A machine learning model for predicting the ballistic impact resistance of unidirectional fiber-reinforced composite plate
文献类型：期刊论文
| 作者 | Lei, X. D.1,2; Wu, X. Q.2; Zhang, Z.1,2 ; Xiao, K. L.1,2; Wang, Y. W.1,2; Huang, C. G.1,2,3
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| 刊名 | SCIENTIFIC REPORTS
 |
| 出版日期 | 2021-03-22 |
| 卷号 | 11 |
| ISSN号 | 2045-2322 |
| DOI | 10.1038/s41598-021-85963-3 |
| 通讯作者 | Wu, X. Q.(wuxianqian@imech.ac.cn) |
| 英文摘要 | It has been a vital issue to ensure both the accuracy and efficiency of computational models for analyzing the ballistic impact response of fiber-reinforced composite plates (FRCP). In this paper, a machine learning (ML) model is established in an effort to bridge the ballistic impact protective performance and the characteristics of microstructure for unidirectional FRCP (UD-FRCP), where the microstructure of the UD-FRCP is characterized by the two-point correlation function. The results showed that the ML model, after trained by 175 cases, could reasonably predict the ballistic impact energy absorption of the UD-FRCP with a maximum error of 13%, indicating that the model can ensure both computational accuracy and efficiency. Besides, the model's critical parameter sensitivities are investigated, and three typical ML algorithms are analyzed, showing that the gradient boosting regression algorithm has the highest accuracy among these algorithms for the ballistic impact problem of UD-FRCP. The study proposes an effective solution for the traditional difficulty of the ballistic impact simulation of composites with both high efficiency and accuracy. |
| 资助项目 | National Natural Science Foundation of China[11672315] ; National Natural Science Foundation of China[11772347] ; Science Challenge Project[TZ2018001] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB22040302] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB22040303] |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| 出版者 | NATURE RESEARCH |
| WOS记录号 | WOS:000634963000022 |
| 资助机构 | National Natural Science Foundation of China ; Science Challenge Project ; Strategic Priority Research Program of Chinese Academy of Sciences |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/121585]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 通讯作者 | Wu, X. Q. |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Mech, Key Lab Mech Fluid Solid Coupling Syst, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Hefei Inst Phys Sci, Hefei 230031, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lei, X. D.,Wu, X. Q.,Zhang, Z.,et al. A machine learning model for predicting the ballistic impact resistance of unidirectional fiber-reinforced composite plate[J]. SCIENTIFIC REPORTS,2021,11. |
| APA | Lei, X. D.,Wu, X. Q.,Zhang, Z.,Xiao, K. L.,Wang, Y. W.,&Huang, C. G..(2021).A machine learning model for predicting the ballistic impact resistance of unidirectional fiber-reinforced composite plate.SCIENTIFIC REPORTS,11. |
| MLA | Lei, X. D.,et al."A machine learning model for predicting the ballistic impact resistance of unidirectional fiber-reinforced composite plate".SCIENTIFIC REPORTS 11(2021). |
入库方式： OAI收割
来源：合肥物质科学研究院
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