Simulation Of Gas Diffusion Research Articles

Simulation of Gas Diffusion–Adsorption Coupling in Adsorbents for Optimizing Pore Structures

Simulation of Gas Diffusion–Adsorption Coupling in Adsorbents for Optimizing Pore Structures

Reconstruction of the Chemical Gas Concentration Distribution Using Partial Convolution-Based Image Inpainting.

An interpolation method, which estimates unknown values with constrained information, is based on mathematical calculations. In this study, we addressed interpolation from an image-based perspective and expanded the use of image inpainting to estimate values at unknown points. When chemical gas is dispersed through a chemical attack or terrorism, it is possible to determine the concentration of the gas at each location by utilizing the deployed sensors. By interpolating the concentrations, we can obtain the contours of gas concentration. Accurately distinguishing the contours of a contaminated region from a map enables the optimal response to minimize damage. However, areas with an insufficient number of sensors have less accurate contours than other areas. In order to achieve more accurate contour data, an image inpainting-based method is proposed to enhance reliability by erasing and reconstructing low-accuracy areas in the contour. Partial convolution is used as the machine learning approach for image-inpainting, with the modified loss function for optimization. In order to train the model, we developed a gas diffusion simulation model and generated a gas concentration contour dataset comprising 100,000 contour images. The results of the model were compared to those of Kriging interpolation, one of the conventional spatial interpolation methods, finally demonstrating 13.21% higher accuracy. This suggests that interpolation from an image-based perspective can achieve higher accuracy than numerical interpolation on well-trained data. The proposed method was validated using gas concentration contour data from the verified gas dispersion modeling software Nuclear Biological Chemical Reporting And Modeling System (NBC_RAMS), which was developed by the Agency for Defense Development, South Korea.

Numerical simulation of gas diffusion and explosion limit of VOCs in containment integrated leak rate test

CILRT is an important work in the overhaul of nuclear power plants. VOCs from paints and cleaners used in the containment during the overhaul will migrate inside the containment, and the numerous rooms and compartments inside the containment make the air flow impeded, and the VOCs may be enriched to bring combustion risk. The complete fire risk analysis method includes volatilization kinetics of chemicals, mixture explosion limits, and numerical simulation of VOCs diffusion and migration. The volatilization rate at the lowest room temperature of 20°C is used as a conservative input, the complement of CAITA realistic model is used as the flow domain, and the geometry is appropriately simplified, and the steady ventilation process, the internal flow and the laws of diffusion and agglomeration of 12 kinds of VOCs gases in the 9-h pressure-holding process are investigated by Computational Fluid Dynamics. The simulation results of steady ventilation show that the VOCs gases are almost uniformly carried by the air to all spaces inside the containment, and the explosion risk is low. The concentration field of the steady ventilation process was taken as the initial boundary condition and unsteady state simulation of the 9-h holding pressure process was performed. The results show that the gas flow inside the containment basically stops after 3456 s of pressure holding. With the extension of time, the VOCs gases accumulate at the bottoms of the three lower layers of the containment under the effect of laminar diffusion and gravitational settling, where the total concentration of the mixed gases reaches the highest at the bottom of the lowest layer. The total concentration of the VOCs gas mixture was below the lower explosion limit throughout the 9-h pressure-holding process, and the explosion risk was low.

