• Wind and Structures
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• 제27권5호
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• pp.325-336
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• 2018

The physical infrastructure of the power systems, including the high-voltage transmission towers and lines as well as the poles and wires for power distribution at a lower voltage level, is critical for the resilience of the community since the failures or nonfunctioning of these structures could introduce large area power outages under the extreme weather events. In the current engineering practices, single circuit lattice steel towers linked by transmission lines are widely used to form power transmission systems. After years of service and continues interactions with natural and built environment, progressive damages accumulate at various structural details and could gradually change the structural performance. This study is to evaluate the typical existing transmission tower-line system subjected to synoptic winds (atmospheric boundary layer winds). Effects from the possible corrosion penetration on the structural members of the transmission towers and the aerodynamic damping force on the conductors are evaluated. However, corrosion in connections is not included. Meanwhile, corrosion on the structural members is assumed to be evenly distributed. Wind loads are calculated based on the codes used for synoptic winds and the wind tunnel experiments were carried out to obtain the drag coefficients for different panels of the transmission towers as well as for the transmission lines. Sensitivity analysis is carried out based upon the incremental dynamic analysis (IDA) to evaluate the structural capacity of the transmission tower-line system for different corrosion and loading conditions. Meanwhile, extreme value analysis is also performed to further estimate the short-term extreme response of the transmission tower-line system.

• 한국수자원학회논문집
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• 제46권6호
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• pp.585-596
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• 2013

본 연구에서는 기후변화에 따른 수자원 영향평가를 위한 지역기후모형과 단계적 스케일링기법을 연계한 혼합상세화기법을 개발하고 그에 따른 적용성을 평가하고자 하였다. 단계적 스케일링기법은 강수량 구간을 총 3구간(극치호우사상, 무강수일수, 기타)으로 나누어 각 구간에 따라 각기 다른 방법을 적용하여 보정하는 기법으로, 극치호우사상은 회귀식을 이용한 보정기법, 무강수일수는 분위사상법, 나머지 부분은 평균 및 분산보정 기법을 적용하였다. 이 기법의 비교 평가를 위해 최근 혼합 상세화기법으로 가장 많이 적용되고 있는 선형보정기법, 분위사상법, 일기상발생기법을 활용하여 기상청 관할 기상관측소 61개 지점을 대상으로 적용성 평가를 수행하였다. 평가 결과, RCM에서 생산된 원자료 및 3가지 기존 기법(선형보정기법, 분위사상법, 일기상발생기법)으로 보정된 기후시나리오에 비해 본 연구에서 제안한 단계적 스케일링기법이 실제 기후특성을 잘 모의하는 것으로 나타나 적용성이 우수한 것으로 판단된다. 이러한 연구결과를 통해 단계적 스케일링기법은 RCM 사용이 증대될 기후변화 연구에 있어 그 활용성이 높을 것으로 기대된다.

• 한국기후변화학회지
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• 제9권1호
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• pp.103-115
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• 2018

The uncertainty of climate scenarios, as initial information, is one of the significant factors among uncertainties of climate change impacts and vulnerability assessments. In this sense, the quantification of the uncertainty of climate scenarios is essential to understanding these assessments of impacts and vulnerability for adaptation to climate change. Here we quantified the precision of surface temperature of ensemble scenarios (high resolution (1km) RCP4.5 and 8.5) provided by Korea Meteorological Administration, with spatiotemporal variation of the standard deviation of them. From 2021 to 2050, the annual increase rate of RCP8.5 was higher than that of RCP4.5 while the annual variation of RCP8.5 was lower than that of RCP4.5. The standard deviations of ensemble scenarios are higher in summer and winter, particularly in July and January, when the extreme weather events could occur. In general, the uncertainty of ensemble scenarios in summer were lower than those in winter. In spatial distribution, the standard deviation of ensemble scenarios in Seoul Metropolitan Area is relatively higher than other provinces, while that of Yeongnam area is lower than other provinces. In winter, the standard deviations of ensemble scenarios of RCP4.5 and 8.5 in January are higher than those of December. Especially, the standard deviation of ensemble scenarios is higher in the central regions including Gyeonggi, and Gangwon, where the mean surface temperature is lower than southern regions along with Chungbuk. Such differences in precisions of climate ensemble scenarios imply that those uncertainty information should be taken into account for the implementation of national climate change policy.

• 한국농공학회논문집
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• 제61권3호
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• pp.1-14
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• 2019

North Korea has frequently suffered from extreme agricultural crop droughts, which have led to food shortages, according to the Food and Agriculture Organization (FAO). The increasing frequency of extreme droughts, due to global warming and climate change, has increased the importance of enhancing the national capacity for drought management. Historically, a meteorological drought index based on data collected from weather stations has been widely used. But it has limitations in terms of the distribution of weather stations and the spatial pattern of drought impacts. Satellite-based data can be obtained with the same accuracy and at regular intervals, and is useful for long-term change analysis and environmental monitoring and wide area access in time and space. The Evaporative Stress Index (ESI), a satellite-based drought index using the ratio of potential and actual evaporation, is being used to detect drought response as a index of the droughts occurring rapidly over short periods of time. It is more accurate and provides faster analysis of drought conditions compared to the Standardized Precipitation Index (SPI), and the Palmer Drought Severity Index (PDSI). In this study, we analyze drought events during 2015-2017 in North Korea using the ESI satellite-based drought index to determine drought response by comparing with it with the SPI and SPEI drought indices.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2002년도 학술발표회 논문집(I)
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• pp.43-50
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2019년도 학술발표회
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• pp.158-158
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• 2019

