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作 者:罗烽月 Luo Fengyue(China Aviation Engine Group Co.,Ltd.,Beijing,100089)
机构地区:[1]中国航空发动机集团有限公司,北京100089
出 处:《当代化工研究》2024年第7期142-146,共5页Modern Chemical Research
摘 要:运用限元分析软件Comsol、Deform、Ansys软件对型面补偿的TC4筒型件离子氮化过程中电流密度与氮离子浓度分布、氮原子扩散分布、温度场进行模拟仿真,最后采用Matlab人工神经网络工具箱进行离子氮化过程综合性能预测。模拟结果表明,TC4筒型件渗氮工艺中,渗层深度误差值分别为9μm和12μm,均小于20μm的指标要求;温度预测中,测量温度与模拟温度差值为4℃,小于10℃的指标要求;应变量误差值分别为12μm和14μm,均小于性能指标20μm。Based on the ion nitriding treatment technology of the type compensation method and the porous hood type,the current density and nitrogen ion concentration distribution,nitrogen atom diffusion distribution,temperature field,stress field and strain field in the ion nitriding process of TC4 cylinder are simulated by using the limited element analysis software COMSOL,DEFORM,and ANSYS software,and finally the MATLAB artificial neural network toolbox is used to predict the comprehensive performance of the ion nitriding process.The simulation results show that in the nitriding process of TC4 cylindrical parts,the deep depth error values are 9μm and 12μm,both of which are less than the index requirements of 20μm.In temperature prediction,the difference between the measured temperature and the simulated temperature is 4℃,which is less than 10℃.The error values of the strain variables were 12μm and 14μm,respectively,which were less than the performance index of 20μm.
分 类 号:TG156[金属学及工艺—热处理]
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