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Direct numerical simulation of natural convection based on parameter-input physics-informed neural networks 期刊论文
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER, 2025, 卷号: 236, 页码: 126379./通讯作者：Wang YW
Authors:  Ye,Shuran;  Huang JL(黄剑霖);  Zhang, Zhen;  Wang YW(王一伟);  Huang CG(黄晨光)
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Natural convection  Physics-informed neural networks  Parameter-input PINNs  Ra number  Deep learning  
AsPINN: Adaptive symmetry-recomposition physics-informed neural networks 期刊论文
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2024, 卷号: 432, 页码: 117405./通讯作者：刘洋，闫循石
Authors:  Liu ZT(刘子提);  Liu Y(刘洋);  Yan, Xunshi;  Liu W(刘文);  Guo SQ(郭帅旗);  Zhang CA(张陈安)
Favorite  |  View/Download：43/0  |  Submit date：2024/11/01
Network structure  Parameter-sharing  Feature-enhanced physics-informed neural  networks  Symmetry decomposition  
A framework of data assimilation for wind flow fields by physics-informed neural networks 期刊论文
APPLIED ENERGY, 2024, 卷号: 371, 页码: 18./通讯作者：Sun, Zhenxu
Authors:  Yan C(闫畅);  Xu SF(许盛峰);  Sun ZX(孙振旭);  Lutz, Thorsten;  Guo DL(郭迪龙);  Yang GW(杨国伟)
Favorite  |  View/Download：44/0  |  Submit date：2024/11/22
Data assimilation  Wind field reconstruction  Physics-informed deep learning  
Chien-physics-informed neural networks for solving singularly perturbed boundary-layer problems 期刊论文
APPLIED MATHEMATICS AND MECHANICS-ENGLISH EDITION, 2024, 卷号: 45, 期号: 9, 页码: 1467-1480./通讯作者：Zhang, Lei
Authors:  Wang L(王笼);  Zhang L(张磊);  He GW(何国威)
Favorite  |  View/Download：55/0  |  Submit date：2024/10/08
physics-informed neural network (PINN)  singular perturbation  boundary-layer problem  composite asymptotic expansion  O302  
Rapid evaluation of capillary pressure and relative permeability for oil-water flow in tight sandstone based on a physics-informed neural network 期刊论文
JOURNAL OF PETROLEUM EXPLORATION AND PRODUCTION TECHNOLOGY, 2023./通讯作者：Lin, M (corresponding author), Chinese Acad Sci, Inst Mech, Key Lab Mech Fluid Solid Coupling Syst, Beijing 100190, Peoples R China., Lin, M (corresponding author), Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100190, Peoples R China., Wu, ST (corresponding author), PetroChina, Res Inst Petr Explorat & Dev, Beijing 100083, Peoples R China.
Authors:  Ji LL(姬莉莉);  Xu, Fengyang;  Lin M(林缅);  Jiang WB(江文滨);  Cao GH(曹高辉);  Wu, Songtao;  Jiang, Xiaohua
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Two-phase flow  Capillary pressure curve  Relative permeability curve  Tight sandstone  Physics-informed neural network  
A practical approach to flow field reconstruction with sparse or incomplete data through physics informed neural network 期刊论文
ACTA MECHANICA SINICA, 2023, 卷号: 39, 期号: 3, 页码: 322302./通讯作者：Sun, ZX, Huang, RF (corresponding author), Chinese Acad Sci, Inst Mech, Key Lab Mech Fluid Solid Coupling Syst, Beijing 100190, Peoples R China.
Authors:  Xu SF(许盛峰);  Sun ZX(孙振旭);  Huang RF(黄仁芳);  Guo DL(郭迪龙);  Yang GW(杨国伟);  Ju SJ(鞠胜军)
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Physics informed neural network  Flow field reconstruction  Particle image velocimetry  Cosine annealing algorithm  Experimental fluid dynamics  
A Direct-Forcing Immersed Boundary Method for Incompressible Flows Based on Physics-Informed Neural Network 期刊论文
Fluids, 2022, 卷号: 7, 期号: 2, 页码: 56./通讯作者：张星
Authors:  Huang Y(黄毅);  Zhang ZY(张治愚);  Zhang X(张星)
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physics-informed neural networks (PINN)  direct-forcing immersed boundary method  incompressible laminar flow  circular cylinder  
On the design of potential turbine positions for physics-informed optimization of wind farm layout 期刊论文
RENEWABLE ENERGY, 2021, 卷号: 164, 页码: 1108-1120./通讯作者：杨晓雷
Authors:  Wu, Chutian;  Yang XL(杨晓雷);  Zhu, Yaxin
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Wind farm layout optimization  Physics-informed  Potential turbine positions  Jensen wake model  Genetic algorithm  
Energy performance prediction of the centrifugal pumps by using a hybrid neural network 期刊论文
Energy, 2020, 卷号: 213, 页码: 119005./通讯作者：Peijian Zhou, Yiwei Wang
Authors:  Huang RF(黄仁芳);  Zhang Z(张珍);  Zhang W;  Mou JG;  Zhou PJ;  Wang YW(王一伟)
Adobe PDF(4596Kb)  |  Favorite  |  View/Download：455/192  |  Submit date：2021/01/29
Centrifugal pump  Energy performance  Loss model  Physics-informed neural network