Gas Diffusion Model Research Articles

Gas Steady-state Diffusion in Fractal Porous Media

Gas diffusion in fractal pores does not follow the classic Fick’s and Knudsen’s laws, so more research on gas diffusion in fractal porous media is needed. Fractal pore models are generated using the random walk method. The gas diffusion governing equations for the fractal pores are derived from the classic kineti theory of gases. The gas diffusion model is used to study the gas diffusion in fractal porous meida and to determine steady-state diffusion coefficient formulas. The results show that the diffusion coefficient is proportional to the mean proe diameter, porosity, and the exponetial function of the fractal dimension in the Knudsen diffusion regime. The diffusion coefficient is not only related to the three pore parameters but is also related to the molecular mean free path in the configurational diffusion regime.

Energy-Efficient Boundary Detection for Continuous Objects in Collaborative Edge Networks

Along with a large and increasing number of resource-constrained and battery-powered smart things being deployed in networks, an energy-efficient mechanism for continuous object boundary detection is fundamental for prolonging the network lifetime. Most of the existing studies focus on how to improve the boundary accuracy of continuous objects while ignoring the energy consumption of smart things in edge networks, which may lead to some smart things being in an unusable state. To address this issue, we propose an ${E}$ nergy-efficient ${C}$ ontinuous object boundary ${D}$ etection ${M}$ echanism, namely ECDM . This mechanism consists of two stages: (i) edge-collaboration monitoring mechanism, where only sensory data relevant to toxic gas are transmitted among multi-edge networks, thus minimizing the number of exchanged sensory data involved in the detection, and reducing the transmission energy consumption of smart things; (ii) gas diffusion model is used to predict the diffusion of toxic gases, such that suspicious edge networks can be located quickly and efficiently, further reducing the energy consumption of smart things transmitting anomalous sensory data. Experimental results show that the energy consumption of ECDM is reduced by 34.5% compared to the latest boundary detection method that introduces a gas diffusion model while maintaining detection accuracy.

Pollution gas concentration and diffusion model in shale gas flowback fluid

Aiming at the uncertainty of the concentration of the pollution gases and the spread of distribution in the process of shale gas development, the open optical path Fourier Transform infrared spectroscopy (FTIR) measurement system designed and built by ourselves is used to invert the concentration of pollution gases in the backflow, and the size of pollution source is calculated by the flow rate of backflow liquid and the size of pollution source. By combining with the field environment and establishing the reference coordinates, the Gaussian diffusion model is derived mathematically, and the non-point source diffusion model of pollution source is constructed and simulated. The result shows that the source intensity, distance, wind speed and atmospheric stability all affect gas concentration diffusion. The concentration of main pollution gas and the strength of non-point source are obtained by continuously measuring the backflow liquid for 80 h. The result shows that C<sub>3</sub>H<sub>8</sub>, C<sub>5</sub>H<sub>12</sub>, C<sub>3</sub>H<sub>6</sub>, CO and SO<sub>2</sub> are the main pollution gases of the backflow liquid, and their maximum concentrations are 4.689 mg/m<sup>3</sup>, 25.494 mg/m<sup>3</sup>, 30.324 mg/m<sup>3</sup>, 0.656 mg/m<sup>3</sup> and 4.620 mg/m<sup>3</sup>, respectively. The maximum strengths of non-point source are 1.9872 g/s, 10.9750 g/s, 12.8513 g/s, 0.2707 g/s and 1.9064 g/s, respectively. By combining the wind speed and daytime environmental conditions, the atmospheric stability is selected and the source strength is substituted into the non-point source diffusion model, the diffusion concentration of polluted gas is obtained, and the real-time monitoring of the concentration distribution of different polluted gases at different locations is realized. The traditional method is used to collect air samples in the field and determine them in the laboratory. It takes a long time and different sampling methods are affected by the preservation time of samples, etc., so there is a great difference between the measured values in the laboratory and the measured values in the field. The country has issued online monitoring standards for volatile organic compounds (VOCs), but most of them are for the determination of non-methane total hydrocarbon, which cannot realize in situ component analysis, and cannot implement the monitoring of VOC concentration distribution within the region. Compared with traditional measurement methods, the method of FTIR and non-point source diffusion model can not only realize the non-contact, long-distance, online measurement of pollution sources, but also set the dynamic factory boundary of the pollution area and determine the safe distribution area.

