受强制性开放获取政策约束的文章 - Zhicheng Wang了解详情
无法在其他位置公开访问的文章：3 篇
Fluid-structure interactions in a flexible pipe conveying two-phase flow
X Zheng, Z Wang, MS Triantafyllou, GE Karniadakis
International Journal of Multiphase Flow 141, 103667, 2021
强制性开放获取政策： US National Science Foundation, US Department of Energy, US Department of …
An entropy viscosity method for large eddy simulation of turbulent thermal flow in a rotor–stator cavity
Q Du, Y Xie, Z Wang, X Jiang, L Xie
Physics of Fluids 35 (3), 2023
强制性开放获取政策： 国家自然科学基金委员会
High-fidelity modeling and optimization of conjugate heat transfer in arrays of heated cables
Z Wang, GEKJ Chalfant, C Chryssostomidis, H Babaee
2017 IEEE Electric Ship Technologies Symposium (ESTS), 557-563, 2017
强制性开放获取政策： US Department of Defense, US National Oceanic and Atmospheric Administration
可在其他位置公开访问的文章：19 篇
Physics-informed neural networks (PINNs) for fluid mechanics: A review
S Cai, Z Mao, Z Wang, M Yin, GE Karniadakis
Acta Mechanica Sinica 37 (12), 1727-1738, 2021
强制性开放获取政策： US Department of Energy, 国家自然科学基金委员会
Physics-informed neural networks for heat transfer problems
S Cai, Z Wang, S Wang, P Perdikaris, GE Karniadakis
Journal of Heat Transfer 143 (6), 060801, 2021
强制性开放获取政策： US Department of Energy, US Department of Defense
Physics-informed neural networks with hard constraints for inverse design
L Lu, R Pestourie, W Yao, Z Wang, F Verdugo, SG Johnson
SIAM Journal on Scientific Computing 43 (6), B1105-B1132, 2021
强制性开放获取政策： Government of Spain
Deep learning of vortex-induced vibrations
M Raissi, Z Wang, MS Triantafyllou, GE Karniadakis
Journal of Fluid Mechanics 861, 119-137, 2019
强制性开放获取政策： US Department of Defense
Flow over an espresso cup: inferring 3-D velocity and pressure fields from tomographic background oriented Schlieren via physics-informed neural networks
S Cai, Z Wang, F Fuest, YJ Jeon, C Gray, GE Karniadakis
Journal of Fluid Mechanics 915, A102, 2021
强制性开放获取政策： US Department of Energy
DeepM&Mnet: Inferring the electroconvection multiphysics fields based on operator approximation by neural networks
S Cai, Z Wang, L Lu, TA Zaki, GE Karniadakis
Journal of Computational Physics 436, 110296, 2021
强制性开放获取政策： US Department of Energy, US Department of Defense
Reinforcement learning for bluff body active flow control in experiments and simulations
D Fan, L Yang, Z Wang, MS Triantafyllou, GE Karniadakis
Proceedings of the National Academy of Sciences 117 (42), 26091-26098, 2020
强制性开放获取政策： US Department of Energy, US National Oceanic and Atmospheric Administration
Forecasting solar-thermal systems performance under transient operation using a data-driven machine learning approach based on the deep operator network architecture
JD Osorio, Z Wang, G Karniadakis, S Cai, C Chryssostomidis, M Panwar, ...
Energy Conversion and Management 252, 115063, 2022
强制性开放获取政策： US Department of Energy
Active-and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows
L Zhao, Z Li, Z Wang, B Caswell, J Ouyang, GE Karniadakis
Journal of Computational Physics 427, 110069, 2021
强制性开放获取政策： US Department of Energy, US Department of Defense
Heat transfer prediction with unknown thermal boundary conditions using physics-informed neural networks
S Cai, Z Wang, C Chryssostomidis, GE Karniadakis
Fluids Engineering Division Summer Meeting 83730, V003T05A054, 2020
强制性开放获取政策： US Department of Defense
A phase-field method for boiling heat transfer
Z Wang, X Zheng, C Chryssostomidis, GE Karniadakis
Journal of Computational Physics 435, 110239, 2021
强制性开放获取政策： US Department of Energy, US Department of Defense
A fast multi-fidelity method with uncertainty quantification for complex data correlations: Application to vortex-induced vibrations of marine risers
X Meng, Z Wang, D Fan, MS Triantafyllou, GE Karniadakis
Computer Methods in Applied Mechanics and Engineering 386, 114212, 2021
强制性开放获取政策： US Department of Energy, US Department of Defense, US National Oceanic and …
Inferring vortex induced vibrations of flexible cylinders using physics-informed neural networks
E Kharazmi, D Fan, Z Wang, MS Triantafyllou
Journal of Fluids and Structures 107, 103367, 2021
强制性开放获取政策： US Department of Energy
An artificial viscosity augmented physics-informed neural network for incompressible flow
Y He, Z Wang, H Xiang, X Jiang, D Tang
Applied Mathematics and Mechanics 44 (7), 1101-1110, 2023
强制性开放获取政策： 国家自然科学基金委员会
An entropy-viscosity large eddy simulation study of turbulent flow in a flexible pipe
Z Wang, MS Triantafyllou, Y Constantinides, GE Karniadakis
Journal of Fluid Mechanics 859, 691-730, 2019
强制性开放获取政策： US Department of Defense
Deep reinforcement transfer learning of active control for bluff body flows at high Reynolds number
Z Wang, D Fan, X Jiang, MS Triantafyllou, GE Karniadakis
Journal of Fluid Mechanics 973, A32, 2023
强制性开放获取政策： US Department of Defense
A stabilized phase-field method for two-phase flow at high Reynolds number and large density/viscosity ratio
Z Wang, S Dong, MS Triantafyllou, Y Constantinides, GE Karniadakis
Journal of Computational Physics 397, 108832, 2019
强制性开放获取政策： US Department of Defense
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