Effect of non-isothermal adsorption model on gas diffusion in coal particle

Gas diffusion is of great importance for coalbed methane (CBM) recovery and CO2 storage in coal seam. Most of the existing models of gas diffusion in coal particles are derived under isothermal conditions, while the coupled effect between gas adsorption/desorption and temperature variation is often neglected. The effect of accurate non-isothermal adsorption model on gas diffusion simulation also needs further study. In this work, isothermal adsorption tests of CO2 in anthracite/bitumite particles at different temperatures are conducted. The fitting results of Langmuir/Freundlich adsorption models are analyzed and the optimal non-isothermal adsorption models for anthracite/bitumite are obtained respectively. Non-isothermal desorption-diffusion tests of CO2 in anthracite/bitumite particles are carried out and corresponding non-isothermal desorption-diffusion model is also proposed, based on which the effect of non-isothermal adsorption model on gas diffusion in coal is numerically analyzed comprehensively. The results show that the non-isothermal Langmuir/Freundlich adsorption models are optimal for anthracite/bitumite respectively. Based on the optimal adsorption models, simulated gas diffusion amounts agree well with the experimental results and consistent diffusion coefficients can be back calculated. For sub-optimal adsorption model with R2 > 0.9, its deviation from adsorption data would significantly affect the accuracy of gas desorption-diffusion simulation. Moreover, if ‘diffusion ratio’ is taken as evaluation index, the inaccurate diffusion amount caused by inaccurate adsorption model in numerical simulation may be ignored, and the diffusion coefficient determined by ‘diffusion ratio’ would deviate from the true value.

Data-based real-time petrochemical gas diffusion simulation approach on virtual reality

BackgroundPetrochemical products possess a high risk of flammability, explosivity, and toxicity, making petrochemical accidents exceedingly destructive. Therefore, disaster analysis, prediction, and real-time simulations have become important means of controlling and reducing accident hazards. MethodsThis study proposes a complete real-time simulation solution of gas diffusion with coordinate and concentration data, which was mainly aimed at simulating the types of harmful gas leakage and diffusion accidents in the petrochemical industry. The rendering effect was more continuous and accurate through grid homogenization and trilinear interpolation. This study presents a data processing and rendering parallelization process to enhance simulation efficiency. Gas concentration and fragment transparency were combined to synthesize transparent pixels in a scene. To ensure the approximate accuracy of the rendering effect, improve the efficiency of real-time rendering, and meet the requirement of intuitive perception using concentration data, a weighted blended order-independent transparency(OIT) with enhanced alpha weight is presented, which can provide a more intuitive perception of the hierarchical information of concentration data while preserving depth information. This study compares and analyzes three OIT algorithms—depth peeling, weighted blended OIT, and weighted blended OIT with enhanced alpha weight—in terms of rendering image quality, rendering time, required memory, and hierarchical information. ResultsUsing weighted blended OIT with an enhanced alpha weight technique, the rendering time was shortened by 53.2% compared with that of the depth peeling algorithm, and the texture memory required was significantly smaller than that of the depth peeling algorithm. The rendering results of weighted blended OIT with an enhanced alpha weight were approximately accurate compared with those of the depth peeling algorithm as the ground truth, and there was no popping when surfaces passed through one another. Simultaneously, compared with weighted blended OIT, weighted blended OIT with an enhanced alpha weight achieved an intuitive perception of the hierarchical information of concentration data.

Acute chlorine poisoning caused by an accident at a swimming pool

Chlorine is an irritant gas that is widely used in water purification. Several previous reports had reported accidents of inhalation injuries at swimming pools. However, there have been limited data on the detection of on-site chlorine concentration. This study aims to report a chlorine leakage accident at a swimming pool caused by improper disinfection operations. Calculation using the gas diffusion simulation software showed that the on-site chlorine concentration was 221.45 ppm. When the accident occurred, there were 92 individuals at the swimming pool and the gym, among which 61 were referred to the emergency department of five different hospitals for feeling ill. Among them, 22 patients underwent chest high-resolution computed tomography scans in our hospital. According to the findings, 4 (18.2%) patients had peribronchitis, 3 (13.6%) had tracheobronchitis, 4 (18.2%) had pneumonia, 4 (18.2%) had interstitial pulmonary edema, and 3 (13.6%) had alveolar pulmonary edema. The symptoms of 22 patients who visited our hospital significantly improved after comprehensive treatment. Three months after the accident, 8 of 17 patients presented obstructive ventilation defects or small airway dysfunction. The accidental exposure to chlorine may induce acute poisoning with various respiratory injuries and prolonged lung dysfunction.

