To investigate air quality away from the coastal urban source region, we used a hybrid Eulerian-Lagrangian method which can describe the formation, transport, transformation and deposition processes in complex terrain. with inclusion of shipping sources that were considered to be important emission in the coastal urban region. The result of the Eulerian advection - diffusion prediction was quite similar to that of the Lagrangian particle diffusion prediction. It showed that pollutants emitted from piers can affect the part of inland, especially Dongrae and the coastal area. Those emitted from Sasang and Janglim industrial complexes can affect Hwamyeong and the coastal, respectively. During the daytime the concentration was low due to large deposition flux and terrain effect.

자연하천에서의 이송-확산 과정의 모의를 위하여 입자위치의 이산확률분포에 기초한 2차원 수송 모형을 개발하였다. 제안된 모형에서는 단위 시간간격동안 격자간의 질량이송을 예측하기 위하여 평균과 분산의 함수로 나타내어진 확률분포를 사용하였다. 개발된 모형은 유속, 확산계수, 단면적이 일정한 단순영역에 대하여 수치확산이 없는 해를 구하였고, 양의 확률을 만족시키는 안정조건이 성립한다면, 해석해와 다른 유한차분법과 비교하였을 때, 좋은 결과를 나타내었다. 본 모

Optimum Ship Routing can be defined as 'The selection of an optimum track for a transoceanic crossing by the application of long-range predictions of wind, waves and currents to the knowledge of how the routed vessel reacts to these variables'. This paper treats the methodology how to solve optimum ship routing problem by network modeling and reveals the validity of the network model by some numerical experiments.

This study aims at the development of the model for a forecasting of water quality in river basins using artificial neural network technique. Water quality by Artificial Neural Network Model forecasted and compared with observed values at the Sangju 1 and Dalsung stations in Nakdong river basin. For it, a multi-layer neural network was constructed to forecast river water quality. The neural network learns continuous-valued input and output data. Input data was selected as BOD, DO, discharge and precipitation. As a result, it showed that method Ⅲ of three methods was suitable more than other methods by statistical test(ME, MSE, Bias and VER). Therefore, it showed that Artificial Neural Network Model was suitable for forecasting river water quality.

Today travel demand continues to increase with spread of economic zones. Also, urban freeway plays an important role in intra-zone transportations as a major corridor in a big city. However, most of urban freeways experience a severe congestion with the excess of inflowing or outflowing traffic through freeway ramps. The purpose of this study is to identify the traffic characteristics, analyze the relationships between the traffic characteristics and finally construct the speed predictive models on the ramp junctions of urban freeway under the intelligent transportation system(ITS) settings. From the analyses of traffic characteristics following results were obtained: ⅰ) 24 hours average traffic characteristics flow, occupancy, speed under the ITS settings showed about 40%, 38%, 8.8% increase each on urban freeway junctions period when compared with that under the non-ITS settings each other. Free flow speed and traffic flow on the mainline sections of urban freeway under the ITS settings also showed about 20% and 17% increase when compared with that under the non-ITS, respectively. ⅱ) The upstream when compared speed( Su)and downstream occupancy( Od) were especially shown to have higher explanatory powers on the stable flow ramp junctions, but the upstream speed( Su) and downstream flow( Vd) were especially shown on the unstable flow ramp junctions of urban freeway under the ITS settings.ngs.ngs.

Recently, in the shipping companies have been employing prudently in order to prevent from sea accidents occurred by human factors. Also the students of merchant marine universities are choosing prudently the shipping companies when taking a job. But many qualitative and quantitative factors are considered in decision making for the employment and the choice of a company. FSM(Fuzzy Structural Modeling) has been widely used in modeling the system composed of such qualitative and quantitative factor. In this paper, a case study is discussed for the analysis of the consciousness of the employment of shining companies and students' choice of such company in maritime university using FSM. Also this paper proposed the planes for educating and recruitment guiding the student in maritime university.

