scholarly journals The Impact of Equilibrium Gas Pressure and Coal Particle Size on Gas Dynamic Diffusion in Coal

Processes ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 571
Author(s):  
Li ◽  
Nie ◽  
Tian ◽  
Zhao ◽  
Zhang
Keyword(s):  
Particle Size ◽  
Diffusion Coefficient ◽  
Diffusion Coefficients ◽  
Effective Diffusion ◽  
Gas Pressure ◽  
Particle Sizes ◽  
Gas Desorption ◽  
The Impact ◽  
And Diffusion ◽  
Dynamic Diffusion

The diffusion coefficient of gases in coal varies with time. This study aims to develop an unsteady dynamic diffusion (UDD) model based on the decay of diffusion coefficient with time and the change of integral. This study conducted a series of gas desorption and diffusion experiments with three different combinations of particle sizes and gas pressures and compared the diffusion coefficients of the three models. The UDD model exhibited good fitting results, and both the UDD and bidisperse models fitted the experimental data better than the unipore model. In addition, the dynamic diffusion coefficient (DDe) decreased rapidly in the initial stage but gradually decreased to a stable level in the later stage. All the effective diffusion coefficients of the three models negatively correlated with the particle size. In the unipore model, the diffusion coefficient of coal samples with three particle sizes increased with gas pressure. In the bidisperse and UDD models, the diffusion coefficients (Dae, Die, and DDe) of 0.25–0.5 mm and 0.5–1.0 mm coal samples increased with gas pressure. However, DDe and Dae of 1.0–1.25 mm coal samples increased first and then decreased. Furthermore, Die decreased first and then increased, with no sign of significant pressure dependence. Finally, the correlation and significance between the constant and diffusion coefficient in the UDD model was investigated.

scholarly journals The Influence of Sorption Pressure on Gas Diffusion in Coal Particles: An Experimental Study

Processes ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 219 ◽  
Author(s):  
Yang ◽  
Wang ◽  
Zhang ◽  
Ren
Keyword(s):  
Diffusion Coefficient ◽  
Diffusion Coefficients ◽  
Gas Diffusion ◽  
Gas Pressure ◽  
Fast Diffusion ◽  
Pore Characteristic ◽  
Coal Particles ◽  
Pore Size Distributions ◽  
Coal Ranks ◽  
And Diffusion

Gas pressure changes during the process of coal mine gas drainage and CBM recovery. It is of great importance to understand the influence of sorption pressure on gas diffusion; however, the topic remains controversial in past studies. In this study, four samples with different coal ranks were collected and diffusion experiments were conducted under different pressures through the adsorption and desorption processes. Three widely used models, i.e., the unipore diffusion (UD) model, the bidisperse diffusion (BD) model and the dispersive diffusion (DD) model, were adopted to compare the applicability and to calculate the diffusion coefficients. Results show that for all coal ranks, the BD model and DD model can match the experimental results better than the UD model. Concerning the fast diffusion coefficient Dae of the BD model, three samples display a decreasing trend with increasing gas pressure while the other sample shows a V-type trend. The slow diffusion coefficient Die of BD model increases with gas pressure for all samples, while the ratio β is an intrinsic character of coal and remains constant. For the DD model, the characteristic rate parameter kΦ does not change sharply and the stretching parameter α increases with gas pressure. Both Dae and Die are in proportion to kΦ, which reflect the diffusion rate of gas in the coal. The impacts of pore characteristic on gas diffusion were also analyzed. Although pore size distributions and specific surface areas are different in the four coal samples, correlations are not apparent between pore characteristic and diffusion coefficients.

