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Skewed bridges have exhibited poorer performance during lateral earthquake loading when compared to non-skewed bridges (Apirakvorapinit et al. 2012; Elnashai et al. 2010). Results from small-scale laboratory tests by Rollins and Jessee (2012) and numerical modeling by Shamsabadi et al. (2006) suggest that skewed bridge abutments may provide only 35% of the non-skewed peak passive resistance when a bridge is skewed 45°. This reduction in peak passive force is of particular importance as 40% of the 600,000 bridges in the United States are skewed (Nichols 2012). Passive force-deflection results based on large-scale testing for this study largely confirm the significant reduction in peak passive resistance for abutments with longitudinal reinforced concrete wingwalls. Large-scale lateral load tests were performed on a non-skewed and 45° skewed abutment with densely compacted sand backfill. The 45° skewed abutment experienced a 54% reduction in peak passive resistance compared to the non-skewed abutment. The peak passive force for the 45° skewed abutment was estimated to occur at 5.0% of the backwall height compared to 2.2% of the backwall height for the non-skewed abutment. The 45° skewed abutment displayed evidence of rotation, primarily pushing the obtuse side of the abutment into the backfill, significantly more than the non-skewed abutment as it was loaded into the backfill. The structural and geotechnical response of the wingwalls was also monitored during large-scale testing. The wingwall on the obtuse side of the 45° skewed abutment experienced nearly 6 times the amount of horizontal soil pressure and 7 times the amount of bending moment compared to the non-skewed abutment. Pressure and bending moment distributions are provided along the height of the wingwall and indicate that the maximum moment occurs approximately 20 in (50.8 cm) below the top of the wingwall. A comparison of passive force per unit width suggests that MSE wall abutments provide 60% more passive resistance per unit width compared to reinforced concrete wingwall and unconfined abutment geometries at zero skew. These findings suggest that changes should be made to current codes and practices to properly account for skew angle in bridge design.

Passive force-deflection behavior for densely compacted backfills must be considered in bridge design to ensure adequate resistance to both seismic and thermally induced forces. Current codes and practices do not distinguish between skewed and non-skewed bridge abutment geometries; however, in recent years, numerical models and small-scale, plane-strain laboratory tests have suggested a significant reduction in passive force for skewed bridge abutments. Also, various case studies have suggested higher soil stresses might be experienced on the acute side of the skew angle. For these reasons, three large-scale tests were performed with abutment skew angles of 0, 15 and 30 degrees using an existing pile cap [11-ft (3.35-m) wide by 15-ft (4.57-m) long by 5.5-ft (1.68-m) high] and densely compacted sand backfill confined by MSE wingwalls. These tests showed a significant reduction in passive force (approximately 38% as a result of the 15 degree skew angle and 51% as a result of the 30° skew angle. The maximum passive force was achieved at a deflection of approximately 5% of the backwall height; however, a substantial loss in the rate of strength gain was observed at a deflection of approximately 3% of the backwall height for the 15° and 30° skew tests. Additionally, the soil stiffness appears to be largely unaffected by skew angle for small displacements. These results correlate very well with data available from numerical modeling and small-scale lab tests. Maximum vertical backfill displacement and maximum soil pressure measured normal to the skewed backwall face were located on the acute side of the skew for the 15° and 30° skew test. This observation appears to be consistent with observations made in various case studies for skewed bridge abutments. Also, the maximum outward displacement of the MSE wingwalls was located on the obtuse side of the skew. These findings suggest that changes should be made to current codes and practices to properly account for skew angle in bridge design.

Bridge abutments are designed to withstand lateral pressures from thermal expansion and seismic forces. Current design curves have been seen to dangerously over- and under-estimate the peak passive resistance and corresponding deflection of abutment backfills. Similar studies on passive pressure have shown that passive resistance changes with different types of constructed backfills. The effects of changing the length to width ratio, or including MSE wingwalls determine passive force-deflection relationships. The purpose of this study is to determine the effects of the wall heights and of the MSE support on passive pressure and backfill failure, and to compare the field results with various predictive methods. To compare the effects of backfill geometries, three large-scale tests with dense compact sand were performed with abutment backfill heights of 3 ft (0.91 m), 5.5 ft (1.68 m), and 5.5 ft (1.68 m) confined with MSE wingwalls. Using an existing pile cap 11 ft (3.35 m) wide and 5.5 ft (1.68 m) high, width to height ratios for the abutment backfills were 3.7 for the 3ft test, and 2.0 for the 5.5ft and MSE tests. The failure surface for the unconfined backfills exhibited a 3D geometry with failure surfaces extending beyond the edge of the cap, increasing the "effective width", and producing a failure "bulb". In contrast, the constraint provided by the MSE wingwalls produced a more 2D failure geometry. The "effective width" of the failure surface increased as the width to height ratio decreased. In terms of total passive force, the unconfined 5.5ft wall provided about 6% more resistance than the 5.5ft MSE wall. However, in terms of passive force/width the MSE wall provided about 70% more resistance than the unconfined wall, which is more consistent with a plane strain, or 2D, failure geometry. In comparison with predicted forces, the MSE curve never seemed to fit, while the 3ft and 5.5ft curves were better represented with different methods. Even with optimizing between both the unconfined curves, the predicted Log Spiral peak passive forces were most accurate, within 12% of the measured peak resistances. The components of passive force between the unconfined tests suggest the passive force is influenced more by frictional resistance and less by the cohesion as the height of the backwall increases.

