Transport and stirring induced by vortex formation

The purpose of this study is to analyse the transport and stirring of fluid that occurs owing to the formation and growth of a laminar vortex ring. Experimental data was collected upstream and downstream of the exit plane of a piston-cylinder apparatus by particle-image velocimetry. This data was used to compute Lagrangian coherent structures to demonstrate how fluid is advected during the transient process of vortex ring formation. Similar computations were performed from computational fluid dynamics (CFD) data, which showed qualitative agreement with the experimental results, although the CFD data provides better resolution in the boundary layer of the cylinder. A parametric study is performed to demonstrate how varying the piston-stroke length-to-diameter ratio affects fluid entrainment during formation. Additionally, we study how regions of fluid are stirred together during vortex formation to help establish a quantitative understanding of the role of vortical flows in mixing. We show that identification of the flow geometry during vortex formation can aid in the determination of efficient stirring. We compare this framework with a traditional stirring metric and show that the framework presented in this paper is better suited for understanding stirring/mixing in transient flow problems. A movie is available with the online version of the paper

Volumetric visualization of 3D data

In recent years, there has been a rapid growth in the ability to obtain detailed data on large complex structures in three dimensions. This development occurred first in the medical field, with CAT (computer aided tomography) scans and now magnetic resonance imaging, and in seismological exploration. With the advances in supercomputing and computational fluid dynamics, and in experimental techniques in fluid dynamics, there is now the ability to produce similar large data fields representing 3D structures and phenomena in these disciplines. These developments have produced a situation in which currently there is access to data which is too complex to be understood using the tools available for data reduction and presentation. Researchers in these areas are becoming limited by their ability to visualize and comprehend the 3D systems they are measuring and simulating

Computational approaches for tortuosity determination in 3D structures

Tortuosity is a parameter of key importance to study transport properties in either solid phase (thermal, electrical) and/or fluid phase (acoustics, mass/heat flow, etc). This structure-related parameter expresses mathematically the real pathway distance in comparison to the straightest one when travelling along certain direction through the material’s internal structure. Tortuosity determination is not reliable in 2D and needs to be computed in 3D structures. However, computation of 3D algorithms in complex structures is not an easy task. This work discusses two methodological approaches based on their correspondent computation algorithms working on a collection of 3D tomography data sets of different cellular materials. The tortuosity analysis is carried out in both solid and fluid phases. Results will be compared and correlated. A detailed discussion in terms of these models and the materials will be given

Topological Chaos in a Three-Dimensional Spherical Fluid Vortex

In chaotic deterministic systems, seemingly stochastic behavior is generated by relatively simple, though hidden, organizing rules and structures. Prominent among the tools used to characterize this complexity in 1D and 2D systems are techniques which exploit the topology of dynamically invariant structures. However, the path to extending many such topological techniques to three dimensions is filled with roadblocks that prevent their application to a wider variety of physical systems. Here, we overcome these roadblocks and successfully analyze a realistic model of 3D fluid advection, by extending the homotopic lobe dynamics (HLD) technique, previously developed for 2D area-preserving dynamics, to 3D volume-preserving dynamics. We start with numerically-generated finite-time chaotic-scattering data for particles entrained in a spherical fluid vortex, and use this data to build a symbolic representation of the dynamics. We then use this symbolic representation to explain and predict the self-similar fractal structure of the scattering data, to compute bounds on the topological entropy, a fundamental measure of mixing, and to discover two different mixing mechanisms, which stretch 2D material surfaces and 1D material curves in distinct ways.Comment: 14 pages, 11 figure

Survey of long-term durability of fiberglass reinforced plastic structures

Included are fluid containment vessels, marine structures, and aircraft components with up to 19 years of service. Correlations were obtained for the variation of static fatigue strength, cyclic fatigue strength, and residual burst strength for pressure vessels. In addition, data are presented for the effects of moisture on strength retention. Data variations were analyzed, and relationships and implications for testing are discussed. Change in strength properties for complete structures was examined for indications of the effects of environmental conditions such as moisture and outdoor exposure (ultraviolet radiation, weathering) on long term durability