O propósito geral desta tese foi modelar a dinâmica do retroespalhamento SAR-X ao longo de um pacote superficial de neve seca através do uso de uma ferramenta computacional de modelagem de micro-ondas (RF Module®, PDETOOL®, MATLAB®), baseado na física da interação entre o feixe de micro–ondas e este pacote de neve, e executar a aplicação de métodos estatísticos para geração de relações entre variáveis estratigráficas desse pacote de neve e o respectivo retroespalhamento SAR-X observado. Para tanto, o presente trabalho buscou avançar na organização de um modelo analítico para o processo de interação entre um feixe de micro–ondas na banda X e o pacote de neve superficial, aplicando ferramentas computacionais para a resolução dos equacionamentos que compõem esse problema. Como área de estudo, delimitou–se a porção ocidental antártica, especificamente junto à área da geleira Union. O modelo de retroespalhamento utilizado pautou–se na consideração do Modelo de Transferência Radiativa (MTR), adotando como variáveis principais a profundidade da neve acumulada, a rugosidade da superfície (interface ar–neve e neve–sologelo), o tamanho dos cristais de neve (tamanho dos grãos), o perfil de densidade da neve acumulada e as características das camadas de neve que formam o pacote de neve superficial (espessura, forma da interface entre camadas, variação dielétrica entre camadas, dentre outros). Posteriormente, através da reversão modelagem estatística do modelo de retroespalhamento criado, foram obtidos dados estratigráficos indiretos modelados (número médio de camadas de neve, densidade média do pacote de neve superficial e tamanho médio dos grãos de neve), permitindo a inferência de variáveis da estratigrafia local a partir de dados de retroespalhamento SAR COSMO–SkyMed, banda X. Por fim, a comparação entre os valores modelados e aqueles observados em campo para a estratigrafia e para o retroespalhamento permitiram estimativas do desempenho da modelagem proposta. Para fins de validação desta modelagem, foram considerados dados comuns de entrada, constituídos de dados estratigráficos e de temperatura da neve em um perfil de 2 m de profundidade e dados SAR–X COSMO–SkyMed (modo de aquisição Stripmap/Himage com resolução espacial de 3x3 m) na banda X coletados na região da geleira Union no verão antártico de 2011–2012. Como resultados, foram obtidas equações analíticas para estimativa do tamanho médio dos grãos de neve, número médio de camadas espalhadoras e densidade média do pacote de neve superficial a partir de dados de retroespalhamento SAR– banda X, com consistência estatística mínima estimada de 86% (R² ≥ 86%). Já o modelo de retroespalhamento utilizado, tendo seus resultados comparados aos dados de retroespalhamento in situ COSMO–SkyMed exibiram estimativas com R² da ordem de 90% ou maior, o que é considerado estatísticamente adequado. Este trabalho traz como contribuição a implementação computacional via ferramenta de modelagem de um modelo de retroespalhamento SAR–X, voltado para massas de neve seca, e propõe a obtenção de dados estratigráficos a partir de dados de retroespalhamento SAR–X com o uso de equações determinadas por regressão estatística. Isto permitiu a espacialização de variáveis estratigráficas em zonas de neve seca a partir de dados SAR obtidos ao longo da banda X. Cabe ressaltar o fato de que devido ao limitado número de amostras de campo (7 amostras), a consistência estatística e a confiabilidade dos resultados deve ser tomada com ressalva, quando considerada a análise glaciológica da variação nos parâmetros do pacote de neve, cabendo melhores testes e análises em sua aplicação. / The present thesis proposes an analytical model for interaction between a beam of microwaves in the X band and surface snowpack. To this end, statistical analysis were performed with SAR-X backscattering data and reference data from snowpits focusing the interaction between the microwave beam and the snowpack in dry snow areas. Numerical methods were employed for solution of differential equations that make up this issue. The model was proposed for Union Glacier, located in the West Antarctic Ice Sheetregarding a study area including the Antarctic western portion, recognized as the Union Glacier. The backscattering model used was based under the assumption of the Radiative Transfer Model (RTM), considering as main variables the depth of accumulated snow, the surface roughness (air-snow interface and snow-ice interface), the size of snow crystals (grain size), the density profile of the accumulated snow and snow characteristics of the layers forming the surface snowpack (thickness, shape of the interface between layers variation between dielectric layers, among others). After that, reversal statistical modelling of backscatter was performed to estimate stratigraphic parameters of the snowpack usingdata allowing the local stratigraphy of estimated variables SAR backscatter data from COSMO-SkyMed satellite. To validate the proposed model, the same input data were considered for all experiments performed experiments. These data were made up of snow stratigraphic data and snow temperature data in a 2 m depth glaciological profiles (snowpits) 2m depth and data SAR-X COSMO-SkyMed X-band SAR data (acquisition mode Stripmap / Himage with 3x3 m spatial resolution 3x3 m) acquired atin Union Glacier snowpits and remote sensing SAR data during summer 2011-2012. The results showed average density of the snow pack surface from SAR-X backscatter data SAR-X with R² ≥ 86%. The main contribution of this work is the resulting model for SAR-X backscattering for dry snow masses, which was proved to be statistically consistent with the ground truth data. Even with limited reference data, this result indicates the soundness of the proposed approach, allowing the estimation of spatial distribution ofvariations in stratigraphic parameters of the snowpack variables in dry snow areas from SAR X-band SAR data over the X band. However, snowpack parameters estimated by the method should be used carefully, as the input data used for model development may underestimate all possible variations found at the snow surface of Union Glacier.

O propósito geral desta tese foi modelar a dinâmica do retroespalhamento SAR-X ao longo de um pacote superficial de neve seca através do uso de uma ferramenta computacional de modelagem de micro-ondas (RF Module®, PDETOOL®, MATLAB®), baseado na física da interação entre o feixe de micro–ondas e este pacote de neve, e executar a aplicação de métodos estatísticos para geração de relações entre variáveis estratigráficas desse pacote de neve e o respectivo retroespalhamento SAR-X observado. Para tanto, o presente trabalho buscou avançar na organização de um modelo analítico para o processo de interação entre um feixe de micro–ondas na banda X e o pacote de neve superficial, aplicando ferramentas computacionais para a resolução dos equacionamentos que compõem esse problema. Como área de estudo, delimitou–se a porção ocidental antártica, especificamente junto à área da geleira Union. O modelo de retroespalhamento utilizado pautou–se na consideração do Modelo de Transferência Radiativa (MTR), adotando como variáveis principais a profundidade da neve acumulada, a rugosidade da superfície (interface ar–neve e neve–sologelo), o tamanho dos cristais de neve (tamanho dos grãos), o perfil de densidade da neve acumulada e as características das camadas de neve que formam o pacote de neve superficial (espessura, forma da interface entre camadas, variação dielétrica entre camadas, dentre outros). Posteriormente, através da reversão modelagem estatística do modelo de retroespalhamento criado, foram obtidos dados estratigráficos indiretos modelados (número médio de camadas de neve, densidade média do pacote de neve superficial e tamanho médio dos grãos de neve), permitindo a inferência de variáveis da estratigrafia local a partir de dados de retroespalhamento SAR COSMO–SkyMed, banda X. Por fim, a comparação entre os valores modelados e aqueles observados em campo para a estratigrafia e para o retroespalhamento permitiram estimativas do desempenho da modelagem proposta. Para fins de validação desta modelagem, foram considerados dados comuns de entrada, constituídos de dados estratigráficos e de temperatura da neve em um perfil de 2 m de profundidade e dados SAR–X COSMO–SkyMed (modo de aquisição Stripmap/Himage com resolução espacial de 3x3 m) na banda X coletados na região da geleira Union no verão antártico de 2011–2012. Como resultados, foram obtidas equações analíticas para estimativa do tamanho médio dos grãos de neve, número médio de camadas espalhadoras e densidade média do pacote de neve superficial a partir de dados de retroespalhamento SAR– banda X, com consistência estatística mínima estimada de 86% (R² ≥ 86%). Já o modelo de retroespalhamento utilizado, tendo seus resultados comparados aos dados de retroespalhamento in situ COSMO–SkyMed exibiram estimativas com R² da ordem de 90% ou maior, o que é considerado estatísticamente adequado. Este trabalho traz como contribuição a implementação computacional via ferramenta de modelagem de um modelo de retroespalhamento SAR–X, voltado para massas de neve seca, e propõe a obtenção de dados estratigráficos a partir de dados de retroespalhamento SAR–X com o uso de equações determinadas por regressão estatística. Isto permitiu a espacialização de variáveis estratigráficas em zonas de neve seca a partir de dados SAR obtidos ao longo da banda X. Cabe ressaltar o fato de que devido ao limitado número de amostras de campo (7 amostras), a consistência estatística e a confiabilidade dos resultados deve ser tomada com ressalva, quando considerada a análise glaciológica da variação nos parâmetros do pacote de neve, cabendo melhores testes e análises em sua aplicação. / The present thesis proposes an analytical model for interaction between a beam of microwaves in the X band and surface snowpack. To this end, statistical analysis were performed with SAR-X backscattering data and reference data from snowpits focusing the interaction between the microwave beam and the snowpack in dry snow areas. Numerical methods were employed for solution of differential equations that make up this issue. The model was proposed for Union Glacier, located in the West Antarctic Ice Sheetregarding a study area including the