PhD Defense by Jie Cao

Event Details
  • Date/Time:
    • Thursday March 29, 2018
      8:30 am - 10:30 am
  • Location: Sustainable Education Building, 122
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Summary Sentence: Digital Image-based Computational Approaches for Three-dimensional Microstructure Characterization

Full Summary: No summary paragraph submitted.

School of Civil and Environmental Engineering


Ph.D. Thesis Defense Announcement

Digital Image-based Computational Approaches for Three-dimensional Microstructure Characterization



Jie Cao



Dr. J. David Frost (CEE)


Committee Members:

Dr. Susan E. Burns (CEE), Dr. Sheng Dai (CEE), Dr. Arun M. Gokhale (MSE)

and Dr. Andrew R. Fuggle (Golder Associates Inc.)



Date & Time: Thursday, March 29, 2018 at 8:30 am

Location: Sustainable Education Building, 122


Employing multiscale approaches provides an innovative solution to advancing the understanding of macro-geomechanical phenomena by capturing quantitative structure information of geomaterials at the particle-pore scale. In the last two decades, microstructural properties of Ottawa sands subjected to laboratory biaxial and triaxial compression testing have been analyzed at Georgia Tech so that their correlation with the mechanisms of strain localization could be explored. Extensive 2-D and some preliminary 3-D knowledge and insights into the inherent variation and evolving behavior induced by shearing in unconsolidated sand microstructures were learned. Aimed at enhancing and complementing these preceding studies, this research focuses on developing appropriate computational methods for 3-D microstructure characterization, with a particular focus on examining the geometry and topology of the highly intricate continuum pore space.

Under a proposed skeleton-based framework, the tortuous nature of pore structure is investigated through characterizing spatial variation of geometrical tortuosity using a novel, generic computational algorithm. Based on specifying and identifying pore throats from the pore skeleton, the physically representative network architecture of pore structure is established. A local sphericity algorithm and a planar surface construction algorithm are introduced to construct pore throats and extract network statistics. The effectiveness of these pore structure analysis tools is evaluated and demonstrated on two simulated idealized packing structures. For the particle phase, image-based separation and size measurements are conducted via morphological watershed processing. The topology of the particle network is represented by the distribution of force-chain tortuosity. Design-based stereological techniques for unbiased sampling and estimation are adopted to guarantee the quantitative analyses can be performed in a scientific manner, independent of the operator.

All the developed methods and tools are applied to characterize three pairs of reconstructed 3-D digital Ottawa sand microstructures, including one pair for biaxial specimens and two for triaxial specimens. Shear-induced alternations in pore structure and particle network are examined from the comparative studies between the sheared microstructure and the unsheared counterpart of each pair, as well as inside and outside the shear zone for the sheared biaxial microstructure. Variations in the inherent structures are analyzed by comparing unsheared triaxial specimens prepared with air pluviation and moist tamping methods. In the characterization of true pore morphology, the encountered geometric complications and then high computational expense highlight the difficulty and challenge of creating a unique pore network for unconsolidated porous media systems.


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Phd Defense
  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: Mar 15, 2018 - 10:41am
  • Last Updated: Mar 15, 2018 - 10:41am