4.1 Article Proceedings Paper

Pore structure analysis of particle beds for fluid transport simulation during filtration

Journal

INTERNATIONAL JOURNAL OF MINERAL PROCESSING
Volume 73, Issue 2-4, Pages 281-294

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/S0301-7516(03)00080-2

Keywords

filtration; fluid flow; transport simulation; porous media; lattice Boltzmann method; X-ray microtomography

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Accurate assessment of the transport properties of porous media (in our case, filter cake) is of major importance in the development of improved filtration processes. Implications from these studies are important in the design and operation of filtration equipment in order to enhance the efficiency of this important solid-liquid separation process. The microstructure and connectivity of pore space are important features to describe detailed fluid flow phenomena in filter cake during fine particle filtration. In this regard, 3D characterization of pore structure is essential. The pore structure has to be described by parameters which are of special relevance to the interpretation of fluid transport phenomena. These parameters should be based on directly measured variables of the pore system and not inferred from indirect variables (such as those determined empirically from transport processes) valid only for a particular pore structure. In this way, fundamental relationships between pore structure and fluid transport at the microstructure level can be described. In order to achieve this level of sophistication, the three-dimensional interconnected pore structure of filter cake must be determined. Study of fluid transport phenomena in filter cake using X-ray microtomography (XMT) to characterize the complex three-dimensional pore geometry is discussed. On this basis, the lattice Boltzmann (LB) method is used to simulate fluid flow and to begin to establish a fundamental relationship between pore microstructure and effective transport coefficients. For example, can network analysis using skeletonization procedures be used to confirm fundamental relationships that might be developed? Eventually then, with this detailed model, design and operating variables could be optimized for improved filtration efficiency. (C) 2004 Elsevier B.V. All rights reserved.

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