In chaos theory and fluid dynamics, chaotic mixing is a process by which flow tracers develop into complex fractals under the action of a fluid flow. The flow is characterized by an exponential growth of fluid filaments.[1] Even very simple flows, such as the blinking vortex, or finitely resolved wind fields can generate exceptionally complex patterns from initially simple tracer fields.[2]
The phenomenon is still not well understood and is the subject of much current research.
http://en.wikipedia.org/wiki/Chaotic_mixing
http://www.lactamme.polytechnique.fr/descripteurs/Galerie_GeneralitiesVisualization.FV.html
IMO, when this is combined with State-Of-The-Art Applied Signal Theory (wavelet transforms), a more realistic view of the universe will result... The phrase 'dynamical dimension' may even catch on...
Dynamical characterization of mixed fractal structures
Luiz Bevilacqua and Marcelo M. Barros
Vol. 6 (2011), No. 1-4, 51–69
DOI: 10.2140/jomms.2011.6.51
Abstract
We present a new technique to determine the fractal or self-similarity dimension of a sequence of curves. The geometric characterization of the sequence is obtained from the mechanical properties of harmonic oscillators with the same shape of the terms composing the given sequence of curves. The definition of “dynamical dimension” is briefly introduced with the help of simple examples. The theory is proved to be valid for a particular type of curves as those of the Koch family. The method is applied to more complex plane curves obtained by superposing two generators of the Koch family with different fractal dimensions. It is shown that this structure is composed by two series of objects one of which is fractal and the other which is not rigorously a fractal sequence but approaches asymptotically a fractal object. The notion of quasifractal structures is introduced. The results are shown to provide good information about the structure formation. It is shown that the dynamical dimension can identify randomness for certain fractal curves.