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…