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基于损伤力学的增材制造金属材料疲劳寿命预测 被引量:5

Damage mechanics-based fatigue life prediction for additive manufacturing metal materials
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摘要 增材制造(AM)技术发展迅速,广泛应用于航空航天领域合金构件的加工制造,而很多增材制造合金构件承受循环载荷,疲劳失效破坏十分普遍。通过建立考虑增材制造过程影响的疲劳损伤模型,计算了增材制造金属材料的疲劳寿命。给出了弹塑性本构模型和考虑增材制造过程参数的疲劳损伤模型,进而给出了疲劳寿命计算的有限元数值方法;对增材制造金属材料进行了疲劳寿命预测,预测值与试验值基本吻合,并从疲劳数据的分散性及增材制造金属材料内部的孔隙率2个方面分析了计算误差;讨论了体积能量密度比对增材制造金属材料疲劳性能的影响,并对结果进行了分析,为增材制造金属材料的疲劳损伤评定提供一种有效的方法。 The additive manufacturing(AM)technology develops rapidly and it is widely employed in the fabrication of aerospace alloy components.Many additive manufacturing alloy components bear cyclic loadings,and the fatigue failure is very common.The fatigue damage model considering the influence of additive manufacturing process is established and the fatigue lives of additive manufacturing alloy materials are predicted.The elastic-plastic constitutive model and the fatigue damage model considering the additive manufacturing process parameters are presented,and the finite element numerical method is presented for the fatigue life computation.The fatigue lives of additive manufacturing metal materials are predicted,which are basically consistent with the experimental results,and the computed errors are analyzed from two aspects including the scatter of fatigue data and the porosity in the additive manufacturing materials.The influence of the volume energy density ratio on the fatigue properties of additive manufacturing metal materials is discussed,and the results are analyzed.This research provides an effective method for the fatigue damage evaluation of additive manufacturing metal materials.
作者 洪海铭 詹志新 王佳莹 HONG Haiming;ZHAN Zhixin;WANG Jiaying(Comprehensive Strength Department,AVIC Shenyang Aircraft Design and Research Institute,Shenyang 110035,China;School of Aeronautic Science and Engineering,Beihang University,Beijing 100083,China)
出处 《北京航空航天大学学报》 EI CAS CSCD 北大核心 2022年第6期950-956,共7页 Journal of Beijing University of Aeronautics and Astronautics
关键词 增材制造(AM) 金属材料 疲劳寿命 预估方法 体积能量密度比 additive manufacturing(AM) metal materials fatigue life prediction method volume energy density ratio
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