945 resultados para particle size distribution


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The study of particulate systems is of great interest in many fields of science and technology. Soil, sediments, powders, granular materials, colloidal and particulate suspensions are examples of systems involving many size particles. For those systems, the statistical description of the particle size distribution (PSD), that is, the mathematical distribution that defines the relative amounts of particles present, sorted according to size, is a crutial issue. The PSD can be important in understanding soil hydraulic properties, the geological origin or sediments or the physical and chemical properties of granular materials and ceramics, among others.

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The study of granular systems is of great interest to many fields of science and technology. The packing of particles affects to the physical properties of the granular system. In particular, the crucial influence of particle size distribution (PSD) on the random packing structure increase the interest in relating both, either theoretically or by computational methods. A packing computational method is developed in order to estimate the void fraction corresponding to a fractal-like particle size distribution.

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Nowadays, translating information about hydrologic and soil properties and processes across scales has emerged as a major theme in soil science and hydrology, and suitable theories for upscaling or downscaling hydrologic and soil information are being looked forward. The recognition of low-order catchments as self-organized systems suggests the existence of a great amount of links at different scales between their elements. The objective of this work was to research in areas of homogeneous bedrock material, the relationship between the hierarchical structure of the drainage networks at hillslope scale and the heterogeneity of the particle-size distribution at pedon scale. One of the most innovative elements in this work is the choice of the parameters to quantify the organization level of the studied features. The fractal dimension has been selected to measure the hierarchical structure of the drainage networks, while the Balanced Entropy Index (BEI) has been the chosen parameter to quantify the heterogeneity of the particle-size distribution from textural data. These parameters have made it possible to establish quantifiable relationships between two features attached to different steps in the scale range. Results suggest that the bedrock lithology of the landscape constrains the architecture of the drainage networks developed on it and the particle soil distribution resulting in the fragmentation processes.

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Nowadays, translating information about hydrologic and soil properties and processes across scales has emerged as a major theme in soil science and hydrology, and suitable theories for upscaling or downscaling hydrologic and soil information are being looked forward. The recognition of low-order catchments as self-organized systems suggests the existence of a great amount of links at different scales between their elements. The objective of this work was to research in areas of homogeneous bedrock material, the relationship between the hierarchical structure of the drainage networks at hillslope scale and the heterogeneity of the particle-size distribution at pedon scale. One of the most innovative elements in this work is the choice of the parameters to quantify the organization level of the studied features. The fractal dimension has been selected to measure the hierarchical structure of the drainage networks, while the Balanced Entropy Index (BEI) has been the chosen parameter to quantify the heterogeneity of the particle-size distribution from textural data. These parameters have made it possible to establish quantifiable relationships between two features attached to different steps in the scale range. Results suggest that the bedrock lithology of the landscape constrains the architecture of the drainage networks developed on it and the particle soil distribution resulting in the fragmentation processes.

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This thesis is the first comprehensive study of important parameters relating to aerosols' impact on climate and human health, namely spatial variation, particle size distribution and new particle formation. We determined the importance of spatial variation of particle number concentration in microscale environments, developed a method for particle size parameterisation and provided knowledge about the chemistry of new particle formation. This is a significant contribution to our understanding of processes behind the transformation and dynamics of urban aerosols. This PhD project included extensive measurements of air quality parameters using state of the art instrumentation at each of the 25 sites within the Brisbane metropolitan area and advanced statistical analysis.

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The issue of using informative priors for estimation of mixtures at multiple time points is examined. Several different informative priors and an independent prior are compared using samples of actual and simulated aerosol particle size distribution (PSD) data. Measurements of aerosol PSDs refer to the concentration of aerosol particles in terms of their size, which is typically multimodal in nature and collected at frequent time intervals. The use of informative priors is found to better identify component parameters at each time point and more clearly establish patterns in the parameters over time. Some caveats to this finding are discussed.

