Reynolds-stress-constrained large-eddy simulation of wall-bounded turbulent flows S Chen, Z Xia, S Pei, J Wang, Y Yang, Z Xiao, Y Shi Journal of Fluid Mechanics 703, 1-28, 2012 | 159 | 2012 |
A hybrid numerical simulation of isotropic compressible turbulence J Wang, LP Wang, Z Xiao, Y Shi, S Chen Journal of Computational Physics 229 (13), 5257-5279, 2010 | 149 | 2010 |
Effect of compressibility on the small-scale structures in isotropic turbulence J Wang, Y Shi, LP Wang, Z Xiao, XT He, S Chen Journal of Fluid Mechanics 713, 588-631, 2012 | 130 | 2012 |
Modeling subgrid-scale forces by spatial artificial neural networks in large eddy simulation of turbulence C Xie, J Wang, E Weinan Physical Review Fluids 5 (5), 054606, 2020 | 112 | 2020 |
Artificial neural network mixed model for large eddy simulation of compressible isotropic turbulence C Xie, J Wang, H Li, M Wan, S Chen Physics of Fluids 31 (8), 085112, 2019 | 107 | 2019 |
Cascade of kinetic energy in three-dimensional compressible turbulence J Wang, Y Yang, Y Shi, Z Xiao, XT He, S Chen Physical review letters 110 (21), 214505, 2013 | 107 | 2013 |
Kinetic energy transfer in compressible isotropic turbulence J Wang, M Wan, S Chen, S Chen Journal of Fluid Mechanics, 2018 | 92 | 2018 |
Effect of shocklets on the velocity gradients in highly compressible isotropic turbulence J Wang, Y Shi, LP Wang, Z Xiao, X He, S Chen Physics of Fluids 23 (12), 2011 | 85 | 2011 |
Deconvolutional artificial neural network models for large eddy simulation of turbulence Z Yuan, C Xie, J Wang Physics of Fluids 32 (11), 2020 | 84 | 2020 |
Artificial neural network-based nonlinear algebraic models for large eddy simulation of turbulence C Xie, Z Yuan, J Wang Physics of Fluids 32 (11), 2020 | 82 | 2020 |
Model reduction with memory and the machine learning of dynamical systems C Ma, J Wang, W E Communications in Computational Physics 25 (4), 947-962, 2019 | 78 | 2019 |
Model reduction with memory and the machine learning of dynamical systems C Ma, J Wang, W E arXiv preprint arXiv:1808.04258, 2018 | 78 | 2018 |
Spectra and statistics in compressible isotropic turbulence J Wang, T Gotoh, T Watanabe Physical Review Fluids 2 (1), 013403, 2017 | 71 | 2017 |
Scaling and statistics in three-dimensional compressible turbulence J Wang, Y Shi, LP Wang, Z Xiao, XT He, S Chen Physical review letters 108 (21), 214505, 2012 | 67 | 2012 |
Modeling subgrid-scale force and divergence of heat flux of compressible isotropic turbulence by artificial neural network C Xie, K Li, C Ma, J Wang Physcial Review Fluids 4 (10), 104605, 2019 | 62 | 2019 |
Artificial neural network approach to large-eddy simulation of compressible isotropic turbulence C Xie, J Wang, K Li, C Ma Physical Review E 99 (5), 053113, 2019 | 61 | 2019 |
Attention-enhanced neural network models for turbulence simulation W Peng, Z Yuan, J Wang Physics of Fluids 34 (2), 2022 | 47 | 2022 |
Simulation of three-dimensional compressible decaying isotropic turbulence using a redesigned discrete unified gas kinetic scheme T Chen, X Wen, LP Wang, Z Guo, J Wang, S Chen Physics of Fluids 32 (12), 2020 | 43 | 2020 |
Shocklet statistics in compressible isotropic turbulence J Wang, T Gotoh, T Watanabe Physical Review Fluids 2 (2), 023401, 2017 | 43 | 2017 |
Artificial neural network-based subgrid-scale models for large-eddy simulation of turbulence X Chenyu, Y Zelong, W Jianchun, W Minping, C Shiyi Chinese Journal of Theoretical and Applied Mechanics 53 (1), 1-16, 2021 | 42 | 2021 |