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Proceedings Paper

Visualization of adaptive mesh refinement data
Author(s): Gunther H. Weber; Hans Hagen; Bernd Hamann; Kenneth I. Joy; Terry J. Ligocki; Kwan-Liu Ma; John M. Shalf
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Paper Abstract

The complexity of physical phenomena often varies substantially over space and time. There can be regions where a physical phenomenon/quantity varies very little over a large extent. At the same time, there can be small regions where the same quantity exhibits highly complex variations. Adaptive mesh refinement (AMR) is a technique used in computational fluid dynamics to simulate phenomena with drastically varying scales concerning the complexity of the simulated variables. Using multiple nested grids of different resolutions, AMR combines the topological simplicity of structured-rectilinear grids, permitting efficient computational and storage, with the possibility to adapt grid resolutions in regions of complex behavior. We present methods for direct volume rendering of AMR data. Our methods utilize AMR grids directly for efficiency of the visualization process. We apply a hardware-accelerated rendering method to AMR data supporting interactive manipulation of color-transfer functions and viewing parameters. We also present a cell-projection-based rendering technique for AMR data.

Paper Details

Date Published: 3 May 2001
PDF: 12 pages
Proc. SPIE 4302, Visual Data Exploration and Analysis VIII, (3 May 2001); doi: 10.1117/12.424922
Show Author Affiliations
Gunther H. Weber, Univ. of California/Davis and Univ. of Kaiserslautern (Germany)
Hans Hagen, Univ. of California/Davis (Germany)
Bernd Hamann, Univ. of California/Davis and Lawrence Berkeley National Lab. (United States)
Kenneth I. Joy, Univ. of California/Davis (United States)
Terry J. Ligocki, Lawrence Berkeley National Lab. (United States)
Kwan-Liu Ma, Univ. of California/Davis (United States)
John M. Shalf, Lawrence Berkeley National Lab. and Univ. of Illinois/Urbana-Champaign (United States)


Published in SPIE Proceedings Vol. 4302:
Visual Data Exploration and Analysis VIII
Robert F. Erbacher; Philip C. Chen; Jonathan C. Roberts; Craig M. Wittenbrink; Matti Grohn, Editor(s)

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