| Determining pressure from velocity via physics-informed neural network | |
Cai, Zemin1; Lin, Xiangqi1; Liu, Tianshu2; Wu F(吴凡)3,4; Wang SZ(王士召)3,4 ; Liu, Yun5
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| Corresponding Author | Liu, Tianshu([email protected]) |
| Source Publication | EUROPEAN JOURNAL OF MECHANICS B-FLUIDS
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| 2025 | |
| Volume | 109Pages:1-21 |
| ISSN | 0997-7546 |
| Abstract | This paper describes a physics-informed neural network (PINN) for determining pressure from velocity where the Navier-Stokes (NS) equations are incorporated as a physical constraint, but the boundary condition is not explicitly imposed. The exact solution of the NS equations for the oblique Hiemenz flow is utilized to evaluate the accuracy of the PINN and the effects of the relevant factors including the boundary condition, data noise, number of collocation points, Reynolds number and impingement angle. In addition, the PINN is evaluated in the twodimensional flow over a NACA0012 airfoil based on computational fluid dynamics (CFD) simulation. Further, the PINN is applied to the velocity data of a flying hawkmoth (Manduca) obtained in high-speed schlieren visualizations, revealing some interesting pressure features associated with the vortex structures generated by the flapping wings. Overall, the PINN offers an alternative solution for the problem of pressure from velocity with the reasonable accuracy and robustness. |
| Keyword | Pressure Velocity PINN Machine learning Neural network Flow Navier-Stokes equations |
| DOI | 10.1016/j.euromechflu.2024.08.007 |
| Indexed By | SCI ; EI |
| Language | 英语 |
| WOS ID | WOS:001306804800001 |
| WOS Keyword | FLUID ; FLOW ; FIELDS ; PIV ; FORCES |
| WOS Research Area | Mechanics ; Physics |
| WOS Subject | Mechanics ; Physics, Fluids & Plasmas |
| Funding Project | National Natural Science Foundation of China[61876104] ; Guangdong Natural Science Foundation[2023A1515011449] ; Presidential Innovation Professorship and Iohn O. Hallquist Endowed Professorship at Western Michigan University |
| Funding Organization | National Natural Science Foundation of China ; Guangdong Natural Science Foundation ; Presidential Innovation Professorship and Iohn O. Hallquist Endowed Professorship at Western Michigan University |
| Classification | 二类 |
| Ranking | 3 |
| Contributor | Liu, Tianshu |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://dspace.imech.ac.cn/handle/311007/96500 |
| Collection | 非线性力学国家重点实验室 |
| Affiliation | 1.Shantou Univ, Dept Elect Engn, Shantou, Peoples R China; 2.Western Michigan Univ, Dept Mech & Aerosp Engn, Kalamazoo, MI 49008 USA; 3.Chinese Acad Sci, Inst Mech, LNM, Beijing, Peoples R China; 4.Univ Chinese Acad Sci, Sch Engn Sci, Beijing, Peoples R China; 5.Purdue Univ Northwest, Dept Mech & Civil Engn, Westville, IN USA |
| Recommended Citation GB/T 7714 | Cai, Zemin,Lin, Xiangqi,Liu, Tianshu,et al. Determining pressure from velocity via physics-informed neural network[J]. EUROPEAN JOURNAL OF MECHANICS B-FLUIDS,2025,109:1-21.Rp_Au:Liu, Tianshu |
| APA | Cai, Zemin,Lin, Xiangqi,Liu, Tianshu,吴凡,王士召,&Liu, Yun.(2025).Determining pressure from velocity via physics-informed neural network.EUROPEAN JOURNAL OF MECHANICS B-FLUIDS,109,1-21. |
| MLA | Cai, Zemin,et al."Determining pressure from velocity via physics-informed neural network".EUROPEAN JOURNAL OF MECHANICS B-FLUIDS 109(2025):1-21. |
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