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| A deep learning-based method for predicting the low-cycle fatigue life of austenitic stainless steel | |
Duan, Hongyan ; Yue, Shunqiang; Liu, Yang; He, Hong; Zhang, Zengwang; Zhao, Yingjian
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| 2023-08-01 | |
| Source Publication | MATERIALS RESEARCH EXPRESS
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| ISSN | 2053-1591 |
| Volume | 10Issue:8 |
| Abstract | In modern engineering, predicting the fatigue life of materials is crucial for safety assessment. The relationship between fatigue life and its influencing factors is difficult to predict by traditional methods, and deep learning can achieve great power and flexibility through nested hierarchies of concepts. Taking the low cycle fatigue life of 316 austenitic stainless steel as an example, a method for predicting the low cycle fatigue life of austenitic stainless steel by deep learning is established based on the limited ability of traditional neural network model and genetic algorithm optimization model. The deep neural network model is introduced to predict the fatigue life of the material. The results show that the prediction correlation coefficient R of the deep neural network prediction model with three hidden layers is 0.991, and the deep neural network learning model has better prediction ability. |
| Keyword | austenitic stainless steel deep neural network life prediction genetic algorithm neural network |
| DOI | 10.1088/2053-1591/aced39 |
| Indexed By | SCIE |
| Language | 英语 |
| WOS Research Area | Materials Science |
| WOS Subject | Materials Science, Multidisciplinary |
| WOS ID | WOS:001049741200001 |
| Publisher | IOP Publishing Ltd |
| Original literature type | Article |
| Citation statistics |
Cited Times [WOS]:0
[WOS Record]
[Related Records in WOS]
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| Document Type | 期刊论文 |
| Identifier | https://ir.lut.edu.cn/handle/2XXMBERH/166171 |
| Collection | 机电工程学院 |
| Corresponding Author | Duan, Hongyan |
| Affiliation | Lanzhou Univ Technol, Sch Mech & Elect Engn, Lanzhou, Peoples R China |
| First Author Affilication | Lanzhou University of Technology |
| Corresponding Author Affilication | Lanzhou University of Technology |
| First Signature Affilication | Lanzhou University of Technology |
| Recommended Citation GB/T 7714 | Duan, Hongyan,Yue, Shunqiang,Liu, Yang,et al. A deep learning-based method for predicting the low-cycle fatigue life of austenitic stainless steel[J]. MATERIALS RESEARCH EXPRESS,2023,10(8). |
| APA | Duan, Hongyan,Yue, Shunqiang,Liu, Yang,He, Hong,Zhang, Zengwang,&Zhao, Yingjian.(2023).A deep learning-based method for predicting the low-cycle fatigue life of austenitic stainless steel.MATERIALS RESEARCH EXPRESS,10(8). |
| MLA | Duan, Hongyan,et al."A deep learning-based method for predicting the low-cycle fatigue life of austenitic stainless steel".MATERIALS RESEARCH EXPRESS 10.8(2023). |
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