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The onset of filamentation on vorticity interfaces in two-dimensional Euler flows

Published online by Cambridge University Press:  07 April 2025

David G. Dritschel*
Affiliation:
Mathematical Institute, University of St Andrews, St Andrews KY16 9SS, UK
Adrian Constantin
Affiliation:
Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria
Pierre M. Germain
Affiliation:
Department of Mathematics, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
*
Corresponding author: David G. Dritschel, david.dritschel@st-andrews.ac.uk

Abstract

Two-dimensional Euler flows, in the plane or on simple surfaces, possess a material invariant, namely the scalar vorticity normal to the surface. Consequently, flows with piecewise-uniform vorticity remain that way, and moreover evolve in a way which is entirely determined by the instantaneous shapes of the contours (interfaces) separating different regions of vorticity – this is known as ‘contour dynamics’. Unsteady vorticity contours or interfaces often grow in complexity (lengthen and fold), either as a result of vortex interactions (like mergers) or ‘filamentation’. In the latter, wave disturbances riding on a background, equilibrium contour shape appear to inevitably steepen and break, forming filaments, repeatedly– and perhaps endlessly. Here, we revisit the onset of filamentation. Building upon previous work and using a weakly nonlinear expansion to third order in wave amplitude, we derive a universal, parameter-free amplitude equation which applies (with a minor change) both to a straight interface and a circular patch in the plane, as well as circular vortex patches on the surface of a sphere. We show that this equation possesses a local, self-similar form describing the finite-time blow up of the wave slope (in a re-scaled long time proportional to the inverse square of the initial wave amplitude). We present numerical evidence for this self-similar blow-up solution, and for the conjecture that almost all initial conditions lead to finite-time blow up. In the full contour dynamics equations, this corresponds to the onset of filamentation.

Information

Type
JFM Papers
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press
Figure 0

Figure 1. Illustration of the linear evolution of disturbances to a vorticity interface, $\eta (\theta ,t)$ in (2.5), for $-\pi \leqslant \theta \leqslant \pi$ (shown as the abscissa). Here, $T=4\pi /\omega$ is the linear wave period and successive times shown are displaced downwards by an equal increment in the ordinate to avoid overlap. Note that the initial disturbance reverses after half a period, then recovers its initial form after one full period. After a quarter of a period, the solution turns from anti-symmetric to symmetric about its centre, and this also reverses after a further half-period.

Figure 1

Figure 2. Time evolution of the wave amplitude $\mathcal {A}$ (a, with real and imaginary parts in blue and red, respectively) for a circular vorticity interface on a sphere, together with the corresponding power spectrum $|a_m|^2$ (b) for 5 selected times $\tilde \tau$ (increasing downwards). Initially, just $a_2$ and $a_3$ are non-zero.

Figure 2

Figure 3. Time evolution of various diagnostics, as labelled, from $\tilde \tau =0$ to $0.355$ (the last reliable time). In the figure for $\textrm {d}\theta _{max }/\textrm {d}\tilde \tau$, 1-2-1 averages (replacing data values, say $f_i$, by $(f_{i-1}+2f_i+f_{i+1})/4$) were repeated 64 times to remove most of the noise occurring around the maximum near $\tilde \tau =0.32$ (endpoint values were replaced by linear extrapolation of the averaged interior data points). This noise arises from the imprecision in locating $\theta _{{max}}$.

Figure 3

Figure 4. Time evolution of the maximum wave slope $s(\tilde \tau )=|\partial \mathcal {A}/\partial \theta |_{max }$ together with a fit to $\sqrt {c/(\tilde \tau _c-\tilde \tau )}$ (a), and the function $f(\tilde \tau )=s^2(\tilde \tau _c-\tilde \tau )-c$ (b) which would be zero for a perfect fit.

Figure 4

Figure 5. Zoom of a portion of the curve $\mathcal {A}_r(\theta ,\tilde \tau )$ at $\tilde \tau \approx 0.3553927$ (blue) compared with a contour dynamics simulation (black) at the equivalent time, here $362$ linear wave periods (see the text for details).

Figure 5

Figure 6. A portion of the interface in the full contour dynamics simulation at successive linear wave periods, from $t=362$ at the top to $t=376$ at the bottom. Here, $\rho (\theta ,t)$ is plotted over the range $1.85\leqslant \theta \leqslant 2$. Note that, between the times shown, the interface exhibits a relatively fast oscillation over the linear wave period, analogous to that illustrated in figure 1.

Figure 6

Figure 7. The estimated self-similar solution $\psi (\xi )$ (real part in cyan, imaginary part in magenta), together with scaled numerical profiles (see the text) at times $\tilde \tau =0.345$, $0.347$, $0.349$, $0.351$, $0.353$ and $0.355$ (real part in blue, imaginary part in red, with fading backwards in time).

Figure 7

Figure 8. Time evolution of the wave amplitude $\mathcal {A}$ (a, with real and imaginary parts in blue and red respectively) for a vorticity interface on the periodic line, together with the corresponding power spectrum $|a_k|^2$ (b) for 5 selected times $\tilde \tau$ (increasing downwards). Initially, just $a_2$ and $a_3$ are non-zero. Compare with figure 2 for the circular case.

Figure 8

Figure 9. Time evolution of various diagnostics, as labelled, from $\tilde \tau =0$ to $0.173$ (the last reliable time). In the figure for $\textrm {d}{x}_{\it max }/ {\rm d}{t}$, 1-2-1 averages were repeated 8 times to remove most of the noise occurring around the maximum near $\tilde \tau =0.16$. Compare with figure 3 for the circular case.

Figure 9

Figure 10. Time evolution of the maximum wave slope $s(\tilde \tau )=|\partial \mathcal {A}/\partial {x}|_{max }$ together with a fit to $\sqrt {c/(\tilde \tau _c-\tilde \tau )}$ (a), and the function $f(\tilde \tau )=s^2(\tilde \tau _c-\tilde \tau )-c$ (b) which would be zero for a perfect fit. Compare with figure 4 for the circular case.

Figure 10

Figure 11. The estimated self-similar solution $\psi (\xi )$ (real part in cyan, imaginary part in magenta), together with scaled numerical profiles (see the text) at times $\tilde \tau =0.163$, $0.165$, $0.167$, $0.169$, $0.171$ and $0.173$ (real part in blue, imaginary part in red, with fading backwards in time). Compare with figure 7 for the circular case.

Figure 11

Figure 12. Time evolution of various diagnostics for a simulation starting from a weakly perturbed travelling wave having $\epsilon =0.1$ (see the text). See figure 3 for the analogous diagnostics in the case of a larger initial perturbation having $\epsilon =0.5$.

Figure 12

Figure 13. As in figure 12 but for a slightly larger disturbance amplitude, here $\epsilon =0.12$.

Figure 13

Figure 14. Late-time evolution of the relative errors in momentum $\mathsf {\textit P}$ and mass $\mathsf {\textit M}$. A subscript ‘0’ refers to their initial values. Prior to $\tilde \tau \approx 34$, errors are $\mathcal {O}(10^{-11})$ but likely smaller because the spectral coefficients $a_m$ were only saved to 11 digit accuracy.