A Unified Pore Network Model for Evaluation of Flow Properties from Pore Size Distribution

2021 ◽  
Author(s):  
Y. Yang
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Network Model ◽  
Pore Network ◽  
Pore Network Model ◽  
Flow Properties

scholarly journals Steady-State Water Drainage by Oxygen in Anodic Porous Transport Layer of Electrolyzers: A 2D Pore Network Study

Processes ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 362 ◽  
Author(s):  
Haashir Altaf ◽  
Nicole Vorhauer ◽  
Evangelos Tsotsas ◽  
Tanja Vidaković-Koch
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Network Model ◽  
Phase Interface ◽  
Pore Network ◽  
Transport Layer ◽  
Pore Network Model ◽  
Network Simulations ◽  
The Impact

Recently, pore network modelling has been attracting attention in the investigation of electrolysis. This study focuses on a 2D pore network model with the purpose to study the drainage of water by oxygen in anodic porous transport layers (PTL). The oxygen gas produced at the anode catalyst layer by the oxidation of water flows counter currently to the educt through the PTL. When it invades the water-filled pores of the PTL, the liquid is drained from the porous medium. For the pore network model presented here, we assume that this process occurs in distinct steps and applies classical rules of invasion percolation with quasi-static drainage. As the invasion occurs in the capillary-dominated regime, it is dictated by the pore structure and the pore size distribution. Viscous and liquid film flows are neglected and gravity forces are disregarded. The curvature of the two-phase interface within the pores, which essentially dictates the invasion process, is computed from the Young Laplace equation. We show and discuss results from Monte Carlo pore network simulations and compare them qualitatively to microfluidic experiments from literature. The invasion patterns of different types of PTLs, i.e., felt, foam, sintered, are compared with pore network simulations. In addition to this, we study the impact of pore size distribution on the phase patterns of oxygen and water inside the pore network. Based on these results, it can be recommended that pore network modeling is a valuable tool to study the correlation between kinetic losses of water electrolysis processes and current density.

scholarly journals Pore network model of primary freeze drying

2018 ◽  
Author(s):  
Nicole Vorhauer ◽  
P. Först ◽  
H. Schuchmann ◽  
E. Tsotsas
Keyword(s):  
Heat Transfer ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Network Model ◽  
Pore Network ◽  
Vapor Transport ◽  
Pore Network Model ◽  
Sublimation Front ◽  
The Impact

The pore scale progression of the sublimation front during primary freeze drying depends on the local vapor transport and the local heat transfer as well. If the pore space is size distributed, vapor and heat transfer may spatially vary. Beyond that, the pore size distribution can substantially affect the physics of the transport mechanisms if they occur in a transitional regime. Exemplarily, if the critical mean free path is locally exceeded, the vapor transport regime passes from viscous flow to Knudsen diffusion. At the same time, the heat transfer is affected by the local ratio of pore space to the solid skeleton. The impact of the pore size distribution on the transitional vapor and heat transfer can be studied by pore scale models such as the pore network model. As a first approach, we present a pore network model with vapor transport in the transitional regime between Knudsen diffusion and viscous flow at constant temperature in the dry region. We demonstrate the impact of pore size distribution, temperature and pressure on the vapor transport regimes. Then we study on the example of a 2D square lattice, how the presence of micro and macro pores affects the macroscopic progression of the sublimation front.   Keywords: pore size distribution; transitional vapor transport; pore network model; fractured sublimation front.

scholarly journals Pore Network Analysis of Zone Model for Porous Media Drying

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Yuan Yuejin ◽  
Zhao Zhe ◽  
Nie Junnan ◽  
Xu Yingying
Keyword(s):  
Porous Media ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Phase Distribution ◽  
Pore Network ◽  
Pore Network Model ◽  
Zone Model ◽  
Drying Process ◽  
Isothermal Drying

In view of the fact that the zone model for porous media drying cannot disclose the mechanism of liquid phase distribution effectively, a pore network model for the slow isothermal drying process of porous media was developed by applying the theories of pore network drying and transport-process, which fused the physical parameters of porous media, such as porosity, pore mean diameter, and pore size distribution into the model parameters, and a sand bed drying experiment was conducted to verify the validity of this model. The experiment and simulation results indicate that the pore network model could explain the slow isothermal drying process of porous media well. The pore size distributions of porous media have a great effect on the liquid phase distribution of the drying process. The dual-zone model is suitable for the porous media whose pore size distribution obeys Gaussian distribution, while the three-zone model is suitable for the porous media whose pore size distribution obeys the lognormal distribution when the drying analysis of porous media is conducted.

