Predictions of turbulent shear flows using deep neural networks

Abstract

The long short-term memory (LSTM) neural network is used to predict the temporal evolution of a low-order representation of near-wall turbulence. This network leads to excellent predictions of turbulence statistics and of the system dynamics, characterized by Poincar\'e maps and Lyapunov exponents.