Radioactive gas diffusion simulation and inhaled effective dose evaluation during nuclear decommissioning

During the decommissioning of the nuclear facilities, the radioactive gases in pressure vessels may leak due to the demolition operations. The decommissioning site has large space, slow air circulation, and many large nuclear facilities, which increase the difficulty of workers' inhalation exposure assessment. In order to dynamically evaluate the activity distribution of radionuclides and the committed effective dose from inhalation in nuclear decommissioning environment, an inhalation exposure assessment method based on the modified eddy-diffusion model and the inhaled dose conversion factor is proposed in this paper. The method takes into account the influence of building, facilities, exhaust ducts, etc. on the distribution of radioactive gases, and can evaluate the influence of radioactive gases diffusion on workers during the decommissioning of nuclear facilities.

Research on the Personnel Shelter Location and Evacuation Route Model Planning under Emergent Events

Based on the reaction lag of emergency response, inadequate emergency rescue capacity and unreasonable emergency supply allocation and shelter location, it was of great significance to study the reasonable shelter locations and rapid evacuation route under major emergencies for the purpose of disaster prevention and mitigation. The Voronoi diagram partition method was carried out to determine the optimal layout and rational allocation of settlements based on the influence mode of emergency events and characteristics of personnel transfer and settlement, as well as the transfer distance impedance value was 2000 m. The possible population capacity of the settlement was used as weight of settlement planning selection, and a nonlinear full coverage solution model of settlements with shortest path was established. The solution method of the escape route for rapid personnel transfer under major emergencies was proposed to which according to the personnel settlement layout optimization model. Based on the poison gas diffusion simulation particle model and the risk assessment model of road section disaster of the cellular automaton, the path solving system of multi-source concurrent gas leakage and rapid diffusion of toxic gas under complex wind field conditions and dynamic prediction were also developed to predict disaster changes over time and provide technical support for early planning to avoid disasters and rapid personnel transfer.

FEM-simulation of gas diffusion in solid closed-cell porous materials

The past decades witnessed growing interest in polymeric closed-cell porous materials. They are lightweight, robust and find applications in many different sectors, like packaging, thermal insulation or cushioning. Numerical simulations are commonly used in the construction process to predict the behaviour of the products in application. So far, gas diffusion has often been neglected, as there are no tools available to include it. Therefore, this paper aims to present an algorithm to include the simulation of gas diffusion into a commercial finite element analysis (FEA) tool, at the example of MSC Marc. Using the similarity of thermal conductivity and gas diffusion, the thermal solver of the FEA program is exploited to perform the simulation of gas diffusion. Some first two-dimensional numerical simulations of porous closed-cell models under long-term load show promising results. Effective diffusion coefficients are obtained and conclusions about the time scale are made. The results agree to analytical estimations of the diffusion process. A notable influence of gas diffusion on long-term loaded porous materials can be shown.

Microscopic Insights into Biological Relevance of Membrane Channels in Gas Transport across Lipid Membranes