Antarctic western portion, recognized as the Union Glacier. The backscattering model used was based under the assumption of the Radiative Transfer Model (RTM), considering as main variables the depth of accumulated snow, the surface roughness (air-snow interface and snow-ice interface), the size of snow crystals (grain size), the density profile of the accumulated snow and snow characteristics of the layers forming the surface snowpack (thickness, shape of the interface between layers variation between dielectric layers, among others). After that, reversal statistical modelling of backscatter was performed to estimate stratigraphic parameters of the snowpack usingdata allowing the local stratigraphy of estimated variables SAR backscatter data from COSMO-SkyMed satellite. To validate the proposed model, the same input data were considered for all experiments performed experiments. These data were made up of snow stratigraphic data and snow temperature data in a 2 m depth glaciological profiles (snowpits) 2m depth and data SAR-X COSMO-SkyMed X-band SAR data (acquisition mode Stripmap / Himage with 3x3 m spatial resolution 3x3 m) acquired atin Union Glacier snowpits and remote sensing SAR data during summer 2011-2012. The results showed average density of the snow pack surface from SAR-X backscatter data SAR-X with R² ≥ 86%. The main contribution of this work is the resulting model for SAR-X backscattering for dry snow masses, which was proved to be statistically consistent with the ground truth data. Even with limited reference data, this result indicates the soundness of the proposed approach, allowing the estimation of spatial distribution ofvariations in stratigraphic parameters of the snowpack variables in dry snow areas from SAR X-band SAR data over the X band. However, snowpack parameters estimated by the method should be used carefully, as the input data used for model development may underestimate all possible variations found at the snow surface of Union Glacier.

This study investigates a way to characterize the geology and biology of the seafloor in two Marine Protected Areas on the West Florida Shelf. Characterization of benthic habitats needs to include sufficient detail to represent the complex and heterogeneous bottom types. Characterizations can be interpreted from multiple data sets and displayed as benthic habitat maps. Multibeam sonar bathymetry and backscatter provide full spatial data coverage, but interpretation of such data requires some form of ground truth (to characterize the habitat). Imagery from towed underwater video provides continuous transects of seafloor data, which provide a more efficient method than data from sediment grabs, stationary cameras, or video from slow-moving remotely-operated vehicles while a ship is on station. Two Marine Protected Areas, Steamboat Lumps and Madison-Swanson, were previously mapped by the USGS using a 95 kHz multibeam sonar system. Researchers at the University of South Florida, using a 300 kHz high-resolution multibeam sonar in 2002 and a 400 kHz high-resolution multibeam sonar in 2016, filled in the northeast triangular portion of Madison-Swanson. Bathymetry and backscatter data were compared to towed underwater-video observations. A modified version of the Coastal and Marine Ecological Classification Standard (CMECS), utilizing a scale-based hierarchy, was used for habitat characterization of video images. Identifiers from the geoform and substrate components of CMECS, as well as substrate-influencing biologic components, were characterized using still images at 15-second intervals from towed underwater video collected using the Camera-Based Assessment Survey System (C-BASS). These characterizations were then georeferenced (located in three-dimensional space) for comparison with bathymetry and backscatter data. In Steamboat Lumps, eight substrate variations were identified from video, while in Madison-Swanson 27 substrate variations were identified, including many combinations of hard and soft substrate types. Four new hard-bottom textures are identified from video in Madison-Swanson: exposed high-relief, moderate-relief, and low-relief hard bottom, as well as covered low-relief hard bottom identified by the presence of attached biota. Hard- and mixed-bottom substrate types identified from video are more heterogeneous than can be resolved from 95 kHz Kongsberg EM 1002 multibeam sonar bathymetry and beam-averaged backscatter. However, in soft bottom areas, more changes are evident in beam-averaged backscatter than are visible in video, though this may be attributed to changes in sonar settings. This does not appear to be the case with high-resolution and ultra-high resolution multibeam sonars, such as the 300 kHz Kongsberg EM 3000 and the 400 kHz Reson SeaBat 7125, which can use time-series rather than beam-averaged backscatter. Analyses of the multibeam bathymetry data indicate that 94.5% of Steamboat Lumps is “flat” (slope < 5°) versus “sloping” for the remaining area (5° < slope < 30°). Only 87% of Madison-Swanson is “flat” versus “sloping”. Both marine protected areas have very low rugosity, i.e., the surface of the seafloor is nearly planar.