Simulation experiment and mathematical model analysis for shale gas diffusion in nano-scale pores

Gas diffusion in nano-scale porous media of deeply burried shale includes bulk diffusion (Fick and Knudsen diffusions) and surface diffusion. To reveal the migration mechanism of this process, the influence of temperature and pressure on diffusion coefficient needs to be quantitatively evaluated. A case study was made with the Cambrian Niutitang Formation in the Maoping area, Zigui, western Hubei, South China. Gas diffusion was simulated by isobaric diffusion experiments under different temperature and pressure conditions. The results indicated that:(1) The diffusion coefficient DF decreases with increasing of pressure (when the pressure is higher than 30 MPa, DF tends to be constant), and increases with increasing of temperature; (2) In the high temperature-pressure setting, DF is affected significantly by pressure and generally tends to decrease. Moreover, the impacts of temperature, pressure, porosity and lithology were quantitatively calculated, and a mathematical model of gas diffusion was established, which had comparable results with simulation experiment. The following conclusions were thus drawn:(1)Higher temperature will cause stronger molecular kinetic energy, resulting in increasing bulk and surface diffusion coefficients, while higher pressure will slightly strengthen the Fick and surface diffusions, but significantly limit the Knudsen diffusion, and cause lower total diffusion coefficient; (2) Larger pore size leads to stronger bulk diffusion, but weaker surface diffusion. Finally, according to the studies of a specific research block, high pressure setting is conducive to the preservation of nano-scale porous gas reservoir in shale, while the uplift accompanied by pressure release is the main stage of shale gas loss.

Spatiotemporal distribution of carbon dioxide partial pressure and its diffusion flux in surface water of Karst wetland

为揭示岩溶湿地表层水体二氧化碳分压（pCO₂）的时空分布规律及其扩散通量，以我国最大的岩溶湿地贵州威宁草海为研究对象，分别于2019年7月（丰水期）和12月（枯水期）通过网格布点法，系统采集草海表层湿地水体，测定水样理化指标和离子组成，利用PHREEQCI软件计算水体pCO₂，并基于Cole提出的气体扩散模型估算水-气界面二氧化碳（CO₂）的扩散通量.结果表明：草海湿地表层水体丰水期pCO₂的变化范围为0.44~645.65 μatm，平均值为（55.94±124.73）μatm；枯水期变化范围为35.48~707.95 μatm，平均值为（310.46±173.54）μatm；丰水期水体整体pCO₂低于枯水期，空间上两期水体均呈现东部区域及河流入湖口处pCO₂较高，而中西部区域pCO₂欠饱和的特征.水-气界面CO₂的扩散通量在丰水期变化范围为-43.27~27.16 mmol/（m²·d），平均值（-34.49±12.93） mmol/（m²·d），枯水期变化范围为-33.36~28.15 mmol/（m²·d），平均值（-8.02±15.85） mmol/（m²·d），与其他岩溶湖库相比，水生植物丰富的草海在两个极端水文期CO₂扩散通量相对较低，总体表现为大气CO₂的汇.;In order to explore the temporal and spatial distribution of the partial pressure of carbon dioxide (pCO₂) and its diffusion flux in the surface water of karst wetland, the largest karst wetlands in China, Weining Chaohai, Guizhou Province, was selected as the research object. The surface wetland water of Lake Caohai was systematically collected through the method of grid placement in July (wet season) and December (dry season), respectively, in 2019. The physicochemical parameters and ion composition of the water samples were measured, the pCO₂ of the water was calculated by PHREEQCI, and the diffusion flux of carbon dioxide (CO₂) at the water-air interface was estimated base on the gas diffusion model proposed by Cole. The results show that the variation of pCO₂ in the surface water of Lake Caohai wetland ranges from 0.44 μatm to 645.65 μatm in the wet season, with an average value of (55.94±124.73) μatm, while 35.48 μatm to 707.95 μatm in the dry season, with an average value of (310.46±173.54) μatm. In general, the distribution of pCO₂ was higher in dry season than in wet season, and higher in the eastern lake area and the entrance of river to the lake but undersaturated in the midwest area of the study region, spatially. The diffusion flux of CO₂ in Lake Caohai wetland water ranges from -43.27 mmol/(m²·d) to 27.16 mmol/(m²·d), with an average value of (-34.49±12.93) mmol/(m²·d) in the wet season, while ranges from -33.36 mmol/(m²·d) to 28.15 mmol/(m²·d), with an average value of (-8.02±15.85) mmol/(m²·d) in the dry season. Compared with other karst lakes and reservoirs, Lake Caohai, which is rich in aquatic plants, has relatively low CO₂ diffusion flux during the two extreme hydrological periods, and is generally a sink of atmospheric CO₂.

