Towards Automatic Feature-based Visualization

Visualizations are well suited to communicate large amounts of complex data. With increasing resolution in the spatial and temporal domain simple imaging techniques meet their limits, as it is quite difficult to display multiple variables in 3D or analyze long video sequences. Feature detection techniques reduce the data-set to the essential structures and allow for a highly abstracted representation of the data. However, current feature detection algorithms commonly rely on a detailed description of each individual feature. In this paper, we present a feature-based visualization technique that is solely based on the data. Using concepts from computational mechanics and information theory, a measure, local statistical complexity, is defined that extracts distinctive structures in the data-set. Local statistical complexity assigns each position in the (multivariate) data-set a scalar value indicating regions with extraordinary behavior. Local structures with high local statistical complexity form the features of the data-set. Volume-rendering and iso-surfacing are used to visualize the automatically extracted features of the data-set. To illustrate the ability of the technique, we use examples from diffusion, and flow simulations in two and three dimensions

Information-theoretic Analysis of Unsteady Data

The temporal evolution of scientific data is of high relevance in many fields of application. Understanding the dynamics over time is a crucial step in understanding the underlying system. The availability of large scale parallel computers has led to a finer and finer resolution of simulation data, which makes it difficult to detect all relevant changes of the system by watching a video or a set of snapshots. In recent years, algorithms for the automatic detection of coherent temporal structures have been developed that allow for an identification of interesting areas and time steps in unsteady data. With such techniques, the user can be guided to interesting subsets of the data or a video can be automatically created that does not occlude relevant aspects of the simulation. In this paper, we give an overview over the different techniques, show how their combination helps to gain deeper insight and look at different directions for further improvement. Two CFD simulations are used to illustrate the different techniques

Reducing Occlusion in Cinema Databases through Feature-Centric Visualizations

In modern supercomputer architectures, the I/O capabilities do not keep up with the computational speed. Image-based techniques are one very promising approach to a scalable output format for visual analysis, in which a reduced output that corresponds to the visible state of the simulation is rendered in-situ and stored to disk. These techniques can support interactive exploration of the data through image compositing and other methods, but automatic methods of highlighting data and reducing clutter can make these methods more effective. In this paper, we suggest a method of assisted exploration through the combination of feature-centric analysis with image space techniques and show how the reduction of the data to features of interest reduces occlusion in the output for a set of example applications

Visualization of Input Parameters for Stream and Pathline Seeding

Uncertainty arises in all stages of the visualization pipeline. However, the majority of flow visualization applications convey no uncertainty information to the user. In tools where uncertainty is conveyed, the focus is generally on data, such as error that stems from numerical methods used to generate a simulation or on uncertainty associated with mapping visualiza-tion primitives to data. Our work is aimed at another source of uncertainty - that associated with user-controlled input param-eters. The navigation and stability analysis of user-parameters has received increasing attention recently. This work presents an investigation of this topic for flow visualization, specifically for three-dimensional streamline and pathline seeding. From a dynamical systems point of view, seeding can be formulated as a predictability problem based on an initial condition. Small perturbations in the initial value may result in large changes in the streamline in regions of high unpredictability. Analyzing this predictability quantifies the perturbation a trajectory is subjugated to by the flow. In other words, some predictions are less certain than others as a function of initial conditions. We introduce novel techniques to visualize important user input parameters such as streamline and pathline seeding position in both space and time, seeding rake position and orientation, and inter-seed spacing. The implementation is based on a metric which quantifies similarity between stream and pathlines. This is important for Computational Fluid Dynamics (CFD) engineers as, even with the variety of seeding strategies available, manual seeding using a rake is ubiquitous. We present methods to quantify and visualize the effects that changes in user-controlled input parameters have on the resulting stream and pathlines. We also present various visualizations to help CFD scientists to intuitively and effectively navigate this parameter space. The reaction from a domain expert in fluid dynamics is also reported. - See more at: http://thesai.org/Publications/ViewPaper?Volume=6&Issue=4&Code=IJACSA&SerialNo=17#sthash.PNlUBslJ.dpu

Aeronautical engineering: A continuing bibliography with indexes (supplement 291)

This bibliography lists 757 reports, articles, and other documents introduced into the NASA scientific and technical information system in May. 1993. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Aeronautical engineering: A continuing bibliography with indexes (supplement 271)

This bibliography lists 666 reports, articles, and other documents introduced into the NASA scientific and technical information system in October, 1991. Subject coverage includes design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Aeronautical engineering: A continuing bibliography with indexes (supplement 218)

This bibliography lists 469 reports, articles, and other documents introduced into the NASA scientific and technical information system in September, 1987

Aeronautical engineering: A continuing bibliography with indexes (supplement 270)

This bibliography lists 600 reports, articles, and other documents introduced into the NASA scientific and technical information system in September, 1991. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics