Characterization Of Porous Media Research Articles

Study on heat and mass transfer characteristics of porous media with different pore structures under continuous wave laser irradiation

The pore structure determined by porosity and particle size will directly affect the remediation efficiency of thermal treatment on contaminated soil. To investigate the remediation capability of continuous wave laser soil remediation technology on soils with different pore structures, this paper establishes a heat and mass transfer model within unsaturated porous media under laser irradiation. Four pore structures were simulated, and the model’s reliability was experimentally validated. Under laser irradiation, energy exchange between the solid and gas phases has a minimal effect on the solid phase temperature. The temperature distribution of the solid phase in the four samples is similar, with the differences primarily arising from moisture content. Interface energy exchange dominated the rise in the temperature of the gas. The intrinsic Nusselt numbers for the four samples were 3.5, 4.4, 4.9, and 6.2, respectively. Laser irradiation causes the Nusselt number to decrease over time, but the relative magnitudes of the Nusselt numbers for the four samples remain unchanged. From the perspective of solid phase temperature, the capability of laser remediation for soils with different pore structures is similar. From the standpoint of gas temperature, the Nusselt number is decisive. However, considering the complex coupling relationship between gas temperature rise and Darcy velocity and evaporation rate, the influence of water saturation and intrinsic permeability cannot be ignored. The research findings can provide a theoretical basis and analytical methods for the efficient laser remediation of soils with different pore structures.

Hydrogeological characterization of low permeability medium for conceptualization of a mine site in Eastern Turkey

The mining site in Eastern Anatolia of Turkey were encounter a significant risk of slope instability within the operational area. One of the processes that govern slope stability is the pore water pressure distribution. The conceptualization and characterization of porous media serve as fundamental prerequisites for the implementation of numerical methods aimed at predicting pore water distribution. This study aims to characterize the hydrogeological properties of water bearing rocks in the active mining site in Eastern Anatolia of Turkey. A total of 21 wells and drill holes were drilled in the study area to conduct in-situ tests, monitoring, and sampling. The large diameter wells drilled in surrounding the carbonate rocks were to determine the groundwater flow and boundary conditions and also wells tapped metasediments and diorite unit for hydraulic testing. The lugeon tests and installation of vibrating wire piezometers were carried out at small diameter drill holes to obtain localized hydraulic conductivity of metasediments and diorite at different depths and monitoring pore water pressure distribution along some critical cross-sections. The results obtained from these tests are used for developing hydrogeological conceptual model for groundwater flow. The results of in-situ tests show that the metasediment and diorite units act as a single hydrostratigraphic unit. The metasediments and diorite have high total porosity and low specific yield indicating that the pore water is retained by electrostatic forces in the medium and it resists flow due to low hydraulic conductivity. The vertical variation in hydraulic conductivity values indicates that the medium is highly heterogeneous.

Comparative Study on Flow Characteristics in Deep Marine and Marine-Continental Transitional Shale in the Southeastern Sichuan Basin, China.

Permeability is a significant characteristic of porous media and a crucial parameter for shale gas development. This study focuses on deep marine and marine-continental transitional shale in the southeastern Sichuan area using the gas pulse decay testing method to systematically analyze the gas permeability, stress sensitivity, and gas transport mechanisms of shale under different pressure conditions and directions. The results show that the porosity and gas permeability of the deep marine shale are greater compared to those of the marine-continental transitional shale. The elevated fluid pressure in the deep marine shale offers superior conditions for the preservation of nanopores, while the high quartz content provides advantageous conditions for fluid transport in nanopore channels. The permeability and stress sensitivity of the deep marine shale are greater than those of the marine-continental transitional shale, and the stress sensitivity is greater in the perpendicular bedding direction than in the parallel bedding direction, possibly related to the mineral composition of shale and the compaction it has undergone. The flow mechanism of the deep marine shale is transition flow and Knudsen flow, while that of the marine-continental transitional shale is transition flow. The deep marine shale possesses smaller nanopore sizes and a higher quantity of micropores, which create advantageous conditions for gas transport within nanopores. During the process of extracting shale gas, the extraction of gas causes a decrease in pore pressure and an increase in effective stress, resulting in a reduction in permeability. However, when the pore pressure reaches a specific value, the enhanced slippage effect leads to an increase in permeability, which is advantageous for gas extraction. In the later stage of shale gas well production, intermittent production plans can be developed considering the strength of the slippage effect, leading to a significant improvement in production efficiency.

