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中国科学院力学研究所机构知识库
Knowledge Management System of Institue of Mechanics, CAS
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洪友士 [2]
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Indexed By：SCI
Funding Organization：National Natural Science Foundation of China [11932020]
Author：洪友士
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Community：非线性力学国家重点实验室
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Fatigue life prediction based on a deep learning method for Ti-6Al-4V fabricated by laser powder bed fusion up to very-high-cycle fatigue regime
期刊论文
INTERNATIONAL JOURNAL OF FATIGUE, 2023, 卷号: 172, 页码: 107645
Authors:
Jia, Yinfeng
;
Fu, Rui
;
Ling, Chao
;
Shen, Zheng
;
Zheng, Liang
;
Zhong, Zheng
;
Hong YS(洪友士)
Adobe PDF(7230Kb)
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View/Download：59/1
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Submit date：2023/06/15
Fatigue life prediction
Deep learning method
Laser powder bed fusion
Ti-6Al-4V
Very -high -cycle fatigue
Effects of loading frequency on fatigue behavior of metallic materials-A literature review
期刊论文
FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES, 2023
Authors:
Hong YS(洪友士)
;
Hu, Yuanpei
;
Zhao, Aiguo
Adobe PDF(4219Kb)
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View/Download：80/9
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Submit date：2023/06/15
fatigue strength
loading frequency
metallic materials
strain rate
very-high-cycle fatigue
