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为了研究微结构对高循环疲劳分散性的影响,发展了考虑多晶材料微结构特征的极值概率分析方法.首先,通过Voronoi算法构造了近似多晶合金微结构的随机多晶胞元模型.其次,应用基于内变量的晶体塑性本构理论,模拟了不同应变幅下处于结构表面和内部多晶微结构胞元的循环应力应变响应.通过计算有限数量的随机多晶微结构,采用疲劳指示参数表征剪应变主导的裂纹萌生驱动力,从而得到不同应变及边界约束情形下的疲劳指示参数分布.最后,应用极值概率理论分析了多晶胞元中疲劳指示参数的极值分布规律.以TC4合金为例,计算结果表明:高循环疲劳分散性随应变幅降低而上升,且在弹性极限附近变化显著;此外,相比于构件内部晶粒,处于表面的晶粒具有更高的裂纹萌生驱动力.
In order to study the effect of microstructure on high cycle fatigue dispersion, an extremum probability analysis method considering the microstructural characteristics of polycrystalline materials has been developed.Firstly, a stochastic multicellular cell model of approximate polycrystalline alloy microstructures was constructed by Voronoi algorithm. Secondly, the cyclic plasticity constitutive theory based on internal variables was used to simulate the cyclic stress and strain responses of the polycrystalline microstructures at the surface and interior of the structure under different strain amplitudes. By calculating a limited number of random polycrystalline microstructures, Parameter to characterize the shear stress-induced initiation of crack initiation, and obtain the fatigue parameter distribution under different strain and boundary constraints.Finally, the extreme value probability theory is used to analyze the extreme value distribution rules of the fatigue index in polycrystalline cells. TC4 alloy as an example, the calculation results show that the dispersion of high cycle fatigue increases with the decrease of strain amplitude, and changes obviously near the elastic limit. In addition, the grain on the surface has higher crack initiation compared with the internal grains Driving force.