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20182022
most citedLinear attention coupled Fourier neural operator for simulation of three-dimensional turbulence

1 citations · 1 across the 1 of their papers we have counts for

collaborators

5 papers

physics.flu-dyn20221 cited

Linear attention coupled Fourier neural operator for simulation of three-dimensional turbulence

Wenhui Peng, Zelong Yuan, Zhijie Li +1

Modeling three-dimensional (3D) turbulence by neural networks is difficult because 3D turbulence is highly-nonlinear with high degrees of freedom and the corresponding simulation i…

physics.flu-dyn2021

Artificial neural network approach for turbulence models: A local framework

Chenyue Xie, Xiangming Xiong, Jianchun Wang

A local artificial neural network (LANN) framework is developed for turbulence modeling. The Reynolds-averaged Navier-Stokes (RANS) unclosed terms are reconstructed by artificial n…

physics.flu-dyn2020

Deconvolutional artificial neural network models for large eddy simulation of turbulence

Zelong Yuan, Chenyue Xie, Jianchun Wang

Deconvolutional artificial neural network (DANN) models are developed for subgrid-scale (SGS) stress in large eddy simulation (LES) of turbulence. The filtered velocities at differ…

physics.flu-dyn2019

Dual channels of helicity cascade in turbulent flows

Zheng Yan, Xinliang Li, Changping Yu +1

Helicity, as one of only two inviscid invariants in three-dimensional turbulence, plays an important role in the generation and evolution of turbulence. From the traditional viewpo…

cs.LG2018

Model Reduction with Memory and the Machine Learning of Dynamical Systems

Chao Ma, Jianchun Wang, Weinan E

The well-known Mori-Zwanzig theory tells us that model reduction leads to memory effect. For a long time, modeling the memory effect accurately and efficiently has been an importan…