be encountered in practice; chaotic flows, while capturing We study, by dynamic modeling, aggregation of compact and some of the aspects of turbulent flows, are still amenable to fractal structures in model flows typifying regular and chaotic in-depth studies.) Two aggregation scenarios are considered: regimes. Emphasis is placed on two-dimensional flows but threein (i) the clusters retain a compact geometry-forming disks dimensional systems are considered as well. The goal is to put and spheres-whereas in (ii) fractal structures are formed.
into evidence flow effects-kinetics of aggregation, cluster size
The primary focus of (i) is kinetics and self-similarity of distribution, and structure of aggregates-with the long-range size distributions, while the main focus of (ii) is the fractal goal of manipulating flows to tailor the structure of clusters. Nustructure of the clusters and its dependence on the flow.
merical simulations show that the average cluster size of compact
The ultimate goal of this work is to put into evidence flow clusters grows algebraically, while the average cluster size of fractal clusters grows exponentially; companion mathematical argu-effects-cluster size distribution and structure of aggrements are used to describe the initial growth of average cluster gates-with the long-range objective of manipulating flows size and polydispersity. It is found that when the system is well to tailor the structure of clusters.
mixed and the capture radius is independent of mass, the polydis-
The paper is organized as follows. We first present a brief persity is constant for long times and the cluster size distribution is review of scaling concepts used throughout the paper as well self-similar. Furthermore, our simulations indicate that the fractal as some of relevant literature in aggregation. This is followed nature of the clusters is dependent upon the mixing. α§ 1996 Academic by a description of the flow system and by an overview Press, Inc.