Permeability Of Porous Materials Research Articles

Permeability prediction of complex porous materials by conjugating generative adversarial and convolutional neural networks

Empirical formulas, established by experimental statistical methods, have been a traditional method for predicting permeability in porous materials, but they suffer from shortcomings in terms of prediction accuracy. In this paper, a framework conjugating generative adversarial nets (GAN) and convolutional neural networks (CNN) is proposed for the rapid prediction of permeability based on 3D Berea sandstone images. This framework aims to surpass the limitations of empirical formulas in achieving accurate predictions. The framework involves three steps: porous material images reconstruction based on a conditional porosity progressive growth of generative adversarial nets (CPPGGAN), permeability label calculation based on the Lattice Boltzmann method (LBM) and deep learning prediction model construction using convolutional neural network (CNN). The CNN predictor trained on 3920 CPPGGAN synthetic images achieved an R2 value of 0.927 and 0.925 on 560 synthetic images and 60 original images, respectively. This indicated the effectiveness of the CPPGGAN synthetic images in the permeability prediction framework. The framework can also be adapted to a wider range of porous material types and shows great potential for exploring materials with exceptional properties in nature.

Influence of pore structure characteristics on the gas permeability of concrete

The permeability of concrete is a key factor in determining its durability. Permeability of porous materials in general is determined by pore characteristics (e.g., porosity, pore size distribution, tortuosity, etc.). In this investigation, we attempted to observe the relationship between the pore characteristics and the permeability of concrete. Nuclear magnetic resonance (NMR), mercury intrusion porosimetry (MIP), nitrogen adsorption, and X-ray computed tomography (X-CT) were used to examine the microstructures of three concrete materials labeled C30, C45, and C50. The results show that the combined aperture size distribution curve generated by N2GA and MIP can more accurately depict the distribution of micro to macro pores in the sample than any single method alone. The three-dimensional visualization model reconstructed by X-CT can provide a more intuitive reflection of the distribution of large pores in concrete. The pore ratios measured by NMR and MIP both have satisfactory correlations with gas permeability, but the pore ratio measured by NMR has a stronger correlation with gas permeability. There is a good correlation between gas permeability and the pore ratios contributed by different segments measured by NMR. In addition, the inherent gas permeability coefficient has a slightly stronger correlation with the median pore size than with the critical pore size.

Magnetohydrodynamics free convection couette flow and heat transfer through a vertical porous plate with heat generation and absorption effect

This research examines the impact of suction/injection and permeability of porous materials on a steady natural convection Couette flow of a viscous incompressible fluid passing through a vertical porous plate. The dimensionless governing momentum and energy equations were solved exactly. Graphs were plotted to check the impact of the governing flow parameters and a table was plotted for comparison of the results. It was found from the investigation that, the fluid injection (λ>0) increases the fluid velocity and temperature distributions while the magnetic field (M) retards the fluid velocity. It is also noteworthy to mention that the suction (λ>0) reduces the fluid velocity and temperature distributions in the channel. The velocity profile is observed to increase with increase in the permeability (K) of the materials.

A study on multi-exponential inversion of nuclear magnetic resonance relaxation data using deep learning

Nuclear magnetic resonance (NMR) is a powerful tool for formation evaluation in the oil industry to determine parameters, such as pore structure, fluid saturation, and permeability of porous materials, which are critical to reservoir engineering. The inversion of the measured relaxation data is an ill-posed problem and may lead to deviations of inversion results, which may degrade the accuracy of further data analysis and evaluation. This paper proposes a deep learning method for multi-exponential inversion of NMR relaxation data to improve accuracy. Simulated NMR data are first constructed using a priori knowledge based on the signal parameters and Gaussian distribution. These data are then used to train the neural network designed to consider noise characteristics, signal decay characteristics, signal energy variations, and non-negative features of the T2 spectra. With the validation from simulated data, the models introduced by multi-scale convolutional neural network (CNN) and attention mechanism outperform other approaches in terms of denoising and T2 inversion. Finally, NMR measurements of rock cores are used to compare the effectiveness of the attention multi-scale convolutional neural network (ATT-CNN) model in practical applications. The results demonstrate that the proposed method based on deep learning has better performance than the regularization method.