Inclined surface mixed convection flow of viscous fluid with porous medium and Soret effects

Abstract The combined heat and mass transfer phenomenon is a significant aspect of engineering and industrial processes. This phenomenon finds applications in various areas such as air conditioning, cooling and heating control of electronic devices, reactors, chemical systems, and emission processes. This research model focuses on the analysis of mixed convection flow of a viscous fluid with heat and mass transfer on an inclined surface with porous medium characteristics. The study also considers external heat transfer effects, radiation, Soret influence, and chemical reactions. A perturbation solution is derived in closed form, and the impact of various parameters on the thermal behavior is investigated. A comparative analysis of the heating and cooling regimes in plate flow is conducted, revealing a reduction in velocity in the heated plate regime with changes in the permeability parameter and an increase in concentration phase due to the Soret number.

Study on heat transfer of waxy crude oil melting phase change based on a novel model

The study of phase change heat transfer of crude oil melting is important for pre-heating and restarting of pipelines. Combining the characteristics of waxy crude oil characteristics of waxy crude oil melting, a novel mathematical model was established, which can accurately describe the non-linear release of latent heat, liquid-solid interface changes, natural convection, and other key heat transfer problems. In the process of heating and melting, the variation law of the solid-phase interface position in the pipe at different initial solidification states was analyzed. The results showed that in the partially solidified pipeline, the liquid crude oil in the pipeline has a higher temperature at the initial heating stage, and continuously loses heat to the low temperature crude oil, resulting in a decline in the liquid-phase ratio at the initial stage. Because crude oil was affected by different degrees of radial thermal resistance, latent heat release and porous medium characteristics at different positions of the pipeline, the temperature drop curves of the crude oil varies greatly.

INTELLIGENT EXTRACTION OF COMPLEXITY TYPES IN FRACTAL RESERVOIR AND ITS SIGNIFICANCE TO ESTIMATE TRANSPORT PROPERTY

Fractal pore structure exists widely in natural reservoir and dominates its transport property. For that, more and more effort is devoted to investigate the control mechanism on mass transfer in such a complex and multi-scale system. Apparently, effective characterization of the fractal structure is of fundamental importance. Although the newly emerged concept of complexity assembly clarified the complexity types and their assembly mechanism in a fractal system, equivalent extraction of the complexity types is the key for effective characterization. For these, we proposed a deep learning-based method to extract the original and behavioral complexity assembled in bed-packing fractal porous media for simplification and without loss of generality. In detail, the UNeXt network model was trained to obtain the independent connected regions of scaling objects with different scales, the edge detection and clustering analysis algorithms were employed to extract the number-size relationship between two successive scaling objects, and the unique inversion of fractal behavior was realized by taking the number-size model and fractal topography together. Consequently, an equivalent characterization method for fractal complex pore structure was developed based on the concept of complexity assembly. Our investigation provides a theoretical guidance and method reference for the quantitative characterization of fractal porous media that will guarantee the fundamental requirement for the accurate evaluation of the transport properties of natural reservoir.

FRACTAL STUDY ON HEAT TRANSFER CHARACTERISTICS OF FRACTURED DUAL POROUS MEDIA WITH ROUGH SURFACE

In order to study the influencing factors of heat transport characteristics in the rough fractured dual porous media, the theoretical model of effective thermal conductivity (TC) in rough fractured dual porous media is established in this paper. By calculating the thermal resistance and TC of rough cracks, it is found that the heat transport capacity of the fracture is inversely proportional to the relative roughness and porosity and is proportional to the solid-liquid TC ratio and the fractal dimension of the fracture. The heat conduction in the fractured dual porous media is mainly controlled by the matrix. In addition, by comparing with other models and existing experimental data, it can be seen that the heat transfer capacity of dual media is stronger than that of single porous media. The predicted TC of rough cracks is lower than the experimental data, which is in line with the actual situation, and the model is reasonable.

