• Korean Journal of Computational Design and Engineering
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• v.17 no.6
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• pp.387-397
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• 2012

The world has faced with various environmental problems such as climatic change, global pollution, and depletion of natural resources. Conventional economic development continues not only to intensify the magnitude of the problems but also to damage growth potential of future generations. Therefore, recent manufacturers are highly required to accommodate themselves to sustainable development that aims at preventing the loss to the future generations. Moreover, the manufacturers are under heavy pressure from various environmental regulations. This paper proposes green bill of material (Green-BOM) which conforms to the environmental regulations to restructure eco-friendly manufacturing system. Green-BOM is useful for managing green product and process information to satisfy several environmental regulations by recording energy consumption, recycle rate, volatile organic compounds (VOCs), substance information, and so on.

• Macromolecular Research
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• v.8 no.6
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• pp.247-252
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• 2000

Suspension polymerizations of styrene were conducted in the aqueous phase with tricalcium phosphate (TCP) as a stabilizer and $\alpha$, $\alpha$'-azobis(isobutyronitrile) (AIBN) as an initiator. Various amounts of initiator and stabilizer were selected and the reaction was carried out at a selected temperature between 60 to 80 $\^{C}$. It was found that the combination of 5 wt% stabilizer and 2.427$\times$10$\^$-3/ mol/L of costabilizer is the minimum amount for suspension polymerization reaction to produce particles in the aqueous phase. Particles were found to be polydisperse in diameter, regardless of reaction conditions. Class transitions were observed to be around 95$\^{C}$, nearly independent of reaction temperature and initiator. Homogenizer was found to be essential in forming particles in the proximity of tens of micrometers in diameter in suspension polymerization with TCP as stabilizer.

• Nuclear Engineering and Technology
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• v.45 no.7
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• pp.979-986
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• 2013

Uranium metal particle dispersion plates have been proposed as targets for Molybdenum-99 (Mo-99) production to improve the radioisotope production efficiency of conventional low enriched uranium targets. In this study, uranium powder was produced by centrifugal atomization, and miniature target plates containing uranium particles in an aluminum matrix with uranium densities up to 9 $g-U/cm^3$ were fabricated. Additional heat treatment was applied to convert the uranium particles into UAlx compounds by a chemical reaction of the uranium particles and aluminum matrix. Thus, these target plates can be treated with the same alkaline dissolution process that is used for conventional $UAl_x$ dispersion targets, while increasing the uranium density in the target plates.

• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.6
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• pp.1050-1059
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• 2017

Drying processes often cause knitted fabrics to shrink. This study obtains proper drying conditions for in the dryer use that can minimize knitted fabric shrinkage by investigating changes in shrinkage according to drying conditions. The experiment samples were all machine washable plain, mesh, and lacoste knitted fabrics made of 100% cotton. Samples were first washed in a washing machine on a normal cycle. They were then layered on a flat surface in an artificial climate chamber and dried for 24 hours at $20^{\circ}C$ and $40^{\circ}C$, respectively. Shrinkage was measured for 180 minutes at 30 minute intervals after washing. The comparison results of the shrinkage in the washing and drying process indicate that 80.0% and 23.0% shrinkage of plain knitted and lacoste knitted fabrics occurred during the washing process. As the samples dried, the shrinkage of the plain and lacoste knitted fabrics then rapidly increased after approximately 30.0% moisture content. The highest air drying shrinkage occurred over one cycle with insignificant changes in shrinkage after repeated treatments.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.3
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• pp.323-331
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• 2021

With global warming and pollution problems, accurate forecasting of the harmful gases would be an essential alarm in our life. In this paper, we forecast the emission of the five gases(SOx, NO₂, NH₃, H₂S, CH₄) using the time series model of ARIMA, the learning algorithms of Random forest, and LSTM. We find that the gas emission data depends on the short-term memory and behaves like a random walk. As a result, we compare the RMSE, MAE, and MAPE as the measure of the prediction performance under the same conditions given to three models. We find that ARIMA forecasts the gas emissions more precisely than the other two learning-based methods. Besides, the ARIMA model is more suitable for the real-time forecasts of gas emissions because it is faster for modeling than the two learning algorithms.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.4_2
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• pp.657-668
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• 2023

