115 citations · 180 across the 2 of their papers we have counts for
6 papers
Convolutional neural networks for fluid flow analysis: toward effective metamodeling and low-dimensionalization
Masaki Morimoto, Kai Fukami, Kai Zhang +2
We focus on a convolutional neural network (CNN), which has recently been utilized for fluid flow analyses, from the perspective on the influence of various operations inside it by…
Phase-consistent dynamic mode decomposition from multiple overlapping spatial domains
Aditya G. Nair, Benjamin Strom, Bingni W. Brunton +1
Dynamic mode decomposition (DMD) provides a principled approach to extract physically interpretable spatial modes from time-resolved flow field data, along with a linear model for…
Cluster-based feedback control of turbulent post-stall separated flows
Aditya G. Nair, Chi-An Yeh, Eurika Kaiser +3
We propose a novel model-free self-learning cluster-based control strategy for general nonlinear feedback flow control technique, benchmarked for high-fidelity simulations of post-…
Network community-based model reduction for vortical flows
Muralikrishnan Gopalakrishnan Meena, Aditya G. Nair, Kunihiko Taira
A network community-based reduced-order model is developed to capture key interactions amongst coherent structures in high-dimensional unsteady vortical flows. The present approach…
Network-theoretic approach to sparsified discrete vortex dynamics
Aditya G. Nair, Kunihiko Taira
We examine discrete vortex dynamics in two-dimensional flow through a network-theoretic approach. The interaction of the vortices is represented with a graph, which allows the use…
Network Structure of Two-Dimensional Decaying Isotropic Turbulence
Kunihiko Taira, Aditya G. Nair, Steven L. Brunton
The present paper reports on our effort to characterize vortical interactions in complex fluid flows through the use of network analysis. In particular, we examine the vortex inter…