Quantifying methane release and dispersion estimations for buried natural gas pipeline leakages

The methane into the soil from buried natural gas pipelines due to small leakages, changes the soil properties, posing potential risks to humans and the environment. It is essential to estimate the leakage rate and monitor the methane diffusion range outside the pipeline, which is challengeable due to the presence of soil. The main contribution of this work is to bridge the gap between estimating the leakage rate of underground pipelines and predicting the diffusion behaviors through calculating the gas concentration in the soil. The quantified leakage rate estimation model for air was firstly established by experimental results and validated by the numerical results, which was further modified by the methane with the numerical simulations. The methane diffusion model in the soil was then performed, through which, the influencing factors were explained and validated. In addition, the methane release and dispersion results in the soil could be used as the boundary conditions of gas diffusion model in the air. The results show that the quantifying estimation correlations can predict the leakage rate and dispersion range in the soil accurately, with errors less than 7.2 % and 15 %, respectively. Moreover, the quantified relations have been validated by the full-field experiments. And, the dispersion behaviors in the air could be portrayed instead of being regarded as a jet flow.

Validation of Gas Diffusivity Models with Chilean Soil Samples

This study compares the goodness of fit of 10 empirical models used to predict gas diffusivity (Dp D0−1) with experimental data obtained from Chilean soil samples from different soil management practices. Nine sites under different soil management practices were sampled at different depths. In total, 275 soil cores were obtained. The gas diffusion coefficient (Dp) was determined at different matric potentials using a gas diffusion chamber saturated with free-oxygen (O2) nitrogen (N2) as the gas that diffuses and oxygen as the measured gas inside the diffusion chamber with a gaseous oxygen sensor. Complementary soil properties were measured in order to modelate the diffusivity with several models. The use of statistical indexes, i.e., determination coefficient (r2), root mean square error (RMSE), mean bias error (BIAS), the agreement index (d), and the mean absolute error (MAE), to rank the models according to the fit of goodness was proposed. The models of Millington and Quirk (M-Q), Penman Water Linear Reduction Model (P-WLR), Millington Water Linear Reduction Model (MI-WLR), and Marshal Water Linear Reduction Model (MA-WLR) showed a high simplicity and had a better prediction of gas diffusivity than more complex models. The Three-Porosity Model (TPM) showed the worst performance among the models. Thus, the use of more complex models does not guarantee a better prediction of gas diffusivity. However, it is necessary to test other complex models that incorporate soil management practices and have presented better results than those used in this work. Also, incorporating new soil management could be the base to develop a more accurate comparison. Finally, the P-WLR and TPM models had the best and worst performances above all models. It is suggested to test new models and to increase soil management in future research.