The four pillars of material science and engineering namely structure, processing, properties and performance form the so-called material paradigm. At the heart of the material paradigm is materials characterization, which is used to measure and identify the relationships. Materials Characterization typically reconstructing the conditions giving rise to a measurement, a classic inverse problem. The solutions of these inverse problems are under or over determined and not unique. The solutions of these inverse problems can be greatly improved if accurate forward models exist for these characterization experiments. In this thesis, we will be focusing of developing forward models for electron diffraction modalities. Specifically, four different forward models for electron diffraction, namely the Electron Backscatter Diffraction, Electron Channeling Patterns, Precession Electron Diffraction and Transmission kikuchi Diffraction modalities are presented. Further, these forward models are applied to important materials characterization problems, including diffraction pattern indexing using the dictionary approach and forward model based orientation refinement. Finally, a novel pole figure inversion algorithm using the cubochoric representation and model based iterative reconstruction is also presented.

Being able to predict the evolution of plastic deformation at the microstructural scale is of paramount importance in the engineering of materials for advanced applications. However, this is not straightforward because of the multiscale nature of deformation heterogeneity, both in space and time . The present thesis combines four related studies in a coherent work, which is aimed to develop experimental methods for studying crystal plasticity at the micro and mesoscale. A novel methodology for gold remodelling is initially proposed and used to apply high-density speckle patterns on the surface of stainless steel specimens. The unique proprieties of the speckle pattern enabled plastic deformation mapping with submicron resolution using digital image correlation (HDIC). It was therefore possible to study the concomitant evolution of microbands and transgranular deformation bands in such alloy. High-resolution deformation mapping also enabled comparison with high-resolution electron backscatter diffraction (EBSD) observations. The only partial correspondence of results proved the limits of EBSD in characterizing plastic deformation. The cause of such limitation is later identified in the reduced sensitivity to lattice slip of the EBSD technique. Hence, a novel method of HDIC data analysis is proposed to separate the contributions of lattice slip and lattice rotation from the deformation mapping. The method is adopted to characterize plasticity in austenitic stainless steel and at the plastic deformation zone (PDZ) around a silicon particle embedded in a softer aluminum matrix. Results show that the proposed experimental methodology has the unique capability of providing a complete description of the micro and mesoscale mechanics of crystal plasticity. HDIC therefore emerges as a key technique in the development of accurate physical-based multiscale crystal plasticity models.

This thesis deals with the design of external backscatter modulator for RFID tag emulator, which is used in UHF band. This modulator is connected with the Universal Software Radio Peripheral and antenna. Realization of a backscatter modulation contains switching between a matched load and an unmatched load. Impedance of the unmatched load is continuously adjustable. Result of this thesis is function prototype.