Determination of the flow rate characteristics of porous media under the positive pressure and vacuum

Determination of the flow rate characteristics of porous media under the positive pressure and vacuum

DETERMINING THE PROPERTIES OF ROCK SAMPLES USING DEEP MACHINE LEARNING

Porosity, absolute permeability, and diffusion coefficient are crucial characteristics governing fluid flow in the porous media of geological formations. Determining these properties traditionally involves resource-intensive and time-consuming processes. However, with the advancement of deep learning methods in the last 3–4 years, artificial neural networks have gained significant traction in predicting the transport properties of the fluid-porous medium system and the geometric characteristics of porous samples based on their images. This approach allows for the rapid determination of these properties with acceptable accuracy. The aim of this article is to conduct a scientific review of literature from open sources on the deter-mination of absolute permeability, diffusion coefficient, and porosity from their images acquired through various scanning methods. Additionally, this article incorporates proprietary data, specifically images from four carbonate samples. Convolutional neural networks were examined as the method of choice.The results of this article comprise a scientific review of moderate depth regarding the effectiveness and applicability of the approach for determining important characteristics of porous media using deep machine learning methods based on sample images. In this article, we also present the results of predict-ing the open porosity of four carbonate samples based on their X-ray images using the convolutional neural network model we constructed. The conducted review has demonstrated that images (scans) of geological rock samples obtained through various scanning methods allow for the calculation of their transport properties with a high degree of accuracy using deep machine learning algorithms, and this can be achieved within a significantly short timeframe. This implies that deep machine learning can serve as a valuable alternative tool for estimating the properties of geological rock samples based on their images. The convolutional neural network model we constructed exhibited predictive capability for the porosity of three carbonate samples with a coefficient of determination ranging from 0.936 to 0.976.

A Novel Evaluation Technique for Mudcake of Drilling Fluid Based on the Nuclear Magnetic Resonance Method

Summary In drilling engineering, mudcake is formed when the drilling fluid invades the near-wellbore zone, which can reduce drilling fluid leakage and reservoir pollution and maintain wellbore stability. Exploring the method that can best represent the field working conditions to evaluate the mudcake is an urgent problem. At present, the macro-evaluation method cannot describe the characteristics of heterogeneity, particle accumulation, and porous media of mudcake. The micro-evaluation method needs local sampling, drying, curing, slicing, and other tedious disturbance treatments, which cannot reflect the overall characteristics of mudcake. To solve these problems, a novel technique for evaluating the pore structure of mudcake was established by taking nuclear magnetic resonance (NMR) T2 tests as the key mean and integrating high-pressure mercury injection tests, fluid isotope tracing, dynamic/static filtration experiment of drilling fluid, pore permeability parameter tests of core, and particle-size distribution tests of drilling fluid. The evaluation results of mudcake formed by drilling fluid static and dynamic filtration show that this technology can study the pore structure characteristics of the outer mudcake and intruded core and the distribution characteristics of the inner mudcake and filtrate in the intruded core. The novel evaluation technique has strong operability and less demand for experimental samples, which can study the micron-scale pore structure of mudcake and provide practical methods for drilling fluid system optimization and application effect evaluation, reservoir damage evaluation, and development or verification of the filtration model.

Effect of mechanical vibration on heat and mass transfer performance of pool boiling process in porous media: a literature review

Pool boiling in porous media has been applied in various thermal management systems by using latent heat and increasing the heat transfer area and thermal conduction path to improve the heat transfer performance. In mechanical equipment, vibration is an inevitable problem due to reasons such as engine operation and high-speed relative motion between transmission system components, which causes the system components to be affected by vibration forces or vibration accelerations. This study focuses on a review of published articles about the effects of mechanical vibration on the characteristics of boiling process in porous media by two aspects: heat transfer performance and bubble dynamics. Heat transfer coefficient (HTC) and critical heat flux are two main parameters used to measure the boiling heat transfer characteristics of porous media. For bubble dynamics investigations, properties such as migration, fragment, coalescence, departure diameter and frequency are the focus of research attention. Different mechanical vibration parameters, i.e., direction, frequency, and amplitude, will have different effects on the above characteristics. It is worth mentioning that the greatest influence occurs under resonance conditions, and this has been verified through experimental and simulation calculations. This review highlights the importance of considering mechanical vibrations in the design and optimization of porous media systems for efficient heat transfer applications. Further research is warranted to explore the detailed mechanisms and optimize the vibration parameters for enhanced heat transfer performance in thermal management systems using porous media.

