1. Low‐cycle fatigue life prediction of powder metallurgy superalloy considering characteristic parameters of inclusions.
- Author
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Feng, Yefei, Zhang, Lu, Wang, Yuzhuo, Yu, Zhiwei, Jiang, Rong, Zhou, Xiaoming, Zou, Jinwen, and Wang, Xuqing
- Subjects
FATIGUE life ,HEAT resistant alloys ,STRAINS & stresses (Mechanics) ,FATIGUE cracks ,ALLOY fatigue ,MATERIAL fatigue - Abstract
Foreign non‐metallic inclusions can significantly reduce the low‐cycle fatigue (LCF) life of powder metallurgy (PM) superalloy and greatly affect the safety and reliability of aeroengines. In this paper, LCF experiments on PM FGH96 superalloy with and without inclusions were conducted. Effects of inclusions on the fatigue life and damage mechanism of FGH96 alloy are discussed by fractography analysis. Parameters related to inclusion characteristics such as strength–inclusion coefficient are proposed. By introducing characteristic parameters of inclusions, the LCF life prediction models are established based on the Manson–Coffin relationship, which significantly improved the prediction accuracy and reduced the scattering band by a factor of 2. Highlights: By performing strain‐controlled low‐cycle fatigue tests at different strain amplitudes, statistical analyses were carried out to assess the influences of size, location, and type of inclusions on LCF life, with a quantitative relationship established between them.The change law of LCF life of powder metallurgy superalloy under different inclusion conditions is summarized. Effects of inclusions on the LCF life of FGH96 alloy were clarified and applied to the establishment of fatigue life prediction models considering characteristic parameters of non‐metal inclusions.A modified Manson–Coffin life prediction model considering inclusion characteristics is proposed to support the safety and reliability assessment of turbine disks made of PM superalloy FGH96.By introducing characteristic parameters of inclusions, the LCF life prediction models are established based on the Manson–Coffin relationship, which significantly improved the prediction accuracy and reduced the scattering band by a factor of 2. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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