• Journal of Korean Society of Rural Planning
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• v.21 no.2
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• pp.33-49
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• 2015

The objective of this study was to predict land use change based on the land use change scenarios for the Hwangguji river watershed, South Korea. The land use change scenario was derived from the representative concentration pathways (RCP) 4.5 and 8.5 scenarios. The CLUE (conversion of land use and its effects) model was used to simulate the land use change. The CLUE is the modeling framework to simulate land use change considering empirically quantified relations between land use types and socioeconomic and biophysical driving factors through dynamical modeling. The Hwangguji river watershed, South Korea was selected as study area. Future land use changes in 2040, 2070, and 2100 were analyzed relative to baseline (2010) under the RCP4.5 and 8.5 scenarios. Binary logistic regressions were carried out to identify the relation between land uses and its driving factors. CN (Curve number) and impervious area based on the RCP4.5 and 8.5 scenarios were calculated and analyzed using the results of future land use changes. The land use change simulation of the RCP4.5 scenario resulted that the area of urban was forecast to increase by 12% and the area of forest was estimated to decrease by 16% between 2010 and 2100. The land use change simulation of the RCP8.5 scenario resulted that the area of urban was forecast to increase by 16% and the area of forest was estimated to decrease by 18% between 2010 and 2100. The values of Kappa and multiple resolution procedure were calculated as 0.61 and 74.03%. CN (III) and impervious area were increased by 0-1 and 0-8% from 2010 to 2100, respectively. The study findings may provide a useful tool for estimating the future land use change, which is an important factor for the future extreme flood.

• Science of Emotion and Sensibility
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• v.8 no.4
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• pp.415-422
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• 2005

The purpose of the present study was to investigate the differences of nonlinear characteristics of electroencephalogram (EEG) depending on different sensitivities of behavioral activation system (BAS) and behavioral inhibition system (BIS) of young and elderly groups. The EEGs from Fpl and Fp2 electrodes were recorded during resting condition. The young and elderly groups consisted of 19 and 31 healthy right-handed volunteers, respectively. We estimated 1/f scaling exponent which reflects the nonlinear dynamical complexity of EEG. As results, we found the differences of 1/f scaling exponent between young ant elderly BAS sensitive groups. The 1/f scaling exponent of young BAS sensitive group showed significantly higher values than those of elderly BAS sensitive group at the left prefrontal area (Fpl). The young BAS sensitive group had also a tendency to higher 1/f scaling exponent at the right prefrontal area (Fp2). Decrease of the 1/f scaling exponent indicates the increase of complexity and the decrease of the amount of information related to the statistical distribution. Therefore, the elderly BAS sensitive group has higher complexity than young BAS sensitive group, though they were all classified as BAS sensitive group by BAS/BIS scale. Our results suggest the possibility of correlation between BAS sensitivity an4 age.

• Nuclear Engineering and Technology
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• v.50 no.3
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• pp.356-367
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• 2018

A series of tests dedicated to station blackout (SBO) accident scenarios have been recently performed at the $Prim{\ddot{a}}rkreislauf-Versuchsanlage$ (primary coolant loop test facility; PKL) facility in the framework of the OECD/NEA PKL-3 project. These investigations address current safety issues related to beyond design basis accident transients with significant core heat up. This work presents a detailed analysis using the best estimate thermal-hydraulic code TRACE (v5.0 Patch4) of different SBO scenarios conducted at the PKL facility; failures of high- and low-pressure safety injection systems together with steam generator (SG) feedwater supply are considered, thus calling for adequate accident management actions and timely implementation of alternative emergency cooling procedures to prevent core meltdown. The presented analysis evaluates the capability of the applied TRACE model of the PKL facility to correctly capture the sequences of events in the different SBO scenarios, namely the SBO tests H2.1, H2.2 run 1 and H2.2 run 2, including symmetric or asymmetric secondary side depressurization, primary side depressurization, accumulator (ACC) injection in the cold legs and secondary side feeding with mobile pump and/or primary side emergency core coolant injection from the fuel pool cooling pump. This study is focused specifically on the prediction of the core exit temperature, which drives the execution of the most relevant accident management actions. This work presents, in particular, the key improvements made to the TRACE model that helped to improve the code predictions, including the modeling of dynamical heat losses, the nodalization of SGs' heat exchanger tubes and the ACCs. Another relevant aspect of this work is to evaluate how well the model simulations of the three different scenarios qualitatively and quantitatively capture the trends and results exhibited by the actual experiments. For instance, how the number of SGs considered for secondary side depressurization affects the heat transfer from primary side; how the discharge capacity of the pressurizer relief valve affects the dynamics of the transient; how ACC initial pressure and nitrogen release affect the grace time between ACC injection and subsequent core heat up; and how well the alternative feeding modes of the secondary and/or primary side with mobile injection pumps affect core quenching and ensure stable long-term core cooling under controlled boiling conditions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.201-217
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• 2022

The United States is one of the largest producers of major crops such as wheat, maize, and soybeans, and is a major exporter of these crops. Therefore, it is important to estimate the crop production of the country in advance based on reliable long- term weather forecast information for stable crops supply and demand in Korea. The purpose of this study is to improve the seasonal predictability of the agro-climatic indices over the United States by using regional-scale daily temperature. For long-term numerical weather prediction, a dynamical downscaling is performed using Weather Research and Forecasting (WRF) model, a regional climate model. As the initial and lateral boundary conditions of WRF, the global hourly prediction data obtained from the Pusan National University Coupled General Circulation Model (PNU CGCM) are used. The integration of WRF is performed for 22 years (2000-2021) for period from June to December of each year. The empirical quantile mapping, one of the bias correction methods, is applied to the timeseries of downscaled daily mean, minimum, and maximum temperature to correct the model biases. The uncorrected and corrected datasets are referred WRF_UC and WRF_C, respectively in this study. The daily minimum (maximum) temperature obtained from WRF_UC presents warm (cold) biases over most of the United States, which can be attributed to the underestimated the low (high) temperature range. The results show that WRF_C simulates closer to the observed temperature than WRF_UC, which lead to improve the long- term predictability of the temperature- based agro-climatic indices.