Pore Space Architecture of Particulate Materials: Characterization and Applications
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Author(s)
Roy, Nimisha
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Abstract
The behavior of particulate materials is of overarching importance across multiple science and engineering fields, given its ubiquitous presence in nature. These materials are typically
composed of two phases, solids and voids, and are therefore described as complex multi-phase materials that exhibit non-linear responses when subjected to varying boundary conditions. While the attributes of the solid phase of particulate materials have been extensively characterized both experimentally and numerically, there is much less understanding of the attributes and behavior of the pore phase. Furthermore, classical pore models incorporate idealized assumptions of feature geometries, limiting the accuracy of the information that can be obtained from these features. This study aims to advance digital characterization capabilities for particulate microstructures, focusing on characterizing the geometry and topology of the highly complex pore space within packed particle systems. A new and robust computational algorithm is proposed that quantifies various characteristics of the three-dimensional pore space of a given particulate media, which is unimpeded by assumptions of feature shapes or user dependency. The method is validated against packings of known pore geometries and implemented on real, simulated, and fabricated microstructures of different packing densities, particle sizes, shapes, gradation, and following different specimen preparation techniques to measure its ability in capturing multi-scale responses of microstructures.
The study also leverages the emergence of machine learning techniques to scale up the findings to real-world field-scale applications comprising particle-pore systems with 10's of millions of particles. In this regard, the use of deep learning tools for the rapid estimation of pore space properties from three-dimensional images is sought. Finally, the developed techniques and tools are implemented on real granular soils to strengthen the understanding of macro-geomechanical phenomena. The findings highlight the importance of accounting for pore space properties when interpreting the macroscopic response of granular assemblies subjected to external mechanical and precipitational loading.
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2021-12-07
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Dissertation