Recent studies show the possibility of more frequent extreme events as a result of the changing climate. These weather extremes, such as excessive rainfall, result to debris flow, river overflow and urban flooding, which post a substantial threat to the community. Therefore, an effective flood model is a crucial tool in flood disaster mitigation. In recent years, a number of flood models has been established; however, the major challenge in developing effective and accurate inundation models is the inconvenience of running multiple models for separate conditions. Among the solutions in recent researches is the development of the combined 1D-2D flood modeling. The coupled 1D-2D river flood modeling allows channel flows to be represented in 1D and the overbank flow to be modeled over two-dimension. To test the efficiency of this approach, this research aims to assess the capability of HEC-RAS model's implementation of the combined 1D-2D hydraulic simulation of river overflow inundation, and compare with the results of GERIS and FLUMENS 2D flood model. Results show similar output to the flood models that had used different methods. This proves the applicability of the HEC-RAS 1D-2D coupling method as a powerful tool in simulating accurate inundation for flood events.

• 식물병연구
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• 제25권2호
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• pp.71-78
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• 2019

2018년 전남 고흥군에서 발생한 유자나무의 집단 고사가 발생했다. 이에 대한 원인 조사를 위해 고흥군 풍양면에 있는 18개 유자 과수원을 무작위로 선정하여 조사를 수행한 결과 과수원별 고사증상을 보인 나무의 비율은 평균 43.6%(7.5%~100% 피해율), 증상을 보인 나무 중 56.5%는 나무 전체가 완전 고사되는 피해를 입은 것으로 나타났다. 고사 증상을 보인 대부분의 유자나무에서는 동해의 전형적인 증상인 표피 안 형성층과 목부의 갈변, 잎눈과 꽃눈의 무 발아, 가지나 줄기에 쪼개짐 증상 등이 관찰되었다. 따라서 기상 조건과 유자나무의 고사 증상이 연관 되어있을 것이라는 가설을 바탕으로 고흥지역의 과거 기상 자료를 분석하였다. 2017년 1월과 2월 고흥지역의 일평균 기온은 $-10^{\circ}C$ 이상이었으나, 2018년의 동 기간에는 $-10^{\circ}C$ 아래로 떨어진 날이 7일이나 되었다. 특히 2018년에는 1월과 2월에 유자의 내한성을 훨씬 넘어선 극최저기온(각각 $-12.6^{\circ}C$와 $-11.5^{\circ}C$)이 관측되었다. 또한 그해 3월 중순과 4월 초에 일 최저기온이 $13^{\circ}C$로 상승한 이상고온 직후 급격히 기온이 $0^{\circ}C$로 떨어지는 현상이 발생하였다. 결론적으로, 2018년 겨울철에 기록적인 극최저기온과 이상고온에 이은 급격한 기온의 저하로 인한 동해가 고흥지역에 대발생한 고사증상의 주요 원인이 되었을 것으로 추정하였다.

• 대기
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• 제26권2호
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• pp.277-288
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• 2016

Polar lows are intense mesoscale cyclones that mainly occur over the sea in polar regions. Owing to their small spatial scale of a diameter less than 1000 km, simulating polar lows is a challenging task. At King Sejong station in West Antartica, polar lows are often observed. Despite the recent significant climatic changes observed over West Antarctica, adequate validation of regional simulations of extreme weather events such as polar lows are rare for this region. To address this gap, simulation results from a recent version of the Polar Weather Research and Forecasting model (Polar WRF) covering Antartic Peninsula at a high horizontal resolution of 3 km are validated against near-surface meteorological observations. We selected a case of high wind speed event on 7 January 2013 recorded at Automatic Meteorological Observation Station (AMOS) in King Sejong station, Antarctica. It is revealed by in situ observations, numerical weather prediction, and reanalysis fields that the synoptic and mesoscale environment of the strong wind event was due to the passage of a strong mesoscale polar low of center pressure 950 hPa. Verifying model results from 3 km grid resolution simulation against AMOS observation showed that high skill in simulating wind speed and surface pressure with a bias of $-1.1m\;s^{-1}$ and -1.2 hPa, respectively. Our evaluation suggests that the Polar WRF can be used as a useful dynamic downscaling tool for the simulation of Antartic weather systems and the near-surface meteorological instruments installed in King Sejong station can provide invaluable data for polar low studies over West Antartica.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2015년도 추계 학술논문 발표대회
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• pp.89-90
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• 2015

Recently, Incidence of natural disasters are growing gradually. The need for a monitoring system for maintaining the structural integrity of the high-rise buildings against extreme weather events such as typhoons, earthquakes is increasing gradually. One of the most important features in the tall building is to guarantee structural safety during the structure's life time. Structural monitoring technologies might be needed to manage structural safety and to protect human life.

• 산업기술연구
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• 제35권
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• pp.47-53
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• 2015

Recent extreme weather events and natural disasters are causing rapid aging of the ancient structures with cultural value. It has threatened the safety and management. The construction design documents are not kept for such long time. Even if they are, they seem to be mismatched with the design structures due to corrosive effects. For these reasons, Korea has been facing difficulties in maintenance, reengineering and safety evaluation. In this study, three dimensional point cloud surface of bobsleigh is obtained using 3D LiDAR scanner. The obtained structure is compared with the original design and found to be highly accurate. The study shows the application of reverse engineering technique and its potential use for other civil structures.