Weiwei Zhang
Cited by
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Machine learning methods for turbulence modeling in subsonic flows around airfoils
L Zhu, W Zhang, J Kou, Y Liu
Physics of Fluids 31 (1), 2019
An improved criterion to select dominant modes from dynamic mode decomposition
J Kou, W Zhang
European Journal of Mechanics-B/Fluids 62, 109-129, 2017
Mechanism of frequency lock-in in vortex-induced vibrations at low Reynolds numbers
W Zhang, X Li, Z Ye, Y Jiang
Journal of Fluid Mechanics 783, 72-102, 2015
Efficient method for limit cycle flutter analysis based on nonlinear aerodynamic reduced-order models
W Zhang, B Wang, Z Ye, J Quan
AIAA journal 50 (5), 1019-1028, 2012
Supersonic flutter analysis based on a local piston theory
WW Zhang, ZY Ye, CA Zhang, F Liu
AIAA Journal 47 (10), 2321-2328, 2009
Deep neural network for unsteady aerodynamic and aeroelastic modeling across multiple Mach numbers
K Li, J Kou, W Zhang
Nonlinear Dynamics 96, 2157-2177, 2019
Data-driven modeling for unsteady aerodynamics and aeroelasticity
J Kou, W Zhang
Progress in Aerospace Sciences 125, 100725, 2021
Mechanism of frequency lock-in in transonic buffeting flow
C Gao, W Zhang, X Li, Y Liu, J Quan, Z Ye, Y Jiang
Journal of Fluid Mechanics 818, 528-561, 2017
Two better loosely coupled solution algorithms of CFD based aeroelastic simulation
W Zhang, Y Jiang, Z Ye
Engineering Applications of Computational Fluid Mechanics 1 (4), 253-262, 2007
A reduced-order model for compressible flows with buffeting condition using higher order dynamic mode decomposition with a mode selection criterion
J Kou, S Le Clainche, W Zhang
Physics of Fluids 30 (1), 2018
The lowest Reynolds number of vortex-induced vibrations
J Kou, W Zhang, Y Liu, X Li
Physics of Fluids 29 (4), 2017
Active control of transonic buffet flow
C Gao, W Zhang, J Kou, Y Liu, Z Ye
Journal of Fluid Mechanics 824, 312-351, 2017
Turbulence closure for high Reynolds number airfoil flows by deep neural networks
L Zhu, W Zhang, X Sun, Y Liu, X Yuan
Aerospace Science and Technology 110, 106452, 2021
Multi-kernel neural networks for nonlinear unsteady aerodynamic reduced-order modeling
J Kou, W Zhang
Aerospace Science and Technology 67, 309-326, 2017
Mode competition in galloping of a square cylinder at low Reynolds number
X Li, Z Lyu, J Kou, W Zhang
Journal of Fluid Mechanics 867, 516-555, 2019
A hybrid reduced-order framework for complex aeroelastic simulations
J Kou, W Zhang
Aerospace science and technology 84, 880-894, 2019
Transonic aeroelasticity: A new perspective from the fluid mode
C Gao, W Zhang
Progress in Aerospace Sciences 113, 100596, 2020
Benchmark aerodynamic shape optimization with the POD-based CST airfoil parametric method
X Wu, W Zhang, X Peng, Z Wang
Aerospace Science and Technology 84, 632-640, 2019
Prospect of artificial intelligence empowered fluid mechanics
Z Weiwei, K Jiaqing, L Yilang
Acta Aeronautica et Astronautica Sinica 42 (4), 524689, 2021
Control law design for transonic aeroservoelasticity
W Zhang, Z Ye
Aerospace Science and Technology 11 (2-3), 136-145, 2007
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