Convolutional neural network based hierarchical autoencoder for nonlinear mode decomposition of fluid field data

Kai Fukami, Taichi Nakamura, Koji Fukagata

We propose a customized convolutional neural network based autoencoder called a hierarchical autoencoder, which allows us to extract nonlinear autoencoder modes of flow fields whil…