FRACTAL ANALYSIS OF SURFACE ROUGHNESS EFFECTS ON GAS DIFFUSION IN POROUS NANOFIBERS

Fractal model of gas diffusion in porous nanofibers with rough surfaces is derived, in which the porous structure is assumed to be composed of a bundle of tortuous capillaries whose pore size distribution and surface roughness follow the fractal scaling laws. The analytical expression for gas relative diffusion coefficient is a function of the relative roughness and the other microstructural parameters (porosity, the fractal dimension for pore size distribution and tortuosity, the maximum and minimum pore diameter and the characteristic length). The proposed fractal model is validated by comparison with available experimental data and correlations. At the same time, the effect of microstructural parameters of porous fibrous materials on gas diffusion has been studied in detail. It is believed that the current model may be extended to porous materials other than fibrous materials.

Fission gas diffusion and release for Cr[formula omitted]O[formula omitted]-doped UO[formula omitted]: From the atomic to the engineering scale

The anticipated benefits of large grains in Cr2O3-doped UO2 pellets include improved mechanical and fission gas retention properties. To support the assessment of fission gas release (FGR) from doped pellets, the impact of doping on fission gas diffusivity for in-reactor conditions must be understood. In this work, we tackle this issue by informing the fission gas model within the BISON fuel performance code using material models developed at the atomic scale. The investigation of intra-granular fission gas diffusivity in Cr2O3-doped UO2 is carried out by adapting a cluster dynamics model that, accounting for UO2 thermochemistry, is capable of describing Xe diffusion under irradiation in undoped UO2 as the starting point. Using a thermodynamic analysis, it is shown that in stoichiometric UO2 with additions of Cr2O3, the oxygen potential is defined by the Cr-Cr2O3 two-phase equilibrium. Using the cluster dynamics model, the predicted Xe diffusivity in doped UO2 was significantly increased in both the intrinsic and irradiation-enhanced regimes compared to undoped UO2, as a result of higher concentrations of uranium and oxygen vacancies, respectively. This is a consequence of the more oxidizing conditions at high temperature, and more reducing conditions at low temperature, as a result of doping. Arrhenius functions have been fitted to the cluster dynamics results to enable implementation of the new diffusivities in the BISON fission gas behavior model. BISON simulations were carried out, showing the competing effects of the enlarged grains and the new fission gas diffusivity model, which act to suppress and enhance fission gas release, respectively. The new physics-informed model was validated against in-reactor experimental measurements under normal operation. Additionally, benchmarking was carried out for power ramp conditions. The predicted fission gas release agreed well with the experimental data, showing noticeable improvements over the standard UO2 model.

Numerical simulation of methane spreading in porous media after leaking from an underground pipe

PurposeNatural gas leak from underground pipelines could lead to serious damage and global warming, whose spreading in soil should be systematically investigated. This paper aims to propose a three-dimensional numerical model to analyze the methane–air transportation in soil. The results could help understand the diffusion process of natural gas in soil, which is essential for locating leak source and reducing damage after leak accident.Design/methodology/approachA numerical model using finite element method is proposed to simulate the methane spreading process in porous media after leaking from an underground pipe. Physical models, including fluids transportation in porous media, water evaporation and heat transfer, are taken into account. The numerical results are compared with experimental data to validate the reliability of the simulation model. The effects of methane leaking direction, non-uniform soil porosity, leaking pressure and convective mass transfer coefficient on ground surface are analyzed.FindingsThe methane mole fraction distribution in soil is significantly affected by the leaking direction. Horizontally and vertically non-uniform soil porosity has a stronger effect. Increasing leaking pressure causes increasing methane mole flux and flow rate on the ground surface.Originality/valueMost existing gas diffusion models in porous media are for one- or two-dimensional simulation, which is not enough for predicting three-dimensional diffusion process after natural gas leak in soil. The heat transfer between gas and soil was also neglected by most researchers, which is very important for predicting the gas-spreading process affected by the soil moisture variation because of water evaporation. In this paper, a three-dimensional numerical model is proposed to further analyze the methane–air transportation in soil using finite element method, with the presence of water evaporation and heat transfer in soil.

