• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2001.11a
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• pp.7-7
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• 2001

The increasing interest in light weight materials coupled to the need for cost -effective processing have combined to create a significant opportunity for aluminum P/M. particularly in the automotive industry in order to reduce fuel emissions and improve fuel economy at affordable prices. Additional potential markets for Al PIM parts include hand tools. Where moving parts against gravity represents a challenge; and office machinery, where reciprocating forces are important. Aluminum PIM adds light weight, high compressibility. low sintering temperatures. easy machinability and good corrosion resistance to all advantages of conventional iron bm;ed P/rv1. Current commercial alloys are pre-mixed of either the AI-Si-Mg or AL-Cu-Mg-Si type and contain 1.5% ethylene bis-stearamide as an internal lubricant. The powder is compacted in closed dies at pressure of 200-500Mpa and sintered in nitrogen at temperatures between $580~630^{\circ}C$ in continuous muffle furnace. For some applications no further processing is required. although most applications require one or more secondary operations such as sizing and finishing. These sccondary operations improve the dimension. properties or appearance of the finished part. Aluminum is often considered difficult to sinter because of the presence of a stable surface oxide film. Removal of the oxide in iron and copper based is usually achieved through the use of reducing atmospheres. such as hydrogen or dissociated ammonia. In aluminum. this occurs in the solid st,lte through the partial reduction of the aluminum by magncsium to form spinel. This exposcs the underlying metal and facilitates sintering. It has recently been shown that < 0.2% Mg is all that is required. It is noteworthy that most aluminum pre-mixes contain at least 0.5% Mg. The sintering of aluminum alloys can be further enhanced by selective microalloying. Just 100ppm pf tin chnnges the liquid phase sintering kinetics of the 2xxx alloys to produce a tensile strength of 375Mpa. an increilse of nearly 20% over the unmodified alloy. The ductility is unnffected. A similar but different effect occurs by the addition of 100 ppm of Pb to 7xxx alloys. The lend changes the wetting characteristics of the sintering liquid which serves to increase the tensile strength to 440 Mpa. a 40% increase over unmodified aIloys. Current research is predominantly aimed at the development of metal matrix composites. which have a high specific modulus. good wear resistance and a tailorable coefficient of thermal expnnsion. By controlling particle clustering and by engineering the ceramic/matrix interface in order to enhance sintering. very attractive properties can be achicved in the ns-sintered state. I\t an ils-sintered density ilpproaching 99%. these new experimental alloys hnve a modulus of 130 Gpa and an ultimate tensile strength of 212 Mpa in the T4 temper. In contest. unreinforcecl aluminum has a modulus of just 70 Gpa.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.17-18
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• 2011

Plasma in liquid phase has attracted great attention in the last few years by the wide domain of applications in material processing, decomposition of organic and inorganic chemical compounds and sterilization of water. The plasma in liquid is characterized by three main regions which interact each - other during the plasma operation: the liquid phase, which supply the plasma gas phase with various chemical compounds and ions, the plasma in the gas phase at atmospheric pressure and the interface between these two regions. The most complex region, but extremely interesting from the fundamental, chemical and physical processes which occur here, is the boundary between the liquid phase and the plasma gas phase. In our laboratory, plasma in liquid which behaves as a glow discharge type, is generated by using a bipolar pulsed power supply, with variable pulse width, in the range of 0.5~10 ${\mu}s$ and 10 to 30 kHz repetition rate. Plasma in water and other different solutions was characterized by electrical and optical measurements. Strong emissions of OH and H radicals dominate the optical spectra. Generally water with 500 ${\mu}S/cm$ conductivity has a breakdown voltage around 2 kV, depending on the pulse width and the repetition rate of the power supply. The characteristics of the plasma initiated in ultrapure water between pairs of different materials used for electrodes (W and Ta) were investigated by the time-resolved optical emission and the broad-band absorption spectroscopy. The deexcitation processes of the reactive species formed in the water plasma depend on the electrode material, but have been independent on the polarity of the applied voltage pulses. Recently, Coherent anti-Stokes Raman Spectroscopy method was employed to investigate the chemistry in the liquid phase and at the interface between the gas and the liquid phases of the solution plasma system. The use of the solution plasma allows rapid fabrication of the metal nanoparticles without being necessary the addition of different reducing agents, because plasma in the liquid phase provides a reaction field with a highly excited energy radicals. We successfully synthesized gold nanoparticles using a glow discharge in aqueous solution. Nanoparticles with an average size of less than 10 nm were obtained using chlorauric acid solutions as the metal source. Carbon/Pt hybrid nanostructures have been obtained by treating carbon balls, synthesized in a CVD chamber, with hexachloro- platinum acid in a solution plasma system. The solution plasma was successfully used to remove the template remained after the mesoporous silica synthesis. Surface functionalization of the carbon structures and the silica surface with different chemical groups and nanoparticles, was also performed by processing these materials in the liquid plasma.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.35-47
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• 2001

