Synthetic turbulent inflow generator using machine learning

Abstract

Machine-learning-based turbulence generators are developed to generate unsteady inflow conditions for turbulent flow simulations. The proposed method can provide inflow conditions with reasonable turbulence statistics without spurious periodicity and at a low computational cost.