Interactive Visual Analysis of Time-dependent Flows:
Physics- and Statistics-based Semantics
Armin Pobitzer
PHDTHESIS,
Apr, 2012
AbstractWith the increasing use of numerical simulations in the fluid mechanics
community in recent years flow visualization increasingly gains importance
as an advanced analysis tool for the simulation output. Up to now, flow
visualization has mainly focused on the extraction and visualization of structures
that are defined by their semantic meaning. Examples for such structures
are vortices or separation structures between different groups of particles that
travel together.
In order to deepen our understanding of structures linked to certain flow phenomena,
e.g., how and why they appear, evolve, and finally are destroyed, also
linking structures to semantic meaning that is not attributed to them by their
very definition, is a highly promising research direction to pursue.
In this thesis we provide several approaches on how to augment structures
stemming from classical flow visualization techniques by additional semantic
information originating from new methods based on physics and statistics. In
particular, we target separation structures, the linking of structures with a local
semantics to global flow phenomena, and minimal representation of particle
dynamics in the context of path line attributes.
Published
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BibTeX
@phdthesis{pobitzer12thesis,
title = {Interactive Visual Analysis of Time-dependent Flows:
Physics- and Statistics-based Semantics},
author = {Armin Pobitzer},
year = {2012},
month = {Apr},
abstract = {With the increasing use of numerical simulations in the fluid mechanics
community in recent years flow visualization increasingly gains importance
as an advanced analysis tool for the simulation output. Up to now, flow
visualization has mainly focused on the extraction and visualization of structures
that are defined by their semantic meaning. Examples for such structures
are vortices or separation structures between different groups of particles that
travel together.
In order to deepen our understanding of structures linked to certain flow phenomena,
e.g., how and why they appear, evolve, and finally are destroyed, also
linking structures to semantic meaning that is not attributed to them by their
very definition, is a highly promising research direction to pursue.
In this thesis we provide several approaches on how to augment structures
stemming from classical flow visualization techniques by additional semantic
information originating from new methods based on physics and statistics. In
particular, we target separation structures, the linking of structures with a local
semantics to global flow phenomena, and minimal representation of particle
dynamics in the context of path line attributes.},
school = {Department of Informatics, University of Bergen, Norway},
ISBN = {978-82-308-2063-6},
url = {https://bora.uib.no/handle/1956/5856},
}
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