Diffusion of Zinc in Two-Phase Mg-Al Alloy

2007 ◽  
Vol 263 ◽  
pp. 189-194
Author(s):  
Ivo Stloukal ◽  
Jiří Čermák
Keyword(s):  
Diffusion Coefficient ◽  
Diffusion Coefficients ◽  
Effective Diffusion ◽  
Residual Activity ◽  
Diffusion Path ◽  
Al Alloy ◽  
Serial Sectioning ◽  
Two Phase ◽  
Interphase Boundaries ◽  
The Mean

Coefficient of 65Zn heterodiffusion in Mg17Al12 intermetallic and in eutectic alloy Mg - 33.4 wt. % Al was measured in the temperature region 598 – 698 K using serial sectioning and residual activity methods. Diffusion coefficient of 65Zn in the intermetallic can be written as DI = 1.7 × 10-2 m2 s-1 exp (-155.0 kJ mol-1 / RT). At temperatures T ≥ 648 K, where the mean diffusion path was greater than the mean interlamellar distance in the eutectic, the effective diffusion coefficient Def = 2.7 × 10-2 m2 s-1 exp (-155.1 kJ mol-1 / RT) was evaluated. At two lower temperatures, the diffusion coefficients 65Zn in interphase boundaries were estimated: Db (623 K) = 1.6 × 10-12 m2 s-1 and Db (598 K) = 4.4 × 10-13 m2 s-1.

scholarly journals Experimental Study on Limestone Cohesive Particle Model and Crushing Simulation

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Huaiying Fang ◽  
Dawei Xing ◽  
Jianhong Yang ◽  
Fulin Liu ◽  
Junlong Chen ◽  
...  
Keyword(s):  
Particle Size ◽  
Simulation Model ◽  
Impact Velocity ◽  
Distribution Curve ◽  
Particle Model ◽  
Particle Sizes ◽  
Particle Crushing ◽  
Discrete Element Method Simulation ◽  
Impact Crushing ◽  
The Impact

This study investigates the effect of impact velocity and particle size on crushing characteristics. We use a discrete-element method simulation and construct cohesive limestone particles with internal microinterfaces and cracks for impact crushing experimentation. The simulation model follows the same process as the impact crushing experiment. Results show that, after crushing at impact velocities of 30 and 40 m/s, the simulated particle-size distribution curve matches experimental results as closely as 95%. For different particle sizes, results are more than 90% in agreement. These results indicate the feasibility of the cohesive-particle crushing simulation model. When the particle size is 15 mm, an approximate linear relationship exists on impact velocity and crushing ratio. For a constant impact velocity, the particle size of 18 mm results in the maximum crushing ratio.

Diffusion-Based Modeling of Gas Transport in Organic-Rich Ultratight Reservoirs

SPE Journal ◽  
2021 ◽  
pp. 1-26
Author(s):  
Zizhong Liu ◽  
Hamid Emami-Meybodi
Keyword(s):  
Diffusion Coefficient ◽  
Adsorption Capacity ◽  
Surface Diffusion ◽  
Diffusion Coefficients ◽  
Gas Transport ◽  
Knudsen Diffusion ◽  
Gas Production ◽  
Hydrocarbon Transport ◽  
The Impact ◽  
And Storage

Summary The complex pore structure and storage mechanism of organic-rich ultratight reservoirs make the hydrocarbon transport within these reservoirs complicated and significantly different from conventional oil and gas reservoirs. A substantial fraction of pore volume in the ultratight matrix consists of nanopores in which the notion of viscous flow may become irrelevant. Instead, multiple transport and storage mechanisms should be considered to model fluid transport within the shale matrix, including molecular diffusion, Knudsen diffusion, surface diffusion, and sorption. This paper presents a diffusion-based semianalytical model for a single-component gas transport within an infinite-actingorganic-rich ultratight matrix. The model treats free and sorbed gas as two phases coexisting in nanopores. The overall mass conservation equation for both phases is transformed into one governing equation solely on the basis of the concentration (density) of the free phase. As a result, the partial differential equation (PDE) governing the overall mass transport carries two newly defined nonlinear terms; namely, effective diffusion coefficient, De, and capacity factor, Φ. The De term accounts for the molecular, Knudsen, and surface diffusion coefficients, and the Φ term considers the mass exchange between free and sorbed phases under sorption equilibrium condition. Furthermore, the ratio of De/Φ is recognized as an apparent diffusion coefficient Da, which is a function of free phase concentration. The nonlinear PDE is solved by applying a piecewise-constant-coefficient technique that divides the domain under consideration into an arbitrary number of subdomains. Each subdomain is assigned with a constant Da. The diffusion-based model is validated against numerical simulation. The model is then used to investigate the impact of surface and Knudsen diffusion coefficients, porosity, and adsorption capacity on gas transport within the ultratight formation. Further, the model is used to study gas transport and production from the Barnett, Marcellus, and New Albany shales. The results show that surface diffusion significantly contributes to gas production in shales with large values of surface diffusion coefficient and adsorption capacity and small values of Knudsen diffusion coefficient and total porosity. Thus, neglecting surface diffusion in organic-rich shales may result in the underestimation of gas production.

