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朱建, 王宏宇, 史东辉, 黄金雷, 毛计洲. 增材制造记忆合金的元素烧损行为及其补损分析[J]. 焊接学报, 2022, 43(9): 50-55. DOI: 10.12073/j.hjxb.20220105001
引用本文: 朱建, 王宏宇, 史东辉, 黄金雷, 毛计洲. 增材制造记忆合金的元素烧损行为及其补损分析[J]. 焊接学报, 2022, 43(9): 50-55. DOI: 10.12073/j.hjxb.20220105001
ZHU Jian, WANG Hongyu, SHI Donghui, HUANG Jinlei, MAO Jizhou. Element loss behavior and compensation of additive manufacturing memory alloy[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2022, 43(9): 50-55. DOI: 10.12073/j.hjxb.20220105001
Citation: ZHU Jian, WANG Hongyu, SHI Donghui, HUANG Jinlei, MAO Jizhou. Element loss behavior and compensation of additive manufacturing memory alloy[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2022, 43(9): 50-55. DOI: 10.12073/j.hjxb.20220105001

增材制造记忆合金的元素烧损行为及其补损分析

Element loss behavior and compensation of additive manufacturing memory alloy

  • 摘要: 在剖析增材制造过程中记忆合金元素烧损行为的基础上,以自制粉芯丝材为原料,采用电弧熔融沉积工艺制备了不同Mn,Si含量的系列FeMnSiCrNi合金,求解了Mn和Si两种易烧损元素的烧损率,拟合了烧损率与设计含量之间关系的数学模型,并通过合金的熔融沉积试验对该模型进行了验证. 结果表明,增材制造记忆合金元素烧损的主要形式为低沸点元素的选择性蒸发,其绝对烧损率与合金中所有易烧损元素设计成分近似呈现线性关系;验证试验结果显示,通过该模型设计所获得的记忆合金成分误差不超过4%,表明该理论模型具有较高的精度,可用于指导增材制造记忆合金成分的准确控制.

     

    Abstract: Based on the analysis of the element loss behavior of the memory alloy in the additive manufacturing process, a series of FeMnSiCrNi alloys with different Mn and Si contents were prepared by arc melting deposition using self-made powder cored wire as raw material. The burning loss ratios of Mn and Si elements is solved, and the mathematical model of the relationship between the burning loss ratio and the design content is fitted. The model is verified by melting deposition experiments. The results show that the main form of element burning loss of additive manufacturing memory alloy is the selective evaporation of low boiling point elements, and its absolute burning loss ratio is approximately linear with the design composition of all burnable elements in the alloy. Meanwhile, the verification experiment results show that the error of the composition of the memory alloy obtained by the model design is not more than 4%, which indicates that the theoretical model has high accuracy and can be used to guide the accurate control of the composition of the memory alloy in the additive manufacturing.

     

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