基于动态贝叶斯网络的变幅载荷下疲劳裂纹扩展预测方法

王泓晖,房鑫,李德江,刘贵杰

Fatigue crack growth prediction method under variable amplitude load based on dynamic Bayesian network

Hong-hui WANG,Xin FANG,De-jiang LI,Gui-jie LIU

表 3 AlMgSi1-T6铝合金的物理性能

Tab.3 Physical properties of AlMgSi1-T6 aluminum alloy

${\sigma _{\rm{u}}}$/MPa ${\sigma _{\rm{Y}}}$/MPa n′ ${K_{{\rm{IC}}}}$/MPa $\Delta {K_{{\rm{th}}}}$/ $({\rm{MPa} }\cdot\sqrt{\rm{ m} })$ $300.0 \pm 2.5$ $245.0 \pm 2.7$ 0.064 32 2.184−1.007R[33]