Defect-induced fatigue scattering and assessment of additively manufactured 300M-AerMet100 steel: An investigation based on experiments and machine learning

doi:10.1016/j.engfracmech.2022.108352

CORC > 力学研究所 > 中国科学院力学研究所 > 非线性力学国家重点实验室

	Defect-induced fatigue scattering and assessment of additively manufactured 300M-AerMet100 steel: An investigation based on experiments and machine learning
	Zhan, Zhixin 3; Ao, Ni 2; Hu, Yanan 2; Liu CQ(刘传奇)1
刊名	ENGINEERING FRACTURE MECHANICS
	2022-04-01
卷号	264 页码:17
关键词	Data-driven modeling Additive manufacturing 300M-AerMet100 steel Experimental investigations Fatigue assessment
ISSN号	0013-7944
DOI	10.1016/j.engfracmech.2022.108352
通讯作者	Liu, Chuanqi(chuanqil@imech.ac.cn)
英文摘要	Additive manufacturing (AM) has attracted much attention recently for its immanent advantages. Assessment of the fatigue performance for AM treated materials becomes vital for both material science and engineering applications. In this study, we extensively investigate the fatigue performance of AM processed 300M-AerMet100 steel by combining experiments, numerical simulations and machine learning. We conduct experiments to obtain fatigue curves as calibration and to determine the parameters used in the theoretical models. Continuum damage mechanics-based fatigue models are presented and numerically implemented to generate sufficient training data for machine learning. We then employ a multi-layer perceptron neural network model to predict the fatigue life of the AM processed 300M-AerMet100 steel. Experimental results show that there are scatters in the fatigue data, which may be caused by the small cracks induced by the laser cladding process via fractographic analyses. Numerical results show that a good prediction of fatigue life can be achieved by combining the continuum damage mechanics-based fatigue models and the multi-layer perceptron neural network model. This work provides a systematic prediction platform for the fatigue performance of the AM fabricated 300M-AerMet100 steel.
分类号	二类/Q1
资助项目	National Natural Science Foundation of China[12002011] ; National Natural Science Foundation of China[12172368] ; Fundamental Research Funds for the Central Universities[YWF-21-BJ-J-1115] ; One Hundred Talents Program of the Chinese Academy of Sciences
WOS关键词	CRACK INITIATION ; SURFACE-ROUGHNESS ; LIFE ; PREDICTION ; RESISTANCE ; STRENGTH ; ALLOY
WOS研究方向	Mechanics
语种	英语
WOS记录号	WOS:000773496200001
资助机构	National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities ; One Hundred Talents Program of the Chinese Academy of Sciences
其他责任者	Liu, Chuanqi
内容类型	期刊论文
源URL	[http://dspace.imech.ac.cn/handle/311007/88829]
专题	力学研究所_非线性力学国家重点实验室
作者单位	1.Chinese Acad Sci, Inst Mech, State Key Lab Nonlinear Mech, Beijing, Peoples R China 2.Southwest Jiaotong Univ, State Key Lab Tract Power, Chengdu, Peoples R China; 3.Beihang Univ, Sch Aeronaut Sci & Engn, Beijing, Peoples R China;
推荐引用方式 GB/T 7714	Zhan, Zhixin,Ao, Ni,Hu, Yanan,et al. Defect-induced fatigue scattering and assessment of additively manufactured 300M-AerMet100 steel: An investigation based on experiments and machine learning[J]. ENGINEERING FRACTURE MECHANICS,2022,264:17.
APA	Zhan, Zhixin,Ao, Ni,Hu, Yanan,&刘传奇.(2022).Defect-induced fatigue scattering and assessment of additively manufactured 300M-AerMet100 steel: An investigation based on experiments and machine learning.ENGINEERING FRACTURE MECHANICS,264,17.
MLA	Zhan, Zhixin,et al."Defect-induced fatigue scattering and assessment of additively manufactured 300M-AerMet100 steel: An investigation based on experiments and machine learning".ENGINEERING FRACTURE MECHANICS 264(2022):17.