Structure-Significant Representation of Structured Datasets

—Numerical simulation of physical phenomena is now an accepted way of scientific inquiry. However, the field is still evolving, with a profusion of new solution and grid-generation techniques being continuously proposed. Concurrent and retrospective visualization are being used to validate the results, compare them among themselves and with experimental data, and browse through large scientific databases. There exists a need for representation schemes which allow access of structures in an increasing order of smoothness (or decreasing order of significance). We describe our methods on datasets obtained from curvilinear grids. Our target application required visualization of a computational simulation performed on a very remote supercomputer. Since no grid adaptation was performed, it was not deemed necessary to simplify or compress the grid. In essence, we treat the solution as if it were in the computational domain. Inherent to the identification of significant structures is determi...

• Type: Journal
• Year: 1998
• Where: TVCG
• Authors: Raghu Machiraju, Zhifan Zhu, Bryan Fry, Robert J. Moorhead
• Keywords: Grid, Representation Scheme, Significant Structures, TVCG 1998