267 resultados para Granulometry


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Green clay layers are reported from the Pliocene-Holocene intervals in five of the six sites drilled in the South China Sea (SCS) during Leg 184. Centimeter-scale discrete, discontinuous, and bioturbated layers, constituted by stiff and porous green clays, were observed, sometimes associated with iron sulfides and pyrite. Detailed mineralogical and geochemical analyses indicate that they differentiate from the host sediments in their higher content of iron, smectite, and mixed-layered clays and lower amounts of calcite, authigenic phosphorus, quartz, and organic matter. Although no glauconite was observed, the mineralogy and geochemistry of green clay layers, along with their geometrical relation to background sediments, suggest that they most likely represent the result of the first steps of glauconitization. Correlation between green layers and volcanic ash layers was suggested for green laminae observed elsewhere in Pacific sediments but was not confirmed at SCS sites. Statistical analysis of the temporal distribution of green layers in the records of the last million years suggests that green clay layers have become more frequent since 600 ka. Only at Site 1148 does the green layer record show a statistically significant cyclicity which may be related to orbital eccentricity. A possible influence of sea level variations, related both to climatic changes and tectonism, is postulated.

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The combination of permafrost history and dynamics, lake level changes and the tectonical framework is considered to play a crucial role for sediment delivery to El'gygytgyn Crater Lake, NE Russian Arctic. The purpose of this study is to propose a depositional framework based on analyses of the core strata from the lake margin and historical reconstructions from various studies at the site. A sedimentological program has been conducted using frozen core samples from the 141.5 m long El'gygytgyn 5011-3 permafrost well. The drill site is located in sedimentary permafrost west of the lake that partly fills the El'gygytgyn Crater. The total core sequence is interpreted as strata building up a progradational alluvial fan delta. Four macroscopically distinct sedimentary units are identified. Unit 1 (141.5-117.0 m) is comprised of ice-cemented, matrix-supported sandy gravel and intercalated sandy layers. Sandy layers represent sediments which rained out as particles in the deeper part of the water column under highly energetic conditions. Unit 2 (117.0-24.25 m) is dominated by ice-cemented, matrix-supported sandy gravel with individual gravel layers. Most of the Unit 2 diamicton is understood to result from alluvial wash and subsequent gravitational sliding of coarse-grained (sandy gravel) material on the basin slope. Unit 3 (24.25-8.5 m) has ice-cemented, matrix-supported sandy gravel that is interrupted by sand beds. These sandy beds are associated with flooding events and represent near-shore sandy shoals. Unit 4 (8.5-0.0 m) is ice-cemented, matrix-supported sandy gravel with varying ice content, mostly higher than below. It consists of slope material and creek fill deposits. The uppermost metre is the active layer (i.e. the top layer of soil with seasonal freeze and thaw) into which modern soil organic matter has been incorporated. The nature of the progradational sediment transport taking place from the western and northern crater margins may be related to the complementary occurrence of frequent turbiditic layers in the central lake basin, as is known from the lake sediment record. Slope processes such as gravitational sliding and sheet flooding occur especially during spring melt and promote mass wasting into the basin. Tectonics are inferred to have initiated the fan accumulation in the first place and possibly the off-centre displacement of the crater lake.

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Texture analysis and textural cues have been applied for image classification, segmentation and pattern recognition. Dominant texture descriptors include directionality, coarseness, line-likeness etc. In this dissertation a class of textures known as particulate textures are defined, which are predominantly coarse or blob-like. The set of features that characterise particulate textures are different from those that characterise classical textures. These features are micro-texture, macro-texture, size, shape and compaction. Classical texture analysis techniques do not adequately capture particulate texture features. This gap is identified and new methods for analysing particulate textures are proposed. The levels of complexity in particulate textures are also presented ranging from the simplest images where blob-like particles are easily isolated from their back- ground to the more complex images where the particles and the background are not easily separable or the particles are occluded. Simple particulate images can be analysed for particle shapes and sizes. Complex particulate texture images, on the other hand, often permit only the estimation of particle dimensions. Real life applications of particulate textures are reviewed, including applications to sedimentology, granulometry and road surface texture analysis. A new framework for computation of particulate shape is proposed. A granulometric approach for particle size estimation based on edge detection is developed which can be adapted to the gray level of the images by varying its parameters. This study binds visual texture analysis and road surface macrotexture in a theoretical framework, thus making it possible to apply monocular imaging techniques to road surface texture analysis. Results from the application of the developed algorithm to road surface macro-texture, are compared with results based on Fourier spectra, the auto- correlation function and wavelet decomposition, indicating the superior performance of the proposed technique. The influence of image acquisition conditions such as illumination and camera angle on the results was systematically analysed. Experimental data was collected from over 5km of road in Brisbane and the estimated coarseness along the road was compared with laser profilometer measurements. Coefficient of determination R2 exceeding 0.9 was obtained when correlating the proposed imaging technique with the state of the art Sensor Measured Texture Depth (SMTD) obtained using laser profilometers.