scholarly journals Field Validation of Concrete Transport Property Measurement Methods

Materials ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1166 ◽  
Author(s):  
Ahmed Abd El Fattah ◽  
Ibrahim Al-Duais ◽  
Kyle Riding ◽  
Michael Thomas ◽  
Salah Al-Dulaijan ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Diffusion Coefficients ◽  
Effective Diffusion Coefficient ◽  
Corrosion Inhibitors ◽  
Effective Diffusion ◽  
Cementitious Materials ◽  
Supplementary Cementitious Materials ◽  
Chloride Diffusion ◽  
Chloride Ingress ◽  
Exposure Site

Reinforcing steel corrosion, caused by chloride ingress into concrete, is the leading cause of reinforced concrete deterioration. One of the main findings in the literature for reducing chloride ingress is the improvement of the durability characteristics of concrete by the addition of supplementary cementitious materials (SCMs) and/or chemical agents to concrete mixtures. In this study, standard ASTM tests—such as rapid chloride permeability (RCPT), bulk diffusion and sorptivity tests—were used to measure concrete properties such as porosity, sorptivity, salt diffusion, and permeability. Eight different mixtures, prepared with different SCMs and corrosion inhibitors, were tested. Apparent and effective chloride diffusion coefficients were calculated using bound chloride isotherms and time-dependent decrease in diffusion. Diffusion coefficients decreased with time, especially with the addition of SCMs and corrosion inhibitors. The apparent diffusion coefficient calculated using the error function was slightly lower than the effective diffusion coefficient; however, there was a linear trend between the two. The formation factor was found to correlate with the effective diffusion coefficient. The results of the laboratory tests were compared and benchmarked to their counterparts in the marine exposure site in the Arabian Gulf in order to identify laboratory key tests to predict concrete durability. The overall performance of concrete containing SCMs, especially fly ash, were the best among the other mixtures in the laboratory and the field.

NUMERICAL ANALYSIS OF THE IMPACT OF ATHEROSCLEROTIC PLAQUE AND DIFFERENT STENT SPACING ON DRUG DEPOSITION

2015 ◽  
Vol 15 (01) ◽  
pp. 1550011
Author(s):  
DONG RUIQI ◽  
JIANG WENTAO ◽  
YAN FEI ◽  
ZHENG TINGHUI ◽  
FAN YUBO
Keyword(s):  
Diffusion Coefficient ◽  
Atherosclerotic Plaque ◽  
Drug Concentration ◽  
Diffusion Coefficients ◽  
Drug Eluting Stent ◽  
Artery Wall ◽  
Obvious Effect ◽  
Drug Deposition ◽  
Curved Artery ◽  
The Impact

Objectives: To investigate the influence of atherosclerotic plaque and different drug-eluting stent (DES) spacing on drug deposition in the curved artery wall. Methods: Based on the computational fluid dynamics (CFD) method, the numerical investigation on distributions of drug concentration in the artery wall was carried out considering three different interstrut distances and five values of the plaque diffusion coefficients. The results were compared with those of the model without plaque. Results: Under the same stent spacing, drug deposition weakly increased with the increasing plaque diffusion coefficient. When the same diffusion coefficient value was taken, drug deposition presented steady growth with the expansion of stent spacing. When the stent spacing was of 1-strut length or the diffusion coefficient of plaque was much smaller than the diffusion coefficient of tissue (an order of magnitude or more), the drug deposition would be evidently reduced. Conclusions: In a curved artery, the stent spacing is still an important factor in drug deposition. The diffusion coefficients of plaque have little influence on the average drug concentration, but they show a relatively obvious effect on drug distributions.

