An Abstraction Space for Fluid Flow Visualization
Master's thesis by Matthew van der Zwan
The increase in computational power available in computers over the past decades allows researchers to run simulations with an increasing amount of grid points. While this improves the accuracy of the simulation results, it poses a challenge when visualizing these results. Traditional flow visualization techniques such as Line Integral Convolution (LIC) require a lot of time to generate the corresponding representation of the flow. Furthermore, visualizing these representations is also demanding. Therefore, other representations of fluid flow have been proposed, such as streamlines and flow topology representations. These methods reduce the amount of data which is visualized and thereby increase performance, but the resulting visualization might be more difficult to understand.
In his thesis, Matthew describes an abstraction space for fluid flow visualization. The goal of this abstraction space is to allow continuous transitions between different representations of the flow, where each representation corresponds to a level of structural abstraction. This abstraction space enables people to understand the relation between the different representations. Besides structural abstraction, Matthew also employs techniques which enhance spatial perception for the different representations. He discusses how to enable a continuous transition between different fluid flow representations and how this structural transition can be combined with the techniques to enhance spatial perception. Throughout this thesis, Matthew presents results created with his realization of the abstraction space.
You can download Matthew van der Zwan's Master's thesis here. The project was also published as a short paper at EuroVis 2012.