Next Generation Data Mining and Visualization Techniques: Application to Global Hybrid Simulations

Details Next Generation Data Mining and Visualization Techniques: Application to Global Hybrid Simulations Next Generation Data Mining and Visualization Techniques: Application to Global Hybrid Simulations

Dec 2004

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004agufmsm52a..04o&link_type=abstract

American Geophysical Union, Fall Meeting 2004, abstract #SM52A-04

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2724 Magnetopause, Cusp, And Boundary Layers, 2728 Magnetosheath, 2753 Numerical Modeling

Scientific paper

Global hybrid simulations, in which electrons are treated as a fluid and ions kinetically, provide high resolution "images" of the magnetosphere on ion temporal and spatial scales. Visualization and analysis of data from these simulations pose serious challenges that need to be addressed. For example, a typical global 2-D simulation run generates over 100 Gb of data even when individual particle data are saved much less frequently than moments and field data. A 3-D global run easily generates over TB of data. Due to their large size, these data sets are often stored in segments over distributed platforms. An added complication is that no off-the-shelf software exists and packages such as IDL, OpenDx and VTK require significant customization. In this talk, we provide an overview of our customized software and illustrate their usage through examples. In particular, three aspects of data analysis techniques are described in some detail. One, has to do with tools developed for visualization of data in various perspectives and application of standard analysis techniques to them. The other, involves the use of intelligent software for data mining and event identification purposes. Third, is the development of special software to facilitate comparison between simulation and spacecraft data. In all cases, we place our focus on bow shock or magnetopause related processes.

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