Repetitive loading cycles originate from a variety of natural and industrial processes, affect soil properties and the long-term performance of geotechnical systems. This thesis provides unprecedented experimental data and physical analyses of repetitive environmental loading cycles on geomaterials. Research tools adopted in this study include long-term experiments in multi-physics cells, microfluidics, seismic and NMR monitoring, and analytical solutions.
The void ratio evolves towards the terminal void ratio as the number of wet-dry cycles increases. Shear wave velocity data indicate that the soil fabric becomes less sensitive to stress changes after repetitive wet-dry cycles. Changes in the soil-water characteristic curve demonstrate that fine-grained soil fabric evolves towards a new stable fabric as the number of wet-dry cycles increases. Precipitation within dual-porosity microfluidic chips provides new insight into salt crystallization phenomena in geomaterials, such as fractured rocks. Deformable PDMS captures the effect of the crystallization force. Pore network topology and surface wetting characteristics govern crystal growth patterns. Pore fluid chemistry cycles in fine-grained soils alter particle level electrical forces and particle-particle associations. The soil fabric evolves with cycles of pore fluid chemistry and leads to chemical-mechanical coupled response. Atmospheric pressure cycles accelerate water transport in unsaturated soils and promote moisture homogenization. The amount of water loss due to pressure cycles is inversely proportional to the number of cycles, and efficiency is frequency dependent.
This study highlights the behavior of sands and fines subjected to repetitive geoenvironmental loads under various boundary conditions. The physics-inspired and data-driven approaches applied in this research can be used to enhance the existing design guidelines of geo-structures for long-term performance, serviceability, and safety.
Dr. J. Carlos Santamarina
Dr. J. David Frost, Dr. Susan E. Burns, Dr. Sheng Dai, and Dr. Guillermo Goldsztein (MATH)