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Curvature adapted triangulation of NURBS surfaces

Authors: Lee Kania; Saif Warsi; Lee Kania; Saif Warsi;

Curvature adapted triangulation of NURBS surfaces

Abstract

Full exploitation of the sophisticated physical modeling capabilities of computational fluid dynamics has been hampered by the inability to generate high quality grids in a timely manner. Complex geometries further exacerbate grid generation difficulties. Despite the potential for fully automatic grid generation with the relatively new unstructured techniques, such a capability has, in large part, remained elusive. The principle difficulty with the generation of such grids lies within the surface discretization, the operation for which, though difficult in its own right, must be intimately coupled with CAD data to retain geometric integrity and achieve the desired efficiency. This paper presents a new method for generating high quality unstructured surface grids directly on NURBS surfaces or any other surface for which a similar parameterization exists; surface distributions are automatically adapted to local curvature which renders a high fidelity representation of the geometry with optimum use of grid points. The method is applied to numerous surfaces possessing large variations in curvature to demonstrate its effectiveness at producing high quality surface grids automatically.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Top 10%
Average
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