HR: 16:15h
AN: H34A-02    [Abstracts]
TI: A Grain-based Algorithm for Constructing Physically Representative Network Mappings of Porous Media
AU: Thompson, K E
EM: karsten@lsu.edu
AF: Louisiana State University, 320 Chemical Engineering Gordon A. and Mary Cain Department of Chemical Engineering, Baton Rouge, LA 70803 United States
AU: * Willson, C S
EM: cwillson@lsu.edu
AF: Louisiana State University, 3418D CEBA Department of Civil and Environmental Engineering, Baton Rouge, LA 70803 United States
AU: Reed, A H
EM: areed@nrlssc.navy.mil
AF: Naval Research Laboratory, Seafloor Sciences Branch, Stennis Space Center, MS 39529 United States
AB: Constructing physically representative network mappings of porous media is a highly challenging problem that, once solved, will facilitate large advances in understanding fluid dynamics and mechanics in complex geometrical systems. High-resolution, three-dimensional imaging is quickly becoming a routine tool for visualizing porous materials. However, algorithms for quantitatively analyzing these systems are lacking. In this work, we will present a new grain-based algorithm that can be used to construct physically representative network mappings of granular materials and to extract quantitative statistics for the material. The algorithm is fundamentally different than previous techniques in that it utilizes the granular structure of the medium as the basic foundation for extracting the pore network structure. The resulting network files are in the same format as the network files used in single and multiphase flow pore-scale models. Here, this algorithm is applied to a variety of computer-generated media, laboratory-grade glass beads, sands, and several natural media systems. Results from these analyses highlight the accuracy and robustness of the algorithm over a range of image resolutions and system types.
DE: 1829 Groundwater hydrology
DE: 1832 Groundwater transport
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting