• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.378-378
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• 2023

본 연구에서는 한반도 전지역의 격자화를 통해 다중유역에 대한 유출량 모의 능력 평가를 제시하고자 한다. 이를 위해 기상청에서 제공하는 ASOS(종관기상관측) 자료를 IDW(Inverse Distance Weighting) 보간법으로 격자화하였고, GIS(Geographic Information System)를 활용하여 지형자료를 격자에 맞추어 구축하였다. 이렇게 구축한 자료를 사용하여 다중유역의 유출량을 Variable Infiltration Capacity(VIC) 모형으로 모의하였다. VIC 모형은 토양, 식생 및 대기 사이의 물과 에너지의 물리적 교환을 모의하는 동시에 식생 다양성, 가변 침투가 있는 다중 토양층 및 비선형 기반 흐름을 고려하는 모형이다. 이러한 모형을 다중유역에 대해 전역 매개변수를 추정하였고 총 26개의 다중관측지점에서 일별 유출량을 모의하였다. 모의된 유출량은 NSE(Nash-Sutcliffe Efficiency)를 통해 평가하였다. 본 연구에서 구축한 대규모 수문모형은 향후 우리나라의 다양한 수자원 관리(Water resources management)에 활용될 수 있을 것이다.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.131-137
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• 2004

Conventional traffic signal optimization models assume that green intervals for pedestrian crossings are given as exogenous inputs such as minimum green intervals for straight-ahead movements. As the result, in reality, the green intervals of traffic movements may not distribute adequately by the volume/saturation-flow of them. In this paper, we proposed signal optimization models formulated in BMILP to integrate pedestrian crossings into traffic movements under under-saturated traffic flow. The model simultaneously optimizes traffic and pedestrian movements to minimize weighted queues of primary queues during red interval and secondary queues during queue clearance time. A set of linear objective function and constraints set up to ensure the conditions with respect to pedestrian and traffic maneuvers. Numerical examples are given by pedestrian green intervals and the number of pedestrian crossings located at an arm. Optimization results illustrated that pedestrian green intervals using proposed models are greater than those using TRANSYT-7F, but opposite in the ratios of pedestrian green intervals to the cycle lengths. The simulation results show that proposed models are superior to TRANSYT-7F in reducing delay, where the longer the pedestrian green interval the greater the effect.

• International Journal of Highway Engineering
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• v.9 no.4
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• pp.21-32
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• 2007

The linear traffic model(Vertical queueing model) that is adopted widely in traffic flow estimation assumes that all vehicles have the identical motion before joining a queue at the stop-line. Thus, a queue is supposed to form vertically not horizontally. Due to the simplicity of this model, the departure time of the leading vehicle is assumed to coincide with the start of effective green time. Thus, the delay estimates given by the Vertical queueing model is not always realistic. This paper explores a microscopic traffic model(a Kinematic Car-following model at Signalised intersections: a KCS traffic model) based on the one dimensional Kinematic equations in physics. A comparative evaluation in delay and sensitivity of delay difference between the KCS traffic model and the previously known Vertical queueing model is presented. The results show that the delay estimate in the Vertical queueing model is always greater than or equal to the KCS traffic model; however, the sensitivity of delay in the KCS traffic model is greater than the Vertical queueing model.

• Journal of Ocean Engineering and Technology
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• v.13 no.2 s.32
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• pp.116-128
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• 1999

A deep water wave prediction model applicable to the East Sea is presnted. This model incorporates rediative transter of energy specrum, atmospheric input form the wind, nonlinear interaction, and energy dissipation by white capping. The propagation scheme by Gadd shows satisfactory results and the characteristics of the nonlinear interaction is simulated well by discrete interaction approximatiion. The application of the model to the sea around the Korean Peninsula shows reasonable agreement with the observation.