Traffic represents one of the largest sources of primary air pollutants in urban area. As a consequence. numerous abatement strategies are being pursued to decrease the ambient concentration of pollutants. A characteristic of most of the these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emission inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for vehicle types. The majority of inventories are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. The study of current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a methodology of motor vehicle emission calculation by using real-time traffic data was studied. A methodology for estimating emissions of CO at a test area in Seoul. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It was calculated speed-related mass of CO emission from traffic tail pipe of data from traffic system, and parameters are considered, volume, composition, average velocity, link length. And, the result was compared with that of a method of emission calculation by VKT(Vehicle Kilometer Travelled) of vehicles of category.

• Economic and Environmental Geology
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• v.48 no.1
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• pp.25-39
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• 2015

$CO_2$ geological storage plays an important role in reduction of greenhouse gas emissions, but there is a lack of research for CCS demonstration. To achieve the goal of CCS, storing $CO_2$ safely and permanently in underground geological formations, it is essential to understand the characteristics of them, such as total storage capacity, stability, etc. and establish an injection strategy. We perform the impedance inversion for the seismic data acquired from the Ulleung Basin in 2012. To review the possibility of $CO_2$ storage, we also construct porosity models and extract attributes of the prospects from the seismic data. To improve the quality of seismic data, amplitude preserved processing methods, SWD(Shallow Water Demultiple), SRME(Surface Related Multiple Elimination) and Radon Demultiple, are applied. Three well log data are also analysed, and the log correlations of each well are 0.648, 0.574 and 0.342, respectively. All wells are used in building the low-frequency model to generate more robust initial model. Simultaneous pre-stack inversion is performed on all of the 2D profiles and inverted P-impedance, S-impedance and Vp/Vs ratio are generated from the inversion process. With the porosity profiles generated from the seismic inversion process, the porous and non-porous zones can be identified for the purpose of the $CO_2$ sequestration initiative. More detailed characterization of the geological storage and the simulation of $CO_2$ migration might be an essential for the CCS demonstration.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.3
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• pp.269-286
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• 2015

24-hr integrated $PM_{2.5}$ measurements were performed between December 2013 and October 2014 at an urban site in Gwangju and the collected samples were analyzed for organic carbon (OC), elemental carbon (EC), ionic species, and elemental species. Objectives of this study were to identify $PM_{2.5}$ pollution episodes, to characterize their chemical components, and to examine their probable origins. Over the course of the study period, average $PM_{2.5}$ concentration was $37.7{\pm}23.6$ $(6.0{\sim}121.5){\mu}g/m^3$. Concentrations of secondary ionic species; $NH_4{^+}$, $NO_3{^-}$, and $SO_4{^{2-}}$ was on average $5.54{\mu}g/m^3$ (0.28~ 20.86), $7.60{\mu}g/m^3$ (0.45~ 33.53), and $9.05{\mu}g/m^3$ (0.50~ 34.98), accounting for 13.7% (4.6~ 22.7), 18.6% (2.9~ 44.8), and 22.9% (4.9~ 55.1) of the $PM_{2.5}$ concentration, respectively. Average OC and EC concentrations were $5.22{\mu}g/m^3$ and $1.54{\mu}g/m^3$, taking possession of 4.6 and 22.2% (as organic mass) of the $PM_{2.5}$, respectively. Frequencies at which 24-hr averaged $PM_{2.5}$ exceeded a 24-hr averaged Korean $PM_{2.5}$ standard of $50{\mu}g/m^3$ (termed as an "episode" in this study) were 30, accounting for 21.3% of total 141 measurements. These pollution episodes were mostly associated with haze phenomenon and weak surface wind speed. It is suggested that secondary formation of aerosol was one important formation mechanism of the episodes. The episodes were associated with enhancements of organic mass, $NO_3{^-}$ and $SO_4{^{2-}}$ in winter, of $NO_3{^-}$ and $SO_4{^{2-}}$ in spring, and of $SO_4{^{2-}}$ in summer. Potential source contribution function results indicate also that $PM_{2.5}$ episodes were likely attributed to local and regional haze pollution transported from northeastern China in winter, to atmospheric processing of local emissions rather than long-range transport of air pollutants in spring, and to the $SO_4{^{2-}}$ driven by photochemistry of $SO_2$ in summer.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.109-116
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• 2020

With the advent of high-speed railways, railways are one of the most frequently used means of transportation at home and abroad. In addition, in terms of environment, carbon dioxide emissions are lower and energy efficiency is higher than other transportation. As the interest in railways increases, the issue related to railway safety is one of the important concerns. Among them, visual abnormalities occur when various obstacles such as animals and people suddenly appear in front of the railroad. To prevent these accidents, detecting rail tracks is one of the areas that must basically be detected. Images can be collected through cameras installed on railways, and the method of detecting railway rails has a traditional method and a method using deep learning algorithm. The traditional method is difficult to detect accurately due to the various noise around the rail, and using the deep learning algorithm, it can detect accurately, and it combines the two algorithms to detect the exact rail. The proposed algorithm determines the accuracy of railway rail detection based on the data collected.

