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An adjoint-based approach for finding invariant solutions of Navier–Stokes equations

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TLDR
In this paper, the trajectories of Kolmogorov flows are derived whose trajectories converge asymptotically to the equilibrium and travelling-wave solutions of the Navier-Stokes equations.
Abstract
We consider the incompressible Navier–Stokes equations with periodic boundary conditions and time-independent forcing. For this type of flow, we derive adjoint equations whose trajectories converge asymptotically to the equilibrium and travelling-wave solutions of the Navier–Stokes equations. Using the adjoint equations, arbitrary initial conditions evolve to the vicinity of a (relative) equilibrium at which point a few Newton-type iterations yield the desired (relative) equilibrium solution. We apply this adjoint-based method to a chaotic two-dimensional Kolmogorov flow. A convergence rate of is observed, leading to the discovery of new steady-state and travelling-wave solutions at Reynolds number . Some of the new invariant solutions have spatially localized structures that were previously believed to exist only on domains with large aspect ratios. We show that one of the newly found steady-state solutions underpins the temporal intermittencies, i.e. high energy dissipation episodes of the flow. More precisely, it is shown that each intermittent episode of a generic turbulent trajectory corresponds to its close passage to this equilibrium solution.

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Citations
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Journal ArticleDOI

Relative periodic orbits form the backbone of turbulent pipe flow

TL;DR: In this paper, a detailed study of pipe flow relative periodic orbits with energies and mean dissipations close to turbulent values is performed, and several approaches to reduce the translational symmetry of the system are outlined.
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Extreme Events: Mechanisms and Prediction

TL;DR: In this paper, the authors review several aspects of extreme events in phenomena described by high-dimensional, chaotic dynamical systems, focusing on two pressing aspects of the problem: (i) Mechanisms underlying the formation of Extreme Events and (ii) Real-time prediction of extreme Events.
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A variational approach to probing extreme events in turbulent dynamical systems

TL;DR: It is found that the intermittent bursts of the energy dissipation are independent of the external forcing and are instead caused by the spontaneous transfer of energy from large scales to the mean flow via nonlinear triad interactions.
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Dynamical indicators for the prediction of bursting phenomena in high-dimensional systems.

TL;DR: This work proposes indicators for the prediction of such rare extreme events which do not require a priori known slow and fast coordinates and uses Bayesian statistics to quantify the predictive power of the proposed indicators.
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Reduced-order prediction of rogue waves in two-dimensional deep-water waves

TL;DR: In this article, a decomposition of the wave field into a discrete set of localized wave groups with optimal length scales and amplitudes is proposed to predict large wave formation in two-dimensional water waves.
References
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Book

Convex Optimization

TL;DR: In this article, the focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them, and a comprehensive introduction to the subject is given. But the focus of this book is not on the optimization problem itself, but on the problem of finding the appropriate technique to solve it.
Journal ArticleDOI

GMRES: a generalized minimal residual algorithm for solving nonsymmetric linear systems

TL;DR: An iterative method for solving linear systems, which has the property of minimizing at every step the norm of the residual vector over a Krylov subspace.
Book

Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)

TL;DR: In this paper, Schnabel proposed a modular system of algorithms for unconstrained minimization and nonlinear equations, based on Newton's method for solving one equation in one unknown convergence of sequences of real numbers.
Book

Numerical methods for unconstrained optimization and nonlinear equations

TL;DR: Newton's Method for Nonlinear Equations and Unconstrained Minimization and methods for solving nonlinear least-squares problems with Special Structure.
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