Membrane transport of small, non-polar gas molecules, such as O2 and CO2, is among fundamental processes of living cells. Because of their size and chemical properties, these molecules may unimpededly transit through the lipid phase of the membrane. However, varying degrees of gas permeability in membranes with different lipid compositions have been reported experimentally, suggesting involvement of protein channels, particularly aquaporins (AQPs), in gas transport across membranes. To account for membrane heterogeneity and to probe potential roles of AQPs in gas transport, we performed extensive MD simulations of gas diffusion through lipid membranes. The systems simulated included POPC bilayers embedded with an AQP tetramer (i.e., AQP1, AQP5 or AQP7), and protein-free lipid bilayer mixtures of POPC, cholesterol (CHL) and sphingomyelin (SM) or DPPC. Each of them contained an excess amount (125 molecules) of a gas species and was simulated for several hundred nanoseconds. Since the gas molecules were allowed to diffuse freely, their permeability coefficients were directly estimated by measuring their flow through the lipid and protein phases. The results showed that gas molecules diffused through the membrane via monomeric water and hydrophobic central pores of AQPs, and via the lipid phase. For fluid-like membranes (e.g., 100% POPC) which exhibited high gas permeability, AQPs would not facilitate the permeation. Highly-ordered or gel-like membranes (e.g., 100% SM and 50:50 SM:CHL or DPPC:CHL), on the other hand, exhibited reduced gas permeability as low as or even lower than through AQPs, suggesting that in such conditions, AQPs would become imminent in facilitating gas transport. Consistently with experimentally observed low gas permeability in high SM-CHL containing membranes, such as those of erythrocytes and ocular lens, our study suggests biological significance of protein-facilitated gas permeation across membranes.

Fire-fighting Training System Based on Virtual Reality

Applying virtual reality technique to fire-fighting training can effectively solve waste of manpower, material, money and so on. In this paper, we will combine HTC Vive and Unity3D engine to carry out the design and development of fire-fighting training system. Particle system, navigation grid, animation system and collision detection technology are applied to achieve flame flus gas diffusion simulation, non- experiencer follow, animation production, interaction functions between characters and objects respectively, to save time for rendering spent and meet the real-time demand of virtual scenes generation, this paper optimizes virtual scenes by using LOD technology and occlusion culling technique. The results show that the fire-fighting training system has a good sense of immersion, and it can meet the demand of fire-fighting training.

Pore-scale simulation of gas diffusion in unsaturated soil aggregates: Accuracy of the dusty-gas model and the impact of saturation

Gas diffusions in soil control all physical and biogeochemical processes in terrestrial ecosystems and correctly describing them is critical to numerical modelling of these processes. The movement of gases in soil needs to overcome the resistances caused by both gas-gas collision and gas-wall collision, and the relative significance of one resistance over another depends on the size and spatial distribution of the pores. Practical models often use the empirical dusty-gas formula to estimate the effective gas diffusion coefficient, assuming that all resistances are addable even after a volumetric average. Since it is impossible to separately measure the two resistances, the accuracy and reliability of this approach remains unknown. We investigate this using pore-scale modelling and tomography. Soil aggregates are acquired using X-ray computed tomography and the size and spatial distribution of their pores are calculated using a morphological model; each pore is associated with a bulk diffusion coefficient and a Knudsen diffusion coefficient, with the latter calculated based on the pore size. We then develop pore-scale models to simulate gas diffusion, and the diffusive flux and gas concentration simulated at pore scale are volumetrically averaged to calculate i) the effective Knudsen diffusion coefficient assuming the bulk diffusion coefficient is infinite, ii) the effective bulk diffusion coefficient assuming the Knudsen diffusion coefficient is infinite, and iii) the overall effective diffusion coefficient considering both the bulk and the Knudsen diffusions. The dusty-gas model estimates the effective diffusion coefficient using the effective bulk and the Knudsen diffusion coefficients, and its accuracy is tested against the effective diffusion coefficient directly calculated from the pore-scale simulations. The results indicate that the dusty-gas model is accurate when the diffusion is dominated by either bulk diffusion or Knudsen diffusion, whereas in the transition regime it systematically overestimates the effective diffusion coefficient. We also investigate the impact of saturation on the effective diffusion coefficients when the aggregates are either hydrophobic or hydrophilic, elucidating the significance of the Knudsen diffusion as the saturation of the aggregates increases.