Preparation of Porous Silicate Cement Membranes via a One-Step Water-Based Hot-Dry Casting Method.

A commercial interest in the improvement in the separation performance and permeability of porous materials is driving efforts to deeply explore new preparation methods. In this study, the porous silicate cement membranes (PSCMs) were successfully prepared through an adjustable combination of hot–dry casting and a cement hydration process. The obtained membrane channel was unidirectional, and the surface layer was dense. The physical characteristics of the PSCMs including their pore morphology, porosity, and compressive strength, were diversified by adjusting the solid content and hot–dry temperature. The results indicated that with the solid content increasing from 40 wt. % to 60 wt. %, the porosity decreased by 8.07%, while the compressive strength improved by 12.46%. As the hot–dry temperature increased from 40 °C to 100 °C, the porosity improved by 23.04% and the BET specific surface area and total pore volume enlarged significantly, while the compressive strength decreased by 27.03%. The pore size distribution of the PSCMs exhibited a layered structure of macropores and mesopores, and the pore size increased with the hot–dry temperature. Overall, the PSCMs, which had typical structures and adjustable physical characteristics, exhibited excellent permeability and separation performance.

Nanoparticle's radius effect on unsteady mixed convective copper-water nanofluid flow over an expanding sheet in porous medium with boundary slip

Nanofluid and its higher thermal performance are displayed more promising outcomes when the flow medium is assumed to be a porous medium. Additionally, the radius size of nanoparticles plays a significant role in enhancing this thermal performance. So, present analysis aims to investigate the time-dependent flow of copper-water nanofluid in porous medium on an expanding sheet in presence of buoyancy force and slip phenomenon under various nanoparticle's radii. The flow is assumed to be boundary layer, two-dimensional, viscous, incompressible, laminar and unsteady. Governing coupled PDEs are changed into ODEs by suitable transformations and the converted ODEs are solved numerically. The study discloses that velocity rises with larger radius of nanoparticles and enlargement in assisting buoyancy force, whereas with unsteadiness of the flow, less permeability of porous material and boundary slip it drops. Also, magnitude of wall-drag force grows with larger radius of nanoparticles and flow unsteadiness. Importantly, for higher value of nanoparticle's radius surface-drag force massively enhances when permeability of porous medium is less. Temperature increment exhibits for boundary slip and less permeability of the porous material. Lastly, wall cooling rate intensifies with flow unsteadiness and higher value of nanoparticle's radius.

Effect of initial powder particle size on permeability and corrosion behavior of biomedical porous Ti6Al4V alloy prepared by powder metallurgy technique

In this work, the influence of initial powder particle size on the properties of biomedical porous Ti6Al4V alloys prepared by the space holder method was investigated. The results show that the particle size of the initial powders has a strong impact on the permeability, mechanical properties and corrosion behavior of the obtained porous Ti6Al4V alloys. When the mean particle size increases from dm ~ 17 ?m to dm ~ 43 ?m, the permeability of the resulted alloys increased about 47 folds, from 6.74?10-13 to 3.15?10-11 m2. On the contrary, the yield strength and modulus decreased from 207 MPa and 4.52 GPa to 98.1 MPa and 3.1 GPa, respectively. In this process, the macropores are defined by the space holders, the micropores presented on the cell walls are generated from partial sintering of powders which have an important role in the enhancement of the connectivity between macropores, porosity and hence, the permeability of porous materials. It is found that using the bigger particles led to the higher corrosion current density, Icorr due to the increase of the contact area with the simulated body fluid solution.

