| A novel defect based fatigue damage model coupled with an optimized neural network for high cycle fatigue analysis of casting alloys with surface defect | |
| Gao, Tongzhou; Ji, Chenhao; Zhan, Zhixin; Huang, Yingying; Liu CQ(刘传奇); Hu, Weiping; Meng, Qingchun | |
| Source Publication | INTERNATIONAL JOURNAL OF FATIGUE
 |
| 2023-05 | |
| Volume | 170Pages:107538 |
| ISSN | 0142-1123 |
| Abstract | A novel defect based fatigue damage model coupled with an optimized neural network is proposed for high cycle fatigue prediction. Based on parametric studies and continuum damage mechanics, the defect based fatigue damage evolution equation is derived, and the numerical simulation and fatigue damage computation are then implemented and validated. After that, more computations are performed to acquire a batch of reliable fatigue data, and the database is obtained. Finally, the architecture of the optimized neural network is established, and the predicted results are verified by experimental fatigue data. The proposed methodology works well for the fatigue analysis of casting alloys with surface defect. |
| Keyword | High cycle fatigue Casting alloys Surface defect Damage model Optimized neural network |
| DOI | 10.1016/j.ijfatigue.2023.107538 |
| Indexed By | SCI ; EI |
| Language | 英语 |
| WOS ID | WOS:000927438000001 |
| WOS Research Area | Engineering, Mechanical ; Materials Science, Multidisciplinary |
| WOS Subject | Engineering ; Materials Science |
| Funding Organization | National Natural Science Foundation of China [12172368, 12002011] ; Fundamental Research Funds for the Central Universities ; Opening fund of State Key Laboratory of Nonlinear Mechanics ; One Hundred Talents Program of the Chinese Academy of Sciences |
| Classification | 一类 |
| Ranking | 3+ |
| Contributor | Zhan, ZX (corresponding author), Beihang Univ, Sch Aeronaut Sci & Engn, Beijing 100191, Peoples R China. |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://dspace.imech.ac.cn/handle/311007/91824 |
| Collection | 非线性力学国家重点实验室 |
| Affiliation | 1.Beihang Univ, Sch Aeronaut Sci & Engn, Beijing 100191, Peoples R China 2.Chinese Acad Sci, Inst Mech, State Key Lab Nonlinear Mech, Beijing 100090, Peoples R China |
| Recommended Citation GB/T 7714 | Gao, Tongzhou,Ji, Chenhao,Zhan, Zhixin,et al. A novel defect based fatigue damage model coupled with an optimized neural network for high cycle fatigue analysis of casting alloys with surface defect[J]. INTERNATIONAL JOURNAL OF FATIGUE,2023,170:107538.Rp_Au:Zhan, ZX (corresponding author), Beihang Univ, Sch Aeronaut Sci & Engn, Beijing 100191, Peoples R China. |
| APA | Gao, Tongzhou.,Ji, Chenhao.,Zhan, Zhixin.,Huang, Yingying.,刘传奇.,...&Meng, Qingchun.(2023).A novel defect based fatigue damage model coupled with an optimized neural network for high cycle fatigue analysis of casting alloys with surface defect.INTERNATIONAL JOURNAL OF FATIGUE,170,107538. |
| MLA | Gao, Tongzhou,et al."A novel defect based fatigue damage model coupled with an optimized neural network for high cycle fatigue analysis of casting alloys with surface defect".INTERNATIONAL JOURNAL OF FATIGUE 170(2023):107538. |
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| File Name/Size | DocType | Version | Access | License | ||
| Jp2023Fa122.pdf（18205KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Download | |
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