Numerical Analysis of Passive Force on Skewed BridgeAbutments with Reinforced Concrete WingwallsScott Karl SnowDepartment of Civil and Environmental Engineering, BYU Master of Science Historically bridges with skewed abutments have proven more likely to fail during earthquake loadings (Toro et al, 2013) when compared to non-skewed bridges (Apirakvorapinit et al. 2012; Elnashai et al. 2010). Previous studies including small-scale laboratory tests by Jessee (2012), large-scale field tests by Smith (2014), and numerical modeling by Shamsabadi et al. (2006) have shown that 45° skewed bridge abutments experience a reduction in peak passive force by about 65%. With numerous skewed bridges in the United States, this study has great importance to the nation's infrastructure.The finite element models produced in this study model the large-scale field-testing performed by Smith (2014), which was performed to study the significant reduction in peak passive resistance for abutments with longitudinal reinforced concrete wingwalls. The finite element models largely confirm the findings of Smith (2014). Two models were created and designed to match the large-scale field tests and were used to calibrate the soil parameters for this study. Two additional models were then created by increasing the abutment widths from 11 feet to 38 feet to simulate a two-lane bridge. The 45° skewed 11-foot abutment experienced a 38% reduction in peak passive resistance compared to the non-skewed abutment. In contrast, the 45° skewed 38-foot abutment experienced a 65% reduction in peak passive resistance compared to the non-skewed abutment. When the wingwalls are extended 10 feet into the backfill the reduction decreased to 59% due to the change in effective skew angle.The finite element models generally confirmed the findings of Smith (2014). The results of the 11- and 38-foot abutment finite element models confirmed that the wingwall on the obtuse side of the 45° skewed abutments experienced approximately 4 to 5 times the amount of horizontal soil pressure and 5 times the amount of bending moment compared to the non-skewed abutment. Increases in the pressures and bending moments are likely caused by soil confined between the obtuse side of the abutment and the wingwall.A comparison of the 11- and 38-foot 45° skewed abutment models showed a decrease in the influence of the wingwalls as the abutment widened. The wingwall on the acute side of the 38-foot abutment developed approximately 50% of the horizontal soil pressure compared to the 11-foot abutment. The heave distribution of the 11-foot abutment showed approximately 1- to 2-inches of vertical displacement over a majority of the abutment backwall versus more than half of the 38-foot abutment producing ½ an inch or less.

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Integrated systems with billions of transistors on a single chip are a now reality. These systems include multi-core microprocessors and are built today using deca-nanometer devices organized into synchronous digital circuits. The movement of data within such systems is regulated by a set of predictable timing signals, called clocks, which must be distributed to a large number of sequential elements. Collectively, these clocks have a significant impact on the frequency of operation and, consequently, on the performance of the systems. The clocks are also responsible for a large fraction of the power consumed by these systems. The objective of this dissertation is to better understand clock distribution in order to identify opportunities and strategies for improvement by analyzing the conditions under which the optimal tradeoff between power and performance can be achieved, by modeling the constraints associated with local and global clocking, by evaluating the impact of noise, and by investigating promising new design strategies for future integrated systems.

