Application of deep learning method to Reynolds stress models of channel flow based on reduced-order modeling of DNS data | |
Zhang Z(张珍); Song XD; Ye SR; Wang YW(王一伟); Huang CG(黄晨光); An YR; Chen YS | |
发表期刊 | JOURNAL OF HYDRODYNAMICS |
2019-02-01 | |
卷号 | 31期号:1页码:58-65 |
ISSN | 1001-6058 |
摘要 | Recently, the methodology of deep learning is used to improve the calculation accuracy of the Reynolds-averaged Navier-Stokes (RANS) model. In this paper, a neural network is designed to predict the Reynolds stress of a channel flow of different Reynolds numbers. The rationality and the high efficiency of the neural network is validated by comparing with the results of the direct numerical simulation (DNS To further enhance the prediction accuracy, three methods are developed by using several algorithms and simplified models in the neural network. In the method 1, the regularization is introduced and it is found that the oscillation and the overfitting of the results are effectively prevented. In the method 2, y(+) is embedded in the input variable while the combination of the invariants is simplified in the method 3. From the predicted results, it can be seen that by using the first two methods, the errors are reduced. Moreover, the method 3 shows considerable advantages in the DNS trend and the smoothness of a curve. Consequently, it is concluded that the DNNs can predict effectively the anisotropic Reynolds stress and is a promising technique of the computational fluid dynamics. |
关键词 | Deep neural network channel flow turbulence model Reynolds stress |
DOI | 10.1007/s42241-018-0156-9 |
收录类别 | SCI ; EI ; CSCD |
语种 | 英语 |
WOS记录号 | WOS:000459199400006 |
关键词[WOS] | NUMERICAL-SIMULATION ; TURBULENT-FLOW ; VERIFICATION ; DYNAMICS |
WOS研究方向 | Mechanics |
WOS类目 | Mechanics |
项目资助者 | National Key RD Program [2016YFC0301601] |
CSCD记录号 | CSCD:6426636 |
论文分区 | Q3 |
力学所作者排名 | 1 |
RpAuthor | Wang, YW |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://dspace.imech.ac.cn/handle/311007/78484 |
专题 | 流固耦合系统力学重点实验室 |
作者单位 | 1.{Zhang, Zhen、Ye, Shu-ran、Wang, Yi-wei、Huang, Chen-guang} Chinese Acad Sci, Inst Mech, Key Lab Mech Fluid Solid Coupling Syst, Beijing 100190, Peoples R China 2.{Zhang, Zhen、Ye, Shu-ran、Wang, Yi-wei、Huang, Chen-guang} Univ Chinese Acad Sci, Coll Engn Sci, Beijing 100049, Peoples R China 3.{Song, Xu-dong、An, Yi-ran、Chen, Yao-song} Peking Univ, Coll Engn, Beijing 100871, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang Z,Song XD,Ye SR,et al. Application of deep learning method to Reynolds stress models of channel flow based on reduced-order modeling of DNS data[J]. JOURNAL OF HYDRODYNAMICS,2019,31,1,:58-65. |
APA | Zhang Z.,Song XD.,Ye SR.,Wang YW.,Huang CG.,...&Chen YS.(2019).Application of deep learning method to Reynolds stress models of channel flow based on reduced-order modeling of DNS data.JOURNAL OF HYDRODYNAMICS,31(1),58-65. |
MLA | Zhang Z,et al."Application of deep learning method to Reynolds stress models of channel flow based on reduced-order modeling of DNS data".JOURNAL OF HYDRODYNAMICS 31.1(2019):58-65. |
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