Theses and Dissertations at Montana State University (MSU)

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    Vehicles, grooming, and other factors affecting snowroad longevity in Yellowstone National Park
    (Montana State University - Bozeman, College of Engineering, 2018) Nelson, Molly McKellar; Chairperson, Graduate Committee: Edward E. Adams
    In winter, the National Park Service (NPS) at Yellowstone grooms snow that builds up on the park roads, making 'snowroads' passable by snowmobiles and snowcoaches. The NPS has recently allowed experimental snowcoaches on low-pressure tires (LPTs) in addition to traditional tracks. As they consider a permanent policy on these LPTS, they want to understand these vehicles' impacts on snowroads compared with those of traditional tracked vehicles and snowmobiles. They also want to know how to optimize other operations (e.g., grooming) to maintain quality roads that support safe travel through the park. This two-year field study investigated the snowroad quality in the park and factors influencing this quality. The approach involved data collection on both parkwide road conditions and individual vehicle passes. Both controllable and non-controllable factors were considered to provide information on their relative influence. Parkwide road quality analysis involved collecting GPS data on grooming activity, weather data from existing stations, road depth through radar measurements, traffic counts from motion-sensor cameras, hardness data, and snow sample analysis. The vehicle-by-vehicle impact study involved both subsurface and surface measurements in the road. Load cells, accelerometers, a high-speed, high-definition camera, a penetrometer, and a 'profilometer' provided measurements. Data analysis combined with existing literature provided insights into best practices for the NPS. Parkwide, snowroads harden throughout the season, with temperatures and traffic load being contributing factors. Grooming results in a harder road if snow disaggregation is followed by compaction, and with a longer set time between grooming and traffic. Individual vehicles' impacts are driven by surface interaction rather than motion at depth in the snowroad. On hard, groomed snowroads, both tracked and LPT snowcoaches can form ruts, but tracked vehicles continue to dig ruts deeper whereas LPT coaches' ruts level out and stop deepening with subsequent passes. This seems to be because LPTs form ruts primarily through compaction and tracked vehicles through snow displacement. Reduced tire pressures reduce rut formation and can harden the road. Results from this study demonstrate that LPT coaches should not be disallowed from Yellowstone based on road impacts. Other results will inform NPS operations to optimize grooming practices.
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    A microstructural investigation of radiation recrystallized snow layers
    (Montana State University - Bozeman, College of Engineering, 2016) Walters, David John; Chairperson, Graduate Committee: Edward E. Adams
    Radiation 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.
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    Statistical validation of a numerical snow cover model and preliminary experimental results to facilitate model improvement
    (Montana State University - Bozeman, College of Engineering, 2000) Lundy, Christopher Charles
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    The development and validation of a snow/icepack pavement temperature thermodynamic model
    (Montana State University - Bozeman, College of Engineering, 2002) Bristow, Jeffrey Ryan
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    A biviscous modified Bingham model of snow avalanche motion
    (Montana State University - Bozeman, College of Engineering, 1982) Dent, Jimmie Duane
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    Visible bidirectional-reflectance measurements for rounded grain and surface hoar snow crystal morphologies
    (Montana State University - Bozeman, College of Engineering, 2013) Stanton, Brad Thomas; Chairperson, Graduate Committee: Daniel Miller
    An understanding of the optical properties of snow is vital to accurately quantifying the effect of snow cover on the Earth's radiative energy balance. Existing radiative transfer models often simplify complex crystal habits by utilizing spheres of equivalent specific surface area (SSA). While these models have had some success in accurately predicting snow albedo, more complex models strive to predict the directional reflectance properties of snow. These models require accurate bidirectional reflectance values for various snow crystal habits against which to compare their results. However, few studies in this area exist and none focus specifically on surface hoar--a well-known surface crystal type often responsible for avalanches once buried by subsequent snows. In this study, it is hypothesized that microstructural changes due to near surface metamorphism, traced by crystal size and type, will alter snow's solar bidirectional reflectance. Specifically, it is postulated that the bidirectional reflectance distribution of the snow's surface before and after surface hoar growth will be predictably and quantifiably different when viewed in the visible wavelengths, thereby allowing the remote detection of surface hoar presence. To test this hypothesis, a methodology for reliably growing surface hoar in a lab setting was developed. Temporal changes in crystal mass and specific surface area were documented using computed tomography and visible microscopic imaging while a suite of meteorological instrumentation recorded environmental chamber conditions. A spectrometer was used to measure bidirectional-reflectance factors (BRF) both before growth (rounded grains) and after growth (surface hoar) from 42 different incident lighting and viewing geometries. These BRF values provide an accurate data set for comparison to modeling studies. Analysis of the result revealed three primary conclusions: 1) In the transition from rounded grains to surface hoar, mean BRF values (essentially albedo) decrease slightly (d2.9%) likely due to an increase in grain size; 2) Accompanying surface hoar growth is an increase in SSA and a departure from Lambertian scattering. That is, surface hoar has significantly brighter peak values and significantly darker minimum values than rounded grains; 3. Incident lighting and viewing geometries at which these maximum and minimum BRF values occur show no discernible pattern.
