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铸件中显微孔洞特征及其对疲劳寿命影响的研究进展
引用本文:姜文,姚卫星,王英玉.铸件中显微孔洞特征及其对疲劳寿命影响的研究进展[J].航空工程进展,2019,10(4):445-455.
作者姓名:姜文  姚卫星  王英玉
作者单位:南京航空航天大学 机械结构力学及控制国家重点实验室,南京,210016;南京航空航天大学 机械结构力学及控制国家重点实验室,南京 210016;南京航空航天大学 飞行器先进设计技术国防重点学科实验室,南京 210016
基金项目:国家自然科学(51875276),航空科学基金(2017ZF52073)
摘    要:铸件在铸造过程中会不可避免地产生显微孔洞,严重降低了铸件疲劳寿命。本文综述铸件中显微孔洞特征(尺寸、形状和空间分布)对疲劳寿命的影响,包括显微孔洞类型,孔洞特征分布规律,孔洞最大尺寸预测方法和含孔洞材料疲劳寿命预测方法;通过对疲劳寿命预测模型的回顾,发现目前含显微孔洞铸件疲劳寿命预测方法还不成熟;展望了显微孔洞特征对疲劳寿命影响的研究。提出未来应该依靠先进光源展开原位疲劳实验或者分子动力学仿真来研究孔洞疲劳失效微观机理,建立考虑不同显微孔洞特征参数,以及不同孔洞间相互影响的疲劳寿命定量预测模型。

关 键 词:铸件  显微孔洞  特征分布规律  尺寸预测  疲劳寿命
收稿时间:2018/11/22 0:00:00
修稿时间:2018/12/10 0:00:00

Progress of Microporosity Characteristics in Casting and Their Effects on Fatigue Life
JIANG Wen,YAO Wei-xing and WANG Ying-yu.Progress of Microporosity Characteristics in Casting and Their Effects on Fatigue Life[J].Advances in Aeronautical Science and Engineering,2019,10(4):445-455.
Authors:JIANG Wen  YAO Wei-xing and WANG Ying-yu
Institution:State Key Laboratory of Mechanics and Control of Mechanical Structures,Nanjing University of Aeronautics and Astronautics,State Key Laboratory of Mechanics and Control of Mechanical Structures,Nanjing University of Aeronautics and Astronautics,State Key Laboratory of Mechanics and Control of Mechanical Structures,Nanjing University of Aeronautics and Astronautics
Abstract:Microporosities in casting alloys cannot be avoided in the casting process. They will destroy the continuity of matrix, cause stress concentration, become the crack source of fatigue failure, and reduce the fatigue life of structure greatly. The current progress of microprosity characteristics (size, shape and position) in casting alloys and their effects on fatigue life is reviewed and prospected in this paper. Most of the microporosities are casting porosities with irregular shape and rough inner wall, and they have great influence on fatigue life of casting alloy. The size characteristic of microporosities well follows the lognormal distribution and the maximum size can be a typical feature to evaluate the fatigue life. And shape characteristics follows the Weibull distribution, however the position characteristics is complex. It is hard to observe the maximum size porosity in large-size casings, so the statistical methods are always used to predict them, and the generalized Pareto distribution method can get the best prediction results. At present, the fatigue life prediction methods of casings with microporosities are not complete and the failure mechanism of microporosity is not clear, the quantitative prediction model of fatigue life needs to be further studied, which considers different characteristic parameters of porosities and the interaction between different porosities under complex loading.
Keywords:casting alloy  microporosity  characterization distribution  size prediction  fatigue life
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