지하수 함양량을 추정하기 위한 방법으로 격자기반의 일변 토양수분 추적기법을 모델링하였다. 본 모델은 GRASS-GIS를 이용하여 모델에 필요한 자료들을 준비하고, 모델은 이들을 ASCII 형태로 받아들여 일별 수행결과(유역출구에서의 유출량, 지표유출 분포도, 토양수분 분포도 등)들을 GRASS상에서 도시하여 주는 형태로 구성하였다. 보청천유역의 일부인 이평교 유역()을 대상으로 모델의 적용성을 검토하였다. '95년 및 '96년도의 IHP유역 연구보고서

The sensitivity analysis of two short-term models (ISCST3, INPUFF2.5) is performed to improve the model accuracy. It appears that the sensitivities on the changes of wind speed, stack height and stack inner diameter in the near distance from source, stability and mixing height in the remote distance from source, are significant. Also, the gas exit velocity, stack inner diameter, gas temperature and air temperature which affect the plume rise have some effects on the concentration values of each model within the downwind distance where final plume rise is determined. And in modeling for the atmospheric dispersion of point pollutant source INPUFF2.5 can calculate amount, trajectory of puff and concentration versus time at each receptors. So, it is compatible to analyze distribution of point pollutants concentration at modeling area.

하천의 유속구조에 관한 지식은 하천 양안의 침식, 사행현상, 유사 및 오염물질의 확산과정을 규명하는데 필수적인 요소이다. 본 연구에서는 적절한 수리량을 사용하여 자연하천에서 종방향유속의 횡분포를 예측할 수 있는 이론식으로 수치모형을 구성하였다. 그리고 이를 낙동강에서 실측된 유속자료에 적용시켰다. 그 결과 수치모형은 실측된 유속분포의 일반적인 형태를 대체적으로 잘 근사하였다. 특히 모형은 유속의 횡분포에 있어서 왜곡도 및 편평도를 적절하게 재현하였다.

Surface complexation models(SCMs) have been performed to predict metal ion adsorption behavior onto the mineral surface. Application of SCMs, however, requires a self-consistent approach to determine model parameter values. In this paper, in order to determine the metal ion adsorption parameters for the triple layer model(TLM) version of the SCM, we used the zeta potential data for Zeolite and Kaolinite, and the metal ion adsorption data for Pb(Ⅱ) and Cd(Ⅱ). Fitting parameters determined for the modeling were as follows ; total site concentration, site density, specific surface area, surface acidity constants, etc. Zeta potential as a new approach other than the acidic-alkalimetric titration method was adopted for simulation of adsorption phenomena. Some fitting parameters were determined by the trial and error method. Modeling approach was successful in quantitatively simulating adsorption behavior under various geochemical conditions.

운동파 이론의 수치해석에는 유한차분법과 특성곡선법이 주로 사용된다. 유한차분법의 경우 지배방정식의 차분과정에서 발생하는 절단오차에 의하여 첨두유량의 감쇠가 발생한다. 특성곡선법의 경우 첨두유량은 양호하게 보존되지만, 수치해석 과정에서 발생하는 충격파를 적절하게 고려하지 못한다. 본 연구에서는 운동파 이론에 근거한 각각의 수차해석 기법의 특성을 살펴보았으며, 특성곡선법으로 수치해석할 때 발생하는 충격파의 수치처리기법인 Propagating Shock Fi

자연하천에 유입된 오염물질의 확산거동을 해석하기 위하여 통계학적인 개념을 이용하여 오염물질 입자의 운동을 묘사하는 2차원 Random-Walk 모형을 개발하였다. 개발된 모형을 검정한 결과, 고정격자의 개수를 증가시키거나 각각의 고정격자 내에 포함된 입자개수의 평균값을 증가시키면 해의 정밀도가 증가하는 것으로 나타났다. 본 모형의 현장 적용성을 검토하기 위하여 캐나다에 위치한 Grand River에서 수행된 정상상태의 색소실험 결과와 본 모형에 의한 계

A three-dimensional ecosystem model is applied to the Suyoung Bay, located at the southeastern part of Korea, to study of the material distribution in the time scale of several tens days. The model has included of the DIN(Dissolved Inorganic Nitrogen), DIP(Dissolved Inorganic Phosphate), phytoplankton, zooplankton and detritus, and also was coupled with the physical processes. The spatial distribution of chlorophyll-a and primary productivity in the model is determined by the physical and chemical-biological parameters. The horizontal distributions of the DIN, DIP and chlorophyll-a are decreased from the coast to the off-shore, though the nutrients show some more complicated pattern than the chlorophyll-a. The nutrient contents in the off shore are low, and thus a relatively low productivity(chlorophyll-a) are presented. On the whole, the distribution of the results of model are smoother than the observed ones and some small scale variation in the observed data cannot be reproduced by the model due to the resolution limits of model. However, the basic pattern and the quantitavities has been reproduced by the model well.