Please use this identifier to cite or link to this item: doi:10.22028/D291-25935
Title: Path-line oriented visualization of dynamical flow fields
Author(s): Shi, Kuangyu
Language: English
Year of Publication: 2008
SWD key words: Strömungsfeld
Free key words: dynamical flow behavior
flow visualization
path-line behaviors
property transport phenomenon
DDC notations: 004 Computer science, internet
Publikation type: Dissertation
Abstract: An effective visual representation of dynamical flow behavior is still a challenging problem of modern flow visualization. Path-lines are important characteristic curves of dynamical flow fields. In this thesis, we focus on the visual analysis of path-line behaviors and uncover the dynamical nature of a flow field. We propose a topological segmentation of periodic 2D time-dependent vector fields based on asymptotic path-line behaviors. A flow domain is classified into different areas based on the converging or diverging path-line behaviors relating to the identified critical path-lines. We also offer an alternative algorithm to extract the separation surfaces of the path-line oriented topological structure. For the interactive visual analysis of fluid motion, we propose an information visualization based approach to explore the dynamical flow behaviors. Attributes associated with path-lines are identified and analyzed and the interesting features or structures are extracted and visualized with human interaction. We also investigate the property transport phenomenon and propose an approach to visualize the finite-time transport structures of property advection which is similar to carry out a line integral convolution over physical properties along path-lines. We demonstrate our approaches on a number of applications and present some interesting results.
Link to this record: urn:nbn:de:bsz:291-scidok-21243
Advisor: Theisel, Holger
Date of oral examination: 10-Dec-2008
Date of registration: 12-May-2009
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Informatik
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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