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In this paper, we examine approaches to estimate a Bayesian mixture model at both single and multiple time points for a sample of actual and simulated aerosol particle size distribution (PSD) data. For estimation of a mixture model at a single time point, we use Reversible Jump Markov Chain Monte Carlo (RJMCMC) to estimate mixture model parameters including the number of components which is assumed to be unknown. We compare the results of this approach to a commonly used estimation method in the aerosol physics literature. As PSD data is often measured over time, often at small time intervals, we also examine the use of an informative prior for estimation of the mixture parameters which takes into account the correlated nature of the parameters. The Bayesian mixture model offers a promising approach, providing advantages both in estimation and inference.

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Three ochre samples (A (orange-red in colour), B (red) and C (purple)) from Clearwell Caves, (Gloucestershire, UK) have been examined using an integrated analytical methodology based on the techniques of IR and diffuse reflectance UV-visible-NIR spectroscopy, X-ray diffraction, elemental analysis by ICP-AES and particle size analysis. It is shown that the chromophore in each case is haematite. The differences in colour may be accounted for by (i) different mineralogical and chemical composition in the case of the orange ochre, where hi,,her levels of dolomite and copper are seen and (ii) an unusual particle size distribution in the case of the purple ochre. When the purple ochre was ground to give the same particle size distribution as the red ochre then the colours of the two samples became indistinguishable. An analysis has now been completed of a range of ochre samples with colours from yellow to purple from the important site of Clearwell Caves. (C) 2004 Elsevier B.V. All rights reserved.

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Three ochre samples (A (orange-red in colour), B (red) and C (purple)) from Clearwell Caves, (Gloucestershire, UK) have been examined using an integrated analytical methodology based on the techniques of IR and diffuse reflectance UV-visible-NIR spectroscopy, X-ray diffraction, elemental analysis by ICP-AES and particle size analysis. It is shown that the chromophore in each case is haematite. The differences in colour may be accounted for by (i) different mineralogical and chemical composition in the case of the orange ochre, where hi,,her levels of dolomite and copper are seen and (ii) an unusual particle size distribution in the case of the purple ochre. When the purple ochre was ground to give the same particle size distribution as the red ochre then the colours of the two samples became indistinguishable. An analysis has now been completed of a range of ochre samples with colours from yellow to purple from the important site of Clearwell Caves. (C) 2004 Elsevier B.V. All rights reserved.

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The influence of the size distribution of particles on the viscous property of an electrorheological fluid has been investigated by the molecular dynamic simulation method. The shear stress of the fluid is found to decrease with the increase of the variance sigma(2) of the Gaussian distribution of the particle size, and then reach a steady value when sigma is larger than 0.5. This phenomenon is attributed to the influence of the particle size distribution on the dynamic structural evolution in the fluid as well as the strength of the different chain-like structures formed by the particles.

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This paper reports on the effect of sonication on SAz-1 and SWy-1 montmorillonite suspensions. Changes in the size of the particles of these materials and modifications of their properties have been investigated. The variation of the particle size has been analyzed by DLS (dynamic light scattering). In all cases the clay particles show a bimodal distribution. Sonication resulted in a decrease of the larger modal diameter, as well as a reduction of its volume percentage. Simultaneously, the proportion of the smallest particles increases. After 60 min of sonication, SAz-1 presented a very broad particle size distribution with a modal diameter of 283 nm. On the other hand, the SWy-1 sonicated for 60 min presents a bimodal distribution of particles at 140 and 454 nm. Changes in the properties of the clay suspensions due to sonication were evaluated spectroscopically from dye-clay interactions, using Methylene Blue. The acidic sites present in the interlamellar region, which are responsible for dye protonation, disappeared after sonication of the clay. The changes in the size of the scattering particles and the lack of acidic sites after sonication suggest that sonication induces delamination of the clay particles. (c) 2008 Elsevier Inc. All rights reserved.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)