Abstract
Surface defects and microstructure have a significant impact on the fatigue properties of materials. In this paper, surface roughness was considered as surface micro-defects, and the correlation between surface defects and fatigue properties of 2024 aluminum alloy was investigated by applying laser scanning microscopy and electron backscatter diffraction (EBSD) techniques, combined with monotonic tensile tests and fatigue tests. It was found that the Gumbel distribution could better describe the size distribution of surface defects. Meanwhile, the fatigue limit was predicted based on the extreme value statistics of surface defects and the modified Murakami model, and compared with the experimental fatigue limit. Then an extended Kitagawa-Takahashi diagram was developed to evaluate the defect tolerance. In addition, a fatigue life prediction model considering surface roughness as a surface defect and taking into account short crack extension was proposed and validated against experimental data.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