• Journal of the Korea Organic Resources Recycling Association
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• v.24 no.4
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• pp.11-20
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• 2016

Depletion of natural resources and reduction of greenhouse gas emissions are an important issue which we have to solve. The recycling of waste has emerged as a global concern. In Korea, the development of cost-effective treatment and recycling technologies also need to be improved. In this study, we compared and analyzed the cost per unit of treatment and recycling of organic waste, and presented an effective recycling scheme. We investigated the current status of treatment and costs for six types of organic wastes from 80 workplaces, including organic wastewater treatment sludge, processed organic sludge, and plant residues. In addition, environmental costs for greenhouse gas reduction were calculated. It's an economic way that organic waste is composted and used as cement additives. In particular, the economic analysis was done by realistic results of the survey target companies. In conclusion, in order for reliable processing and recycling of organic wastes, wastewater treatment sludge and sewage sludge need to be classified based on hazard characteristics. Finally, technical difficulties need to be further resolved such as odors, leachate, and debris on recycling organic wastes.

• Korean Chemical Engineering Research
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• v.58 no.4
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• pp.588-595
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• 2020

Prediction and control of nitrogen oxides (NO_x) emission is of great interest in industry due to stricter environmental regulations. Herein, we propose an artificial intelligence (AI)-based framework for prediction of NO_x emission. The framework includes pre-processing of data for training of neural networks and evaluation of the AI-based models. In this work, Long-Short-Term Memory (LSTM), one of the recurrent neural networks, was adopted to reflect the time series characteristics of NO_x emissions. A decision tree was used to determine a time window of LSTM prior to training of the network. The neural network was trained with operational data from a heating furnace. The optimal model was obtained by optimizing hyper-parameters. The LSTM model provided a reliable prediction of NO_x emission for both training and test data, showing an accuracy of 93% or more. The application of the proposed AI-based framework will provide new opportunities for predicting the emission of various air pollutants with time series characteristics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.281-286
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• 2021

The International Maritime Organization recently proposed a policy to establish a preemptive response strategy for exhaust gas pollution on board ships according to the recent strengthening of the sulfur content regulations. Discussions on improving the fuel oil quality and reducing emissions are also ongoing. Fuel oil quality information, which is one of the main concerns internationally, is increasing as the sulfur content standard is being applied from the current 3.5% to 0.5% by 2020. From the perspective of shipping companies and recipients, the essential quality of fuel oil is also requested for domestic and international fuel oil information, basic properties, correlation information between characteristics for application of solid ships and ships. The current standard for the basic quality of fuel oil is generally used, but the nature and composition of the fuel oil are very complex, and the interpretation of the basic quality is complicated because there are many cases outside the scope of the basic standard. Various factors were analyzed for the basic quality of fuel oil in terms of the basic quality of fuel oil, optimization of operation in ships, and fuel efficiency in ships. Moreover, the possibility of applying the standard according to the dilution was suggested.

• Korean Journal of Environmental Agriculture
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• v.34 no.2
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• pp.69-76
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• 2015

BACKGROUND: Contamination of soils by heavy metals is the serious environmental problem. In particular, industrial processing is one of the main sources of heavy metal contamination. The objective of this study was to investigate the distribution characteristics of heavy metals in soils collected from industrial complex. METHODS AND RESULTS: In this study, the soil contamination and enrichment factor (EF) of heavy metals were investigated in three national industrial complexes such as Yeosu, Ulsan and Sihwa Banwal industrial complexes. The target heavy metals includes Cd, Cu, As, Hg, Pb, Cr, Zn, and Ni. The results showed that the contents of Cd, Hg, Pb, Zn and Ni in Yeosu and the contents of Cu, As and Cr in Sihwa Banwal were higher than in any other industrial complex. The results of principal component analysis(PCA) in Yeosu, Ulsan and Sihwa Banwal complex could be explained up to approximately 81.4, 69.1 and 70.9% by two factor, respectively. Enrichment factors of Cd, Pb and Zn in all the investigated industrial complexes were above 1.0 that was the value judged to be a high contamination. And EF of Cr was above 1.0 in Sihwa Banwal complex. EF of Zn in all sites was generally high from the other heavy metals. CONCLUSION: Therefore, soils maybe significantly affected by heavy metals (especially, Cd, Pb and Zn) present in the emissions from industrial complexes.