• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3695-3702
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• 2022

South Korea, a country that built a world-class nuclear power infrastructure, shifted to a nuclear phaseout during the previous government's reign. This shift was pursued as part of a larger task of electricity mix reform, and one of the integral motives for such reform is addressing greenhouse gas (GHG) and fine dust problems. Thus, verifying the relationships between the public's concerns about GHG/fine dust and their acceptance of nuclear power generation is essential for designing public communication strategies to revive nuclear power under the ongoing environmental regime. Our analysis using a nationwide survey sample of South Korea (N = 1009, through proportionated quota sampling method) showed that the more people are concerned about GHG and fine dust, the less they accept nuclear power. These relationships held even after controlling for the effect of a third variable-energy-related environmentalism. This finding means that despite past communication efforts positioning nuclear power as a generation source that can mitigate GHG/fine dust emissions and the widely accepted scientific evidence that supports such positioning, nuclear power in Korea is in jeopardy. Our finding provides implications for public communications and fundamental knowledge for research on the determinants of nuclear power acceptance.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3703-3716
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• 2022

Target alignment technology is one of the most critical technologies in laser fusion experiments and is an important technology related to the success of laser fusion experiments. In this study, by combining the open-loop and closed-loop errors of the target alignment, the Kalman state observer is used to estimate the position of the target, which improves the observation precision of the target alignment. Then the optimized result is used to guide the alignment of the target. This method can greatly optimize the target alignment error and reduce uncertainty. With the improvement of the target alignment precision, it will greatly improve the reliability and repeatability of the experiments' results, thereby improving the success rate of the experiments.

• Proceedings of the Optical Society of Korea Conference
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• 2001.08a
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• pp.176-176
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• 2001

• Journal of the Society of Disaster Information
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• v.18 no.3
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• pp.532-541
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• 2022

Purpose: The purpose of this study is to suggest that the existing power demand prediction method including power demand according to fine dust is included in the existing power consumption by using an air purifier to improve the air quality due to fine dust. Method: The method of the study was compared and analyzed using data on the concentration of fine dust in Seoul for three years, household power consumption, and climate observation, and the effect of fine dust on power consumption in Seoul was identified in April and October. Result: The power consumption of home air purifiers in Seoul due to fine dust differences between April and October was calculated to be 2,141 MWh, accounting for 3.4% of the total difference in the use of home appliances in April and October. Conclusion: The effect of fine dust on household power consumption was verified, and power demand prediction is essential for economic system operation and stable power supply, so power consumption due to fine dust should be considered as well as focusing on power consumption of existing air conditioners and heaters.

• Environmental and Resource Economics Review
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• v.30 no.4
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• pp.627-648
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• 2021

The fine-dust season management system refers to the policy of implementing enhanced reduction measures in transportation, power, business and living sectors in winter, when fine dust levels are high. The fine dust season management system is a regulatory policy that causes social costs and transfers to various economic players. Equity is an important issue for the cost burden. Therefore, in this study, the cost of each power generator was analyzed using the coal power generation reduction amount of each power generator to verify that the cost of the power sector is evenly distributed. In particular, the effect of the fine dust season management system on coal power generation of power generators was analyzed by applying a synthetic control method that can identify the time-variable effect of the policy. It was confirmed that the fine dust season management system reduced volume of fuel and power generation in coal power plants, resulting in an increase in the cost of the power generation sector, even considering the effect of some power demand due to the COVID-19 crisis. However, it could be seen that these costs were not distributed equally among the generators, and that they were more costly to the specific generators.Social costs incurred by fine dust season management need to be improved so that stakeholders are equally burdened.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.4
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• pp.455-460
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• 2020

In order to identify the characteristics of fine particle emissions from thermal power plants, this study conducted measurement of the primary emission concentration of TPM, PM₁₀ and PM_2.5 according to Korea standard test method (ES 01301.1) and ISO 23210 method (KS I ISO 23210). Particulate matters were sampled in total 74 units of power plants such as 59 units of coal-fired power plants, 7 units of heavy oil power plants, 2 units of biomass power plant, and 6 units of liquid natural gas power plants. The average concentration of TPM, PM₁₀, PM_2.5 by fuel are 3.33 mg/m³, 3.01 mg/m³, 2.70 mg/m³ in coal-fired plant, 3.02 mg/m³, 2.99 mg/m³, 2.93 mg/m³ in heavy oil plant, 0.114 mg/m³, 0.046 mg/m³, 0.036 mg/m³ in LNG plant, respectively. These results of TPM, PM₁₀ and PM_2.5 were satisfied with the standards of fine dust emission allowance in all units of power plants, respectively. Also, this study evaluated the characteristics of fine particle emissions by conditions of power plants including generation sources, boiler types and operation years and calculated emission factors and then evaluated fine particle emissions by sources of electricity generation.

