A hierarchical mechanism-informed neural network approach for assessing fretting fatigue of dovetail joints

被引:7
作者
Liu, Yujin [1 ]
Yuan, Huang [1 ,2 ]
机构
[1] Tsinghua Univ, Sch Aerosp Engn, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Inst Aero Engines, Beijing 100084, Peoples R China
关键词
Artificial neural network; Fretting fatigue; Multi-axial fatigue; Fatigue life prediction; Nickel-based superalloy; MULTIAXIAL FATIGUE; WEAR; PREDICTION; PLASTICITY; EVOLUTION; DEBRIS;
D O I
10.1016/j.ijfatigue.2022.107453
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
In the present paper, a hierarchical mechanism-informed neural network (HMNN) life prediction method was proposed. The fretting fatigue was decomposed into different fatigue problems and considered in four neural network layers, which were hierarchically and progressively established for proportional multi-axial fatigue, non-proportional multi-axial fatigue, notch fatigue and fretting fatigue, respectively. Each layer can be used to assess the fatigue life of the previous layer based on the progressive construction of fatigue complexity. The HMNN approach can predict all kinds of fatigue implemented in the method with reasonable accuracy and provides a new approach for complex fatigue assessment.
引用
收藏
页数:16
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