Helical model based on artificial neural network for large eddy simulation of compressible wall-bounded turbulent flows
文献类型：期刊论文
| 作者 | Liu, Wanhai; Qi H(齐涵); Shi, Haoyu; Yu ZP(于长平) ; Li XL(李新亮)
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| 刊名 | PHYSICS OF FLUIDS
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| 出版日期 | 2023-04 |
| 卷号 | 35期号:4页码:45120 |
| ISSN号 | 1070-6631 |
| DOI | 10.1063/5.0137607 |
| 英文摘要 | Similar to the kinetic energy cascade, a helicity cascade is also a basic and key process in the generation and evolution of the turbulent flows. Furthermore, the helicity flux (HF) plays a crucial role between two scales in the helicity cascade. In this study, we will supply a new helical model constrained by the helicity flux for the large eddy simulation of the compressible turbulent flows. Then, in order to obtain a more precise HF, the local coefficient of the modeled HF is determined by the artificial neural network (ANN) method. The new model combines merits of the high robustness and the correlation with the real turbulence. In the test case of the compressible turbulent channel flow, the new model can supply a more accurate mean velocity profile, turbulence intensities, Reynolds stress, etc. Then, for the test in the compressible flat-plate boundary layer, the new model can also precisely predict the onset and peak of the transition process, the skin-friction coefficient, the mean velocity in the turbulent region, etc. Moreover, the ANN here is a semi-implicit method, and the new model would be easier to be generalized to simulate other types of the compressible wall-bounded turbulent flows. |
| 分类号 | 一类/力学重要期刊 |
| WOS研究方向 | WOS:000964505700012 |
| 语种 | 英语 |
| 资助机构 | National Key Research and Development Program of China [2020YFA0711800, 2019YFA0405302] ; NSFC [12072349, 12232018, 91852203, 12202457] ; National Numerical Wind Tunnel Project, Science Challenge Project [TZ2016001] ; Strategic Priority Research Program of Chinese Academy of Sciences [XDC01000000] ; Natural Science Foundation of Gansu Provincial Science and Technology Department [21JR7RE171] ; Natural Science Foundation of Zhejiang Guangsha Vocational and Technical University of Construction [2022KYQD-LWH] |
| 其他责任者 | Yu, CP |
| 源URL | [http://dspace.imech.ac.cn/handle/311007/92264]  |
| 专题 | 力学研究所_高温气体动力学国家重点实验室 |
| 作者单位 | 1.(Liu Wanhai, Qi Han, Yu Changping, Li Xinliang) Chinese Acad Sci Inst Mech LHD Beijing 100190 Peoples R China 2.(Liu Wanhai) Zhejiang Guangsha Vocat & Tech Univ Construct Intelligent Mfg Dongyang 322100 Peoples R China 3.(Shi Haoyu) Lanzhou Univ Dept Mech Lanzhou 730000 Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Wanhai,Qi H,Shi, Haoyu,et al. Helical model based on artificial neural network for large eddy simulation of compressible wall-bounded turbulent flows[J]. PHYSICS OF FLUIDS,2023,35(4):45120. |
| APA | Liu, Wanhai,齐涵,Shi, Haoyu,于长平,&李新亮.(2023).Helical model based on artificial neural network for large eddy simulation of compressible wall-bounded turbulent flows.PHYSICS OF FLUIDS,35(4),45120. |
| MLA | Liu, Wanhai,et al."Helical model based on artificial neural network for large eddy simulation of compressible wall-bounded turbulent flows".PHYSICS OF FLUIDS 35.4(2023):45120. |
入库方式： OAI收割
来源：力学研究所
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