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Study on high cycle fatigue behaviours and modelling of cast aluminium alloy at elevated temperatures

  • Yongsen Liang
  • , Zhengxing Zuo
  • , Jundiao Wang
  • , Chengzhang Zhao
  • , Peirong Ren*
  • , Weiqing Huang
  • *此作品的通讯作者
  • Beijing Institute of Technology
  • China North Engine Research Institute
  • National Key Laboratory of Multi-perch Vehicle Driving Systems
  • China North Vehicle Research Institute
  • Chinese Scholar Tree Ridge State Key Laboratory

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

High cycle fatigue (HCF) behaviours of cast aluminium alloys at room temperature (RT) and elevated temperatures are examined in this study. The results show that fatigue life significantly decreases at 300 ℃ compared to RT, while the decline at 200 ℃ is relatively small. The coefficient of variation (CV) in fatigue life increases with decreasing load levels at all temperatures. The fracture analysis reveals that pores are primary sites for crack nucleation at both RT and 200 ℃, while cracks also nucleate from hard particles and slip bands at 300 ℃, with the presence of multiple nucleation sites. Correlation analysis shows that the temperature and load level have a comparable impact on the uncertainty in fatigue life, while the effect of crack nucleation defect size is lower than temperature and load level. Fatigue life models were established using linear elastic fracture mechanic (LEFM) and artificial neural network (ANN), respectively, with the former showing lower accuracy due to its inability to capture non-linear material softening at 300 ℃, and the latter demonstrating higher performance with the majority of predictions falling within ± 2.5X scatter bands. Finally, the omni-direction inference between cause and effect is performed using the Bayesian network (BN), which can predict fatigue life distribution interval probabilistically, achieving a balance in predictive and explanatory purposes well.

源语言英语
期刊论文编号109031
期刊Engineering Failure Analysis
卷168
DOI
出版状态已出版 - 1 2月 2025

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