Thermal extraction of water ice from the lunar surface - A 3D numerical model

We have used a three-dimensional thermal and gas diffusion model to study the heated extraction of water ice from lunar regolith. Both surface heating and the insertion of heated drills were investigated for various heating power levels and expected soil ice fractions. Our calculations rely on the use of the Crank-Nicolson finite difference method for the diffusion equations.We find that the extraction of water vapor from lunar regolith requires high levels of heating power in the investigated configurations. Any heating below about 1000 ​W per m2 or per heated drill produces negligible amounts of vapor. We also find that extraction efficiencies are highly dependent on the heating configuration, as well as the initial ice fraction present in the regolith. In addition, we find that, depending on the heating configuration, significant amounts of water escape the heated volume and are lost through refreeze in colder regions.We conclude that water extraction through heating will be a power-hungry process if not optimized through additional controls (e.g. volume confinement by heated walls). In addition, the choice of a heating configuration for optimal extraction efficiency depends on the ice content of the soil. Therefore, detailed prospecting will be essential to the design of future ISRU activities on the Moon.

A model for gas diffusion in multiscale pores of coal coupling multiple diffusion mechanisms

ABSTRACT Gas diffusion in coal is an important process for coalbed methane extraction. Multiple diffusion mechanisms and various gas states exist in the pores of coal, causing gas diffusion to be a complex process. In this study, a gas diffusion model for multiscale pores of coal coupling multiple diffusion mechanisms was established, and the effect of pore size distribution type on gas diffusion was studied. Verified through experimental results, we found that the tortuosity for coal is very high and can be expressed by a power function relationship between tortuosity and porosity with the index n set as 3. The calculations show that the average pore size and pore type can clearly affect gas desorption, including the desorption ratio, gas diffusion type and diffusion coefficient. For free gas in coal, bulk diffusion dominates in macropores, and transition diffusion dominates in mesopores and micropores. Free gas diffusion plays a leading role in macropores and is also the main form in mesopores, while in micropores, surface diffusion accounts for the main proportion and cannot be ignored. The effective diffusion coefficient for coal with macropores is of the order of magnitude of 10−11 – 10−10 m2 s−1, increasing in gas desorption; the effective diffusion coefficient for coal with mesopores is of the order of magnitude of 10−12 – 10−11 m2 s−1, having a limited increase as gas desorption; the effective diffusion coefficient for coal with micropores is on the order of magnitude of 10−12 m2 s−1, rarely affected by desorption; and the effective diffusion coefficient has a great difference in coal having bimodal distributions, showing the gas diffusion heterogeneity in coal.

Numerical Study on Gas Transport in Shale Kerogen with Adsorption Effect Using LBM

Gas transport and storage mechanism in gas reservoirs with complex pore size distribution play a key role in gas production. In the nano-scale, during the process of density disturbance caused by depressurization development, notable output gas collides with the wall as they convey along the channel. The continuum assumption of fluid flow is therefore invalid, and taking the influence of particles to collide with solid walls into account is necessary. The effective viscosity and slip boundary conditions were introduced in the simulation. Meanwhile, because of the adsorption effect is one of the most important intrinsic properties of shale, the impact of surface adsorption on the solid wall by using Langmuir adsorption kinetics was also involved in our investigation. In this work, a unified LB model was developed for gas multiple transports and surface adsorption in nanopores. In the model, the double distribution function was employed for a coupled bulk flow and gas diffusion model. The model is valid within the range of the continuum regime to the transition regime and has been verified by the analytical solution and the results of some previously published works. The results show that (1) the driven force of the fluid, the combination coefficient of slippage and the Knudsen number of the flow have an impact on the adsorption rate, (2) adsorption effect only directly influence the local small region of the solid surface, and the induced concentration gradient makes the global concentration variation, (3) once acting the surface adsorption on the boundary, the flux falls more significant as Knudsen number increases.

