Interactive, High-Dimensional Flow Visualization Using Image Space-Based Approaches

Currently, we as a civilization, are experiencing an information big bang ,i.e., an explosion of data. According to a study conducted by Peter Lymanand Hal R. Varian at the University of California Berkeley ( How muchinformation ?) new data generated in the period from 2003 to 2005 is greaterthan that of all previously created documents, more than 90% of which isin digital form. The amount of digital data vastly exceeds that produced inpaper or film. Raw data itself is not necessarily very valuable. It is ourability to interpret and extract meaning from the data that is important.One of, if not the greatest, challenge of the 21st century is to effectivelymanage, understand, and make use of the enormous amounts of data currentlybeing generated. Visualization is the key to navigating through the vastamounts of data we are constantly bombarded with. Visualization takesmegabytes, gigabytes, or terabytes of data and generates meaningful imagesusing computing machinery. We can summarize underlying patterns and importantphenomenon in the data using pictures. Pictures harness the very powerfulhuman visual system which provides a very high bandwidth connection to thebrain.This proposal is concerned with advancing a specific sub-field ofvisualization, namely, flow visualization. Flow visualization is concernedwith depicted vector field data, a special category of data with bothmagnitude and direction. Moreover, we are concerned with the depiction ofnot just any type of vector field data, but rather, with Computational FluidDynamics (CFD) simulation data. CFD is an engineering discipline whose goalis to predict the behavior of flow in a quantitative fashion. For example,simulation can be used to study the behavior of ocean currents and weatherpatterns.The number of engineers who use CFD analysis is growing rapidly. More andmore engineers rely on computer aided modeling, simulation, and visualizationtools in order to find the best solutions for a multitude of design andmanufacturing challenges. Computer aided engineering is motivated stronglyby the ability to build prototypes and propose optimizations using asoftware-based process that is faster than building real, heavyweightcomponents. Furthermore, scientists and researchers rely ever more onsimulation software in order to study natural phenomena such as flooding,volcanoes, and chemical reactions etc. that are simply not feasible tore-create in the real world.Despite the advantages that computer aided engineering and simulationoffers, such as more rapid prototyping, a more rapid feedback loop, and areduction in manufacturing costs, and the ability to study natural phenomena that would otherwise be impractical, these software tools bring several challenges with them. Computational Fluid Dynamics (CFD) simulations result in very large, complex data sets, e.g., measured in gigabytes or terabytes. The software tools needed to analyze, explore, and present simulation results must face several closely related challenges. This research proposal will address these challenges in a novel way by developing new computer algorithms, new interaction techniques, and hence new visualizations that will provide valuable insight into CFDsimulation data.