Analytical modelling of a novel test for determination of porosity and permeability of porous materials

Porosity and permeability are important properties of porous materials, such as rocks and concrete. This paper presents the physical-mathematical modelling of a novel test, based on one previously developed by one of the authors (standardized in Switzerland, Japan and China) for measuring the air-permeability of concrete structures. In the present case, a cylindrical specimen is placed inside an air-tight cell, subjected to an initial vacuum pressure P 0, which is afterwards isolated from the pump. The rate of pressure increase (due to the extraction of air originally at atmospheric pressure Pa ) is related to the coefficient of permeability of the material whilst the final pressure attained is a function of the porosity (total amount of air extracted). The analysis assumes a unidirectional radial flow of air, which can be achieved by a special serial three-chamber vacuum cell (with pressure regulation of the external chambers) or by an air-tight sealing of the extreme faces of the cylinder. The analysis is developed under the assumption of viscous laminar flow. To account for the molecular diffusion flow, the test can be performed under vacuum (P 0 ≪ Pa) and under overpressure (P 0 ≫ Pa ), enabling the application of the Klinkenberg correction to get the intrinsic coefficient of permeability.

Model of Flow Resistance Coefficient for a Fragment of a Porous Material Deposit with Skeletal Structure

The hydrodynamic conditions resulting from the permeability of porous materials are based not only on the assessment of the gas flow through these materials, but also the losses related to the pressure energy in this flow. Flow resistance is a direct measure of this loss. The aim of this experimental research was to evaluate the flow resistance of the porous material in relation to the gas flow. The research was carried out on a material with a slit-porous structure. The tests were carried out on a system for measuring gas permeability under the conditions of gas bubbling through the char. The issue of the total pressure drop process in the porous bed was considered in the Reynolds number category. The coefficient of flow resistance for the char was determined and the value of this coefficient was compared with the gas stream, and an experimental evaluation of the total pressure drop on the porous bed was made. The novelty of this article is the determination of the tortuosity and the gas permeability coefficient for a solid of any shape—a rigid skeleton.

On the use of tapered channels gas distributors to promote convection in PEM Fuel Cells

Polymeric Exchange Membrane Fuel Cells (PEMFC) are promising power propulsion systems for the decarbonization of the transportation sector. Despite being a well-known method for the direct production of electric current from the reactants chemical energy, one of the major limitations to their large-scale industrial development are fluid dynamics and mass transport aspects, crucially limiting the electrochemistry rate under critical conditions. This is especially verified in PEMFC with serpentine-type gas distributors, for which such areas are identified in proximity of the gas channel bends where the dominant mechanism for species transport shifts from a convection-enhanced to a diffusion-limited one. An engineering method to enhance the convective transport in such deficient areas is the use of gas distributors with tapered channels, effectively forcing the flow in diffusive media and improving the reactants delivery rate and products removal. A numerical analysis is presented on a limited domain representing a section of a serpentine gas distributor. A multi-dimensional CFD study is carried out comparing conventional-type and tapered channel distributors, evaluating the combined effect of pressure losses, catalyst layers utilization, flow regime in anisotropic diffusion media and convection/diffusion balance via a non-dimensional analysis. The study covers various inlet Reynolds numbers and in-plane permeability of porous materials for two diffusion media thicknesses, with the aim to extend the generality of the study. Conclusions based on the simulation results outline channel tapering as a very effective way to improve the power density of PEMFC, although an energetic cost/benefit analysis indicates a reduced cell efficiency.

Hydrodynamic Model of a Wedge-Shaped Sliding Support with an Easy-Melting Metal Coating

This study presents the method of forming an exact self-similar solution to the problem of hydrodynamic computation of a wedge-shaped support (slider, guide), which operates in the presence of a lubricant, a fusible metal coating on the surface of the guide, and a porous material on the surface of the slider taking the dependence of the viscosity of the lubricant and the permeability of porous material on pressure into account.

Using Scanning Ion Conductance Microscopy to Measure Ion Conductivity and Permeability in Porous Materials

Composite electrodes can significantly improve the performance of an electrochemical device by maximizing surface area and active material loading. Typically, additives such as carbon are used to improve conductivity and a polymer is used as a binder leading to a heterogeneous surface film with thickness on the order of tens of microns.For such composite electrodes, good ionic conduction within the film is critical to capitalize on the increased loading of active material and surface area. Ionic conductivity within a film can be tricky to measure directly and homogenization models based on porosity are often used as a proxy. Scanning Ion Conductance Microscopy (SICM) has traditionally been a topography-mapping microscopy method. We will outline a new function and demonstrate SICM’s capacity for measuring ion conductivity within lithium-ion battery composite electrodes.

