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Prediction of residual stress induced by laser shock processing based on artificial neural networks for FGH4095 superalloy
Wu JJ(吴嘉俊)1,2,3; Li YH(李营浩)1,2,3; Zhao JB(赵吉宾)1,2; Qiao HC(乔红超)1,2; Lu Y(陆莹)1,2; Sun BY(孙博宇)1,2; Hu XL(胡宪亮)1,2,3; Yang YQ(杨玉奇)1,2,3
Department工艺装备与智能机器人研究室
Source PublicationMaterials Letters
ISSN0167-577X
2021
Volume286Pages:1-4
Indexed ByEI
EI Accession number20210209751306
Contribution Rank1
Funding OrganizationNSFC-Liaoning Province United Foundation of China (Grant No.U1608259) ; National Natural Science Foundation of China (Grant No.51875558)
KeywordLaser shock processing FGH4095 superalloy Artificial neural network Residual stress
Abstract

FGH4095 superalloy samples were single point treated by laser shock processing (LSP) with laser energy of 5–7 J, and shocked times of 1& 3, and laser profile of Gaussian distribution & Flat top distribution. The residual stress of treated samples were determined by PROTO LXRD stress device. Artificial neural network (ANN) was used to predict the residual stress induced by LSP. The experimental residual stresses with laser energy of 5 J and 7 J were used as training datasets, and that with laser energy of 6 J were reserved as test datasets to validate the trained network. And this work showed a good fitness of experimental results and predicted results, which can provide theoretical reference for predicting the mechanical properties and servery performance of materials by LSP.

Language英语
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/28161
Collection工艺装备与智能机器人研究室
Corresponding AuthorWu JJ(吴嘉俊); Zhao JB(赵吉宾)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang
2.Liaoning 110016, China
3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang
4.Liaoning 110169, China
5.University of Chinese Academy of Sciences, Beijing 100049, China
Recommended Citation
GB/T 7714
Wu JJ,Li YH,Zhao JB,et al. Prediction of residual stress induced by laser shock processing based on artificial neural networks for FGH4095 superalloy[J]. Materials Letters,2021,286:1-4.
APA Wu JJ.,Li YH.,Zhao JB.,Qiao HC.,Lu Y.,...&Yang YQ.(2021).Prediction of residual stress induced by laser shock processing based on artificial neural networks for FGH4095 superalloy.Materials Letters,286,1-4.
MLA Wu JJ,et al."Prediction of residual stress induced by laser shock processing based on artificial neural networks for FGH4095 superalloy".Materials Letters 286(2021):1-4.
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