Made available in DSpace on 2014-12-17T15:48:04Z (GMT). No. of bitstreams: 1 TiagoSS_DISSERT.pdf: 2900373 bytes, checksum: ea7bd73351348f5c75a5bf4f337c599f (MD5) Previous issue date: 2012-08-17 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / The segmentation of an image aims to subdivide it into constituent regions or objects that have some relevant semantic content. This subdivision can also be applied to videos. However, in these cases, the objects appear in various frames that compose the videos. The task of segmenting an image becomes more complex when they are composed of objects that are defined by textural features, where the color information alone is not a good descriptor of the image. Fuzzy Segmentation is a region-growing segmentation algorithm that uses affinity functions in order to assign to each element in an image a grade of membership for each object (between 0 and 1). This work presents a modification of the Fuzzy Segmentation algorithm, for the purpose of improving the temporal and spatial complexity. The algorithm was adapted to segmenting color videos, treating them as 3D volume. In order to perform segmentation in videos, conventional color model or a hybrid model obtained by a method for choosing the best channels were used. The Fuzzy Segmentation algorithm was also applied to texture segmentation by using adaptive affinity functions defined for each object texture. Two types of affinity functions were used, one defined using the normal (or Gaussian) probability distribution and the other using the Skew Divergence. This latter, a Kullback-Leibler Divergence variation, is a measure of the difference between two probability distributions. Finally, the algorithm was tested in somes videos and also in texture mosaic images composed by images of the Brodatz album / A segmenta??o de uma imagem tem como objetivo subdividi-la em partes ou objetos constituintes que tenham algum conte?do sem?ntico relevante. Esta subdivis?o pode tamb?m ser aplicada a um v?deo, por?m, neste, os objetos est?o presentes nos diversos quadros que comp?em o v?deo. A tarefa de segmentar uma imagem torna-se mais complexa quando estas s?o compostas por objetos que contenham caracter?sticas texturais, com pouca ou nenhuma informa??o de cor. A segmenta??o difusa, do Ingl?s fuzzy, ? uma t?cnica de segmenta??o por crescimento de regi?es que determina para cada elemento da imagem um grau de pertin?ncia (entre zero e um) indicando a confian?a de que esse elemento perten?a a um determinado objeto ou regi?o existente na imagem, fazendo-se uso de fun??es de afinidade para obter esses valores de pertin?ncia. Neste trabalho ? apresentada uma modifica??o do algoritmo de segmenta??o fuzzy proposto por Carvalho [Carvalho et al. 2005], a fim de se obter melhorias na complexidade temporal e espacial. O algoritmo foi adaptado para segmentar v?deos coloridos tratando-os como volumes 3D. Para segmentar os v?deos, foram utilizadas informa??es provenientes de um modelo de cor convencional ou de um modelo h?brido obtido atrav?s de uma metodologia para a escolha dos melhores canais para realizar a segmenta??o. O algoritmo de segmenta??o fuzzy foi aplicado tamb?m na segmenta??o de texturas, fazendo-se uso de fun??es de afinidades adaptativas ?s texturas de cada objeto. Dois tipos de fun??es de afinidades foram utilizadas, uma utilizando a distribui??o normal de probabilidade, ou Gaussiana, e outra utilizando a diverg?ncia Skew. Esta ?ltima, uma varia??o da diverg?ncia de Kullback- Leibler, ? uma medida da diverg?ncia entre duas distribui??es de probabilidades. Por fim, o algoritmo foi testado com alguns v?deos e tamb?m com imagens de mosaicos de texturas criadas a partir do ?lbum de Brodatz e outros

Les données d’expression génique sont reconnues comme étant de grande dimension, etnécessitant l’emploi de méthodes statistiques adaptées. Mais dans le contexte des essaisvaccinaux, d’autres mesures, comme par exemple les mesures de cytométrie en flux, sontégalement de grande dimension. De plus, ces données sont souvent mesurées de manièrelongitudinale. Ce travail est bâti sur l’idée que l’utilisation d’un maximum d’informationdisponible, en modélisant les connaissances a priori ainsi qu’en intégrant l’ensembledes différentes données disponibles, améliore l’inférence et l’interprétabilité des résultatsd’analyses statistiques en grande dimension. Tout d’abord, nous présentons une méthoded’analyse par groupe de gènes pour des données d’expression génique longitudinales. Ensuite,nous décrivons deux analyses intégratives dans deux études vaccinales. La premièremet en évidence une sous-expression des voies biologiques d’inflammation chez les patientsayant un rebond viral moins élevé à la suite d’un vaccin thérapeutique contre le VIH. Ladeuxième étude identifie un groupe de gènes lié au métabolisme lipidique dont l’impactsur la réponse à un vaccin contre la grippe semble régulé par la testostérone, et donc liéau sexe. Enfin, nous introduisons un nouveau modèle de mélange de distributions skew t àprocessus de Dirichlet pour l’identification de populations cellulaires à partir de donnéesde cytométrie en flux disponible notamment dans les essais vaccinaux. En outre, nousproposons une stratégie d’approximation séquentielle de la partition a posteriori dans lecas de mesures répétées. Ainsi, la reconnaissance automatique des populations cellulairespourrait permettre à la fois une avancée pratique pour le quotidien des immunologistesainsi qu’une interprétation plus précise des résultats d’expression génique après la priseen compte de l’ensemble des populations cellulaires. / Gene expression data is recognized as high-dimensional data that needs specific statisticaltools for its analysis. But in the context of vaccine trials, other measures, such asflow-cytometry measurements are also high-dimensional. In addition, such measurementsare often repeated over time. This work is built on the idea that using the maximum ofavailable information, by modeling prior knowledge and integrating all data at hand, willimprove the inference and the interpretation of biological results from high-dimensionaldata. First, we present an original methodological development, Time-course Gene SetAnalysis (TcGSA), for the analysis of longitudinal gene expression data, taking into accountprior biological knowledge in the form of predefined gene sets. Second, we describetwo integrative analyses of two different vaccine studies. The first study reveals lowerexpression of inflammatory pathways consistently associated with lower viral rebound followinga HIV therapeutic vaccine. The second study highlights the role of a testosteronemediated group of genes linked to lipid metabolism in sex differences in immunologicalresponse to a flu vaccine. Finally, we introduce a new model-based clustering approach forthe automated treatment of cell populations from flow-cytometry data, namely a Dirichletprocess mixture of skew t-distributions, with a sequential posterior approximation strategyfor dealing with repeated measurements. Hence, the automatic recognition of thecell populations could allow a practical improvement of the daily work of immunologistsas well as a better interpretation of gene expression data after taking into account thefrequency of all cell populations.