Numerical calculation of permeability of periodic porous materials: Application to periodic arrays of spheres and 3D scaffold microstructures

SummaryIn this paper, an efficient numerical method is proposed to calculate the anisotropic permeability in porous materials characterized by a periodic microstructure. This method is based on pore‐scale fluid dynamic simulations using a static volume of fluid method. Unlike standard solution procedures for this type of problem, we here solve an average constitutive equation over both fluid and solid domain by use of a subgrid model to accurately capture momentum transfer from the fluid to solid interface regions. Using numerical simulations on periodic arrays of spheres, we first demonstrate that, by using the subgrid interface model, more accurate results can be produced, for the velocity and pressure fields, than via more conventional approaches. We then apply numerical upscaling over the unit cell to calculate the full anisotropic permeability from the pore‐scale numerical results. The obtained permeability values for a variety of periodic arrays of spheres in different arrangements and packing orders are in good agreement with semianalytical results reported in literature. This validation allows for the permeability assessment of more complex structures such as isotropic gyroid structures, or anisotropic cases, here modeled in their simplest form, the ellipsoidal inclusion.

Experimental Assessment of Porous Material Anisotropy and its Effect on Gas Permeability

The results of experimental research upon the assessment of porous material anisotropy and its effect on gas permeability of porous materials with respect to the gas flow. The conducted research applied to natural materials with an anisotropic gap-porous structure and - for comparative purposes - to model materials such as coke, pumice and polyamide agglomerates. The research was conducted with the use of a special test stand that enables measuring the gas permeability with respect to three flow orientations compared with symmetric cubic-shaped samples. The research results show an explicit impact of the flow direction on the permeability of materials porous, which results from their anisotropic internal structures. The anisotropy coefficient and permeability effective coefficient of such materials was determined and an experimental evaluation of the value of this coefficient was conducted with respect to the gas stream and the total pressure drop across the porous deposit. The process of gas permeability was considered in the category of hydrodynamics of gas flow through porous deposits. It is important to broaden the knowledge of gas hydrodynamics assessment in porous media so far unrecognised for the development of a new generation of clean energy sources, especially in the context of biogas or raw gas production.

Improvement of fractal model for porosity and permeability in porous materials

The investigation of porosity and permeability of porous materials is a challenge due to its complex pore microstructures. In this paper, an improved model of porosity is proposed based on the pore filling method, in which the facts of microscopic observation are considered that the smaller pores will be found with the decreasing observation scale or increasing magnification. The model is verified by two-dimensional and three-dimensional experiments, and the results show that the improved model can accurately describe the porosity and the pore volume distribution of fractal porous materials. Besides, a probability density function of pore size without conventional restrictions is also proposed based on the improved model of porosity, which makes the scope of application of the model of tortuosity fractal dimension much wider. Moreover, an improved model of permeability is finally proposed based on the improved model of porosity and the probability density function. By comparing the predicted values of the new permeability model with the experimental data, it is confirmed that the permeability model proposed in this paper could accurately predict the permeability of fractal porous materials.

Assessment of gas permeability through porous skeletal media with anisotropic internal structure

The results of experimental studies in the field of gas permeability of porous materials referring to gas flow have been shown. Coal chars with anisotropic porous-slotted structure have been tested. The studies have been carried out on a special test bench that allows for the measurement of gas permeability in terms of three flow orientations related to symmetrical specimens in the cubic form. The results of the measurements indicate that there is a considerable effect of the flow directivity on the permeability of carbonizers, which results from their integral anisotropic structure. A permeability coefficient for such materials has been defined and the experimental assessment of the value of this coefficient against gas flow and the total pressure drop on a porous medium has been made. The usefulness of computation methods characterising the hydrodynamics of gas flow through porous materials has been made, and the possibility of a numerical mapping of the flow geometry of solid materials with tortuous structure has been indicated.

