We present a new visualization method for 2d flows which allows us to combine multiple data values in an image for simultaneous viewing. We utilize concepts from oil painting, art, and design as introduced in [1] to examine problems within fluid mechanics. We use a combination of discrete and continuous visual elements arranged in multiple layers to visually represent the data. The representations are inspired by the brush strokes artists apply in layers to create an oil painting. We display commonly visualized quantities such as velocity and vorticity together with three additional mathematically derived quantities: the rate of strain tensor (defined in section 4), and the turbulent charge and turbulent current (defined in section 5). We describe the motivation for simultaneously examining these quantities and use the motivation to guide our choice of visual representation for each particular quantity. We present visualizations of three flow examples and observations concerning some o...

We present a new algorithm for identifying the distribution of different material types in volumetric datasets such as those produced with Magnetic Resonance Imaging (MRI) or Computed Tomography (CT). Because we allow for mixtures of materials and treat voxels as regions, our technique reduces errors that other classification techniques can create along boundaries between materials and is particularly useful for creating accurate geometric models and renderings from volume data. It also has the potential to make volume measurements more accurately and classifies noisy, low-resolution data well. There are two unusual aspects to our approach. First, we assume that, due to partial-volume effects, or blurring, voxels can contain more than one material, e.g., both muscle and fat; we compute the relative proportion of each material in the voxels. Second, we incorporate information from neighboring voxels into the classification process by reconstructing a continuous function, ##x#, from the...

Art in particular painting, has had clear impacts on the style, techniques, and processes of scientific visualization. Artists strive to create visual

The partial volume effect is an imaging artefact associated with tomographic biomedical imaging data. Three-dimensional volumetric data points (voxels) enclose finite sized regions so that they may contain a mixture of signals which are then known as partial volume voxels. The limited spatial resolution of tomographic biomedical imaging data, due to the complex biomedical image acquisition processes, often results in large numbers of these partial volume voxels. Clinical applications of biomedical imaging data often require accurate estimates of tissues or metabolic activity, where many voxels in the data are partial volume voxels. Therefore accurate modelling of the partial volume effect can be very important for such quantitative applications. The probabilistic models discussed and presented in this thesis provide a generic mathematically consistent framework in which the partial volume effect is modelled. Novel developments include an improved model of an intensity and gradient magnitude feature space to model the PV effect; a novel analytically derived formulation of the ground truth (prior) description of the PV effect; a novel gradient controlled spatially regulated classifier that utilises Markov Chain Monte Carlo simulations; and a fully automatic

Scientific visualization not only expands our understanding of fluid flow phenomena by allowing us to examine the evolution of different flow quantities, but also it can be used as a catalyst for the development of mathematical models which describe the time evolution of complex flows. We believe that the simultaneous examination of multiple flow quantities can provided a better understanding of the underlying processes of fluid flow. This project report describes the work of three projects in which I have participated. All research contained herein had as its end goal the investigation of techniques for visualizing fluid flow data. The first project sought to use concepts from painting for visualizing two dimensional flows. For the two dimensional flow examples, we present visualizations of three flow examples and observations concerning some of the physical relationships made apparent by the multi-valued data display technique that we employed. The second and third projects had as a goal the use of interactive immersive environments for studying three dimensional flows. For the three dimensional flow examples, we describe the development of two components sufficient for interactive immersion in the Cave. The second project was the implementation of DOGL, an OpenGL-based library for distributed rendering systems used for distributing geometry for display on our four-wall immersive display system. The third project was the implementation of a C++ class within the Jot graphics system for visualizing fluid flow data produced by N εκT αr. An arterial bypass flow simulation provides a case study for the combination of DOGL and N εκT αr simulation data for visualizing fluid flow phenomena in 3D using an interactive immersive viewing environment.