April 15-17

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Abstracts

Author: Simon Woodruff
Requested Type: Poster
Submitted: 2019-04-01 16:15:06

Co-authors: T. Meyer, A. Lau, J. Stuber, K. Martin

Contact Info:
Woodruff Scientific
3900 Paseo Del Sol
Santa Fe, NEW MEXICO   87507
United States

Abstract Text:
Computational physicists and diagnosticians need to analyze 3-Dimensional data to gain understanding of their simulations or diagnostic results. Visualizing 3D Physics effects by use of 2D screens can limit understanding or even create misunderstandings. Communication of results between collaborators can be difficult when using 2D images or movies, sent by email with written explanations. 3D models can be seen with the use of stereoscopic motion-tracking head-mounted displays such as Oculus VR's Oculus Rift or Microsoft's Hololens. These devices attach to the head like over-sized ski goggles and project separate images to each eye creating an illusion to the user of a 3-dimensional immersive space. By immersing the user into a virtual reality, the user can more easily visualize, explore, and interact with their data. By augmenting the reality of the user with holograms, they can view, explore, and interact their data with colleagues as if it were physically in the room with them. Full 3D data already is collected by computational physicists and diagnosticians. Existing simulation code and diagnostics data would not need to be modified for use with this program. Additionally, Oculus VR's Oculus Rift can be used in a collaborative fashion. Multiple scientists could both view and interpret a data-set in real-time, facilitating quick and accurate information transfer. We have developed a Physics Visualization tool for use with major commerical VR/AR head-mounted display products and open-source visualization software Paraview's virtual reality interface. Common data visualization models such as contour, psuedocolor, vector, etc, will be available to the user. The visualization tool will use existing data formats like HDF5 and VTK to facilitate use with existing datasets.

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