Control of Vortex Dynamics using Invariants
Kartik Krishna, Aditya G. Nair, Anand Krishnan, Steven L. Brunton,, Eurika Kaiser

TL;DR
This paper introduces a novel control approach for vortex dynamics using invariants and Koopman eigenfunctions, enabling manipulation of chaotic vortex behavior and mixing in a 4-vortex system.
Contribution
It develops a Koopman-based invariant control method for vortex dynamics, applying it to chaotic vortex systems to modify their states and enhance mixing.
Findings
Controlling invariants can transition vortex states from chaos to quasiperiodicity.
The invariant control method effectively manipulates vortex behavior.
Demonstrated improved mixing in a 4-vortex system.
Abstract
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 enhancement. However, the strongly nonlinear behavior of the vortex dynamics makes this a challenging task. In this work, we investigate the control of vortex dynamics by using a change of coordinates from the Biot-Savart equations into well-known invariants, such as the Hamiltonian, linear, and angular impulses, which are Koopman eigenfunctions. We then combine the resulting model with model predictive control to generate control laws that force the vortex system using "virtual cylinders". The invariant model is beneficial as it provides a linear, global description of the vortex dynamics through a recently developed Koopman control scheme for conserved quantities and invariants. The use of this model has not…
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Taxonomy
TopicsLattice Boltzmann Simulation Studies · Model Reduction and Neural Networks · Fluid Dynamics and Vibration Analysis