Thesis advisor: Seth C. Kruckenberg / Quantitatively describing the deformational behavior (i.e. the rheology) of lower crustal materials has proven challenging due to the highly variable nature of structural and compositional fabrics in the lower crust. Further, many flow laws describing the rheology of monophase aggregates are experimentally derived and do not necessarily apply to polyphase materials, such as gabbro, that dominate the lower crust. Here, we present the results of integrated microstructural analysis and electron backscatter diffraction (EBSD) textural analysis from exhumed lower crustal granulites in the Mount Hay block of central Australia. The preservation of heterogeneous mafic and felsic granulites containing monophase and/or polyphase mixtures of anorthite, pyroxene, and quartz (interlayered on the mm- to m-scale) make this region uniquely suited for advancing our knowledge of the processes that affect deformation and the rheology of the lower crust. Forty-two samples from distinct structural and compositional domains were chosen to compare the microstructural record of deformation, the development of crystallographic textures, and to provide estimates of lower crustal rheology and deformation conditions. Full thin-section maps of crystallographic texture were produced using EBSD methods. The resultant orientation maps were processed to characterize crystallographic textures in all constituent phases, and all other quantifiable aspects of the rock microstructure (e.g., grain size, grain shape, misorientation axes). The EBSD analysis reveals the presence of strong crystallographic preferred orientations (CPO) in nearly all constituent phases, suggesting deformation dominated by dislocation creep. Differential stresses during deformation are calculated using grain size piezometry for all major phases, and range between 34-54 MPa in quartz within monophase layers. Two-pyroxene geothermometry was used to constrain deformation temperatures to ca. 780-810 C. Based on the estimated CPO patterns, stress, and temperature, we quantify strain rates and effective viscosities of all major phases through application of monophase flow laws. Monophase strain rates range from 2.10 x 10-12 s-1 to 1.56 x 10-11 s-1 for quartz, 4.68 x 10-15 s-1 to 2.48 x 10-13 s-1 for plagioclase feldspar, 1.56 x 10-18 s-1 to 1.64 x 10-16 s-1 for enstatite, and 5.66 x 10-16 s-1 to 1.00 x 10-14 s-1 for diopside. The determined flow law variables used for monophase calculations were subsequently applied to two different models – the Minimized Power Geometric model of Huet et al. (2014) and the Asymptotic Expansion Homogenization (AEH) method of Cook (2006) – in order to calculate a bulk aggregate viscosity of the polyphase material. At a strain rate of 10-14 s-1, polyphase effective viscosities for our samples range from 3.07 x 1020 to 2.74 x 1021 Pa·s. We find that the bulk viscosity of heterogeneous, gabbroic lower crust in the Mount Hay region lies between that of monophase plagioclase and monophase quartz, and varies as a function of composition. These results are consistent with past modeling studies and geophysical estimates. / Thesis (MS) — Boston College, 2019. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Earth and Environmental Sciences.

Satellite radiometers are used to remotely measure properties of the Earth's surface. Radiometers enable wide spatial coverage and daily temporal coverage. Radiometer measurements are used in a wide array of applications, including freeze/thaw states inference, vegetation index calculations, rainfall estimation, and soil moisture estimation. Resolution enhancement of these radiometer measurements enable finer details to be resolved and improve our understanding of Earth. The Soil Moisture Active Passive (SMAP) radiometer was launched in April 2014 with a goal to produce high resolution soil moisture estimates. However, due to hardware failure of the radar channels, prepared algorithms could no longer be used. Current algorithms utilize a narrow spatial and temporal overlap between the SMAP radiometer and the SENTINEL-1 radar to produce high resolution soil moisture estimates that are spatially and temporally limited. This thesis explores the use of resolution enhancing algorithms to produce high resolution soil moisture estimates without the spatial coverage limitations caused by using multiple sensors. Two main approaches are considered: calculating the iterative update in brightness temperature and calculating the update in soil moisture. The best performing algorithm is the Soil Moisture Image Reconstruction (SMIR) algorithm that is a variation of the Radiometer form of the Scatterometer Image Reconstruction (rSIR) algorithm that has been adapted to operate in parameter space. This algorithm utilizes a novel soil moisture measurement response function (SMRF) in the reconstruction. It matches or exceeds the performance of other algorithms and allows for wide spatial coverage.

