One-dimensional parametric determining form for the two-dimensional Navier-Stokes equations
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One-dimensional parametric determining form for the two-dimensional Navier-Stokes equations

  • Author(s): Foias, C
  • Jolly, MS
  • Lithio, D
  • Titi, ES
  • et al.
Abstract

The evolution of a determining form for the 2D Navier-Stokes equations (NSE), which is an ODE on a space of trajectories is completely described. It is proved that at every stage of its evolution, the solution is a convex combination of the initial trajectory and the fixed steady state, with a dynamical convexity parameter $\theta$, which will be called the characteristic determining parameter. That is, we show a remarkable separation of variables formula for the solution of the determining form. Moreover, for a given initial trajectory, the dynamics of the infinite-dimensional determining form are equivalent to those of the characteristic determining parameter $\theta$ which is governed by a one-dimensional ODE. %for the parameter specifying the position on the line segment. This one-dimensional ODE is used to show that if the solution to the determining form converges to the fixed state it does so no faster than $\mathcal{O}(\tau^{-1/2})$, otherwise it converges to a projection of some other trajectory in the global attractor of the NSE, but no faster than $\mathcal{O}(\tau^{-1})$, as $\tau \to \infty$, where $\tau$ is the evolutionary variable in determining form. The one-dimensional ODE also exploited in computations which suggest that the one-sided convergence rate estimates are in fact achieved. The ODE is then modified to accelerate the convergence to an exponential rate. Remarkably, it is shown that the zeros of the scalar function that governs the dynamics of $\theta$, which are called characteristic determining values, identify in a unique fashion the trajectories in the global attractor of the 2D NSE. Furthermore, the one-dimensional characteristic determining form enables us to find unanticipated geometric features of the global attractor, a subject of future research.

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