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.

scholarly journals Influence rules and mechanisms of mechanical vibration at different frequencies on dynamic process of gas diffusion from coal particles

2021 ◽  
pp. 014459872110135
Author(s):  
Maoliang Shen ◽  
Xuexi Chen
Keyword(s):  
Diffusion Coefficient ◽  
Pore Structure ◽  
Vibration Frequency ◽  
Gas Diffusion ◽  
Diffusion Resistance ◽  
Diffusion Kinetic ◽  
Gas Desorption ◽  
Coal Particles ◽  
Gas Molecules ◽  
And Diffusion

To study the influence of vibration on gas desorption and diffusion in particle coal, gas desorption experiments on soft coal with outburst risk under different frequency vibrations were carried out by using a self-designed gas adsorption and desorption platform under vibration conditions, and the influence of different frequency vibrations on the diffusion kinetic parameters was quantitatively analyzed by using a dynamic diffusion coefficient model. The influence mechanism of vibration on gas desorption and diffusion in coal was further analyzed from the three aspects of gas molecules, energy conversion and pore structure through theoretical analysis and mercury injection experiments. The results showed that with increasing vibration frequency, the gas desorption of the coal samples first increases and then decreases. The initial diffusion coefficient of gas in the coal samples increases linearly with increasing vibration frequency, but the attenuation coefficient of the diffusion coefficient decreases first and then increases with increasing vibration frequency. The "throwing effect" and thermal effect of vibration on the gas molecules are both conducive to the desorption of gas molecules. In addition, vibration causes changes in the pore structure in coal, increasing gas diffusion paths and reducing diffusion resistance.

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.

Research on the Relationship between the Drilling Cutting Gas Desorption Index △h2 and Parameters of Gas Occurrence

2011 ◽  
Vol 99-100 ◽  
pp. 1312-1318 ◽  
Author(s):  
Jian Liang Gao ◽  
Yu Wang
Keyword(s):  
Diffusion Coefficient ◽  
Linear Relationship ◽  
Gas Diffusion ◽  
Gas Pressure ◽  
Diffusion Resistance ◽  
Power Relationship ◽  
Gas Desorption ◽  
Coal Particles ◽  
Gas Occurrence ◽  
The Relationship

The drilling cutting gas desorption index △h2is one of the most important indexes for the prediction of coal and gas outburst. Based on the mathematical and physical model of the gas diffusion of coal particles, the analytical solution of △h2was deduced. The relationship between the drilling cutting gas desorption index △h2and parameters of gas occurrence such as the gas diffusion coefficient, adsorption constants (a and b), gas pressure, and gaSubscript textSubscript texts content were studied. The results show that △h2increases and gas diffusion resistance decreases with the gas diffusion coefficient. The drilling cutting gas desorption index △h2increases with the adsorption constant a, and the two meet the linear relationship. △h2increases with the adsorption constant b and the raising rate gets lower gradually. And, △h2increases with the gas pressure, and the two meet the power relationship with very high correlation coefficient.△h2and gas content are in linear relationship.

A Power-Law Mixing Rule for Predicting Apparent Diffusion Coefficients of Binary Gas Mixtures in Heavy Oil

2017 ◽  
Vol 140 (5) ◽  
Author(s):  
Hyun Woong Jang ◽  
Daoyong Yang ◽  
Huazhou Li
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Heavy Oil ◽  
Diffusion Coefficients ◽  
Gas Mixtures ◽  
Gas Diffusion ◽  
Gas Mixture ◽  
Mixing Rule ◽  
Heavy Oils ◽  
Apparent Diffusion