A continuous one-domain framework for fluid flow in superposed clear and porous media

Based on generalized porous flow model, we present a one-domain framework for the simulation of incompressible flow in superposed clear and porous media. The continuous change in the characteristics of the porous medium is naturally taken into account by the model. In presence of any strong discontinuities in the domain, the sudden changes are approximated as a continuous but rapid variations over a thin layer across the regions of contrast. The governing equations are solved by a consistent second-order projection scheme on finite volume octree cells. The numerical scheme evaluates advection as well as porous drag terms at fractional time step and employs Godunov type procedure to obtain fractional step velocity at face center. The consistent property of the scheme ensures a discrete balance between pressure gradient and porous drags and, thereby, recovers Darcy-Forchheimer law exactly. The implication of inconsistent discretization of porous drags and pressure gradient is also highlighted. Benchmark problems with flow parallel and perpendicular to the homogeneous porous layer are considered to test the accuracy of the proposed numerical model especially with regard to the artificial transition region. Although the incorporation of the transition layer introduces error into the system, it reduces non-linearity in the field variables and, therefore, decreases the demand of higher grid density near the interface in one-domain approach. Furthermore, we simulate a series of physical problems with varying complexity in flow and characteristics of porous medium. The simulation results illustrate the ability of our solver to handle flows with viscous as well as inertial effects around a planar or circular interface geometry without loss of stability.

Seepage Evolution Law and Deformation Failure Characteristics of Porous Media Based on Smoothed Particle Hydrodynamics

Seepage Evolution Law and Deformation Failure Characteristics of Porous Media Based on Smoothed Particle Hydrodynamics

Thermal management of the central processing unit cooling system using a cylindrical metal foam heat sink under the influence of magnetohydrodynamic nanofluid flow

PurposeEfficient thermal management of central processing unit (CPU) cooling systems is vital in the context of advancing information technology and the demand for enhanced data processing speeds. This study aims to explore the thermal performance of a CPU cooling setup using a cylindrical porous metal foam heat sink.Design/methodology/approachNanofluid flow through the metal foam is simulated using the Darcy–Brinkman–Forschheimer equation, accounting for magnetic field effects. The temperature distribution is modeled through the local thermal equilibrium equation, considering viscous dissipation. The problem’s governing partial differential equations are solved using the similarity method. The CPU’s hot surface serves as a solid wall, with nanofluid entering the heat sink as an impinging jet. Verification of the numerical results involves comparison with existing research, demonstrating strong agreement across numerical, analytical and experimental findings. Ansys Fluent® software is used to assess temperature, velocity and streamlines, yielding satisfactory results from an engineering standpoint.FindingsInvestigating critical parameters such as Darcy number (10−4 ≤ DaD ≤ 10−2), aspect ratio (0.5 ≤ H/D ≤ 1.5), Reynolds number (5 ≤ ReD,bf ≤ 3500), Eckert number (0 ≤ ECbf ≤ 0.1) , porosity (0.85 ≤ ε ≤ 0.95), Hartmann number (0 ≤ HaD,bf ≤ 300) and the volume fraction of nanofluid (0 ≤ φ ≤ 0.1) reveals their impact on fluid flow and heat sink performance. Notably, Nusselt number will reduce 45%, rise 19.2%, decrease 14.1%, and decrease 0.15% for Reynolds numbers of 600, with rising porosity from 0.85 to 0.95, Darcy numbers from 10−4 to 10−2, Eckert numbers from 0 to 0.1, and Hartman numbers from 0 to 300.Originality/valueDespite notable progress in studying thermal management in CPU cooling systems using porous media and nanofluids, there are still significant gaps in the existing literature. First, few studies have considered the Darcy–Brinkman–Forchheimer equation, which accounts for non-Darcy effects and the flow and geometric interactions between coolant and porous medium. The influence of viscous dissipation on heat transfer in this specific geometry has also been largely overlooked. Additionally, while nanofluids and impinging jets have demonstrated potential in enhancing thermal performance, their utilization within porous media remains underexplored. Furthermore, the unique thermal and structural characteristics of porous media, along with the incorporation of a magnetic field, have not been fully investigated in this particular configuration. Consequently, this study aims to address these literature gaps and introduce novel advancements in analytical modeling, non-Darcy flow, viscous dissipation, nanofluid utilization, impinging jets, porous media characteristics and the impact of a magnetic field. These contributions hold promising prospects for improving CPU cooling system thermal management and have broader implications across various applications in the field.