Diffusion Coefficients from Capillary Flow

1963 ◽  
Vol 3 (03) ◽  
pp. 256-266 ◽  
Author(s):  
H.R. Bailey ◽  
W.B. Gogarty
Keyword(s):  
Differential Equation ◽  
Diffusion Coefficient ◽  
Numerical Solution ◽  
Diffusion Coefficients ◽  
Molecular Diffusion ◽  
Capillary Flow ◽  
Molecular Diffusion Coefficient ◽  
Flow Method ◽  
And Diffusion ◽  
Flow Experiments

Abstract Methods are presented for determining molecular diffusion coefficients by using data from capillary flow experiments. These methods are based on a numerical solution (presented in a previous paper) of the partial differential equation describing the combined mechanisms of flow and diffusion. Results from this numerical solution are given and compared with the approximate analytical solution of G. I. Taylor. The numerical solution is valid over a much larger time range. These methods are applied to experimental results for the fluid pairs water-potassium permanganate solution and amyl acetateorthoxylene. Both of these fluid pairs have approximately equal densities and viscosities. Graphical and numerical techniques are presented for deters mining diffusion coefficients from the flow data. Values obtained by these techniques are compared with values obtained by other methods. Introduction The molecular diffusion coefficient is known to be a variable in determining the amount of mixing in a miscible displacement process. The effect of molecular diffusion on dispersion in longitudinal flow through porous media has been examined by different investigators. These investigators concluded that at low velocities of flow, the amount of dispersion is approximately proportional to the molecular diffusion coefficient. The influence of diffusion on fingering, channeling, and overriding has been mentioned by other investigators. Recent studies have been made on the effects of molecular diffusion in connection with the problem of gravity segregation. Many different methods have been developed for the experimental determination of molecular diffusion coefficients. These methods differ mainly according to boundary conditions selected and analytical procedures used. Nevertheless, all of these methods have the condition in common that the bulk fluids in which diffusion is occurring are stationary with respect to each other. In connection with a series of papers on mixing in capillary flow, Taylor suggested the use of a flow method for determining molecular diffusion coefficients. Additional studies have been conducted on miscible displacements in capillary tubes, but the data from these studies were not used for the specific purpose of determining diffusion coefficients. The flow method proposed by Taylor results in a single value of the diffusion coefficient for the fluid pair used in the displacement experiments. This single value represents the true value for the fluid pair when the diffusion coefficient is independent of concentration. If the diffusion coefficient is a function of concentration, the single value obtained by the flow method gives an average value for the coefficient of the fluid pair. These average values are based on diffusion taking place over the entire range of concentration, i.e., from 0 per cent of one fluid to 100 per cent of that same fluid. In field applications of the miscible displacement process, gradients occur over the same range of concentration as are found in the displacements in capillary tubes. Molecular diffusion coefficients obtained from the capillary flow method should, therefore, be especially relevant to field operations. This investigation was undertaken to evaluate the feasibility of obtaining molecular diffusion coefficients from capillary flow experiments. In making this evaluation, diffusion coefficients were first determined for two systems from data obtained in capillary flow experiments. These values of the diffusion coefficient were then compared to values obtained by other methods. MIXING IN CAPILLARY FLOW-THEORETICAL The theoretical basis for determining molecular diffusion coefficients from capillary flow experiments is the partial differential equation relating the mechanisms of flow and diffusion. SPEJ P. 256^

Diffusion velocity lattice Boltzmann formulation applied to transport in macroscopic porous media

2014 ◽  
Vol 25 (12) ◽  
pp. 1441006 ◽  
Author(s):  
Janez Perko ◽  
Ravi A. Patel
Keyword(s):  
Porous Media ◽  
Diffusion Coefficient ◽  
Lattice Boltzmann ◽  
Diffusion Coefficients ◽  
Effective Diffusion ◽  
Hydrodynamic Dispersion ◽  
Traditional Treatment ◽  
Dissipative Term ◽  
Diffusion Velocity ◽  
Variable Diffusion