• ETRI Journal
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• v.33 no.3
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• pp.466-469
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• 2011

As a fine-grained power gating method for achieving greater power savings, our approach takes advantage of the finite state machine with a datapath (FSMD) characteristic which shows sequential idleness among subcircuits. In an FSMD-based power gating, while only an active subcircuit is expected to be turned on, more subcircuits should be activated due to the power overhead. To reduce the number of missed opportunities for power savings, we deactivated some of the turned-on subcircuits by slowing the FSMD down and predicting its behavior. Our microprocessor experiments showed that the power savings are close to the upper bound.

• The Korean Journal of Ecology
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• v.17 no.2
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• pp.113-119
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• 1994

Vertical and horizontal distribution and seasonal changes of fine roots as well as inorganic nitrogen content in soil were determined in Quercus mongolica and Quercus acutissima stands in Mt. Taemosan, Seoul. The vertical distribution of fine rooth phytomass showed a power-functional decrease as descending soil depth. Fine root phytomass was 170 g $DM/m^2$(46%) and 225 g $DM/m^2$(47%) in top soil of 5 cm depth, and 370 g $DM/m^2$ and 480 g $DM/m^2$ from soil surface to 50 cm depth in Q. mongolica and Q. acutissima stands, respectively. Fine roots in relation to the distance from the nearest tree were evenly distributed horizontally in both stands. Fine roots phytomass in top soil of 5 cm depth reached a peak in June, and thereafter decreased gradually in both stands. Patterns of seasonal changes in fine root phytomass were closely related to inorganic nitrogen and moisture content.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.92-111
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• 2021

As fine dust negatively affects disease, industry and economy, the people are sensitive to fine dust. Therefore, if the occurrence of fine dust can be predicted, countermeasures can be prepared in advance, which can be helpful for life and economy. Fine dust is affected by the weather and the degree of concentration of fine dust emission sources. The industrial sector has the largest amount of fine dust emissions, and in industrial complexes, factories emit a lot of fine dust as fine dust emission sources. This study targets regions with old industrial complexes in local cities. The purpose of this study is to explore the factors that cause fine dust and develop a predictive model that can predict the occurrence of fine dust. weather data and fine dust data were used, and variables that influence the generation of fine dust were extracted through multiple regression analysis. Based on the results of multiple regression analysis, a model with high predictive power was extracted by learning with a machine learning regression learner model. The performance of the model was confirmed using test data. As a result, the models with high predictive power were linear regression model, Gaussian process regression model, and support vector machine. The proportion of training data and predictive power were not proportional. In addition, the average value of the difference between the predicted value and the measured value was not large, but when the measured value was high, the predictive power was decreased. The results of this study can be developed as a more systematic and precise fine dust prediction service by combining meteorological data and urban big data through local government data hubs. Lastly, it will be an opportunity to promote the development of smart industrial complexes.

• Journal of the Korea Institute of Building Construction
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• v.15 no.6
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• pp.553-559
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• 2015

In this study, to suggest the application method of recycled fine aggregate, the non-cement mortar was prepared and studied with the binders of blast furnace slag, fly ash, and fly ash from combined heat power plant. As a basic experiment, a series of tests was conducted to determine the potions of the binders and types of activator. When the binder was consisted with 20% of fly ash and 40% of fly ash from combined heat power plant, the highest strength of the mortar was obtained, and as an activator, the combination of sodium hydroxide 2.5%, and calcium hydroxide 7.5% showed the highest strength of the mortar. Therefore, this study focuses on engineering properties of mortar contains fly ash from combined heat power plant and recycled fine aggregate according to replacement ratio of recycled fine aggregate based on the optimum mix from the basic experiment. As a result, the best replacement ratio of recycled fine aggregate is 75%.