Scatterometry and radiometry are used to obtain measurements of Earth properties with extensive spatial coverage at daily or near-daily temporal resolution. Their measurements are used in many climate studies and weather applications, such as iceberg tracking, ocean wind estimation, and volumetric soil moisture measurements. The spatial resolution of these data products ranges from a few kilometers to tens of kilometers. Techniques to enhance the spatial resolution of these products help reveal finer scale features, but come at the cost of increased noise. This thesis explores the application of neural networks as a possible method to handle the noise and uncertainty in enhanced resolution scatterometer and radiometer data products. The specific sensors discussed are the Advanced Scatterometer (ASCAT) and its Ultrahigh Resolution (UHR) winds, and the Soil Moisture Active Passive (SMAP) radiometer and its soil moisture measurements. ASCAT UHR winds have already been validated in previous studies [1], but inherent ambiguity in the wind retrieval model couples with higher noise levels to decrease overall accuracy. Neural networks are tested as an alternate modeling method to possibly improve the accuracy compared with the current method. It is found that the feed forward neural networks tested are able to accurately estimate winds in most calculations, but struggle with the same ambiguity that occurs in the current model. The neural networks handle this ambiguity inconsistently, which results in worse overall network performance compared to the current wind retrieval method. For the SMAP soil moisture measurements, the radiometer form of the Scatterometer Image Reconstruction algorithm is validated as a method to enhance resolution. While the increased noise at higher resolution does worsen overall accuracy, the performance remains within about 0.04 cm^3 cm^−3 RMSE of a validated soil moisture product, suggesting that fine scale features revealed as resolution is enhanced are accurate. Corrections to the soil moisture extraction model used in these tests could further improve these results. Neural networks are then applied and compared with the theory-based approach to extract soil moisture from the brightness temperature measurements, and are found to give slightly more accurate results than the theoretical model, though with somewhat higher error variance.

Further understanding of mesoscale slip mechanics is crucial to future development of polycrystalline metals with improved performance. The research contained within this thesis aims to characterize localized mesoscale slip on slip bands further through two studies. First, a comprehensive comparison of slip system identification techniques was carried out to further validate each method as well as compare advantages and disadvantages of each. Second, slip bands in the presence of grain boundaries were studied to better characterize the dislocation content and behavior. In the first study, the use of SEM-DIC, AFM, ECCI, and HR-EBSD to characterize slip-system activity was assessed on the same material volume of Ti-7Al. This study presents a robust comparison of the various methods for the first time, including an assessment of their advantages and disadvantages, and how they can be used effectively in a complementary manner. The analysis of the different approaches was carried out in a blind manner independently at three different universities. A Ti-7Al specimen was deformed in uniaxial tension to approximately 3% axial strain, and the active slip systems were independently identified using (i) trace analysis; (ii) in-SEM digital image correlation, (iii) observations of residual dislocations from ECCI, and (iv) long-range rotation gradients through HR-EBSD, with consistent trace identification in all cases. Displacement data from AFM was used to augment the SEM-DIC displacement data by providing complementary out of plane displacement information. Furthermore, short-range dislocation gradients (measured by DIC) provided insight into the residual geometrically necessary dislocation (GND) content, and was consistent with the GND content extracted from EBSD data and ECCI images, confirming the presence of residual GNDs on the dominant slip systems resulting in visible slip bands. These approaches can be used in tandem to provide multi-modal information on slip band identification, strain and orientation gradients, out-of-plane displacements, and the presence of GNDs and SSDs, all of which can be used to inform and validate the development of dislocation-based crystal plasticity and strain gradient models. In the second study, shear strain profiles along slip bands in a modified Rolls-Royce nickel superalloy (RR1000) were analyzed for a tensile sample deformed by 2%. The strain increased with distance away from a grain boundary (GB), with maximum shear strain towards the center of the grain, indicating that dislocation nucleation generally occurred in the grain interior. The strain gradients in the neighborhood of the GBs were quantified and generally correlated with rotation about the active slip system line direction. This leads to an ability to determine the active slip system in these regions. The dislocation spacing and pileup stresses were inferred. The dislocation spacing closely follows an Eshelby analytical solution for a single ended pileup of dislocations under an applied stress. The distribution of pileup stress values for GBs of a given misorientation angle follows a log-normal distribution, with no correlation between the pileup stress and the GB misorientation angle. Furthermore, there is no observed correlation between various transmissivity factors and slip band pileup stress. Hence it appears that the obstacle strength of any of the observed GBs is adequate to facilitate the dislocation pileups present in the slip bands. However, slip band transmission does correlate with transmissivity factors, with the current study focusing on the Luster and Morris m'-factor. Observation of strain profiles of transmitted bands indicate dislocation nucleation locations.