• Journal of the Korean Institute of Gas
• /
• v.23 no.6
• /
• pp.67-73
• /
• 2019

Hydrogen is difficult to accurately measure the amount of charge due to sudden temperature changes and pressure rise when charging the vehicle. In order to construct a hydrogen infrastructure, it is important to precisely measure the amount of charge that can be a sensitive issue in commercial transactions. In this study, the accuracy of metering of domestic hydrogen stations was evaluated as a study for metering management of hydrogen dispenser. For the experiment, we constructed metering system using master meter method and measured the flow rate in the actual hydrogen vehicle charging environment. As a result of error occurred about 10% on average, and the hydrogen loss per one charge was found to be up to 60g.

• Geomechanics and Engineering
• /
• v.13 no.5
• /
• pp.861-879
• /
• 2017

Coal and gas outburst is a serious dynamic disaster that occurs during coal mining and threatens the lives of coal miners. Currently, coal and gas outburst is commonly predicted using single indicator and its critical value. However, single indicator is unable to fully reflect all of the factors impacting outburst risk and has poor prediction accuracy. Therefore, a more accurate prediction method is necessary. In this work, we first analyzed on-site impacting factors and precursors of coal and gas outburst; then, we constructed a Fisher discriminant analysis (FDA) index system using the gas adsorption index of drilling cutting ${\Delta}h_2$, the drilling cutting weight S, the initial velocity of gas emission from borehole q, the thickness of soft coal h, and the maximum ratio of post-blasting gas emission peak to pre-blasting gas emission $B_{max}$; finally, we studied an FDA-based multiple indicators discriminant model of coal and gas outburst, and applied the discriminant model to predict coal and gas outburst. The results showed that the discriminant model has 100% prediction accuracy, even when some conventional indexes are lower than the warning criteria. The FDA method has a broad application prospects in coal and gas outburst prediction.

• The Bulletin of The Korean Astronomical Society
• /
• v.40 no.1
• /
• pp.77.2-77.2
• /
• 2015

Galaxies are known to evolve passively in the cluster environment. Indeed, much evidence for HI stripping has been found in cluster galaxies to date, which is likely to be connected to their low star formation rate. What is still puzzling however, is that the molecular gas, which is believed to be more directly related to star formation, shows no significant difference in its fraction between the cluster population and the field galaxies. Therefore, HI stripping alone does not seem to be enough to fully understand how galaxies become passive in galaxy clusters. Intriguingly, our recent high resolution CO study of a subsample of Virgo spirals which are undergoing strong ICM pressure has revealed a highly disturbed molecular gas morphology and kinematics. The morphological and kinematical peculiarities in their CO data have many properties in common with those of HI gas in the sample, indicating that strong ICM pressure in fact can have impacts on dense gas deep inside of a galaxy. This implies that it is the molecular gas conditions rather than the molecular gas stripping which is more responsible for quenching of star formation in cluster galaxies. In this study, using multi transitions of 12CO and 13CO, we investigate the density and temperature distributions of CO gas of a Virgo spiral galaxy, NGC 4402 to probe the physical and chemical properties of molecular gas and their relations to star formation activities.

• Journal of the Korean Society of Safety
• /
• v.23 no.6
• /
• pp.51-56
• /
• 2008

As RFID/USN technology is used in the latest industry trend, the information analysis paradigm shifts to intelligence service environment. The intelligent service includes autonomic operation, which select activity by defining itself to the status of industry facilities. Furthermore, information analysis based on IT used to frequently data mining for detecting the meaning information and deriving new pattern. This paper suggest self-classifying of context-aware by applying data mining in gas facilities for serving the intelligent gas safety management. We modify data algorithm for fitting the domain of gas safety, construct context-aware model by using the proposed algorithm, and demonstrate our method. As the accuracy of our model is improved over 90%, the our approach can apply to intelligent gas safety management based on RFID/USN environments.

• Journal of Environmental Health Sciences
• /
• v.46 no.6
• /
• pp.719-725
• /
• 2020

Objectives: With the growth of national interest in fine particulate matter, many complaints about pollutants emitted from air pollution emitting facilities have arisen in recent years. In particular, it is thought that a large volume of particulate pollutants are discharged from workplaces that use Solid Refuse Fuel (SRF). Therefore, particulate contaminants generated from SRF were measured and analyzed in this study in terms of respective particle sizes. Methods: In this study, particulate matter in exhaust gas was measured by applying US EPA method 201a using a cyclone. This method measures Filterable Particulate Matter (FPM), and does not consider the Condensable Particulate Matter (CPM) that forms particles in the atmosphere after being discharged as a gas in the exhaust gas. Results: The mass concentration of Total Suspended Particles (TSP) in the four SRF-using facilities was 1.16 to 11.21 mg/Sm3, indicating a very large concentration deviation of about 10 times. When the fuel input method was the continuous injection type, particulate matter larger than 10 ㎛ diameter showed the highest particle size fraction, followed by particulate matter smaller than 10 ㎛ and larger than 2.5 ㎛, and particulate matter of 2.5 ㎛ or less. Contrary to the continuous injection type, the batch injection type had the smallest particle size fraction of particulate matter larger than 10 ㎛. The overall particulate matter decreased as the operating load factor decreased from 100% to 60% at the batch input type D plant. In addition, as incomplete combustion significantly decreased, the particle size fraction also changed significantly. Both TSP and heavy metals (six items) satisfied the emissions standards. The measured value of the emission factor was 38-99% smaller than the existing emissions factor. Conclusions: In the batch injection facility, the particulate matter decreased as the operating load factor decreased, as did the particle size fraction of the particulate matter. These results will help the selection of effective methods such as reducing the operating load factor instead of adjusting the operating time during emergency reduction measures.

• Journal of Korean Society for Atmospheric Environment
• /
• v.34 no.4
• /
• pp.534-541
• /
• 2018

Concentrations of total particulate matter (TPM), $PM_{10}$ and $PM_{2.5}$ were measured at three different sites based on each different fuel type (solid, liquid and gas) used in thermal power plants operating in Yeosu and Gwangyang National Industrial Complexes during 2017. The highest concentrations of TPM, $PM_{10}$, and $PM_{2.5}$ were observed at the solid fuel facility, and these values were $3.356mg/Sm^3$, $2.342mg/Sm^3$ and $1.834mg/Sm^3$, respectively. The ratio of $PM_{2.5}$ to TPM was the highest value of 54.6% in solid fuel case, and the lowest was 35.7% found in liquid fuel case. As a result of analyzing 9 kinds of metal compound with respect to each particle size, the metal concentration of TPM is higher than those of $PM_{10}$ and $PM_{2.5}$ in all fuel types. Total concentrations of metal elements in TPM by fuel difference are $1.2702mg/Sm^3$ in solid fuel, 0.0603 mg/Sm3 in liquid fuel, and $0.0733mg/Sm^3$ in gas fuel, respectively. Relatively higher total metal concentration in gas fuel than in liquid fuel was found; and this could be higher Cr and Al concentrations in use of gas fuel. As a result of estimating the emission factors of each facility, in case of solid fuel, TPM emissions per electricity production were found to be 0.7080 kt/PJ, followed by liquid fuel and gas fuel. $PM_{10}$ and $PM_{2.5}$ emissions per hour of electricity production were similar to those of TPM.

• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 2005.11a
• /
• pp.332-333
• /
• 2005

• 한국가스학회:학술대회논문집
• /
• 2006.11a
• /
• pp.221-232
• /
• 2006

• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 2004.05a
• /
• pp.179-180
• /
• 2004

• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 2004.11a
• /
• pp.473-474
• /
• 2004