期刊
PHYSICA D-NONLINEAR PHENOMENA
卷 238, 期 16, 页码 1625-1657出版社
ELSEVIER
DOI: 10.1016/j.physd.2009.05.005
关键词
Invariant manifolds; Nonautonomous dynamical systems; Hyperbolic trajectories; Material surfaces; Three-dimensional flows
We present a computational method for determining the geometry of a class of three-dimensional invariant manifolds in non-autonomous (aperiodically time-dependent) dynamical systems. The presented approach can be also applied to analyse the geometry of 3D invariant manifolds ill three-dimensional, time-dependent fluid flows. The invariance property of such manifolds requires that, at any fixed time, they are given by surfaces in R-3. We focus on a class of manifolds whose instantaneous geometry is given by orientable surfaces embedded in R-3. The presented technique can be employed, in particular, to compute codimension one (invariant) stable and unstable manifolds of hyperbolic trajectories in 3D non-autonomous dynamical systems which are crucial in the Lagrangian transport in a analysis. The same approach can also be used to determine evolution of an orientable 'material surface' fluid flow. These developments represent the first step towards a non-trivial 3D extension of the so-called lobe dynamics - a geometric, invariant-manifold-based framework which has been very successful in the analysis of Lagrangian transport in unsteady, two-dimensional fluid flows. in the developed algorithm, the instantaneous geometry of an invariant manifold is represented by an adaptively evolving triangular mesh with piecewise C-2 interpolating functions. The method employs an automatic mesh refinement which is Coupled with adaptive vertex redistribution. A variant of the advancing front technique is used for remeshing, whenever necessary. Such an approach allows for computationally efficient determination of highly convoluted, evolving geometry of codimension one invariant manifolds in unsteady three-dimensional flows. We show that the developed method is capable of providing detailed information on the evolving Lagrangian flow structure in three dimensions over long periods of time, which is crucial for a meaningful 3D transport analysis. (C) 2009 Elsevier B.V. All rights reserved.
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