Pollen-structured hierarchically meso/macroporous silica spheres with supported gold nanoparticles for high-performance catalytic CO oxidation

Pollen-structured hierarchically meso/macroporous silica spheres (PHMSs) are synthesized using rape pollen grains and a triblock copolymer poly(ethylene oxide-block-propylene oxide-block-ethylene oxide) (P123) as templates. The PHMSs are comprised of mesoporous walls that form a macroporous structure replicating the net-like morphology of the pollen grain exine. The unique structure has a high BET surface area of 626m2g−1 and uniform mesopores with average pore size below 5nm. With the Au content fixed at 6.8wt%, the Au nanoparticles supported on the PHMSs achieved a higher CO conversion at an ambient temperature (30°C) than those supported on typical mesoporous silica SBA-15. Au nanoparticles supported on PHMSs also reached 100% CO conversion at a lower temperature than those supported on the SBA-15. The effects of silica support on the catalytic performances are investigated through calculation of the diffusion coefficients and simulation of gas diffusion in PHMSs and SBA-15. It is shown that the hierarchical PHMSs facilitate gas diffusion better than the non-hierarchical SBA-15, hence leading to higher CO oxidation catalytic performance.

Molecular dynamics simulation of gas diffusion in polyethylene-clay nanocomposites with different silicate layers configurations

Barrier properties of pristine polyethylene (PE) and polyethylene/montmorillonite-clay (PE/MMT) nanocomposite films with different MMT layers configurations were studied using molecular dynamics simulation within NVT ensemble. The force field parameters were optimized for bond lengths, bond angles and torsion angles of the MMT structure. A special simulation box was designed to simulate the diffusion of oxygen, nitrogen and methane, through pristine PE and PE/MMT nanocomposite films. The diffusion coefficients of these gases and the tortuosity values were calculated and analyzed. Results showed that the configuration of clay nanoparticles has strong effect on the barrier properties of the nanocomposite films. The parallel configuration for layered silicates was predicted to have a low diffusion coefficient and a high tortuosity parameter for gas diffusive molecules. The simulation could also indicate that the diffusion coefficient of oxygen is higher than those of nitrogen and methane gases in the examined systems which can be attributed to the smaller kinetic diameter of oxygen.

Benchmarking Rapid TLES Simulations of Gas Diffusion in Proteins: Mapping O2 Migration and Escape in Myoglobin as a Case Study.

Standard molecular dynamics (MD) simulations of gas diffusion consume considerable computational time and resources even for small proteins. To combat this, temperature-controlled locally enhanced sampling (TLES) examines multiple diffusion trajectories per simulation by accommodating multiple noninteracting copies of a gas molecule that diffuse independently, while the protein and water molecules experience an average interaction from all copies. Furthermore, gas migration within a protein matrix can be accelerated without altering protein dynamics by increasing the effective temperature of the TLES copies. These features of TLES enable rapid simulations of gas diffusion within a protein matrix at significantly reduced (∼98%) computational cost. However, the results of TLES and standard MD simulations have not been systematically compared, which limits the adoption of the TLES approach. We address this drawback here by benchmarking TLES against standard MD in the simulation of O2 diffusion in myoglobin (Mb) as a case study since this model system has been extensively characterized. We find that 2 ns TLES and 108 ns standard simulations map the same network of diffusion tunnels in Mb and uncover the same docking sites, barriers, and escape portals. We further discuss the influence of simulation time as well as the number of independent simulations on the O2 population density within the diffusion tunnels and on the sampling of Mb's conformational space as revealed by principal component analysis. Overall, our comprehensive benchmarking reveals that TLES is an appropriate and robust tool for the rapid mapping of gas diffusion in proteins when the kinetic data provided by standard MD are not required. Furthermore, TLES provides explicit ligand diffusion pathways, unlike most rapid methods.

