Stochastic higher-order three-scale strength prediction model for composite structures with micromechanical analysis
文献类型：期刊论文
| 作者 | Dong, Hao1; Yang, Zihao2; Guan, Xiaofei3; Cui, Junzhi2,4 |
| 刊名 | JOURNAL OF COMPUTATIONAL PHYSICS
 |
| 出版日期 | 2022-09-15 |
| 卷号 | 465页码:30 |
| ISSN号 | 0021-9991 |
| 关键词 | Composite structures Multiscale random configurations SHTSP model Multilevel strategy Strength prediction |
| DOI | 10.1016/j.jcp.2022.111352 |
| 英文摘要 | Stochastic multiscale modeling and analysis for the strength prediction of composite structures with complex multiscale random configurations remain a challenging problem. This is mainly due to the high-dimensional physical properties, the non-linear and non-Gaussian features, and the fact that many repeated evaluations of the corresponding stochastic multiscale model are often required. In this paper, we develop a stochastic higher-order three-scale strength prediction (SHTSP) model for composite structures, which is designed to overcome the limitations of prohibitive computation involving the microscale, the mesoscale, and the macroscale. By virtue of asymptotic homogenization theory and micromechanical analysis, the SHTSP model is established from the detailed stochastic higher-order three-scale homogenization analysis implemented with analytic solutions of typical composite structures subjected to tension, bending, and twist loads. The SHTSP model represents strength anisotropy through different strength criteria for evaluating the yield state of the different component materials of composite structures, which are induced by material interface deboning or matrix cracking in multiple scales. Moreover, these are constructed and calibrated from the high-accuracy mechanical analysis with help of two classes of mesoscopic and microscopic auxiliary cell functions, respectively. The corresponding numerical algorithm of the SHTSP model and a preprocessing multilevel strategy is designed to improve the computational efficiency. Finally, the numerical experiments in 3D cases illustrate the outstanding performance of the proposed SHTSP model, and the proposed method can significantly reduce the computational time. (c) 2022 Elsevier Inc. All rights reserved. |
| 资助项目 | National Natural Science Foundation of China[12001414] ; Young Talent Fund of Association for Science and Technology in Xi'an, China[095920221338] ; Fundamental Research Funds for the Central Universities[JB210702] ; Aeronautical Science Foundation of China[2020001053002] ; National Key R&D Program of China[2020YFA0713603] ; Natural Science Foundation of Shanghai[21ZR1465800] ; Science Challenge Project[TZ2018001] ; Xidian University |
| WOS研究方向 | Computer Science ; Physics |
| 语种 | 英语 |
| 出版者 | ACADEMIC PRESS INC ELSEVIER SCIENCE |
| WOS记录号 | WOS:000814746100001 |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/61253]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 通讯作者 | Guan, Xiaofei |
| 作者单位 | 1.Xidian Univ, Sch Math & Stat, Xian 710071, Peoples R China 2.Northwestern Polytech Univ, Sch Math & Stat, Xian 710129, Peoples R China 3.Tongji Univ, Sch Math Sci, Shanghai 200092, Peoples R China 4.Chinese Acad Sci, Acad Math & Syst Sci, Inst Computat Math & Sci Engn Comp, LSEC, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Dong, Hao,Yang, Zihao,Guan, Xiaofei,et al. Stochastic higher-order three-scale strength prediction model for composite structures with micromechanical analysis[J]. JOURNAL OF COMPUTATIONAL PHYSICS,2022,465:30. |
| APA | Dong, Hao,Yang, Zihao,Guan, Xiaofei,&Cui, Junzhi.(2022).Stochastic higher-order three-scale strength prediction model for composite structures with micromechanical analysis.JOURNAL OF COMPUTATIONAL PHYSICS,465,30. |
| MLA | Dong, Hao,et al."Stochastic higher-order three-scale strength prediction model for composite structures with micromechanical analysis".JOURNAL OF COMPUTATIONAL PHYSICS 465(2022):30. |
入库方式： OAI收割
来源：数学与系统科学研究院
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