Review on biologically based grout material to prevent soil liquefaction for ground improvement

There is great interest among geotechnical engineers to develop environment-friendly grouting materials for ground improvement. Biomineralisation is the process where micro-organisms produce minerals; mainly carbonate products that provide a basis to develop ‘biogrout’. Biogrout could be an excellent material for the purpose of ground improvement with several advantages over current remedial measures, to improve the mechanical properties, to decrease the permeability of porous materials, and to modify the properties of soil. In this review article, the conventional soil improvement practices are discussed with their drawbacks. In order to overcome drawbacks of those conventional processes, state-of-art on biologically based grout material is proposed for soil improvement. Further, an attempt has been made to compile the current knowledge on biogrout and identify research gaps for future research.

Design of Reservoir Recognition Technique Component - Open Porosity in Non-Polarizing Electrodes

In the present study modeling of permeability of open-porosity ceramic materials used in non-polarizing electrodes is addressed. The structure of the material filling the electrode determines the infiltration of the ceramic structure by electrolyte, which influences the efficiency of the electrodes. The composition of electrode material was characterized with Scanning Electron Microscope Hitachi S3500N with EDS detector and the structure was determined with use of XRadia XCT400 tomograph . The complex geometry of porous materials has been designed using procedure based on Laguerre-Voronoi tessellations (LVT). A set of porous structures with different geometrical features has been developed using LVT algorithm. The approach used here allows to investigate the influence of geometrical features such pore size variation on the permeability of studied materials. Pressure drop characteristics of the developed structures has been analyzed using finite volume method (FVM). The results show that permeability of porous materials is strongly related with distribution of pore size. The study exhibits the utility of developed design procedure for optimization of non-polarizing electrodes performance.

Counter-intuitive reduction of thermal contact resistance with porosity: A case study of polymer electrolyte membrane fuel cells

The present study reveals that the conventional notion that thermal contact resistance increases with porosity does not necessary hold. It is proved through a mechanistic robust model that, under specific circumstances, the porosities of two contacting bodies attain a critical value beyond which the contact resistance counter-intuitively drops. The model focuses on micro porous layers (MPLs) coated on gas diffusion layers (GDLs) of polymer electrolyte membrane fuel cells (PEMFCs) and is validated with the MPL-GDL thermal contact resistance measured over a range of pressure.The counter-intuitive reduction of the contact resistance with porosity can find important applications in energy conversion systems such as PEMFCs and batteries where contact resistance plays a major role in ohmic loss and heat management. This game-changing finding can lead to improving mass and heat transfer, diffusivity and permeability of porous materials by increasing the porosity without any compromise on contact resistance or ohmic loss. The present cutting-edge research can also open new avenues for fuel cell and any other manufacturers to develop state-of-the-art materials with higher porosities but lower contact resistances, which are currently not available in the market.

Fracture Sealing with Microbially-Induced Calcium Carbonate Precipitation: A Field Study

A primary environmental risk from unconventional oil and gas development or carbon sequestration is subsurface fluid leakage in the near wellbore environment. A potential solution to remediate leakage pathways is to promote microbially induced calcium carbonate precipitation (MICP) to plug fractures and reduce permeability in porous materials. The advantage of microbially induced calcium carbonate precipitation (MICP) over cement-based sealants is that the solutions used to promote MICP are aqueous. MICP solutions have low viscosities compared to cement, facilitating fluid transport into the formation. In this study, MICP was promoted in a fractured sandstone layer within the Fayette Sandstone Formation 340.8 m below ground surface using conventional oil field subsurface fluid delivery technologies (packer and bailer). After 24 urea/calcium solution and 6 microbial (Sporosarcina pasteurii) suspension injections, the injectivity was decreased (flow rate decreased from 1.9 to 0.47 L/min) and a reduction in the in-well pressure falloff (>30% before and 7% after treatment) was observed. In addition, during refracturing an increase in the fracture extension pressure was measured as compared to before MICP treatment. This study suggests MICP is a promising tool for sealing subsurface fractures in the near wellbore environment.