• Horticultural Science & Technology
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• v.29 no.5
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• pp.420-432
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• 2011

Population dynamics of greenhouse whitefly, Trialeurodes vaporariorum (Westwood), were modeled and simulated to compare the temperature effects of air and tomato leaf inside greenhouse using DYMEX model simulator (pre-programed module based simulation program developed by CSIRO, Australia). The DYMEX model simulator consisted of temperature dependent development and oviposition modules. The normalized cumulative frequency distributions of the developmental period for immature and oviposition frequency rate and survival rate for adult of greenhouse whitefly were fitted to two-parameter Weibull function. Leaf temperature on reversed side of cherry tomato leafs (Lycopersicon esculentum cv. Koko) was monitored according to three tomato plant positions (top, > 1.6 m above the ground level; middle, 0.9 - 1.2 m; bottom, 0.3 - 0.5 m) using an infrared temperature gun. Air temperature was monitored at same three positions using a Hobo self-contained temperature logger. The leaf temperatures from three plant positions were described as a function of the air temperatures with 3-parameter exponential and sigmoidal models. Data sets of observed air temperature and predicted leaf temperatures were prepared, and incorporated into the DYMEX simulator to compare the effects of air and leaf temperature on population dynamics of greenhouse whitefly. The number of greenhouse whitefly immatures was counted by visual inspection in three tomato plant positions to verify the performance of DYMEX simulation in cherry tomato greenhouse where air and leaf temperatures were monitored. The egg stage of greenhouse whitefly was not counted due to its small size. A significant positive correlation between the observed and the predicted numbers of immature and adults were found when the leaf temperatures were incorporated into DYMEX simulation, but no significant correlation was observed with the air temperatures. This study demonstrated that the population dynamics of greenhouse whitefly was affected greatly by the leaf temperatures, rather than air temperatures, and thus the leaf surface temperature should be considered for management of greenhouse whitefly in cherry tomato grown in greenhouses.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.133-133
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• 2012

기후변화에 관한 정부 간 패널 IPCC의 4차 보고서에 의하면 지난 100년간 지구 평균 기온의 선형추세선 기울기가 $0.74^{\circ}C$/년을 보이고 있으며 21세기말 지구의 평균기온은 최대 $6.3^{\circ}C$까지 더 상승할 것으로 전망하고 있다. 이러한 대기기온의 상승은 저수지 및 하천의 수온과 밀접한 관계를 지니는데, 저수지 표층 수온 및 유입 하천의 수온을 증가시켜 저수지 수온 성층형성시기를 앞당겨 성층화 기간을 증가시키고 또한 성층강도도 증가하게 된다. 이러한 수온성층기간 및 강도의 증가는 심수층의 용존산소 고갈과 이에 따른 퇴적층의 영양염류 용출량을 증가시켜 저수지 수질관리에 어려움을 야기할 것으로 전망되고 있다. 특히 온대기후대에 속하는 우리나라의 대부분의 대형 인공 저수지는 여름철 뚜렷한 수온성층구조가 확인되고 있어 대기기온 상승이 수온성층구조에 미치는 영향을 분석하는 것은 미래 기후변화에 대비한 저수지 수질관리 전략 수립을 위해 필요한 기초 연구라 판단되어진다. 본 연구에서는 2차원 횡방향 평균 수치모형(CE-QUAL-W2)을 활용하여 대기 온도 변화에 따른 충주호의 수온분포를 모의하고 수온 성층구조의 변동경향을 분석하였다. 지구 온난화 영향 모의에 앞서 2010년과 2008년의 충주호 수문조건에 모형을 적용하여 수온 성층구조의 재현성을 확인하였다. 미래 대기기온 자료는 국립기상연구소에서 제공하는 한반도 기후전망 모의자료(RCM) 중 충주댐 유역의 평균 기온자료를 수집하여 사용하였으며, 모의연도는 2011, 2040, 2070, 2100으로 하였다. 또한, 대기기온과 유입수온 자료를 제외한 모든 입력자료는 보정년도인 2010년과 동일하다고 가정하여 대기기온 변화의 영향만을 고려하였다. 2011년에 비해 2100년의 대기기온이 연평균 $2.44^{\circ}C$ 증가하였을 때 표층수온은 평균 $1.72^{\circ}C$, 최대 $4.31^{\circ}C$ 증가하는 것으로 나타났으며, 심층수온은 평균 $0.36^{\circ}C$, 최대 $1.33^{\circ}C$ 증가하는 것으로 나타났다. 성층구조 형성기간의 비교를 위해 표층과 심층의 수온이 $5^{\circ}C$ 이상의 차이를 보이는 기간을 조사한 결과 2011년에 비해 2100년에서 5일 일찍 시작되어 11일 더 지속되는 것으로 나타났다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.165-174
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• 2019

