Diffusive tortuosity factor of solid and soft cake layers: A random walk simulation approach

Kim, Albert S.; Chen, Huaiqun

doi:10.1016/j.memsci.2005.11.042

Cited by 61 publications

(31 citation statements)

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“…Dias et al (2006) further consider the function to be that of an inverse power law, but primarily for granular and spherical packings within the range of porosity 0.4-0.5. Moreover, the non-linear trend between tortuosity and porosity is found to be true for both systematic and random packings (Kim and Chen 2006, Zalc et al 2004, Moldrup et al 2001). Non-spherical models, such as those of Koponen (1998) and Alam et al (2006) suggest inverse linear proportionality between the two parameters.…”

Section: Characterisation Of Pore Spacementioning

confidence: 83%

Porous Particle-Polymer Composites

Alam¹

2011

Advances in Composite Materials - Analysis of Natural and Man-Made Materials

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Section: Characterisation Of Pore Spacementioning

confidence: 83%

Porous Particle-Polymer Composites

Alam¹

2011

Advances in Composite Materials - Analysis of Natural and Man-Made Materials

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“…Após realizado o cálculo das distâncias quadráticas médias, para as três direções, a tortuosidade é calculada a partir do conceito de difusividade efetiva, mostrado nas Equações 6, 7 e 8 [5,6]. (6 Foi realizado também um estudo de sensibilidade do valor de tortuosidade em relação ao número de iterações realizadas no algoritmo Andarilhos Aleatórios.…”

Section: Figura 4: Representação Simplificada Da Tortuosidadeunclassified

Reconstrução digital de volume de eletrodo de PaCOS para cálculo de porosidade e tortuosidade

et al. 2013

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RESUMOO objetivo do presente trabalho é aplicar técnicas de medição de porosidade e tortuosidade através da reconstrução digital de volume. A técnica pode ser aplicada em eletrodos reais de PaCOS onde a amostra é seccionada através de feixe de íons focalizado (FIF). A reconstrução é feita a partir das imagens de cada camada da amostra gerada pelo FIF.Os parâmetros geométricos, porosidade e tortuosidade, foram calculados a partir do empilhamento das imagens binarizadas. A porosidade foi obtida pela razão entre os voxels referentes aos poros e o volume total da amostra. A tortuosidade foi estimada com base no algoritmo Andarilhos Aleatórios, que simula as condições de difusão molecular, sem inserir um viés de direção preferencial.O uso da reconstrução 3D propiciou resultados de cálculo de porosidade mais precisos do que a classificação tradicional em duas dimensões. O modelo difusional descrito pelo algoritmo Andarilhos Aleatórios resultou em valores coerentes e aceitáveis do cálculo da tortuosidade.Palavras-chave: Feixe de íons focalizado, Processamento de Imagens, Pilhas a combustível de óxidos sólidos, porosidade, tortuosidade. ABSTRACTThe aim of this work is to make tortuosity and porosity measurements by the use of digital volume reconstruction technique. It can be applied on real SOFC electrodes where the sample is sliced by focused ion beam (FIB). The reconstruction is done from the images of each layer of the sample generated by FIB.The geometric parameters, such as porosity and tortuosity, were calculated from a stack of binary images. Porosity was obtained by the ratio between the voxels concerned to pores and the total sample volume. Tortuosity was measured by the use of the Random Walkers algorithm that simulates molecular diffusion conditions without adding a preferential direction bias.The use of 3D reconstruction provided results of porosity calculation more accurate than the traditional classification in two dimensions. The diffusional model described by Random Walkers algorithm represented coherent and well acceptable values for tortuosity.

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“…[17] In addition to the methods described so far, in the literature can be found others methodologies. For example, we can quote those based on the random walk method, [18] fractal modelling, [19,20] and Monte Carlo simulations. [21][22][23] In this work, we focus on the mass effective diffusion and dispersion coefficients for one porous medium composed by particles whose size follows a given probability density function.…”

Section: Introductionmentioning

confidence: 99%

Effective mass diffusion and dispersion in random porous media

2015

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In this work, the effect of the stochastic nature of porous medium on porosity, effective diffusion and mass dispersion was investigated. To this end, a methodology to build idealized media composed by solid particles with random size has been introduced. Gaussian and uniform probability distribution functions were employed to design the size and orientation of rectangular cylinders and cubes. Predictions of effective parameters were performed by using numerical procedures based on the volume averaging method. From the porosity and effective diffusion analysis, it was found that a minimum number of particles minimizes fluctuations of predictions. Thus, a minimum sampling size to measure properties was inferred. The minimum number of particles depends on the probability distribution functions and the dimensionality of particles used (cylinders or cubes). The methodology to build porous media also allows the creation of anisotropic media, and its effect is marked over the longitudinal and transverse components of effective diffusivity tensor. But this is not the case for the mass dispersion tensor, where the flow direction is the main cause for anisotropy. In fact, the flow taking place at pore‐scale increases noticeable the randomness of predictions of mass dispersion, specifically when the number of particles or the particle Péclet number are increased. This effect is more significant on the transverse mass dispersion.

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Diffusive tortuosity factor of solid and soft cake layers: A random walk simulation approach

Cited by 61 publications

References 50 publications

Porous Particle-Polymer Composites

Porous Particle-Polymer Composites

Reconstrução digital de volume de eletrodo de PaCOS para cálculo de porosidade e tortuosidade

Effective mass diffusion and dispersion in random porous media

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