134 citations · 601 across the 15 of their papers we have counts for
15 papers
Control of Vortex Dynamics using Invariants
Kartik Krishna, Aditya G. Nair, Anand Krishnan +2
Vortex-dominated flows are ubiquitous in engineering, and the ability to efficiently manipulate the dynamics of these vortices has broad applications, from wake shaping to mixing e…
Network-theoretic modeling of fluid-structure interactions
Aditya G. Nair, Samuel B. Douglass, Nitish Arya
The coupling interactions between deformable structures and unsteady fluid flows occur across a wide range of spatial and temporal scales in many engineering applications. These fl…
Stabilizing two-dimensional turbulent Kolmogorov flow via selective modification of inviscid invariants
Gaurav Kumar, Aditya G. Nair
We stabilize two-dimensional turbulent Kolmogorov flow by selectively altering the time rate of change of inviscid invariants (energy and enstrophy) of the flow. This method has ea…
Network-based analysis of fluid flows: Progress and outlook
Kunihiko Taira, Aditya G. Nair
The network of interactions among fluid elements and coherent structures gives rise to the incredibly rich dynamics of vortical flows. These interactions can be described with the…
Data-driven unsteady aeroelastic modeling for control
Michelle Hickner, Urban Fasel, Aditya G. Nair +2
Aeroelastic structures, from insect wings to wind turbine blades, experience transient unsteady aerodynamic loads that are coupled to their motion. Effective real-time control of f…
Selective energy and enstrophy modification of two-dimensional decaying turbulence
Aditya G. Nair, James Hanna, Matteo Aureli
In two-dimensional decaying homogeneous isotropic turbulence, kinetic energy and enstrophy are respectively transferred to larger and smaller scales. In such spatiotemporally compl…
Model fusion with physics-guided machine learning
Suraj Pawar, Omer San, Aditya Nair +2
The unprecedented amount of data generated from experiments, field observations, and large-scale numerical simulations at a wide range of spatio-temporal scales have enabled the ra…
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-based control of periodic fluid flows
Aditya G. Nair, Kunihiko Taira, Bingni W. Brunton +1
Fluid flows play a central role in scientific and technological development, and many of these flows are characterized by a dominant oscillation, such as the vortex shedding in the…
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…
Networked oscillator based modeling and control of unsteady wakes
Aditya G. Nair, Steven L. Brunton, Kunihiko Taira
A networked oscillator based analysis is performed for periodic bluff body flows to examine and control the transfer of kinetic energy. Spatial modes extracted from the flow field…
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…