A power-law mixing rule has been developed to determine apparent diffusion coefficient of a binary gas mixture on the basis of molecular diffusion coefficients for pure gases in heavy oil. Diffusion coefficient of a pure gas under different pressures and different temperatures is predicted on the basis of the Hayduk and Cheng's equation incorporating the principle of corresponding states for one-dimensional gas diffusion in heavy oil such as the diffusion in a pressure–volume–temperature (PVT) cell. Meanwhile, a specific surface area term is added to the generated equation for three-dimensional gas diffusion in heavy oil such as the diffusion in a pendant drop. In this study, the newly developed correlations are used to reproduce the measured diffusion coefficients for pure gases diffusing in three different heavy oils, i.e., two Lloydminster heavy oils and a Cactus Lake heavy oil. Then, such predicted pure gas diffusion coefficients are adjusted based on reduced pressure, reduced temperature, and equilibrium ratio to determine apparent diffusion coefficient for a gas mixture in heavy oil, where the equilibrium ratios for hydrocarbon gases and CO2 are determined by using the equilibrium ratio charts and Standing's equations, respectively. It has been found for various gas mixtures in two different Lloydminster heavy oils that the newly developed empirical mixing rule is able to reproduce the apparent diffusion coefficient for binary gas mixtures in heavy oil with a good accuracy. For the pure gas diffusion in heavy oil, the absolute average relative deviations (AARDs) for diffusion systems with two different Lloydminster heavy oils and a Cactus Lake heavy oil are calculated to be 2.54%, 14.79%, and 6.36%, respectively. Meanwhile, for the binary gas mixture diffusion in heavy oil, the AARDs for diffusion systems with two different Lloydminster heavy oils are found to be 3.56% and 6.86%, respectively.

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^

scholarly journals Studies on Transformations of Hemophilus influenzae

1961 ◽  
Vol 44 (6) ◽  
pp. 1229-1239 ◽  
Author(s):  
Sol H. Goodgal ◽  
Roger M. Herriott
Keyword(s):  
Diffusion Coefficient ◽  
Diffusion Coefficients ◽  
Sedimentation Coefficient ◽  
Close Correlation ◽  
Erythromycin Resistance ◽  
Hemophilus Influenzae ◽  
A Value ◽  
Transforming Activity ◽  
Separation Cell ◽  
And Diffusion

The sedimentation and diffusion coefficients have been determined for Hemophilus influenzae transforming activity and DNA using P32-labeled DNA. The methods employed the Spinco fixed boundary separation cell for measurements of the sedimentation coefficient and the Northrop-Anson diffusion cell to determine the diffusion coefficient. There was a very close correlation between the amount of DNA and transforming activity sedimented or diffused. The sedimentation coefficient (s20°), for both biological activity and DNA was 27 and the diffusion coefficient (D20°) 1 x 10-8 cm2/sec. The molecular weight calculated from these coefficients gave a value of 16 million. There was no difference in the sedimentation coefficients for the two unlinked markers, streptomycin and erythromycin resistance, and the diffusion coefficients for single markers or the linked markers, streptomycin and cathomycin, were the same.

A Study about Diffusion Coefficient of Carbon Dioxide in Heavy Oil

2014 ◽  
Vol 962-965 ◽  
pp. 578-582
Author(s):  
Bo Su ◽  
Yong Chen Song ◽  
Yu Liu ◽  
Yue Chao Zhao ◽  
Min Hao ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Oil Recovery ◽  
Heavy Oil ◽  
Initial Pressure ◽  
Gas Diffusion ◽  
Geological Sequestration ◽  
Equilibrium Pressure ◽  
Enhance Oil Recovery ◽  
The Relationship ◽  
And Diffusion

CO2 injection into oil reservoirs can both enhance oil recovery and realize CO2 geological sequestration. The gas diffusion coefficient of CO2 in oil and water is a very important factor for EOR. This paper developed a simple experimental technique for measuring the CO2 diffusion coefficient in heavy oil. In this paper, we find the relationship between initial pressure and diffusion coefficient and equilibrium pressure at the same temperature.

scholarly journals Dependence of Viscosity and Diffusion on β-Cyclodextrin and Chloroquine Diphosphate Interactions

Processes ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1433
Author(s):  
Lenka Musilová ◽  
Aleš Mráček ◽  
Eduarda F. G. Azevedo ◽  
M. Melia Rodrigo ◽  
Artur J. M. Valente ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Diffusion Coefficients ◽  
Mutual Diffusion ◽  
Binary Diffusion Coefficient ◽  
Concentration Gradients ◽  
Cross Diffusion ◽  
Taylor Dispersion Technique ◽  
Dispersion Technique ◽  
And Diffusion ◽  
Chloroquine Diphosphate