Encoder–Decoder Convolutional Neural Networks for Flow Modeling in Unsaturated Porous Media: Forward and Inverse Approaches

The computational cost of approximating the Richards equation for water flow in unsaturated porous media is a major challenge, especially for tasks that require repetitive simulations. Data-driven modeling offers a faster and more efficient way to estimate soil moisture dynamics, significantly reducing computational costs. Typically, data-driven models use one-dimensional vectors to represent soil moisture at specific points or as a time series. However, an alternative approach is to use images that capture the distribution of porous media characteristics as input, allowing for the estimation of the two-dimensional soil moisture distribution using a single model. This approach, known as image-to-image regression, provides a more explicit consideration of heterogeneity in the porous domain but faces challenges due to increased input–output dimensionality. Deep neural networks (DNNs) provide a solution to tackle the challenge of high dimensionality. Particularly, encoder–decoder convolutional neural networks (ED-CNNs) are highly suitable for addressing this problem. In this study, we aim to assess the precision of ED-CNNs in predicting soil moisture distribution based on porous media characteristics and also investigate their effectiveness as an optimizer for inverse modeling. The study introduces several novelties, including the application of ED-CNNs to forward and inverse modeling of water flow in unsaturated porous media, performance evaluation using numerical model-generated and laboratory experimental data, and the incorporation of image stacking to account for transient moisture distribution. A drainage experiment conducted on a sandbox flow tank filled with monodisperse quartz sand was employed as the test case. Monte Carlo simulation with a numerical model was employed to generate data for training and validation of the ED-CNN. Additionally, the ED-CNN optimizer was validated using images obtained through non-intrusive photographic imaging. The results show that the developed ED-CNN model provides accurate approximations, addressing the high-dimensionality problem of image-to-image regression. The data-driven model predicted soil moisture with an R2 score of over 91%, while the ED-CNN optimizer achieved an R2 score of over 89%. The study highlights the potential of ED-CNNs as reliable and efficient tools for both forward and inverse modeling in the analysis of unsaturated flow.

Improving Thermal Performance of Rectangular Microchannel Heat Sinks using Porous Layer: CFD Simulation and Optimization

Microchannel heat sinks are very widely used due to their high heat transfer coefficients and low refrigerant requirements. Nevertheless, microchannel heat sinks still perform sub-optimally when it comes to thermal performance. Therefore, this paper investigates the individual and combined impacts of different characteristics of porous media on the thermal performance of microchannel. Four porosity values are considered: 0.8, 0.85, 0.9, and 0.95. The evaluation is based on three-dimensional computational fluid dynamics simulations. Due to the large number of degrees of freedom in this study, Constructal Theory and Design of Experiments are employed. In this study, the response surface type is Genetic Aggregation, while the Latin Hypercube Sampling algorithm is used for data sampling and Genetic algorithm is used for optimization. Combining porous layers with microchannel heat sinks reduces maximum temperatures about 3K. It is also observed that a lower maximum surface temperature is achieved in the cases with less porosity. Furthermore, the optimal geometry and size of the microchannels with porous layers are determined.

Minkowski functional evaluation of representative elementary volume of rock microtomography images at multiple resolutions

