957 resultados para Granular Sludge


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Constitutive modeling in granular materials has historically been based on macroscopic experimental observations that, while being usually effective at predicting the bulk behavior of these type of materials, suffer important limitations when it comes to understanding the physics behind grain-to-grain interactions that induce the material to macroscopically behave in a given way when subjected to certain boundary conditions.

The advent of the discrete element method (DEM) in the late 1970s helped scientists and engineers to gain a deeper insight into some of the most fundamental mechanisms furnishing the grain scale. However, one of the most critical limitations of classical DEM schemes has been their inability to account for complex grain morphologies. Instead, simplified geometries such as discs, spheres, and polyhedra have typically been used. Fortunately, in the last fifteen years, there has been an increasing development of new computational as well as experimental techniques, such as non-uniform rational basis splines (NURBS) and 3D X-ray Computed Tomography (3DXRCT), which are contributing to create new tools that enable the inclusion of complex grain morphologies into DEM schemes.

Yet, as the scientific community is still developing these new tools, there is still a gap in thoroughly understanding the physical relations connecting grain and continuum scales as well as in the development of discrete techniques that can predict the emergent behavior of granular materials without resorting to phenomenology, but rather can directly unravel the micro-mechanical origin of macroscopic behavior.

In order to contribute towards closing the aforementioned gap, we have developed a micro-mechanical analysis of macroscopic peak strength, critical state, and residual strength in two-dimensional non-cohesive granular media, where typical continuum constitutive quantities such as frictional strength and dilation angle are explicitly related to their corresponding grain-scale counterparts (e.g., inter-particle contact forces, fabric, particle displacements, and velocities), providing an across-the-scale basis for better understanding and modeling granular media.

In the same way, we utilize a new DEM scheme (LS-DEM) that takes advantage of a mathematical technique called level set (LS) to enable the inclusion of real grain shapes into a classical discrete element method. After calibrating LS-DEM with respect to real experimental results, we exploit part of its potential to study the dependency of critical state (CS) parameters such as the critical state line (CSL) slope, CSL intercept, and CS friction angle on the grain's morphology, i.e., sphericity, roundness, and regularity.

Finally, we introduce a first computational algorithm to ``clone'' the grain morphologies of a sample of real digital grains. This cloning algorithm allows us to generate an arbitrary number of cloned grains that satisfy the same morphological features (e.g., roundness and aspect ratio) displayed by their real parents and can be included into a DEM simulation of a given mechanical phenomenon. In turn, this will help with the development of discrete techniques that can directly predict the engineering scale behavior of granular media without resorting to phenomenology.

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The effective refractive index of a kind of granular composite, which consists of granular metallic and magnetic inclusions with different radius embedded in a host medium, is theoretically investigated. Results show that for certain volume fractions of these two inclusions, the negative permittivity peak shifts to low frequency and the peak value increases with increasing radius ratio of the radius of magnetic granulae to that of metallic granulae. Simultaneously, peak value of permeability decreases with the radius ratio, and value peak shifts to high frequency with increasing volume fraction of magnetic inclusion. Therefore, the radius ratio can affect the effective refractive index considerably, and it is found that by adjusting the radius ratio, the refractive index may change between negative and positive values for certain volume fractions of the two inclusions. (c) 2005 Elsevier B.V. All rights reserved.

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Wastewater treatment reduces environmental contamination by removing gross solids and mitigating the effects of pollution. Treatment also reduces the number of indicator organisms and pathogens. In this work, the fates of two coliform bacteria, Escherichia coli and Serratia marcescens, were analyzed in an activated sludge process to determine the main mechanisms involved in the reduction of pathogenic microorganisms during wastewater treatment. These bacteria, modified to express green fluorescent protein, were inoculated in an activated sludge unit and in batch systems containing wastewater. The results suggested that, among the different biological factors implied in bacterial removal, bacterivorous protozoa play a key role. Moreover, a representative number of bacteria persisted in the system as free-living or embedded cells, but their distribution into liquid or solid fractions varied depending on the bacterium tested, questioning the real value of bacterial indicators for the control of wastewater treatment process. Additionally, viable but nonculturable cells constituted an important part of the bacterial population adhered to solid fractions, what can be derived from the competition relationships with native bacteria, present in high densities in this environment. These facts, taken together, emphasize the need for reliable quantitative and qualitative analysis tools for the evaluation of pathogenic microbial composition in sludge, which could represent an undefined risk to public health and ecosystem functions when considering its recycling.

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