Computational Field Visualization
Inhaltsverzeichnis
Reference
Johnson, C.R., Livnat, Y., Zhukov, L., David Augustus Hart, and Kindlmann, G.: Computational Field Visualization. Mathematics Unlimited - 2001 and Beyond. Engquist, B., Royal Institute of Technology, Stockholm, Sweden, and Schmid, W., Harvard University, Cambridge, MA, USA (Eds.) Book Chapter, Springer-Verlag, ISBN 978-3-540-66913-5
DOI
Abstract
Since computers were first introduced, scientists, mathematicians, and engi- neers have attempted to harness their power to simulate complex physical phe- nomena. Today, the computer is an almost universal tool used in a wide range of scientific and engineering domains. Scientific visualization clearly plays a central role in the analysis of data generated by scientific and engineering sim- ulations.
The field of computational science and engineering has grown out of the widespread use of computers to numerically simulate physical phenomena as- sociated with many problems in science and engineering. In recent years, the scientific computing community has experienced an explosive growth in both the size and the complexity of numeric computations that can be performed in simulations. One of the significant benefits of this increased computing power is the ability to perform complex three-dimensional simulations. How- ever, such simulations present new challenges for computational scientists, in- cluding the need to effectively analyze and visualize complex three-dimensional data.
Computational field problems; such as computational fluid dynamics (CFD), electromagnetic field simulation, and weather modeling – essentially any prob- lems whose physics can be modeled effectively by ordinary and/or partial dif- ferential equations–constitute the majority of computational science and en- gineering simulations. The output of such simulations might be a single field variable (such as pressure or velocity) or a combination of fields involving a number of scalar fields, vector fields, and/or tensor fields. As such, scien- tific visualization researchers have concentrated on effective ways to visualize large-scale computational fields. Much current and previous visualization re- search has focused on methods and techniques for visualizing a computational field variables (such as the extraction of a single scalar field variable as an isosurface). While single variable visualization often satisfies the needs of the user, it is clear that it would also be useful to be able to effectively visualize multiple fields simultaneously. Take Poisson’s equation, for example. It has variants through just about all of science and engineering ...
Extended Abstract
Bibtex
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