期刊
INTERNATIONAL JOURNAL OF FATIGUE
卷 143, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ijfatigue.2020.105993
关键词
Multiaxial fatigue life prediction; Aircraft aluminum alloy; Critical plane approach; Additional hardening; Non-proportional loading
资金
- Natural Science Foundation of China [52005087, U1708255, 51775355]
- Fundamental Research Funds for the Central Universities
A new multiaxial fatigue life prediction model was proposed for aircraft aluminum alloy, defining a subcritical plane and building a corresponding damage parameter to describe the fatigue failure mechanism under non-proportional loading condition. The effectiveness of the new model was verified through multiaxial fatigue experiments, demonstrating its superior stability and accuracy compared to traditional models.
Considering the frequent failure of aircraft caused by the multiaxial fatigue damage, it is very necessary to develop a reliable mathematical model to predict the multiaxial fatigue life for aircraft aluminum alloy. In our study, a new multiaxial fatigue life prediction model was proposed for both thin-walled tubular and notched specimens. In presented model, a new characteristic plane (subcritical plane) was defined to describe the particularity of additional cyclic hardening under non-proportional loading condition. On the new defined subcritical plane, a corresponding damage parameter containing the effect of additional hardening was also built, by which the dynamic path of stress spindle, combining material property and loading environment, was fully analysed. Finally, in order to verify the effectiveness of the new model for the multiaxial fatigue life prediction of aircraft aluminum alloy, multiaxial fatigue experiment for 2A12 aluminum alloy in four types of fatigue specimens was employed for the material fatigue failure simulation of the aircraft. Through the comparison result with three traditional models, it was evident the stability and accuracy of the new proposed model were much superior to those of the other three traditional models.
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