Formation and gas-sensing properties of a porous-alumina-assisted 3-D niobium-oxide nanofilm

For advanced gas-sensing applications, we have synthesized a 3-dimensional (3-D) metal/oxide/metal nanofilm that merges the benefits of advanced composite inorganic materials with the flexibility of non-lithographic electrochemical technologies based on so-called porous-anodic-alumina-assisted anodizing of a refractory metal and the original point electrodeposition of noble metals. The film is composed of an NbO2 layer, 200nm thick, with upright-standing Nb2O5 nanocolumns (diameter ∼50nm, length 900nm, density 8×109cm−2), which work as semiconducting nano-channels, assembled between two parallel metal electrodes, whose resistivity measured along the columns is greatly impacted by the surface and interface reactions. A laboratory microdevice employing the 3-D niobium-oxide nanofilm, mounted on a standard TO-8 package, revealed asymmetric electron transfer properties due to a Schottky barrier formed at the Au/Nb2O5 interface, resistive switching mechanism in the film, and superior characteristics for hydrogen and, especially, ethanol detection with best response times to 1000ppm H2 and 500ppm H2C6O being 3 and 1min, respectively. A computer-aided simulation of gas diffusion in the 3-D nanofilm predicts a possibility to substantially improve sensor performance through the formation of a perforated top electrode and by introducing certain innovations in the electrode design.

Rapid Simulation and Visualization Analysis of Liquid Ammonia Tank Leakage Risk

For the complex calculation and analysis problems existing in the liquid ammonia tank leakage and gas diffusion simulation, by selecting appropriate gas diffusion model and writing a program to simulate and analyze the spread of dangerous gas, This article could draw the ammonia diffusion concentration distribution, and the hazardous areas of ammonia diffusion could be divided accurately and rapidly, then used the program to simulate and analyze the effects of the factors such as wind velocity, ground roughness and liquid ammonia leakage rate on ammonia diffusion. The results proved that when wind direction was in line with the direction of leakage source, ammonia diffusion distance and the hazardous areas showed a trend of decrease with the increase of wind velocity; Ammonia diffusion distance decreased with the increase of ground roughness in the direction of down-wind; Ammonia diffusion distance and hazardous areas increased with the increase of liquid ammonia leakage rate.

リスク評価のためのウォーターカーテンを考慮した気体拡散シミュレーションに関する研究

リスク評価のためのウォーターカーテンを考慮した気体拡散シミュレーションに関する研究

Simulation of gas diffusion in highly porous nanostructures by direct simulation Monte Carlo

A Direct Simulation Monte Carlo (DSMC) method is utilized to simulate gas diffusion in nanoscaled highly porous layers. An open source solver has been extended with the variable soft sphere (VSS) binary collision model and the inflow boundary model was adjusted for small numbers of DSMC particle initialization. Comparison with the analytical diffusion equation illustrate the improvement of the VSS model compared to the variable hard sphere model (VHS). Subsequently, several highly porous particle layers (gas sensors synthesized by flame spray pyrolysis and isotropic layers) build up by 10nm particles have been investigated. Results for DSMC gas diffusion in the porous structures are in agreement with the well established dusty gas model (DGM). However, while DGM requires measurements or estimations of pore sizes, porosity, and tortuosity and furthermore is limited to homogenous layers, the present contribution shows significant advantages of DSMC in describing gas diffusion in non-isotropic porous structures.

Excess-Entropy Scaling for Gas Diffusivity in Nanoporous Materials

We present an efficient computational procedure for the rapid prediction of the self-diffusivity of gas molecules in nanoporous materials by a combination of the Knudsen model, Rosenfeld's excess-entropy scaling method, and a classical density functional theory (DFT). The self-diffusivity conforms to the Knudsen model at low density, and the effects of intermolecular interactions at higher densities are accounted for by Rosenfeld's excess-entropy scaling method. The classical DFT provides a convenient way to calculate the excess entropy used in the scaling analysis. The hybrid computational procedure has been calibrated with MD simulation for the adsorption of H2, He, Ne, and Ar gases in several nanoporous materials over a broad range of pressure. It predicts adsorption isotherms and different types of diffusion behavior in excellent agreement with the simulation results. Although the simulation of gas diffusion in nanoporous materials is extremely time-consuming, the new procedure is computationally very efficient because it uses only single molecular and thermodynamic parameters.