227 citations · 386 across the 3 of their papers we have counts for
3 papers
physics.flu-dyn2021★ 15 cited
Inserting machine-learned virtual wall velocity for large-eddy simulation of turbulent channel flows
Naoki Moriya, Kai Fukami, Yusuke Nabae +3
We propose a supervised-machine-learning-based wall model for coarse-grid wall-resolved large-eddy simulation (LES). Our consideration is made on LES of turbulent channel flows wit…
physics.flu-dyn2020★ 227 cited
Convolutional neural network and long short-term memory based reduced order surrogate for minimal turbulent channel flow
Taichi Nakamura, Kai Fukami, Kazuto Hasegawa +2
We investigate the applicability of machine learning based reduced order model (ML-ROM) to three-dimensional complex flows. As an example, we consider a turbulent channel flow at t…
physics.flu-dyn2018★ 144 cited
Synthetic turbulent inflow generator using machine learning
Kai Fukami, Yusuke Nabae, Ken Kawai +1
We propose a methodology for generating time-dependent turbulent inflow data with the aid of machine learning (ML), which has a possibility to replace conventional driver simulatio…