| Data-driven turbulence model for unsteady cavitating flow | |
Zhang Z(张珍); Wang JZ(王静竹); Huang RF(黄仁芳); Qiu RD(丘润荻); Chu, Xuesen; Ye SR(叶舒然); Wang YW(王一伟) ; Liu, Qingkuan
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| Corresponding Author | Wang, Yiwei([email protected]) |
| Source Publication | PHYSICS OF FLUIDS
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| 2023 | |
| Volume | 35Issue:1Pages:18 |
| ISSN | 1070-6631 |
| Abstract | Unsteady Reynolds-averaged Navier-Stokes (URANS) equations have been widely used in engineering fields to investigate cavitating flow owing to their low computational cost and excellent robustness. However, it is challenging to accurately obtain the unsteady characteristics of flow owing to cavitation-induced phase transitions. In this study, we propose an implicit data-driven URANS (DD-URANS) framework to analyze the unsteady characteristics of cavitating flow. In the DD-URANS framework, a basic computational model is developed by introducing a cavitation-induced phase transition into the equations of Reynolds stress. To improve the computational accuracy and generalization performance of the basic model, the linear and nonlinear parts of the anisotropic Reynolds stress are predicted through implicit and explicit methods, respectively. A data fusion approach, allowing the input and output of characterized parameters at multiple time points, is presented to obtain the unsteady characteristics of the cavitating flow. The DD-URANS model is trained using the numerical results obtained via large-eddy simulation. The training data consist of two parts: (i) the results obtained at cavitation numbers of 2.0, 2.2, and 2.7 for a Venturi flow, and (ii) those obtained at cavitation numbers of 0.8 and 1.5 for a National Advisory Committee for Aeronautics (NACA) 66 hydrofoil. The DD-URANS model is used to predict the cavitating flow at cavitation numbers of 2.5 for a Venturi flow and 0.8 for a Clark-Y hydrofoil. It is found that the DD-URANS model is superior to the baseline URANS model in predicting the instantaneous periodic shedding of a cavity and the mean flow fields. |
| DOI | 10.1063/5.0134992 |
| Indexed By | SCI ; EI |
| Language | 英语 |
| WOS ID | WOS:000912891900005 |
| WOS Keyword | LARGE-EDDY SIMULATION ; UNCERTAINTY ; DYNAMICS ; TRANSPORT ; NETWORKS ; CLOSURE ; NUMBER |
| WOS Research Area | Mechanics ; Physics |
| WOS Subject | Mechanics ; Physics, Fluids & Plasmas |
| Funding Project | National Natural Science Foundation of China ; Youth Innovation Promotion Association CAS ; [12202291] ; [12122214] ; [12272382] ; [12293000] ; [12293003] ; [12293004] ; [2022019] |
| Funding Organization | National Natural Science Foundation of China ; Youth Innovation Promotion Association CAS |
| Classification | 一类/力学重要期刊 |
| Ranking | 1 |
| Contributor | Wang, Yiwei |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://dspace.imech.ac.cn/handle/311007/91544 |
| Collection | 流固耦合系统力学重点实验室 |
| Recommended Citation GB/T 7714 | Zhang Z,Wang JZ,Huang RF,et al. Data-driven turbulence model for unsteady cavitating flow[J]. PHYSICS OF FLUIDS,2023,35,1,:18.Rp_Au:Wang, Yiwei |
| APA | 张珍.,王静竹.,黄仁芳.,丘润荻.,Chu, Xuesen.,...&Liu, Qingkuan.(2023).Data-driven turbulence model for unsteady cavitating flow.PHYSICS OF FLUIDS,35(1),18. |
| MLA | 张珍,et al."Data-driven turbulence model for unsteady cavitating flow".PHYSICS OF FLUIDS 35.1(2023):18. |
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| Jp2023A249.pdf（4681KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Download | |
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