Entropy Time Evolution In A Twin-flight Single-screw Extruder And Its Relationship To Chaos

Chaotic Manifold Analysis of Four-Screw Extruders Based on Lagrangian Coherent Structures

The four-screw extruder (FSE) is a novel equipment for polymer processing. In this paper, from a new viewpoint of Lagrangian coherent structures (LCS), two-dimensional fluid transport and chaotic mixing characteristics within three kinds of novel industrial FSEs are explored based on LCS to better understand the flow and mixing natures in the FSEs. Firstly, based on the finite-time invariant manifold theory, the finite-time Lyapunov exponent (FTLE) and LCS of FSEs are calculated by considering the different initial time. Hyperbolic LCSs from the FTLE maps are adopted to identify chaotic mixing manifolds in FSEs. Moreover, particle tracking and Poincaré sections are used to illustrate the different fluid motions in the above three isolated regions. Finally, the effects of relative rotating directions and layout of four screws on the chaotic manifolds in FESs are discussed in order to enhance local mixing performance. Furthermore, quantitative mixing measures, such as the segregation scale, logarithmic of stretching, and mean-time mixing efficiency are employed to compare the mixing efficiencies in three kinds of FSEs. The results show that the relative rotating directions and positions of four screws can change the chaotic manifolds and increase mixing performance in local poor mixing regions. FTLE and LCS analysis are helpful to better understand the chaotic mixing nature in the novel screw extruders.

Transport phenomena in chaotic laminar flows

In many important chemical processes, the laminar flow regime is inescapable and defines the performance of reactors, separators, and analytical instruments. In the emerging field of microchemical process or lab-on-a-chip, this constraint is particularly rigid. Here, we review developments in the use of chaotic laminar flows to improve common transport processes in this regime. We focus on four: mixing, interfacial transfer, axial dispersion, and spatial sampling. Our coverage demonstrates the potential for chaos to improve these processes if implemented appropriately. Throughout, we emphasize the usefulness of familiar theoretical models of transport for processes occurring in chaotic flows. Finally, we point out open challenges and opportunities in the field.