This paper describes the application of a single relaxation time (SRT) lattice Boltzmann scheme to the transport in porous media with large spatial variations of diffusion coefficients. Effective diffusion coefficients can vary substantially within porous media because of their dependence on porosity and tortuosity which can span over several orders of magnitude, depending on pore size and connectivity. Moreover, when mass is transported with pore-water in porous media, the hydrodynamic dispersion, which depends on Darcy's velocity, contributes additionally to the usually anisotropic variation of the dissipative term. In contrast to the traditional treatment of spatially variable diffusion coefficient by the variation of a SRT, here the variability is accommodated through the use of diffusion velocity formulation which allows for larger variabilities of diffusion coefficient. The volume averaged properties of mass transport in macroscopic porous media are resolved through the additional source term which is similar to the existing force adjusting methods. The applicability of both the proposed schemes is demonstrated on two examples. The first demonstrates that the method is accurate for the large variation of diffusion coefficients and porosities. The second example introduces mass diffusion in a real, geometrically complex system with spatially contrasting properties.

scholarly journals Impact of Pore Geometry and Water Saturation on Gas Effective Diffusion Coefficient in Soil

2018 ◽  
Vol 8 (11) ◽  
pp. 2097 ◽  
Author(s):  
Wulong Hu ◽  
Yao Jiang ◽  
Daoyi Chen ◽  
Yongshui Lin ◽  
Qiang Han ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Power Law ◽  
Diffusion Coefficients ◽  
Effective Diffusion Coefficient ◽  
Pore Diameter ◽  
Water Saturation ◽  
Knudsen Diffusion ◽  
Effective Diffusion ◽  
Pore Geometry ◽  
Effective Diffusion Coefficients

Gas flow in soil plays a crucial role in terrestrial ecosystems, and numerical simulation of their movement needs to know their effective diffusion coefficients. How pore structure influences the effective diffusion coefficient has been studied intensively for dry porous media, but much remains unknown for unsaturated soils. Here, we employed the X-ray tomography technique at the pore scale to directly obtain the soil structures, the geometry of their pores and the water distribution under different water saturation levels were calculated using a morphological model. The results show that pore structures including porosity, interface area of gas–solid–water and pore diameter are closely related to water saturation. The increase of mean pore diameter with gas saturation can be fitted into a power law. We also investigated the impact of pore geometry and water saturation on the effective diffusion coefficients, which is independent of the molecular mass of gas after normalization. As the normalized effective Knudsen diffusion coefficient increases with average pore diameter following a power law, with the scaling factor related to pore geometry and the exponent is a constant, we explained and proved that the Knudsen diffusion coefficient increases with gas saturation, also following a power law.

scholarly journals Study on the gas desorption law and indicator influencing factors of fixed-size coal samples

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Lei Li ◽  
Zhongguang Sun ◽  
Fakai Wang ◽  
Kaizhi Zhang
Keyword(s):  
Particle Size ◽  
Diffusion Coefficient ◽  
Coal Particle ◽  
Diffusion Theory ◽  
Mathematical Expression ◽  
Experimental System ◽  
Size Composition ◽  
Critical Value ◽  
Gas Pressure ◽  
Fixed Size

AbstractThe prediction of dangerous hazards in working faces is an important link to prevent coal and gas outbursts. Improving the accuracy of predictive indicators is of great significance for reducing the phenomenon of being prominently below the critical value and ensuring safe production. The fixed-size desorption index K1 is one of the important indicators for coal face and gas outburst prediction. Based on the diffusion theory and the physical meaning of fixed-size coal samples, the mathematical expression of K1 is established by the self-developed high/low temperature pressure swing adsorption-desorption experimental system. According to the equation, the effects of gas pressure, loss time, coal particle size and diffusion coefficient on K1 are studied. The results show that the K1 index is logarithmically related to the gas pressure. Under the same conditions, the longer the loss time is, the smaller the measured K1 is, and the smaller the particle sizes of the drill cuttings are, the more notable the performance is; the diffusion coefficient represents the ability of gas to bypass micropores and the coal matrix. The greater the ability to bypass the matrix is, the larger the diffusion coefficient under the same conditions is, and the larger K1 is; the coal particle size has a greater influence on K1, and the smaller the size is, the more likely it is that the phenomenon of being prominently below the critical value occurs. Therefore, the particle size composition of coal during on-site measurements is crucial for obtaining the true K1 and the exact critical values.

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