Research on Gaussian Plume Model of Gas Diffusion in Coal Mine Roadway Based on BP Neural Network Optimized by Genetic Algorithm

Intelligent monitoring and control of harmful gas in a coal mine is an important aspect of the building on intelligent and green mine. It is a hot spot of artificial intelligence research in the coal mine to study the new technology of dynamic prediction of harmful gas by using artificial intelligence, big data and other interdisciplinary fusion methods, and gradually replace the artificial monitoring work. By researching the gas diffusion theory and the characteristics of the coal mine environment, this paper uses the Gaussian plume model to simulate the gas diffusion law of coal mine roadway, and puts forward a gas prediction model optimized by genetic algorithm and BP neural network. The algorithm takes the absolute error between the predicted output of gas source term and the field measured value as the peculiar fitness value and optimizes it. The results show that the optimized BP neural network can obtain the best concentration prediction value for short time and a small error. Compared with the traditional gas prediction method in coal mine, this method has the advantages of small calculation amount and high prediction accuracy, and it can improve the reliability of the model by continuous machine learning combined with daily monitoring, which provides a new technical solution for the intelligent detection of environmental information in coal mine roadway.

Observed volatilization behavior of silicon carbide in flowing hydrogen above 2000 K

AbstractThe intrinsic compatibility of silicon carbide (SiC) and hydrogen (H2) at high temperatures (2000‐2473 K) and pressure near one atmosphere was evaluated through a combination of thermodynamic calculations and hot hydrogen exposure testing. Thermodynamic calculations predict the decomposition of SiC in a hydrogen environment to form free silicon (Si) and free carbon (C). Free Si is predicted to vaporize from the surface as a volatile species, while free C may interact with H2 to form the hydrocarbons CH4 (T < 2100 K) or C2H2 (T > 2100 K). Coupons of high purity chemical vapor deposition (CVD) β‐SiC were exposed to slowly flowing hydrogen at temperatures ranging between 2000 and 2473 K. SiC experienced active attack as the result of H2 exposure, exhibiting linear weight loss kinetics and an Arrhenius dependence of weight loss on exposure temperature. The linear volatilization constant was experimentally evaluated to correspond with an activation energy of 370 ± 18 kJ/mol. Due to the dependence of observed corrosion rates on gas velocity, corrosion of SiC in flowing H2 was determined to be governed by external mass transfer of volatile Si species through the boundary layer. Experimentally derived mass losses were in good agreement with mass losses predicted by a boundary layer limited gas diffusion model.

Research on Gas Diffusion Law of Coal Mine Roadway Based on Gauss Plume Model

The gas environment of coal mine is complex, so it is urgent to monitor gas automatically and accurately through fixed instruments and mobile equipment. Combine with gas diffusion theory, a gas concentration prediction method based on the Gauss plume model was proposed, and the gas diffusion model in coal mine roadway was constructed. According to the virtual image source method, the influence of boundary reflection on gas diffusion was introduced, and the gas diffusion coefficient was modified by genetic algorithm. The results of simulation analysis and actual data analysis indicate that this method can reveal the gas distribution law of coal mine roadway, besides it can improve the real-time, convenience and reliability of gas concentration detection in the roadway.

Neuroprotection of dopamine neurons by xenon against low-level excitotoxic insults is not reproduced by other noble gases

Using midbrain cultures, we previously demonstrated that the noble gas xenon is robustly protective for dopamine (DA) neurons exposed to l-trans-pyrrolidine-2,4-dicarboxylate (PDC), an inhibitor of glutamate uptake used to generate sustained, low-level excitotoxic insults. DA cell rescue was observed in conditions where the control atmosphere for cell culture was substituted with a gas mix, comprising the same amount of oxygen (20%) and carbon dioxide (5%) but 75% of xenon instead of nitrogen. In the present study, we first aimed to determine whether DA cell rescue against PDC remains detectable when concentrations of xenon are progressively reduced in the cell culture atmosphere. Besides, we also sought to compare the effect of xenon to that of other noble gases, including helium, neon and krypton. Our results show that the protective effect of xenon for DA neurons was concentration-dependent with an IC50 estimated at about 44%. We also established that none of the other noble gases tested in this study protected DA neurons from PDC-mediated insults. Xenon’s effectiveness was most probably due to its unique capacity to block NMDA glutamate receptors. Besides, mathematical modeling of gas diffusion in the culture medium revealed that the concentration reached by xenon at the cell layer level is the highest of all noble gases when neurodegeneration is underway. Altogether, our data suggest that xenon may be of potential therapeutic value in Parkinson disease, a chronic neurodegenerative condition where DA neurons appear vulnerable to slow excitotoxicity.

