-Database Development

机译:智能热处理:铁素体渗氮过程的仿真-数据库开发

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Heat treaters need an effective simulation tool to predict the nitriding performance for a wide variety of steels. This tool is needed not only to predict the hardness and nitrogen concentration profiles as a function of process parameters but also to optimize the process in terms of cycle time and cost. To develop a tool, it is necessary to predict the phase evolution in the hardened case during nitriding. In the present work, thermodynamic calculations and experimental work have been completed to help determine the effects of process parameters (i.e. temperature and nitriding potential as well as the starting steel microstructure and composition) on the nitriding process. The thermodynamic calculations show that γ'-Fe_4N should coexist with ε-Fe_(2-3)(C, N) phase in the compound layer, while only Fe_4N is found in the compound layer by X-ray diffraction. However, the SEM results show the existence of two phases in the compound layer and the TEM results at the interface between the compound layer and the diffusion zone verify the coexistence of γ'-Fe_4N and ε - Fe_(2-3)(C, N) phases. The nitriding characteristics were also examined in terms of weight gain, microhardness, and nitrogen concentration profiles. These data will be used to develop the simulation tool to optimize and control the nitriding process.
机译:热处理人员需要一种有效的模拟工具来预测多种钢的氮化性能。该工具不仅需要根据工艺参数预测硬度和氮浓度曲线,而且还需要在循环时间和成本方面优化工艺。为了开发工具,有必要预测渗氮过程中硬化情况下的相变。在目前的工作中,已经完成了热力学计算和实验工作,以帮助确定工艺参数(即温度和氮化势以及起始钢的显微组织和成分)对氮化工艺的影响。热力学计算表明,γ'-Fe_4N应与ε-Fe_(2-3)(C,N)相共存于复合层中,而通过X射线衍射只能在复合层中发现Fe_4N。然而,SEM结果显示化合物层中存在两相,并且在化合物层与扩散区之间的界面处的TEM结果证实了γ'-Fe_4N与ε-Fe_(2-3)(C, N)个阶段。还根据重量增加,显微硬度和氮浓度曲线检查了渗氮特性。这些数据将用于开发仿真工具,以优化和控制氮化过程。

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