Theses and Dissertations at Montana State University (MSU)
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/733
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Item Micromechanical analysis of energy expenditure in snow fracture(Montana State University - Bozeman, College of Engineering, 2017) LeBaron, Anthony Michael; Chairperson, Graduate Committee: Daniel MillerA microstructure-based evaluation of snow combining experimental and analytical approaches was performed. Shear tests were performed on both homogeneous and layered samples of un-notched snow. Force and displacement during loading were recorded. Immediately after testing, small subsamples of snow were subjected to micro-CT scanning to capture 3D microstructure details. Microstructure was then modeled as a grain-bond network. The grain-bond network was subject to minimum energy fracture path calculations as well as discrete element modeling. The discrete element model showed good agreement with experiments. Taken together, results from models and experiments show a widespread damage accumulation process in snow. A large fracture process zone (FPZ) is observed, even in samples with weak layers. Evidence indicates that even in snow avalanches, there is likely significant energy dissipation within the slab.Item A microstructural investigation of radiation recrystallized snow layers(Montana State University - Bozeman, College of Engineering, 2016) Walters, David John; Chairperson, Graduate Committee: Edward E. AdamsRadiation recrystallized snow is a pervasive weak layer of snow that, once buried, increases the threat of snow avalanches. While much is known about the conditions required to form radiation recrystallized snow layers, little is understood about the microstructural intricacies that develop resulting in decreased macro-scale mechanical stability. This study utilizes the Subzero Science and Engineering Research Facility at Montana State University to recreate clear daytime meteorological conditions to induce near surface metamorphism in snow. This metamorphic process develops radiation recrystallized layers of faceted crystals in the top 1-2 cm of snow over the course of 12 hours. Mechanical testing is performed before and after recrystallization to compute the relative change in mechanical properties of the recrystallized snow sample. Near surface samples are also extracted and imaged at regular intervals using computed tomography. Imaging results in a 3-D reconstruction of representative snow microstructures recording the temporal evolution of faceted crystal formation. The microstructural data is utilized in two modeling approaches which seek to describe the macro-scale mechanical properties of the snow. A previously developed homogenization approach, which computes macro-scale effective stiffness properties using micromechanical interactions and texture, is enhanced by incorporating measures of individual grain shapes and differing textural measures. Another approach leverages the microstructure directly by simulating the response of macro-scale loads on a geometric mesh of the imaged microstructure using finite element methods. Following recrystallization, physical mechanical testing demonstrated that the metamorphism process forms a stiff and strong sublayer capped by a weaker layer of faceted snow that is 75-80% less stiff in shear and 80-90% less stiff in compression than the strong layer below it. Microstructural analysis revealed multiple fine layers of unique crystal morphologies existing within the faceted region. Homogenization reflected reasonable trends in relative changes of effective stiffness properties but suffered from volumetric scale problems when analyzing the faceted layer. Finite element methods also reasonably computed the relative change in macro-scale effective properties as a result of changes to the microstructural geometry. Additionally, the finite element method estimates changes to effective strength and the location of mechanical failure within the faceted layers.Item Fabric tensors and effective properties of granular materials with application to snow(Montana State University - Bozeman, College of Engineering, 2011) Shertzer, Richard Hayden; Chairperson, Graduate Committee: Edward E. AdamsGranular materials e.g., gravel, sand, snow, and metallic powders are important to many engineering analysis and design problems. Such materials are not always randomly arranged, even in a natural environment. For example, applied strain can transform a randomly distributed assembly into a more regular arrangement. Deviations from random arrangements are described via material symmetry. A random collection exhibits textural isotropy whereas regular patterns are anisotropic. Among natural materials, snow is perhaps unique because thermal factors commonly induce microstructural changes, including material symmetry. This process temperature gradient metamorphism produces snow layers that can exhibit anisotropy. To adequately describe the behavior of such layers, mathematical models must account for potential anisotropy. This feature is absent from models specifically developed for snow, and, in most granular models in general. Material symmetry is quantified with fabric tensors in the constitutive models proposed here. Fabric tensors statistically characterize directional features in the microstructure. For example, the collective orientation of intergranular bonds impacts processes like conduction and loading. Anisotropic, microstructural models are analytically developed here for the conductivity, diffusivity, permeability, and stiffness of granular materials. The methodology utilizes homogenization an algorithm linking microscopic and macroscopic scales. Idealized geometries and constitutive assumptions are also applied at the microscopic scale. Fabric tensors tying the granular arrangement to affected material properties are a natural analysis outcome. The proposed conductivity model is compared to measured data. Dry dense snow underwent temperature gradient metamorphism in a lab. Both the measured heat transfer coefficient and a developing ice structure favored the direction of the applied gradient. Periodic tomography was used to calculate microstructural variables required by the conductivity model. Through the fabric tensor, model evolution coincides with measured changes in the heat transfer coefficient. The model also predicts a different conductivity in directions orthogonal to the gradient due to developing anisotropy. Models that do not consider directional microstructural features cannot predict such behavior because they are strictly valid for isotropic materials. The conclusions are that anisotropy in snow can be significant, fabric tensors can characterize such symmetry, and constitutive models incorporating fabric tensors offer a more complete description of material behavior.