Mutual diffusion coefficients of chloroquine diphosphate (CDP) in aqueous solutions both without and with β-cyclodextrin (β-CD) were measured at concentrations from (0.0000 to 0.0100) mol dm−3 and 298.15 K, using the Taylor dispersion technique. Ternary mutual diffusion coefficients (Dik) measured by the same technique are reported for aqueous CDP + β-CD solutions at 298.15 K. The presence of β CD led to relevant changes in the diffusion process, as showed by nonzero values of the cross-diffusion coefficients, D12 and D21. β-CD concentration gradients produced significant co-current coupled flows of CDP. In addition, the effects of β-CD on the transport of CDP are assessed by comparing the binary diffusion coefficient of aqueous CDP solutions with the main diffusion coefficient (D11) measured for ternary {CDP(1) + β-CD(2)} solutions. These observations are supported by viscosity analysis. All data allow to have a better interpretation on the effect of cyclodextrin on the transport behavior of CDP.

scholarly journals Gas diffusivity in chinampas soils in Mexico City .

2014 ◽  
Vol 2 ◽  
Author(s):  
Elena Ikkonen ◽  
Ervin Stephan-Otto ◽  
Norma Eugenia García-Calderón ◽  
Amparo Martínez-Arroyo
Keyword(s):  
Diffusion Coefficient ◽  
Organic Carbon ◽  
Mexico City ◽  
Predictive Models ◽  
Diffusion Coefficients ◽  
Gas Diffusion ◽  
Gas Diffusivity ◽  
Free Air ◽  
Classical Gas ◽  
Mineral Soils

In this laboratory experiment we measured soil gas diffusion coefficients (<em>D</em>) on undisturbed cores of anthropogenic <em>chinampas</em> soils and tested the validity of some classical gas diffusivity models for predicting the ratio of <em>D</em> to the gas diffusion coefficient in free air (<em>D</em><sub><em>0</em></sub>) as a function of the soil air-filled porosity (<em>ε</em>). The A1 horizon (0-7 cm) of <em>chinampas </em>soils had the highest gas diffusivity and a linear relationship between <em>D/D</em><sub><em>0</em></sub> and <em>ε</em>, and thus, the Penman model gave an adequate prediction for this sub-horizon. The Millington-Quirk model was similar to the <em>D/D</em><sub><em>0</em></sub> at all values of <em>ε</em> for the A2 sub-horizon (7-18 cm) and at <em>ε</em> &lt; 0.5 cm<sup>3</sup> cm<sup>-3</sup> for the A3 (18-30 cm) and A4 (30-50 cm) sub-horizons. Gas diffusivities in <em>chinampas</em> soils were lower than in mineral soils, as predicted by <em>D/D</em><sub><em>0</em></sub>(<em>ε</em>) models, likely due to the high content of soil organic carbon. The predictive models could be used for the evaluation of greenhouse gases emission from <em>chinampas</em> soil.

scholarly journals A New Approach to Determine Gas Diffusion Coefficients in Porous Solids by EIS: Application for NH3 and CO2 Adsorption on Zirconia and Zeolite Type 5A

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Tien-Quang Nguyen ◽  
Maja Glorius ◽  
Cornelia Breitkopf
Keyword(s):  
Carbon Dioxide ◽  
Diffusion Coefficient ◽  
Diffusion Coefficients ◽  
Gas Adsorption ◽  
Transport Coefficients ◽  
Gas Diffusion ◽  
Porous Solids ◽  
Ammonia Adsorption ◽  
Zeolite Type ◽  
The Difference

A new theoretical approach has been established to define transport coefficients of charge and mass transport in porous materials directly from impedance data; thus four transport coefficients could be determined. In case of ammonia adsorption on sulfated zirconia, the diffusion coefficient was figured out to be approximately the mobility diffusion coefficient of ammonium ions: 1.2 x 10-7 cm2/s. The transport of carbon dioxide was examined for samples of zeolite type 5A in different hydration states. By impedance spectroscopy measurements, the diffusion coefficient of water vapor at 373 K is estimated to be about 7 x 10-6 cm2/s. The influence of carbon dioxide adsorption on diffusion coefficients is studied based on two pellet types of zeolite 5A. The difference between polar and non-polar gas adsorption in porous solids is considered as changed characteristic of impedance.

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