• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.3
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• pp.304-308
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• 2024

In this paper, in order to analyze the PMU data of the accident section, we collected the raw data of a total of 35 PMU installed at the Yeonggwang substation and tried to find a way to analyze the data, and analyzed the data using Excel format and formula. As a result, the three-phase voltage and current data of the PMU were calculated using formulas in Excel and interpreted as effective and reactive power, and it was possible to check the effective and reactive power of the accident section through the graph to see why it was different from before the accident. As a result, it was confirmed that each power was greatly reduced in the graph of the effective and reactive power of the accident section, and it was confirmed that the loss occurred as the power of the accident section was greatly reduced.

• Journal of the Korean Wood Science and Technology
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• v.44 no.5
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• pp.655-663
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• 2016

Increasing green house gas and it consequent climate change problems are discussed as a global issue. Accordingly, future local green house gas emission will increase up to 40% of the entire local green house gas emission and therefore, efforts to reduce the emission in construction industry is urgently required. Therefore, in this study, heating energy demand was analyzed by using the EnergyPlus simulation according to wood material finishes configuration. EnergyPlus has the entry for a variety of buildings and heating, ventilation, air conditioning (HAVC) system components, in particular buildings, air conditioning systems, and performs simultaneous integrated calculated through the feedback between the heat source unit, a verification program according to the ASHRAE Standard 140-2007 to be. The climate data for the simulation we used the data IWEC in Incheon and Gwangju provided by EnergyPlus. The analysis of simulation model was farm and fishing house standard design drawings: 2012, presented at the Korea Rural Community Corporation. The results of simulation of central region and southern region were effected by wood products of simulation model into the interior finish, exterior finish, windows, wooden structure. Also, it was confirmed that the reduced heating energy demand.

• Journal of the Korean Geographical Society
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• v.41 no.6 s.117
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• pp.682-700
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• 2006

This study aims to show a model of environmental planning towards sustainable science parks. For the purpose of this study, an analysis of the environment of green space at sustainable science parks as pertaining to environmental soundness, ecological stability and landscape aesthetics is applied as a case study to Osong Bio-Health Science Technopolis, a developmental promoted district. Considering the factors resulting from Habitat Agenda(II) and other preceding studies, this study derives fifteen elements of environmental planning for sustainable science parks. A questionnaire/survey was conducted with relation to these fifteen elements to officials who would be moved to Osong Bio-Health Science Technopolis. From this survey, it is shown that respondents have a strong awareness that for the sustainable environment of a science park, the park should preserve as much green space as possible, and that the park should be in harmony with the surrounding natural environment. The practice of forestation at sustainable science parks not only develops a healthy environment that promotes an image of green, but also promotes a stable ecological system. As such, this study suggests alternatives to environmental planning from the perspective of landscape ecology by assessing the project of developing Osong Bio-Health Science Technopolis. To continuously maintain landscape aesthetics, one needs to control the height of buildings, lest the forests should be hidden by the buildings.

• Journal of Korea Water Resources Association
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• v.33 no.3
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• pp.365-374
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• 2000

This paper is to present the determination of the optimal Joss rate parameters and urnt bydrographs from the observed single rainfall-runoff event using optimization models coupled with a stochastic technique for the global solution. Two kinds of the linear program models are formulated to derive the optimal unit hydrographs and loss rate parameters for gaged basins; one mimmizes the summation of the absolute residual between predlCted and observed runoff ordinates and the other, the maximum absolute residuaL Multistart algorithm which is one or stochastic techniques for the global optimum is adopted to perturb the parameters of the loss rate equations. Multistart efficiently searches the feasIble region to identify the global optimlUll for loss rate parameters, which yields the optimal loss rate parameters and unit hydrograph for Kostiakov's, Plulip's, and Horton's equation. The unique unit hydrograph ordinates for a gIven rainfall-runoff event iS exclusrvely obtained WIth $\Phi$ index, but unit hydrograph ordinates depend upon the parameters [or each loss rate equations. The parameters of Green-Ampt's are determined through a trial and error method. In this paper the single rainfall-nmoff event observed from a watershed is considered to test the proposed method. The optimal unit hydrograph herein found has smaller deviations than the ones reported previously by other researchers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.40-51
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• 2020

Much time has passed since Korea's expressway congestion-threshold speed was revised in 2011. In the meantime, various expressway environments have changed owing to improved performance of vehicles, expanded operations of transport competition (i.e., the KTX), and increased speed limits along some expressway sections. In addition, the speed that expressway users expect to travel at is also increasing. Therefore, through a survey, this study investigates expressway users' perceptions of congestion, and reviews the adjustment of the expressway speed congestion threshold by analyzing expressway traffic flow. One result of the survey confirms that the threshold speed expressway users consider to be congestion has slightly increased. Analyzing traffic and speed data through a K-means algorithm found that the threshold speed for congestion is 60 km/h. In addition, assuming the congestion threshold speed increase from 40 km/h to 50 km/h and 60 km/h, frequently congested expressway sections are identified, determining that 50 km/h is appropriate as a congestion threshold for proper expressway mobility management.

