Many different studies of magnetism models have presented theories on energy minimization. These studies, however, do not give a visual confirmation of what is occurring during minimization. In this paper, we describe a model and visualization system designed to illustrate the principles of energy minimization in magnetic systems.

This paper describes a "nifty" programming assignment that requires students to use files, loops, and if-statements to implement an algorithm that will remove the red-eye artifact from an image. The assignment is most suitable for a CS1 course, but could be altered to accommodate a CS0 or CS2 course.

The analysis of data that consists of multiple vector fields can be greatly facilitated by the simultaneous visualization of the vector fields. An effective visualization must accurately reflect the key physical structures of the fields in a way that does not allow for an unintended bias towards one distribution. While there are several effective techniques to visualize a single vector field through equally-spaced streamlines, applying these techniques to individual vector fields and combining them in a single image yields several undesirable artifacts. In this paper, we present strategies for the effective visualization of two vector fields through the use of streamlines.

This paper describes a series of exercises and assignments suggested for an introductory computer organization or computer architecture course. The primary objective of these exercises is to engage a class of students by introducing the practical, hands-on application of assembling a computer by selecting and purchasing individual components.

Our group is involved in magnetohydrodynamic simulations that track the time and space evolution of the full 3D velocity and magnetic vector fields, plus fundamental scalar fields such as density and pressure. To accomplish the complex visualization of these jets, we developed FieldVis, a simulation tool that focuses primarily on representing 3D vector and scalar fields.

The use of textures provides a rich and diverse set of possibilities for the visualization of flow data. We present methods designed to produce oriented and controlled textures that accurately reflect the complex patterns that occur in vector field visualizations.

Strategies for effectively visualizing co-located 2D vector fields enable understanding of key physical structures of one vector field within the context of a related vector field. We describe the range of effects possible by combining several existing flow visualization techniques for analyzing multiple vector fields.

The goal through this work is to enable researchers to obtain a succinct, meaningful visual summary of the contents of a dataset that consists of multiple, coincident variables. This is accomplished through providing techniques that allow the creation of an image in which the important features of multiple scalar or vector fields can be understood both independently and in the context of the other fields.

We discuss several techniques to display scalar distributions within an image depicting a 2D flow field. We address how contrast and luminance can effectively be used, present modifications to an algorithm that uses dense streamlines to represent flow direction, and present a new technique, based on embossing, to encode the out-of-plane component of a 3D vector field over a 2D domain.

The vector field in any visualization is dependent on the relative velocity of the observer. Traditionally, the average value of the streamwise component of the global vector field is calculated and subtracted from each vector. However, the resulting LIC image, critical points, and vector field features are greatly influenced by the magnitude of the value subtracted from the streamwise velocity. Examples of this phenomenon are shown here.

In this paper we offer several new insights and techniques for effectively using color and texture to simultaneously convey information about multiple 2D scalar and vector distributions, in a way that facilitates allowing each distribution to be understood both individually and in the context of one or more of the other distributions.

Stereo PIV datasets contain three dimensional information over a plane from which multiple quantities can be derived at each point. The task of visualizing these different parameters simultaneously is challenging and this inhibits our ability to analyze and derive firm conclusions about the physics of the flow. In this paper, we discuss several different ways in which the primary quantities can be viewed simultaneously in the same image.

We present several techniques to effectively visualize multi-valued flow data using contrast, color, 3D visualization, and texture. The ultimate goal through this work is to enable researchers to obtain a succinct, meaningful visual summary of the contents of a dataset through providing techniques that allow the creation of images in which the important features of multiple scalar distributions can be understood both independently and in the context of multiple other distributions.

The objective of this study is to apply Stereo PIV in streamwise-spanwise planes to measure three-dimensional velocity fields and to develop methods for the identification of typical flow structures. These methods can then be applied to quantify the strength, size, and frequency of various structures and therefore to examine the existence, nature, and symmetry of hairpin-like vortices and vortex packets.

We describe an interactive toolkit used to perform comparative analysis of two or more data sets arising from numerical simulations. An industrial application aimed at designing an efficient, low-NOx burner for industrial furnaces is used. Critical insights are obtained by interactively adjusted color maps, data culling, and data manipulation. New paradigms for scaling small values in the data comparison technique are described. The display device used for this application was the CAVE virtual reality theater, and we describe the user interface to the visualization toolkit and the benefits of immersive 3D visualization for comparative analysis.