Query-Driven Visualization of Time-Varying Adaptive Mesh Refinement Data
نویسندگان
چکیده
منابع مشابه
Visualization of Time-Dependent Adaptive Mesh Refinement Data
Analysis of phenomena that simultaneously occur on quite different spatial and temporal scales require adaptive, hierarchical schemes to reduce computational and storage demands. For data represented as grid functions, the key are adaptive, hierarchical, time-dependent grids that resolve spatio-temporal details without too much redundancy. Here, so-called AMR grids gain increasing popularity. F...
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Adaptive Mesh Refinement (AMR) is a highly effective computation method for simulations that span a large range of spatiotemporal scales, such as astrophysical simulations, which must accommodate ranges from interstellar to sub-planetary. Most mainstream visualization tools still lack support for AMR grids as a first class data type and AMR code teams use custom built applications for AMR visua...
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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 (CFD) to simulate phenomen...
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Adaptive Mesh Refinement (AMR) is a highly effective method for simulations that span a large range of spatiotemporal scales, such as astrophysical simulations that must accomodate ranges from interstellar to sub-planetary. Most mainstream visualization tools still lack support for AMR as a first class data type and AMR code teams use custom built applications for AMR visualization. The Departm...
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iii Acknowledgments Twenty years from now you will be more disappointed by the things you didn't do than by the ones you did do. So throw off the bowline. Sail away from the safe harbor. Catch the trade winds in your sails. Explore. Dream. Discover. — Mark Twain I want to use this opportunity to thank all people who made this work possible. First, I would like to thank my advisors The continuou...
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ژورنال
عنوان ژورنال: IEEE Transactions on Visualization and Computer Graphics
سال: 2008
ISSN: 1077-2626
DOI: 10.1109/tvcg.2008.157