Günther T (2016)
Publication Language: English
Publication Type: Thesis
Publication year: 2016
Vector field visualization is a major discipline of scientific
visualization that helps to push the frontiers of research in fluid
mechanics, medicine, biology, astrophysics and many more. In particular,
vector field visualization is concerned with the discovery of
relationships in possibly large and complex vector fields, which serve
as general descriptors of air and fluid flows, magnetic fields and
dynamical systems. The visualization community found a number of
different ways to assist in the analysis and exploration of these
fields. Two major classes of approaches are the so-called geometry-based
and feature-based / topology-based techniques. The first and second
part of this thesis introduce techniques that reside in these two
classes, respectively. The third part of the thesis addresses the
analysis of inertial particles, i.e., finite-sized objects carried by
fluid flows.
When it comes to 3D flow visualization, we often
encounter occlusion problems when displaying dense sets of lines or
multiple surfaces. A vital aspect is the careful selection of the
primitives that best communicate the relevant features in a data set. In
the first part of the thesis, we present optimization-based approaches
that adjust the opacity of lines and surfaces to strive for a balance
between the presentation of relevant information and occlusion
avoidance.
The second part of the thesis is dedicated to novel
rendering techniques for the visualization of unsteady flows. For this,
we will apply techniques from light transport in heterogeneous
participating media to the unbiased rendering of Lagrangian scalar
fields, namely finite-time Lyapunov exponents. Further, we propose a new
class of vortex definitions for flows that are induced by rotating
mechanical parts, such as stirring devices, hydrocyclones, centrifugal
pumps or ventilators.
In the third part of this thesis, we
introduce inertial particles as a new application domain to the flow
visualization community. Recent research in flow visualization focused
on the analysis ofmassless particles. However, in many application
scenarios, the mass of particles and their resulting inertia are
essential, such as when sand particles interact with aircraft. The
governing ODE of even simple inertial flow models is up to seven
dimensional, which makes feature extraction a challenging task. We
abstract the description of mass-dependent particle trajectories and
apply existing flow visualization methods to the mass-dependent case. In
particular, we extract and visualize integral geometry, study the
vortical motion and separation behavior of inertial particles, extend
traditional vector field topology to the inertial case and present a new
approach to the source inversion problem, i.e., the recovery of the
source of dispersed pollutants.
We demonstrate the usefulness of our methods by applying them to a variety of synthetic and real-world data sets.
APA:
Günther, T. (2016). Opacity Optimization and Inertial Particles in Flow Visualization (Dissertation).
MLA:
Günther, Tobias. Opacity Optimization and Inertial Particles in Flow Visualization. Dissertation, 2016.
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