Date of Award
Master of Science
Khalid A. Alshibli
Angelica M. Palomino, Timothy J. Truster
Many experimental studies have demonstrated that mechanical response of granular materials is highly influenced by micro-structural fabric and its evolution. In the literature, quantification of fabric and its evolution has been developed based on microstructural observations using Discrete Element Method (DEM) or 2D experiments with simple particle shapes. The emergence of x-ray computed tomography (CT) technique has made quantification of such experimental micro-structural properties possible using 3D high-resolution images. Synchrotron micro-computed tomography (SMT) was used to acquire 3D images during in-situ conventional triaxial compression experiments on granular materials with different morphologies. 3D images were processed to quantify fabric and its evolution based on experimental measurements of contact normal vectors between particles. Overall, the directional distribution of contact normals exhibited the highest degree of isotropy at initial configuration (i.e., zero global axial strain). As compression progressed, contact normals evolved in the direction of loading until reaching a constant fabric when experiments approached the critical state condition. Further assessment of the influence of confining pressure, initial density state, and particle-level morphology on fabric and its evolution was formed. Results show that initial density state and applied confining pressure significantly influence the fabric-induced internal anisotropy of tested specimens at initial configurations as well as the magnitude of fabric evolution throughout triaxial compression experiments. Relatively, a higher applied confining pressure and a looser initial density state resulted in a higher degree of fabric-induced internal anisotropy. Influence of particle-scale morphology was also found to be significant particularly on fabric evolution.
Imseeh, Wadi Habeeb, "3D Experimental Quantification of Fabric and Fabric Evolution of Sheared Granular Materials Using Synchrotron Micro-Computed Tomography. " Master's Thesis, University of Tennessee, 2017.