Numerical simulation to evaluate gas diffusion of turbulent flow in mine ventilation system

Tracer gas technique is a method to analyze the airflow path, measure the airflow quantity, and detect any recirculation or leakages in underground mine. In addition, it is also possible to evaluate the axial gas diffusion of gas in turbulent bulk flow by utilizing the tracer gas data. This paper discussed about the measurement using tracer gas technique in Cibaliung Underground Mine, Indonesia and the evaluation of effective axial diffusion coefficient, E, by numerical simulation. In addition, a scheme to treat network flow in mine ventilation system was also proposed. The effective axial diffusion coefficient for each airway was evaluated based on Taylor's theoretical equation. It is found that the evaluated diffusion coefficient agrees well with Taylor's equation by considering that the wall friction factor, f, is higher than those for smooth pipe flow. It also shows that the value of effective diffusion coefficient can be inherently determined and the value is constant when matching with other measurements. Furthermore, there are possibilities to utilize the tracer gas measurement data to evaluate the airway friction factors.

Seasonal Change in CO2 Production Rate along Depth in a Grassland Field

Soil is a large terrestrial carbon pool so that the evaluation and prediction of soil respiration is important for understanding and managing carbon cycling between the pedosphere and the atmosphere. For better understanding about characteristics and mechanisms of soil respiration, this study monitored seasonal behaviors of soil gaseous CO2 concentration profile with relevant soil physical conditions in a meadow field, and numerically analyzed the monitored data sets to inversely determine time-series of depth distributions of CO2 production rate in the field by assuming optimum ranges of depth and moisture condition for aerobic respiration of soil fauna and flora. The results of the inverse analyses showed that the depth range of intense CO2 production resided in top soil layers during summer and moved down into subsoil layers in winter, implying that the depth range of main CO2 sources can change dynamically with seasons. The surface CO2 emission rates derived from the inverse analyses fell in the range typically found in the same kind of land use. The evaluated mean residence time of gaseous CO2 in the study field was around half a day. These findings suggested that the modelling assumptions about soil respiration in this study are effective to probe spatial and temporal behavior of respiratory activity in a soil layer, and it is still important to integrate facts about in-situ CO2 concentration profiles with soil physical parameters for quantitatively predicting possible behaviors of soil respiration in response to hypothetical changes in atmospheric and soil climates.

Diffusivity Models and Greenhouse Gases Fluxes from a Forest,Pasture,Grassland and Corn Field in Northern Hokkaido,Japan

Information on the most influential factors determining gas flux from soils is needed in predictive models for greenhouse gases emissions. We conducted an intensive soil and air sampling along a 2 000 m transect extending from a forest, pasture, grassland and corn field in Shizunai, Hokkaido （Japan）, measured CO2, CH4, N20 and NO fluxes and calculated soil bulk density （Pb）, air-filled porosity （fa） and total porosity （Ф）. Using diffusivity models based on either fa alone or on a combination of fa and 4, we predicted two pore space indices： the relative gas diffusion coefficient （Ds/Do） and the pore tortuosity factor （T）. The relationships between pore space indices （Ds/Do and T） and C02, CH4, N2O and NO fluxes were also studied. Results showed that the grassland had the highest Pb while fa and Ф were the highest in the forest. CO2, CH4, N20 and NO fluxes were the highest in the grassland while N20 dominated in the corn field. Few correlations existed between fa, Ф, Pb and gases fluxes while all models predicted that Ds/Do and T significantly correlated with CO2 and CH4 with correlation coefficient （r） ranging from 0.20 to 0.80. Overall, diffusivity models based on fa alone gave higher Ds/Do, lower τ, and higher R2 and better explained the relationship between pore space indices （Ds/Do and τ） and gases fluxes. Inclusion of Ds/Do and τ in predictive models will improve our understanding of the dynamics of greenhouse gas fluxes from soils. Ds/Do and τ can be easily obtained by measurements of soil air and water and existing diffusivity models.

Sourcing the merits of 3D integrated air cathodes for highperformance Zn-air batteries by bubble pump consumption chronoamperometry

Zn-air batteries(ZABs)as a potential energy conversion system suffer from low power density(typically≤200 mW·cm^(−2)).Recently,three-dimensional(3D)integrated air cathodes have demonstrated promising performance over traditional twodimensional(2D)plane ones,which is ascribed to enriched active sites and enhanced diffusion,but without experimental evidence.Herein,we applied a bubble pump consumption chronoamperometry(BPCC)method to quantitatively identify the gas diffusion coefficient(D)and effective catalytic sites density(ρEC)of the integrated air cathodes for ZABs.Furthermore,the D andρEC values can instruct consequent optimization on the growth of Co embedded N-doped carbon nanotubes(CoNCNTs)on carbon fiber paper(CFP)and aerophilicity tuning,giving 4 times D and 1.3 timesρEC over the conventional 2D Pt/C-CFP counterparts.As a result,using the CoNCNTs with half-wave potential of merely 0.78 V vs.RHE(Pt/C:0.89 V vs.RHE),the superaerophilic CoNCNTs-CFP cathode-based ZABs exhibited a superior peak power density of 245 mW·cm^(−2) over traditional 2D Pt/C-CFP counterparts,breaking the threshold of 200 mW·cm^(−2).This work reveals the intrinsic feature of the 3D integrated air cathodes by yielding exact D andρEC values,and demonstrates the feasibility of BPCC method for the optimization of integrated electrodes,bypassing trial-and-error strategy.