Minimal seeds for shear flow turbulence: using nonlinear transient growth to touch the edge of chaos

TL;DR

This paper introduces a variational approach to identify minimal disturbances that can trigger turbulence in shear flows, using nonlinear transient growth analysis to find the 'minimal seed' for transition.

Contribution

It develops a novel variational method to determine the smallest disturbance amplitude capable of inducing turbulence in shear flows, extending linear transient growth concepts to nonlinear regimes.

Findings

The variational problem converges below the transition threshold.

The optimal disturbance acts as the 'minimal seed' for turbulence.

The approach applies to pipe flow and identifies critical perturbations.

Abstract

We propose a general strategy for determining the minimal finite amplitude isturbance to trigger transition to turbulence in shear flows. This involves constructing a variational problem that searches over all disturbances of fixed initial amplitude, which respect the boundary conditions, incompressibility and the Navier--Stokes equations, to maximise a chosen functional over an asymptotically long time period. The functional must be selected such that it identifies turbulent velocity fields by taking significantly enhanced values compared to those for laminar fields. We illustrate this approach using the ratio of the final to initial perturbation kinetic energies (energy growth) as the functional and the energy norm to measure amplitudes in the context of pipe flow. Our results indicate that the variational problem yields a smooth converged solution providing the amplitude is below the threshold amplitude for transition. This optimal is the nonlinear analogue of the well-studied (linear) transient growth optimal. At and above this threshold, the optimising search naturally seeks out disturbances that trigger turbulence by the end of the period, and convergence is then practically impossible. The first disturbance found to trigger turbulence as the amplitude is increased identifies the `minimal seed' for the given geometry and forcing (Reynolds number). We conjecture that it may be possible to select a functional such that the converged optimal below threshold smoothly converges to the minimal seed at threshold. This seems at least approximately true for our choice of energy growth functional and the pipe flow geometry chosen here.