Analysis of Water Agglomeration Inside the GDL Using a Pore-Network Model

2010 ◽  
Author(s):  
Mehdi Shahraeeni ◽  
Mina Hoorfar
Keyword(s):  
Pore Size ◽  
Analytical Model ◽  
Network Model ◽  
Transient Response ◽  
Pore Network ◽  
Pore Network Model ◽  
Size Distributions ◽  
Water Motion ◽  
Pore Size Distributions

This article investigates the transient response of water motion inside the GDLs having different pore size distributions. A pore-network model is developed and applied to the problem. The results of the simulation are in agreement with the analytical model available in the literature.

Porosity and pore size distribution of shales: a case study of the Carynginia Formation, Perth Basin, Western Australia

2017 ◽  
Vol 57 (2) ◽  
pp. 660
Author(s):  
M. Nadia Testamanti ◽  
Reza Rezaee ◽  
Jie Zou
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Gas Adsorption ◽  
Pore Network ◽  
Pore Sizes ◽  
Wide Range ◽  
Pore Characterisation ◽  
Shale Reservoirs ◽  
Mercury Injection Capillary Pressure

The evaluation of the gas storage potential of shale reservoirs requires a good understanding of their pore network. Each of the laboratory techniques used for pore characterisation can be applied to a specific range of pore sizes; but if the lithology of the rock is known, usually one suitable method can be selected to investigate its pore system. Shales do not fall under any particular lithological classification and can have a wide range of minerals present, so a combination of at least two methods is typically recommended for a better understanding of their pore network. In the laboratory, the Low-Pressure Nitrogen Gas Adsorption (LP-N2-GA) technique is typically used to examine micropores and mesopores, and Mercury Injection Capillary Pressure (MICP) tests can identify pore throats larger than 3 nm. In contrast, a wider range of pore sizes in rock can be screened with Nuclear Magnetic Resonance (NMR), either in laboratory measurements made on cores or through well logging, provided that the pores are saturated with a fluid. The pore network of a set of shale core samples from the Carynginia Formation was investigated using a combination of laboratory methods. The cores were studied using the NMR, LP-N2-GA and MICP techniques, and the experimental porosity and pore size distribution results are presented. When NMR results were calibrated with MICP or LP-N2-GA measurements, then the pore size distribution of the shale samples studied could be estimated.

Depth and composition dependent nanopore structures of Indian shale gas reservoirs: An implication on storage potential

2021 ◽  
Author(s):  
Abinash Bal ◽  
Santanu Misra ◽  
Manab Mukherjee
Keyword(s):  
Fractal Dimension ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Negative Correlation ◽  
Fractal Dimensions ◽  
Clay Content ◽  
Pore Network Model ◽  
Cambay Basin ◽  
Gas Reservoirs

<p>We investigated the nanopore structures of shale samples obtained from Cambay and Krishna-Godavari (KG) basins in India using low-pressure N<sub>2</sub> sorption method. The samples occurred at variable depths (1403-2574m and 2599-2987m for Cambay and KG basins, respectively) and have wide ranges of clay contents (56-90%) both in volume and mineralogy. The results of this study indicate the specific surface area (SSA) and pore diameters of the samples share a non-linear negative correlation. The SSA is a strong function of the clay content over the samples’ depth. The specific micropore volumes of the KG basin have relatively higher (8.29-24.4%) than the Cambay basin (0.1-3.6%), which leads to higher SSA in the KG basin. From different statistical thickness equations, the Harkins Jura equation was found to be most suitable for the computation of BJH pore size distribution and t-plot inversion in shale. Shale samples from Cambay basin show unimodal pore size distribution, with a modal diameter of 4-5nm, while in the KG basin, show bi-modal to multimodal pore size distribution, mostly ranges from 3-12 nm. In the fractal FHH method, fractal exponent D<sub>f</sub>-3 provides a better realistic result than fractal dimensions calculated from (D<sub>f</sub>-3)/3. In our samples, pore surface fractal dimension (D<sub>f1</sub>) show a positive correlation with SSA and a negative correlation with pore diameter, and pore structure fractal dimension (D<sub>f2</sub>) shows a negative correlation both with clay(%) and depth. The experimental data obtained in this study are instrumental in developing the pore-network model to assess the hydrocarbon reserve and recovery in shale.</p>

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