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Computing heteroclinic orbits using adjoint-based methods

Published online by Cambridge University Press:  12 November 2018

M. Farano*
Affiliation:
DMMM, Politecnico di Bari, Via Re David 200, 70125 Bari, ItalyDynFluid Laboratory, Arts et Metiers ParisTech, 151 Bd de l’Hopital, 75013 Paris, FranceECPS, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
S. Cherubini*
Affiliation:
DMMM, Politecnico di Bari, Via Re David 200, 70125 Bari, Italy
J.-C. Robinet
Affiliation:
DynFluid Laboratory, Arts et Metiers ParisTech, 151 Bd de l’Hopital, 75013 Paris, France
P. De Palma
Affiliation:
DMMM, Politecnico di Bari, Via Re David 200, 70125 Bari, Italy
T. M. Schneider*
Affiliation:
ECPS, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland

Abstract

Transitional turbulence in shear flows is supported by a network of unstable exact invariant solutions of the Navier–Stokes equations. The network is interconnected by heteroclinic connections along which the turbulent trajectories evolve between invariant solutions. While many invariant solutions in the form of equilibria, travelling waves and periodic orbits have been identified, computing heteroclinic connections remains a challenge. We propose a variational method for computing orbits dynamically connecting small neighbourhoods around equilibrium solutions. Using local information on the dynamics linearized around these equilibria, we demonstrate that we can choose neighbourhoods such that the connecting orbits shadow heteroclinic connections. The proposed method allows one to approximate heteroclinic connections originating from states with multi-dimensional unstable manifold and thereby provides access to heteroclinic connections that cannot easily be identified using alternative shooting methods. For plane Couette flow, we demonstrate the method by recomputing three known connections and identifying six additional previously unknown orbits.

Information

Type
JFM Rapids
Copyright
© 2018 Cambridge University Press 
Figure 0

Figure 1.Sketch describing the CHELA algorithm: the initial condition and the related trajectory towards the final EQ change after updating the time $T$ (dashed lines). The algorithm stops when $T$ is sufficiently large to lead the flow field close enough to the final state (solid line).

Figure 1

Table 1.Computed heteroclinic connections for $Re=400$ and corresponding symmetry subspaces. The dimension of the unstable manifold of the initial equilibrium ($EQ_{out}$) is $d(W^{u})$, while $d(W_{S}^{u})$ is the dimension of the intersection of the unstable manifold with the symmetry-invariant subspace reported here for the initial and final equilibrium ($EQ_{in}$). The last column provides the passage time for the different orbits with shell around the initial state of radius $r_{out}=10^{-4}$ ($r_{out}=10^{-3}$ for underlined ones).

Figure 2

Figure 2.(a) Distances of the velocity field $\boldsymbol{u}(t)$ to the final equilibrium $\boldsymbol{u}_{EQ_{in}}$ (continuous line) and to the initial one $\boldsymbol{u}_{EQ_{out}}$ (dashed line) along three heteroclinic connections found by Halcrow et al. (2009) versus time. (b) Distances to the final equilibrium $\boldsymbol{u}_{EQ_{in}}$ for the new computed heteroclinic connections (continuous lines). The dashed line represents the highest residual value for the heteroclinic connections computed in Halcrow et al. (2009). The L2-norm of the considered equilibria ranges from 0.1259 to 0.4049. (Gibson et al.2009).

Figure 3

Figure 3.Time evolution of contributions in the stable and unstable subspaces of $EQ_{out}$ during the initial part of the trajectory $EQ5\rightarrow EQ1$. (a) L2-norms $\Vert \boldsymbol{u}^{\prime \,s/u}\Vert _{2}$ of the projections onto the unstable ($\boldsymbol{u}^{\prime \,u}$, solid line) and stable ($\boldsymbol{u}^{\prime \,s}$, dashed line) subspace. The difference between the linearized and the full nonlinear evolution $\unicode[STIX]{x1D702}=(\Vert \boldsymbol{u}_{lin}^{\prime }(t)-\boldsymbol{u}^{\prime }(t)\Vert _{2}^{2}/\Vert \boldsymbol{u}_{lin}^{\prime }(t)\Vert _{2}^{2})$ (dotted line, right axis) characterizes the deviation of the invariant manifolds from the approximating linear subspaces due to manifold curvature in the direction of the trajectory. (b) Relative contribution measured in terms of relative energy in the unstable (solid line) and stable (dashed line) subspace. Vertical red dotted lines indicates when the relative contribution of the stable subspace $E^{s}(t)/E(t)$ drops below 1 %. Vertical blue dotted line indicates when the difference between the linearized and the full nonlinear evolution $\unicode[STIX]{x1D702}$ reaches 1 %.

Figure 4

Figure 4.State-space projection (Gibson et al.2008) of the orbit connecting $EQ5\rightarrow EQ1$ (blue) and $EQ4\rightarrow EQ1$ (green), for which the dimension of the intersection is three and two, respectively. For a specific connection, changing the energy shell around the initial equilibrium from $E_{0_{out}}=10^{-6}$ (solid line) to $E_{0_{out}}=10^{-8}$ (dashed line) results in finding different orbits. For those connections for which the dimension of the intersection is one, g.e. $EQ4\rightarrow EQ3$ (cyan), the algorithm finds the only existing connection.

Figure 5

Figure 5.(a) Projection of the heteroclinic connections onto the energy input, $I$, and the dissipation rate, $D$, normalized by their value in the laminar flow. (b) State-space projection onto the 3D orthonormal basis $\boldsymbol{a}_{1,2,3}$ of all the computed heteroclinic connections. Colours are the same as in figure 2.

Farano et al. supplementary movie

All 9 heteroclinic connections. (Left) State-space projection onto the 3D orthonormal basis. Symbols represent equilibria. (Right) Streamwise averaged velocity field, color represent streamwise velocity (blue negative, red positive) and arrows represent in-plane velocity.

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