Network broadcast analysis and control of turbulent flows
arXiv:2006.16240 · doi:10.1017/jfm.2020.965
Abstract
We present a network-based modal analysis technique that identifies key dynamical paths along which perturbations amplify over a time-varying base flow. This analysis is built upon the Katz centrality, which reveals the flow structures that can effectively spread perturbations over a time-evolving network of vortical interactions on the base flow. Motivated by the resolvent form of the Katz function, we take the singular value decomposition of the resulting communicability matrix, complementing the resolvent analysis for fluid flows. The right-singular vectors, referred to as the broadcast modes, give insights into the sensitive regions where introduced perturbations can be effectively spread and amplified over the entire fluid-flow network that evolves in time. We apply this analysis to a two-dimensional decaying isotropic turbulence. The broadcast mode reveals that vortex dipoles are important structures in spreading perturbations. By perturbing the flow with the principal broadcast mode, we demonstrate the utility of the insights gained from the present analysis to effectively modify the evolution of turbulent flows. The current network-inspired work presents a novel use of network analysis to guide flow control efforts, in particular for time-varying base flows.
References in corpus (16)
- Statistical mechanics of complex networks
- The structure and function of complex networks
- The Web of Human Sexual Contacts
- A critical layer model for turbulent pipe flow
- Resolvent-analysis-based design of airfoil separation control
- A Spectral Clustering Approach to Lagrangian Vortex Detection
- Network Structure of Two-Dimensional Decaying Isotropic Turbulence
- Flow networks: A characterization of geophysical fluid transport
- Coherent structure coloring: identification of coherent structures from sparse data using graph theory
- Network-theoretic approach to sparsified discrete vortex dynamics
- Machine-aided turbulence theory
- Network community-based model reduction for vortical flows
- Lagrangian network analysis of turbulent mixing
- From time-series to complex networks: Application to the cerebrovascular flow patterns in atrial fibrillation
- A nested polyhedra model of turbulence
- Monte-Carlo science
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- Selective energy and enstrophy modification of two-dimensional decaying turbulence
- Network-theoretic modeling of fluid-structure interactions
- Network-based analysis of fluid flows: Progress and outlook
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- Stabilizing two-dimensional turbulent Kolmogorov flow via selective modification of inviscid invariants
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