Enhanced fast inertial relaxation engine (FIRE) for multiscale simulations
文献类型：期刊论文
| 作者 | Tang MJ(唐明健)2,3; Shuang, Fei1; Xiao P(肖攀)3
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| 刊名 | COMPUTATIONAL MATERIALS SCIENCE
 |
| 出版日期 | 2024-09-01 |
| 卷号 | 244页码:12 |
| 关键词 | Multiscale structural relaxation Fast inertial relaxation engine Atomistic to continuum coupling |
| ISSN号 | 0927-0256 |
| DOI | 10.1016/j.commatsci.2024.113234 |
| 通讯作者 | Xiao, Pan(xiaopan@lnm.imech.ac.cn) |
| 英文摘要 | In multiscale modeling methods (MMM), the integration of atomistic to continuum coupling is a common practice, where two regions have their own distinct length scales. The equilibrium configurations of such multiscale systems under given conditions are typically obtained through energy minimization algorithms (EMA). However, traditional EMAs, such as the conjugate gradient (CG) and limited-memory Broyden-Fletcher-GoldfarbShanno (LBFGS) algorithms, are unable to discern the diverse scales inherent in such systems. In this work, it is found that the convergence rate of energy minimization in multiscale simulations is significantly slower than that in full atomistic simulations, regardless of using CG, LBFGS algorithms or the latest fast inertial relaxation engine (FIRE). The lower efficiency emerges due to the coexistence of atoms and nodes with distinct length scales within the multiscale framework, yet the current EMAs fail to differentiate between them. It results in disparate convergence rates across different scales, which undermines both computational accuracy and efficiency. To address the issue, a multiscale FIRE algorithm which updates positions of atoms and nodes synchronously by employing appropriate effective mass is proposed. The optimal effective mass is determined by synchronizing the vibration of harmonic oscillators across different scales. By employing the multiscale FIRE algorithm, the computational efficiency increased by 24.4 and 23.7 times compared to the CG and LBFGS algorithms when used for multiscale nanoindentation simulations. These findings and the proposed algorithm provide valuable insights for structural relaxations of multiscale physical problems and are promising to further improve the computational accuracy and efficiency of MMMs. |
| 分类号 | 二类 |
| WOS关键词 | QUASI-STATIC DEFORMATION ; STATISTICAL THERMODYNAMICS ; CONTINUUM METHOD ; BRIDGING SCALE ; FINITE-ELEMENT ; NANOINDENTATION ; EFFICIENCY ; MECHANICS ; METALS ; MODELS |
| 资助项目 | National Natural Science Foundation of China (NSFC)[11790292] ; National Natural Science Foundation of China (NSFC)[11672298] ; NSFC Basic Science Center Program[11988102] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB0620103] |
| WOS研究方向 | Materials Science |
| 语种 | 英语 |
| WOS记录号 | WOS:001279425100001 |
| 资助机构 | National Natural Science Foundation of China (NSFC) ; NSFC Basic Science Center Program ; Strategic Priority Research Program of Chinese Academy of Sciences |
| 其他责任者 | Xiao, Pan |
| 源URL | [http://dspace.imech.ac.cn/handle/311007/96199]  |
| 专题 | 力学研究所_非线性力学国家重点实验室 |
| 作者单位 | 1.Delft Univ Technol, Fac Mech Engn, Dept Mat Sci & Engn, Mekelweg 2, NL-2628 CD Delft, Netherlands 2.Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China; 3.Chinese Acad Sci, Inst Mech, LNM, Beijing 100190, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Tang MJ,Shuang, Fei,Xiao P. Enhanced fast inertial relaxation engine (FIRE) for multiscale simulations[J]. COMPUTATIONAL MATERIALS SCIENCE,2024,244:12. |
| APA | 唐明健,Shuang, Fei,&肖攀.(2024).Enhanced fast inertial relaxation engine (FIRE) for multiscale simulations.COMPUTATIONAL MATERIALS SCIENCE,244,12. |
| MLA | 唐明健,et al."Enhanced fast inertial relaxation engine (FIRE) for multiscale simulations".COMPUTATIONAL MATERIALS SCIENCE 244(2024):12. |
入库方式： OAI收割
来源：力学研究所
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