Effects of particle size and adsorption pressure on methane gas desorption and diffusion in coal

A self-developed gas desorption and diffusion experimental system was used to conduct isothermal methane gas desorption and diffusion experiments, and the pore structure of coal samples was analyzed. A new mathematical model for gas diffusion in coal particles was established, and the diffusion coefficient was calculated using the new model. The influences of particle size and the adsorption equilibrium pressure on the methane gas diffusion rate, gas diffusion quantity, and diffusion coefficient were analyzed and discussed. The results show that under different adsorption equilibrium pressures and different particle sizes, the diffusion rate and quantity vary substantially. The larger the particle size, the slower the initial gas diffusion rate and the longer the time required to reach desorption equilibrium. The larger the adsorption pressure, the greater the initial gas diffusion rate and the larger the quantity of diffusion gas accumulated. However, the coal particle size has little influence on the amount of gas diffusion. It was found that as the particle size decreases, the diffusion coefficient in the first diffusion phase is significantly reduced, which decays with a negative exponential function over time. However, the adsorption equilibrium pressure has no obvious influence on the diffusion coefficient. In addition, the methane gas diffusion process was divided into three phases, namely, phase I, rapid diffusion phase (0–10 min); phase II, slow diffusion phase (10–100 min); and phase III, smooth diffusion phase (100 min); and the diffusion mechanism corresponding to each phase was analyzed. These research results provide a theoretical and practical reference value for gas prevention and control in coal mines.

Implementation of multi-component dusty-gas model for species transport in quasi-three-dimensional numerical analysis of solid oxide fuel cell. Part I: hydrogen fuel

Quasi-three-dimensional numerical model of solid oxide fuel cell, which assumes constant physicochemical properties within the cell components in the thickness direction, typically employs a simple gas diffusion model for species transport in the porous electrodes, such as the Fick’s model. In this study, a three-dimensional grid system is introduced in the anode layer and coupled with the quasi-three-dimensional solid oxide fuel cell model. The multi-component dusty-gas model is implemented to solve the conservation of species on this three-dimensional grid system. The results with the developed model are compared with experimental data obtained under hydrogen fuel. The obtained results show that the dusty-gas model can accurately predict the transport of gas species in the porous anode.

Mass Transfer Mechanisms and Rates of CO2 and N2 in 13X Zeolite from Volumetric Frequency Response

The mass transfer mechanisms and rates of CO2 and N2 in 13X zeolite beads were determined using volumetric frequency response (VFR) methods. The VFR experiments were conducted with each gas over a wide range of frequencies from 7 × 10–5 to 9.5 Hz at 100, 200, and 750 Torr at 25 °C for CO2 and at 200, 400, and 750 Torr at 25 °C and at 40 and 55 °C at 400 Torr for N2. The resulting experimental intensity response curves were fitted to four different non-isothermal mass transfer models, including micropore diffusion, macropore gas diffusion, macropore viscous (Poiseuille) flow, and macropore surface diffusion. The resulting experimental phase lag response curves were predicted from the resulting model parameters. The macropore gas diffusion model fitted and predicted the experimental response curves the best for both gases, confirming the mass transport of both CO2 and N2 in 13X zeolite beads is macropore gas diffusion controlled. The corresponding diffusional time constant Dp/Rp2 values were 3.32 s–1 for CO...