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    Nonequilibrium thermodynamics of temperature gradient metamorphism in snow
    (Montana State University - Bozeman, College of Engineering, 2013) Staron, Patrick Joseph; Chairperson, Graduate Committee: Edward E. Adams
    In the presence of a sufficient temperature gradient, snow evolves from an isotropic network of ice crystals to a transversely isotropic system of depth hoar chains. This morphology is often the weak layer responsible for full depth avalanches. Previous research primarily focused on quantifying the conditions necessary to produce depth hoar. Limited work has been performed to determine the underlying reason for the microstructural changes. Using entropy production rates derived from nonequilibrium thermodynamics, this research shows that depth hoar forms as a result of the snow progressing naturally toward thermal equilibrium. Laboratory experiments were undertaken to examine the evolution of snow microstructure at the macro scale under nonequilibrium thermal conditions. Snow samples with similar initial microstructure were subjected to either a fixed temperature gradient or fixed heat input. The metamorphism for both sets of boundary conditions produced similar depth hoar chains with comparable increases in effective thermal conductivity. Examination of the Gibbs free energy and entropy production rates showed that all metamorphic changes were driven by the system evolving to facilitate equilibrium in the snow or the surroundings. This behavior was dictated by the second law of thermodynamics. An existing numerical model was modified to examine depth hoar formation at the grain scale. Entropy production rate relations were developed for an open system of ice and water vapor. This analysis showed that heat conduction in the bonds had the highest specific entropy production rate, indicating they were the most inefficient part of the snow system. As the metamorphism advanced, the increase in bond size enhanced the conduction pathways through the snow, making the system more efficient at transferring heat. This spontaneous microstructural evolution moved the system and the surroundings toward equilibrium by reducing the local temperature gradients over the bonds and increasing the entropy production rate density. The employment of nonequilibrium thermodynamics determined that the need to reach equilibrium was the underlying force that drives the evolution of snow microstructure. This research also expanded the relevance of nonequilibrium thermodynamics by applying it to a complicated, but well bounded, natural problem.
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    Numerical analysis of conditions necessary for near-surface snow metamorphism
    (Montana State University - Bozeman, College of Engineering, 2010) Slaughter, Andrew Edward; Chairperson, Graduate Committee: Edward E. Adams
    Faceted snow crystals develop at or near the snow surface due to temperature gradients. After burial, snow avalanches regularly fail on these layers. Generally, surface hoar deposits when the snow surface is cooler than the surrounding environment; near-surface facets form when the subsurface is warmed by solar radiation and the surface is cooled by radiative, convective, and latent heat exchange. Field research stations were established that included daily observations and meteorological data. In two seasons, 14 surface hoar and 26 near-surface facet events were recorded. Statistical analysis of the surface hoar events indicated three factors that were related to surface hoar growth: incoming long-wave radiation, snow surface temperature, and relative humidity. The ideal conditions for each of these parameters were 190-270 W/m², -22 to -11°C, and 45-80%, respectively. For near-surface facet formation, long- and short-wave radiation and relative humidity were statistically linked to the events. The ideal conditions for these parameters ranged from 380-710 W/m², 210-240 W/m², and 23-67%, respectively. Using a thermal model, sensitivity analysis, and Monte Carlo simulations the conditions that lead to facet formation were explored. Based on computed mass-flux, the formation of surface hoar was mainly driven by changes in long-wave radiation, air temperature, wind velocity, and relative humidity. From these terms graphical tools were developed to predict surface hoar; the numerical results matched reasonably well with the field observations. Based on the presence of a specific temperature gradient understood to lead to near-surface facets, three terms were determined to be the most influential: density, thermal conductivity, and incoming long-wave radiation. Using these terms, albedo, and incoming short-wave radiation--a requirement for radiation-recrystallization--a means for predicting the presence of near-surface facets was presented. The physical and analytical data presented indicates that incoming long-wave radiation is the most influential parameter governing the conditions that lead to surface hoar and near-surface facet growth. The analysis suggests that snow with low density and high thermal conductivity may be conducive to the formation of near-surface facets.
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    Experimental investigation of interactions between explosive detonations and the resulting snowpack response
    (Montana State University - Bozeman, College of Engineering, 2012) Bones, Josephine Anne; Chairperson, Graduate Committee: Daniel Miller
    Avalanches threaten many areas of the world. For many years, risk has been mitigated through artificial avalanche initiation using explosives. Even with extensive use, a lack of experimental determinations of the interactions between explosive detonations and the snowpack response exists. To address this, a multiyear field based research project was conducted at Montana State University, Bozeman, MT. A portable instrument array consisting of pressure and accelerometer sensors was fabricated and utilized to record the overpressure and acceleration of the snowpack resulting from detonation of pentolite cast boosters. Explosives were detonated 0-2 m above the snow surface, at 0.5 m increments. All sensors were placed within a 7 m radius of the explosive in soft slab and hard slab snow conditions. The data was used to characterize relationships between explosive size and location to the resulting overpressure and snow acceleration based on various snow parameters. The snow surface was shown to be able to reflect shockwaves, thus, increasing the shockwave pressure. It was shown that elevating an explosive off the snow surface resulted in greater overpressure and peak snowpack acceleration than surface detonations. Elevating an explosive was found to not influence the vertical or radial attenuation. Therefore raising a charge increased the volume of influence. Overpressure and acceleration were shown to be nonlinearly related to the explosive mass. Doubling the mass resulted in less than double the response. The acceleration of moist snow was determined to be less and the attenuation greater than for dry snow conditions. Hard slab conditions indicated lower acceleration and greater shockwave attenuation than soft slab snow. Snowpack peak acceleration and attenuation were shown to have little dependence on either the total snow water equivalent or snow density. For rock bed surfaces the shockwave was reflected back through the snow while meadow bed surfaces did not. This project verified past theoretical and experimental results, but further research would be beneficial for avalanche mitigation work. A continuation of this work could lead to increased efficiency and safety for the avalanche community.
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    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. Adams
    Granular 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.
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