As a nonstationarity is observed in hydrological data, various studies on nonstationary frequency analysis for hydraulic structure design have been actively conducted. Although the inherent diversity in the atmosphere-ocean system is known to be related to the nonstationary phenomena, a nonstationary frequency analysis is generally performed based on the linear trend. In this study, a nonstationary frequency analysis was performed using climate indices as covariates to consider the climate variability and the long-term trend of the extreme rainfall. For 11 weather stations where the trend was detected, the long-term trend within the annual maximum rainfall data was extracted using the ensemble empirical mode decomposition. Then the correlation between the extracted data and various climate indices was analyzed. As a result, autumn-averaged AMM, autumn-averaged AMO, and summer-averaged NINO4 in the previous year significantly influenced the long-term trend of the annual maximum rainfall data at almost all stations. The selected seasonal climate indices were applied to the generalized extreme value (GEV) model and the best model was selected using the AIC. Using the model diagnosis for the selected model and the nonstationary GEV model with the linear trend, we identified that the selected model could compensate the underestimation of the rainfall quantiles.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.577-586
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• 2016

Hazardous air pollution caused by heavy metals in the air is at a serious level. Although manganese(Mn), one of the heavy metals, is a non-carcinogenic substance, it has a harmful influence on the human body. It is partially measured because automatic monitoring technologies have not yet be fully established. We introduced a statistical model for the daily concentration of manganese. Incorporating a linkage between Mn and meteorology, the proposed model is formulated in way to identify meteorological effects and to allow for seasonal trends, enabling not only accurate measurement of manganese concentration, but also information about the evaluation on a Hazard Quotient (non-cancer risk).

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.27 no.5
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• pp.281-294
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• 2015

In order to quantitatively estimate the nonlinear destructive interaction of wave load with wind load, which is very vital for the optimal design of offshore wind energy converter, we carried out a hydraulic model test and wind tunnel test. As a substructure of offshore wind energy converter, we would deploy the monopile, which is popular due to its easiness in construction. Based on the simulation using Monte Carlo simulation using Kaimal spectrum and cross spectrum, the instantaneous maximum wind velocity is adjusted to 10 m/s. And, considering the wave conditions of the Western Sea where a pilot wind farm is planned to be constructed, $H_s=0.1m$, 0.15 m, 0.2 m is carefully chosen. It turns out that the nonlinear destructive interaction between the wind and wave loads acting on the offshore wind energy converter is more clearly visible at rough seas rather than at mild seas, which strongly support our deduction that a Large eddy, a swirling vortex developed near the bumpy water surface in the opposite direction of the wind, is the driving mechanism underlying nonlinear destructive interaction between the wind and wave loads.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1119-1127
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• 2009

In PGA golf, total prize money and average score are good response variable related to golf skills such as driving distance, green in regulation and putts per green in regulation. But it's not easy to predict the winner of coming tournament. Thus I applied Neural Networks which has pretty good advantages for non-linear complex modeling to binary data. In neural network architectures, I applied NRBF and MLP architecture model for binary data which represent who had a win or not.