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Titolo: A phase field model for continuous clustering on vector fields
Autore: Garcke, H; Preusser, T; Rumpf, M; Telea, AC; Weikard, U; van Wijk, JJ;
 Indirizzi:
 Univ Bonn, Inst Appl Math, D53115 Bonn, Germany Univ Bonn Bonn Germany D53115 nn, Inst Appl Math, D53115 Bonn, Germany Eindhoven Univ Technol, Dept Math & Comp Sci, NL5600 MB Eindhoven, Netherlands Eindhoven Univ Technol Eindhoven Netherlands NL5600 MB ven, Netherlands
 Titolo Testata:
 IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
fascicolo: 3,
volume: 7,
anno: 2001,
pagine: 230  241
 SICI:
 10772626(200107/09)7:3<230:APFMFC>2.0.ZU;21
 Fonte:
 ISI
 Lingua:
 ENG
 Keywords:
 flow visualization; clustering; CahnHilliard; multiscale; nonlinear diffusion; finite elements; skeletonization;
 Tipo documento:
 Article
 Natura:
 Periodico
 Settore Disciplinare:
 Engineering, Computing & Technology
 Citazioni:
 29
 Recensione:
 Indirizzi per estratti:
 Indirizzo: Garcke, H Univ Bonn, Inst Appl Math, Wegelerstr 6, D53115 Bonn, Germany Univ Bonn Wegelerstr 6 Bonn Germany D53115 53115 Bonn, Germany



 Citazione:
 H. Garcke et al., "A phase field model for continuous clustering on vector fields", IEEE VIS C, 7(3), 2001, pp. 230241
Abstract
A new method for the simplification of flow fields is presented. It is based on continuous clustering. A wellknown physical clustering model, the Cahn Hilliard model, which describes phase separation, is modified to reflectthe properties of the data to be visualized. Clusters are defined implicitly as connected components of the positivity set of a density function. An evolution equation for this function is obtained as a suitable gradient flow of an underlying anisotropic energy functional. Here, time serves as the scale parameter. The evolution is characterized by a successive coarsening of patternsthe actual clusteringduring which the underlying simulation data specifies preferable pattern boundaries. We introduce specific physical quantities in the simulation to control the shape, orientation and distribution of the clusters as a function of the underlying flow field. In addition, the model is expanded, involving elastic effects. In the early stages ofthe evolution shear layer type representation of the flow field can thereby be generated, whereas, for later stages, the distribution of clusters canbe influenced. Furthermore, we incorporate upwind ideas to give the clusters an oriented dropshaped appearance. Here, we discuss the applicability of this new type of approach mainly for flow fields, where the cluster energy penalizes cross streamline boundaries. However, the method also carries provisions for other fields as well. The clusters can be displayed directly as a flow texture. Alternatively, the clusters can be visualized by iconic representations, which are positioned by using a skeletonization algorithm.
ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 29/01/20 alle ore 19:52:33