Multi-touch 3D Exploratory Analysis of Ocean Flow Models

Modern ocean flow simulations are generating increasingly complex, multi-layer 3D ocean flow models. However, most researchers are still using traditional 2D visualizations to visualize these models one slice at a time. Properly designed 3D visualization tools can be highly effective for revealing the complex, dynamic flow patterns and structures present in these models. However, the transition from visualizing ocean flow patterns in 2D to 3D presents many challenges, including occlusion and depth ambiguity. Further complications arise from the interaction methods required to navigate, explore, and interact with these 3D datasets. We present a system that employs a combination of stereoscopic rendering, to best reveal and illustrate 3D structures and patterns, and multi-touch interaction, to allow for natural and efficient navigation and manipulation within the 3D environment. Exploratory visual analysis is facilitated through the use of a highly-interactive toolset which leverages a smart particle system. Multi-touch gestures allow users to quickly position dye emitting tools within the 3D model. Finally, we illustrate the potential applications of our system through examples of real world significance

An Empirical Evaluation of Visual Cues for 3D Flow Field Perception

Three-dimensional vector fields are common datasets throughout the sciences. They often represent physical phenomena that are largely invisible to us in the real world, like wind patterns and ocean currents. Computer-aided visualization is a powerful tool that can represent data in any way we choose through digital graphics. Visualizing 3D vector fields is inherently difficult due to issues such as visual clutter, self-occlusion, and the difficulty of providing depth cues that adequately support the perception of flow direction in 3D space. Cutting planes are often used to overcome these issues by presenting slices of data that are more cognitively manageable. The existing literature provides many techniques for visualizing the flow through these cutting planes; however, there is a lack of empirical studies focused on the underlying perceptual cues that make popular techniques successful. The most valuable depth cue for the perception of other kinds of 3D data, notably 3D networks and 3D point clouds, is structure-from-motion (also called the Kinetic Depth Effect); another powerful depth cue is stereoscopic viewing, but none of these cues have been fully examined in the context of flow visualization. This dissertation presents a series of quantitative human factors studies that evaluate depth and direction cues in the context of cutting plane glyph designs for exploring and analyzing 3D flow fields. The results of the studies are distilled into a set of design guidelines to improve the effectiveness of 3D flow field visualizations, and those guidelines are implemented as an immersive, interactive 3D flow visualization proof-of-concept application

Imaging sediment structure: the emerging use of Magnetic Resonance Imaging (MRI) for 3D analysis of sediment structures and internal flow processes

Magnetic Resonance Imaging (MRI) can be used for 3D analysis of small-scale porous media structure and internal flow-related processes. It offers notable advantages over traditional sediment sampling (e.g. cores or surface-based scanning) as it is capable of high spatio-temporal resolution of the full 3D volume, including the sub-surface. Similarly, compared to X-Ray tomography, the extensive catalogue of MR pulse sequences typically provides: faster capture for imaging dynamic fluid processes; greater flexibility in resolving chemical species or tracers; and a safer radiation-free methodology. To demonstrate the relevance of this technique in geomorphological research, three exemplar applications are described: porous media structure of gravel bed rivers; measurements of fluid processes within aquifer pores and fractures; and, concentration mapping of contaminants through sand/gravel frameworks. Whilst, this emerging technique offers significant potential for visualizing many other ‘black-box’ processes important to the wider discipline, attention is afforded to discussion of the present constraints of the technique in field-based analysis

Streamsurface Smoke Effect for Visualizing Dragon Fly CFD Data in Modern OpenGL with an Emphasis on High Performance

Visualizing 3D, time dependent velocity vector fields is a difficult topic. Streamlines can be used to visualize 3D vector fields. A smoke effect where the streamline is faded out as time progresses can provide a better visualization of a time dependent flow. This work uses modern OpenGL to create a smoke trail effect with streamsurfaces in the dragon fly data set. Many aspects affecting performance are tested to determine the best options or approach

Elastic turbulence generates anomalous flow resistance in porous media

Diverse processes rely on the viscous flow of polymer solutions through porous media. In many cases, the macroscopic flow resistance abruptly increases above a threshold flow rate in a porous medium---but not in bulk solution. The reason why has been a puzzle for over half a century. Here, by directly visualizing the flow in a transparent 3D porous medium, we demonstrate that this anomalous increase is due to the onset of an elastic instability. We establish that the energy dissipated by the unstable flow fluctuations, which vary across pores, generates the anomalous increase in flow resistance through the entire medium. Thus, by linking the pore-scale onset of unstable flow to macroscopic transport, our work provides generally-applicable guidelines for predicting and controlling polymer solution flows

Visualizing 2D Flows with Animated Arrow Plots

Flow fields are often represented by a set of static arrows to illustrate scientific vulgarization, documentary film, meteorology, etc. This simple schematic representation lets an observer intuitively interpret the main properties of a flow: its orientation and velocity magnitude. We propose to generate dynamic versions of such representations for 2D unsteady flow fields. Our algorithm smoothly animates arrows along the flow while controlling their density in the domain over time. Several strategies have been combined to lower the unavoidable popping artifacts arising when arrows appear and disappear and to achieve visually pleasing animations. Disturbing arrow rotations in low velocity regions are also handled by continuously morphing arrow glyphs to semi-transparent discs. To substantiate our method, we provide results for synthetic and real velocity field datasets

Fine-grained traffic state estimation and visualisation

Tools for visualising the current traffic state are used by local authorities for strategic monitoring of the traffic network and by everyday users for planning their journey. Popular visualisations include those provided by Google Maps and by Inrix. Both employ a traffic lights colour-coding system, where roads on a map are coloured green if traffic is flowing normally and red or black if there is congestion. New sensor technology, especially from wireless sources, is allowing resolution down to lane level. A case study is reported in which a traffic micro-simulation test bed is used to generate high-resolution estimates. An interactive visualisation of the fine-grained traffic state is presented. The visualisation is demonstrated using Google Earth and affords the user a detailed three-dimensional view of the traffic state down to lane level in real time