DOI: https://doi.org/10.15368/theses.2009.73
Available at: https://digitalcommons.calpoly.edu/theses/117
Date of Award
6-2009
Degree Name
MS in Computer Science
Department/Program
Computer Science
Advisor
Zoe J. Wood
Abstract
Computer-generated imagery is ubiquitous in today's society, appearing in advertisements, video games, and computer-animated movies among other places. Much of this imagery needs to be as realistic as possible, and animators have turned to techniques such as fluid simulation to create scenes involving substances like smoke, fire, and water. The Lattice-Boltzmann Method (LBM) is one fluid simulation technique that has gained recent popularity due to its relatively simple basic algorithm and the ease with which it can be distributed across multiple processors. Unfortunately, current LBM simulations also suffer from high memory usage and restrict free surface fluids to domains of fixed size. This thesis modifies the LBM to utilize a recursive run-length-encoded (RLE) grid data structure instead of the standard fixed array of grid cells, which reduces the amount of memory required for LBM simulations as well as allowing the domain to grow and shrink as necessary to accomodate a liquid surface. The modified LBM is implemented within the open-source 3D animation package Blender and compared to Blender's current LBM simulator using the metrics of memory usage and time required to complete a given simulation. Results show that, although the RLE-based simulator can take several times longer than the current simulator to complete a given simulation, the memory usage is significantly reduced, making an RLE-based simulation preferable in a few specific circumstances.