Pore-scale properties can be obtained by building a reliable digital twin of porous media through the digital rock physics (DRP) workflow. The two prerequisites of DRP are reliable imaging and computing power. Determining a proper image resolution that can reveal the actual pore-scale properties is challenging as there is a trade-off between the resolution and the representative elementary volume (REV). The REV is the smallest volume that reproduces the properties of the whole porous medium. The REV is a function of heterogeneities on the pore scale, the parameter of interest, and the scale range. Although the REV analysis for hydraulic properties is straightforward, it is computationally expensive. This study aims to estimate hydraulic pore-scale properties during REV evaluations by the geometric characterization of porous media using the Minkowski morphological functionals. Two sandstone and one carbonate rock samples were scanned at multiple imaging resolutions by both laboratory and synchrotron tomography. The REVs of various parameters of interest (porosity, permeability, surface area, tortuosity, Minkowski functionals) were computed, and the effect of image resolution and artificial rebinning on the final REV values was examined. After reaching the REV for porosity, the REV for the integrals of mean and total curvature agreed well with the permeability REV for large-volume image sizes. At constant porosity, the Minkowski integrals were found to be indicators for pore throat sizes. We also showed that the properties obtained from the rebinned (or coarsened) images differ entirely from that of actual scans at the same resolution.

Experimental investigation and prediction model of permeability in solidified coarse-grained soil under freeze-thaw cycles in water-rich environments

In freeze–thaw and water-rich environments, high-speed railway subgrade systems experience significant changes in their moisture field due to the combined effects of temperature and pore pressure gradients. This poses a serious challenge to the long-term safety of high-speed railways. To address this issue, the permeability of high-speed railway subgrade fill materials before and after modification was tested using a self-developed infiltration instrument. Modifications included increasing the fine particle content and adding self-developed solidifying additives. Based on experimental results and discussions on the solidification mechanism of the fill, a model for predicting the permeability coefficient of the fill was proposed and analyzed. Results show that the self-developed additive is an efficient material for reducing permeability, with effects reaching up to the order of 107. The additive also demonstrates excellent resistance to freeze–thaw environments. Mineral-based cementitious materials have a greater impact on permeability coefficient than cement-based materials. The permeability coefficient prediction model was validated, showing a 92.3% consistency level with laboratory test results. Parameter analysis revealed that the model's parameters effectively characterize the pore structure, fluid environmental temperature, pore pressure, and other characteristics of porous media. The findings have important implications for stable control and moisture field guarantee in high-speed railway subgrades under freeze–thaw and water-rich conditions.

MHD micropolar fluid flow in porous media

The analysis of mass and heat transfer in magnetohydrodynamic (MHD) flows has significant applications in heat exchangers, cooling nuclear reactors, designing energy systems and casting and injection processes of different types of fluids. On the other hand, extraction of crude oil, the flow of human or animal blood, as well as other polymer fluids or liquid crystals are just some examples of micropolar fluid flows. Due to the broad application spectrum of the theory of micropolar fluid flows, and the significance the impact the external magnetic field has on the flow of these fluids, this paper considers the stationary flow of a micropolar fluid between two plates under the influence of an external magnetic field which is perpendicular to the direction of the flow. Stationary plates are maintained at constant and different temperatures, while the whole problem is considered in the non-inductive approximation. The equation system used to define the physical problem under consideration is reduced to the system of differential equations that have been solved analytically and the solutions of which are of general nature. In addition to the solutions for velocity, microrotation and temperature, the paper gives solutions for shear stress at plates, the Nusselt number and flow rate. The provided solutions have been applied in order to reach some general conclusions about the influence of the magnetic field and physical characteristics of a micropolar fluid and the characteristics of porous media on the nature of micropolar fluid flows in porous media by means of chart analysis. General conclusions, obtained in the result analysis in this paper, give us the opportunity to understand the flows of micropolar fluids and highlight their significance.

Observation of magnetic structural universality and jamming transition with NMR

Nuclear magnetic resonance (NMR) has been instrumental in deciphering the structure of proteins. Here we show that transverse NMR relaxation, through its time-dependent relaxation rate, is distinctly sensitive to the structure of complex materials or biological tissues at the mesoscopic scale, from micrometers to tens of micrometers. Based on the ideas of universality, we show analytically and numerically that the time-dependent transverse relaxation rate approaches its long-time limit in a power-law fashion, with the dynamical exponent reflecting the universality class of mesoscopic magnetic structure. The spectral line shape acquires the corresponding non-analytic power law singularity at zero frequency. We experimentally detect the change in the dynamical exponent as a result of the transition into maximally random jammed state characterized by hyperuniform correlations. The relation between relaxational dynamics and magnetic structure opens the way for noninvasive characterization of porous media, complex materials and biological tissues