It's important to note that air compressors in the industrial sector are major energy consumers, accounting for a significant portion of total energy costs in manufacturing plants, ranging from 12% to 40%. To address this issue, researchers have compared forecasting models that can predict the power consumption of air compressors. The forecasting models were designed to incorporate variables such as flow rate, pressure, temperature, humidity, and dew point, utilizing statistical methods, machine learning, and deep learning techniques. The model performance was compared using measures such as RMSE, MAE and SMAPE. Out of the 21 models tested, the Elastic Net, a statistical method, proved to be the most effective in power comsumption forecasting.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_3
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• pp.1205-1213
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• 2023

This study delves into methods for enhancing the power efficiency of air compressor systems, with the primary objective of significantly impacting industrial energy consumption and environmental preservation. The paper scrutinizes Shinhan Airro Co., Ltd.'s power efficiency optimization technology and employs machine learning ensemble models to simulate power efficiency optimization. The results indicate that Shinhan Airro's optimization system led to a notable 23.5% increase in power efficiency. Nonetheless, the study's simulations, utilizing machine learning ensemble techniques, reveal the potential for a further 51.3% increase in power efficiency. By continually exploring and advancing these methodologies, this research introduces a practical approach for identifying optimization points through data-driven simulations using machine learning ensembles.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.378-383
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• 2005

This experimental study presents the results of the cooling performance test of a $CO_2$ heat pump system for fuel cell vehicles. The experimental facility provides the cool ing and heating environment for cabin and heat releasing component. The test loop is designed to target the cooling capacity of 5kW and its coefficient of performance (COP) of 2.2. The cooling performance of the heat pump system is strongly dependent on the refrigerant charge and the degree of superheat. We carried out basic experiments to obtain optimum refrigerant charge and the degree of superheat level at the internal heat exchanger outlet. The heat pump system for fuel cell vehicles is different from that of engine-driven vehicles, where the former has an electricity-driven compressor and the latter has the belt-driven (engine-driven) compressor. In the fuel cell vehicle, the compressor speed is an independent operating parameter and it is controlled to meet the cooling/heating loads. Experiments were carried out at cooling mode with respect to the compressor speed and the incoming outdoor air speed. The results obtained in this study can provide the fundamental cool ing performance data using the $CO_2$ heat pump system for fuel cell vehicles.

• The Korean Journal of Archival Studies
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• no.54
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• pp.5-44
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• 2017

This study investigates the theoretical discourses about the principle of original order. It reviews the literature about the theory in the context of personal and family papers. The authors examine the practical application of the principle of original order in the case of the No Gun Ri archives. No Gun Ri collections started with the records that the Chung family's have accumulated and created. Without an understanding of the Chung family papers, it is extremely difficult to identify a way to arrange No Gun Ri reords. This paper analyzes the meaning and interpretation of the principle of original order to find a way to apply it to the No Gun Ri records.

• Journal of Korean Society of Archives and Records Management
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• v.21 no.1
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• pp.19-40
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• 2021

This study aims to explore alternative strategies for the archival professional training system in response to changing records management environments. It found implications in the training and qualification system for overseas archival professionals and compared and analyzed the qualification system for Korean archival professionals. In addition, by analyzing the archival graduate schools' general status and the instructors' research performance, the study confirmed that many instructors have low academic interest in archival studies and the gap between schools was significant. Based on this, interviews with professors and experts were conducted to gather opinions on improving the archival professional training system. In conclusion, the study presents prerequisite tasks of organizing an archival community governance system and securing self-regulatory power. Moreover, it proposes innovative measures for the archival professional training system with three major tasks: creating graduate education guidelines, establishing a continuing and deepening education system, and transforming educational institutions.