• Korean Journal of Food Science and Technology
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• v.38 no.2
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• pp.153-158
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• 2006

Changes in contents of amino acids, caffeine, trigonelline, chlorogenic acid, and monosaccharides in green coffee beans during roasting were investigated. During roasting, amino acid contents of Arabica and Robusta coffees decreased by 30%, among which cysteine, serine, lysine, and arginine contents markedly decreased, whereas those of glutamic acid, glycine, alanine, valine, isoleucine, leucine, and phenylalanine slightly decreased or increased. Caffeine contents of Arabica and Robusta were 1 and 2%, respectively, and remained unchanged during roasting. Trigonellin content of Arabica (0.87%-0.90%) was slightly higher than that of Robusta (0.74%), and 50 to 65% trigonellin degraded when green beans were heavily roasted. Chlorogenic acid levels of Robusta and Arabica were 4.82, and 4.38-4.66%, respectively. About 90% chIorogenic acid degraded with heavy roating. Total monosaccharide contents of Arabica and Robusta were 38.1-38.7 and 37.7%, respectively, and gradually decreased with roasting.

• Applied Chemistry for Engineering
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• v.25 no.3
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• pp.262-267
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• 2014

SAGD (steam assisted gravity drainage) process is the most commonly used in-situ technology for the recovery of bitumen from oil sand. It was investigated that the effects of different additives on bitumen recovery rate from oil sand in SAGD process among many possible mechanisms studied throughout the study. Bitumen recovery from thin layer oil sand reservoirs was simulated by using an experimental SAGD apparatus with scale of 150:1. To improve the simulation accuracy of thin layer oil reservoir, we have attached geological model (GM). Oil sand was simulated by using a mixture of extra heavy oil and glass beads with a diameter of 1.5 mm. $CO_2$ was used as an additive and the evolution of steam chambers were closely monitored, and the effects of $CO_2$ as an additive was investigated. Two types of injection methods were tested; continuous ($cCO_2$-SAGD) and sequential interruption ($sCO_2$-SAGD) $CO_2$ injection. For the $sCO_2$-SAGD experiment, it was observed that the recovery rates and CSOR were efficiently improved control experiment from 60.2% to 69.3% and 7.1 to 6.0, respectively, whereas $cCO_2$-SAGD experiment decreased from 60.2% to 57.6% and 7.1 to 7.3.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.121-132
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• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.4
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• pp.87-96
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• 2021

Determining design rainfall is the first step to plan an agricultural drainage facility. The objective of this study is to evaluate whether the current method for parameter estimation is reasonable for computing the design rainfall. The current Gumbel-Kendall (G-K) method was compared with two other methods which are Gumbel-Chow (G-C) method and Probability weighted moment (PWM). Hourly rainfall data were acquired from the 60 ASOS (Automated Synoptic Observing System) stations across the nation. For the goodness-of-fit test, this study used chi-squared (𝛘²) and Kolmogorov-Smirnov (K-S) test. When using G-K method, 𝛘² statistics of 18 stations exceeded the critical value (𝑥²_a=0.05,df=4=9.4877) and 10, 3 stations for G-C method, PWM method respectively. For K-S test, none of the stations exceeded the critical value (D^a=0.05_n=0.19838). However, G-K method showed the worst performances in both tests compared to other methods. Subsequently, this study computed design rainfall of 48-hour duration in 60 ASOS stations. G-K method showed 5.6 and 6.4% higher average design rainfall and 15.2 and 24.6% higher variance compared to G-C and PWM methods. In short, G-K showed the worst performance in goodness-of-fit tests and showed higher design rainfall with the least robustness. Likewise, considering the basic assumptions of the design rainfall estimation, G-K is not an appropriate method for the practical use. This study can be referenced and helpful when revising the agricultural drainage standards.

• Environmental and Resource Economics Review
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• v.31 no.4
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• pp.645-668
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• 2022

Hydrogen energy is emerging as an important means of carbon neutrality in the various sectors including power, transportation, storage, and industrial processes. Fuel cell power plants are the fastest spreading in the hydrogen ecosystem and are one of the key power sources among means of implementing carbon neutrality in 2050. However, high volatility in system marginal price (SMP) and renewable energy certificate (REC) prices, which affect the profits of fuel cell power plants, delay the investment timing and deployment. This study applied the real option methodology to analyze how the dual uncertainties in both SMP and REC prices affect the investment trigger price level in the irreversible investment decision of fuel cell power plants. The analysis is summarized into the following three. First, under the current Renewable Portfolio Standard (RPS), dual price uncertainties passed on to plant owners has significantly increased the investment trigger price relative to one under the deterministic price case. Second, reducing the volatility of REC price by half of the current level caused a significant drop in investment trigger prices and its investment trigger price is similar to one caused by offering one additional REC multiplier. Third, investment trigger price based on gray hydrogen and green hydrogen were analyzed along with the existing byproduct hydrogen-based fuel cells, and in the case of gray hydrogen, economic feasibility were narrowed significantly with green hydrogen when carbon costs were applied. The results of this study suggest that the current RPS system works as an obstacle to the deployment of fuel cell power plants, and policy that provides more stable revenue to plants is needed to build a more cost-effective and stable hydrogen ecosystem.