The State of the Art in Flow Visualization: Dense and Texture-Based Techniques

Flow visualization has been a very attractive component of scientific visualization research for a long time. Usually very large multivariate datasets require processing. These datasets often consist of a large number of sample locations and several time steps. The steadily increasing performance of computers has recently become a driving factor for a reemergence in flow visualization research, especially in texture-based techniques. In this paper, dense, texture-based flow visualization techniques are discussed. This class of techniques attempts to provide a complete, dense representation of the flow field with high spatio-temporal coherency. An attempt of categorizing closely related solutions is incorporated and presented. Fundamentals are shortly addressed as well as advantages and disadvantages of the methods. Categories and Subject Descriptors (according to ACM CCS): I.3 [Computer Graphics]: visualization, flow visualization, computational flow visualizatio

Surface-based flow visualization

This is the author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Elsevier and can be found at: http://www.journals.elsevier.com/computers-and-graphics/.With increasing computing power, it is possible to process more complex fluid simulations. However, a gap between increasing\ud data size and our ability to visualize them still remains. Despite the great amount of progress that has been made in the field of\ud flow visualization over the last two decades, a number of challenges remain. Whilst the visualization of 2D flow has many good\ud solutions, the visualization of 3D flow still poses many problems. Challenges such as domain coverage, speed of computation, and\ud perception remain key directions for further research. Flow visualization with a focus on surface-based techniques forms the basis\ud of this literature survey, including surface construction techniques and visualization methods applied to surfaces. We detail our\ud investigation into these algorithms with discussions of their applicability and their relative strengths and drawbacks. We review the\ud most important challenges when considering such visualizations. The result is an up-to-date overview of the current state-of-the-art\ud that highlights both solved and unsolved problems in this rapidly evolving branch of research

A Phase Field Model for Continuous Clustering on Vector Fields

A new method for the simplification of flow fields is presented. It is based on continuous clustering. A well-known physical clustering model, the Cahn Hilliard model, which describes phase separation, is modified to reflect the properties of the data to be visualized. Clusters are defined implicitly as connected components of the positivity set of a density function. An evolution equation for this function is obtained as a suitable gradient flow of an underlying anisotropic energy functional. Here, time serves as the scale parameter. The evolution is characterized by a successive coarsening of patterns-the actual clustering-during which the underlying simulation data specifies preferable pattern boundaries. We introduce specific physical quantities in the simulation to control the shape, orientation and distribution of the clusters as a function of the underlying flow field. In addition, the model is expanded, involving elastic effects. In the early stages of the evolution shear layer type representation of the flow field can thereby be generated, whereas, for later stages, the distribution of clusters can be influenced. Furthermore, we incorporate upwind ideas to give the clusters an oriented drop-shaped appearance. Here, we discuss the applicability of this new type of approach mainly for flow fields, where the cluster energy penalizes cross streamline boundaries. However, the method also carries provisions for other fields as well. The clusters can be displayed directly as a flow texture. Alternatively, the clusters can be visualized by iconic representations, which are positioned by using a skeletonization algorithm.

[Activity of Institute for Computer Applications in Science and Engineering]

This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, fluid mechanics, and computer science

Sand transverse dune aerodynamics: 3D Coherent Flow Structures from a computational study

The engineering interest about dune fields is dictated by the their interaction with a number of human infrastructures in arid environments. Sand dunes dynamics is dictated by wind and its ability to induce sand erosion, transport and deposition. A deep understanding of dune aerodynamics serves then to ground effective strategies for the protection of human infrastructures from sand, the so-called sand mitigation. Because of their simple geometry and their frequent occurrence in desert area, transverse sand dunes are usually adopted in literature as a benchmark to investigate dune aerodynamics by means of both computational or experimental approaches, usually in nominally 2D setups. The present study aims at evaluating 3D flow features in the wake of a idealised transverse dune, if any, under different nominally 2D setup conditions by means of computational simulations and to compare the obtained results with experimental measurements available in literature

On Simulating Tip-Leakage Vortex Flow to Study the Nature of Cavitation Inception

Cavitation is detrimental to the performance of ships and submarines, causing noise, erosion, and vibration. This study seeks to understand cavitation inception and delay on a typical ducted propulsor by utilizing the SimCenter\u27s unstructured simulation and design system: U2NCLE. Specifically, three fundamental questions are addressed: 1. What are the macroscale flow physics causing cavitation inception? 2. How does cavitation inception scale with Reynolds number? 3. How can tip-leakage vortex cavitation inception be suppressed? To study the physics of cavitation inception, a ducted propulso simulation is developed and extensively validated with experimental results. The numerical method is shown to agree very well with experimental measurements made in the vortex core. It was discovered that the interaction of the leakage and trailing edge vortices cause the pressure to drop to a local minimum, providing ideal conditions for inception to occur. However, experimental observation shows that inception does not occur at the minimum pressure location, but rather at the point where the two vortices completely coalesce. At the point of coalescence, the simulation reveals that the streamwise core velocity decelerates, causing the air nuclei to stretch and burst. A Reynolds number scaling analysis is performed for the minimum pressure and maximum velocity in the vortex core. First, the numerical method is validated on a flate plate at various Reynolds numbers to assess the ability of typical turbulence models to predict Reynolds numbers ranging from one million to one billion. This scaling analysis methodology is then applied to the propulsor simulation, revealing that the minimum pressure in the vortex core is much less dependent on Reynolds number than was previously hypothesized. Lastly, to investigate means of delaying cavitation inception, the propulsor is parameterized and studied using design optimization theory. Concepts of vortex alleviation evident in nature are used to suggest suitable parameterizations. Also, dimension reduction is used to reduced the number of design variables. Finally, the concepts are implemented, evaluated, and shown to completely decouple the two vortices causing cavitation inception. Moreover, the minimum pressure in the vortex core is significantly increased