While the assessment of mean flow field is very important to characterize the hydrodynamic aspect of the flow regime in river, the conventional methodologies have required very time-consuming efforts and cost to obtain the mean flow field. The paper provides an efficient technique to quickly assess mean flow field by developing and applying spatial averaging method utilizing repeatedly surveyed acoustic Doppler current profiler(ADCP)’s cross-sectional measurements. ADCP has been widely used in measuring the detailed velocity and discharge in the last two decades. In order to validate the proposed spatial averaging method, the averaged velocity filed using the spatial averaging was compared with the bench-mark data computed by the time-averaging of the consistent fix-point ADCP measurement, which has been known as a valid but a bit inefficient way to obtain mean velocity field. The comparison showed a good agreement between two methods, which indicates that the spatial averaging method is able to be used as a surrogate way to assess the mean flow field. Bed shear stress distribution, which is a derived hydrodynamic quantity from the mean velocity field, was additionally computed by using both spatial and time-averaging methods, and they were compared each other so as to validate the spatial averaging method. This comparison also gave a good agreement. Therefore, such comparisons proved the validity of the spatial averaging to quickly assess mean flow field. The mean velocity field and its derived riverine quantities can be actively used for characterizing the flow dynamics as well as potentially applicable for validating numerical simulations.

Wind power energy is one of the favorable and fast growing renewable energies. It is most important for exact analysis of wind to evaluate and forecast the wind power energy. The purpose of this study is to improve the performance of numerical atmospheric model by data assimilation over a complex coastal area. The benefit of the profiler is its high temporal resolution and dense observation data at the lower troposphere. Three wind profiler sites used in this study are inhomogeneously situated near south-western coastal area of Korean Peninsula. The method of the data assimilation for using the profiler to the model simulation is the three-dimensional variational data assimilation (3DVAR). The experiment of two cases, with/without assimilation, were conducted for how to effect on model results with wind profiler data. It was found that the assimilated case shows the more reasonable results than the other case compared with vertical observation and surface Automatic Weather Station(AWS) data. Although the effect of sonde data was better than profiler at a higher altitude, the profiler data improves the model performance at lower atmosphere. Comparison with the results of 4 June and 5 June suggests that the efficiency with hourly assimilated profiler data is strongly influenced by synoptic conditions. The reduction rate of Normalized Mean Error(NME), mean bias normalized by averaged wind speed of observation, on 4 June was 28% which was larger than 13% of 5 June. In order to examine the difference in wind power energy, the wind power density(WPD) was calculated and compared.

수문자료의 계절성은 수자원관리의 관점에서 매우 중요한 요소로서 계절성의 변동은 댐의 운영, 홍수조절, 관개용수 관리 등 다양한 분야와 밀접한 관계를 가지고 있다. 수문빈도해석을 위해 POT 자료와 같은 부분기간치계열을 사용함으로써 자료의 확충, 계절성 확보, 발생빈도모형의 구축 등이 가능하다. 본 연구에서는 POT 자료의 장점을 효과적으로 빈도해석에 연계시키는 방법론으로서 POT 자료로부터 계절성을 추출하고 이를 빈도해석과 연계시켜 Bayesian 기법

본 연구에서는 한국 기온자료에 적용할 품질검정 알고리즘을 개발하고 알고리즘에 적용되는 기준값 및 기준값 도출 방법을 제시하였다. 이렇게 개발된 알고리즘을 부산 기상관측지점에 적용하여 검증하였고 그 검증결과를 제시하였다. 부산 기상관측지점은 극한값 검사와 기후범위 검사에서는 오류와 의심자료가 검출되지 않았고, 내적일치성 검사와 공간분포 검사에서 오류 및 의심자료가 검출되었다. 본 연구의 기온자료 품질검정 알고리즘은 구조적으로 명백한 오류자료 뿐만 아니라 자료의 시·공간적인 비교를 통해 잠재적 오류 의심자료를 분석자에게 제시하는 장점이 있다.

본 논문에서는 각각의 시점에서의 변화확률을 산정하여 변화시점을 추정하는 Barry and Hartigan (BH)의 베이지안 변화시점 추정방법(Bayesian changing points estimation method)을 이용하여 측우기 관측자료계열(CWK)과 근대우량계 관측자료계열(MRG)간의 변화에 대한 상대확률적 절점의 발생여부를 분석하였다. 어떠한 자연 현상도 완전히 동일하게 재현되지 않기때문에 시간적인 순서를 고려하지못하는 통계적 방법은 구체

본 연구에서는 우리나라 전역에 대한 토양수분 분포도 작성을 위하여 지상관측 토양수분, 강수량, 지면온도, NDVI, 토지피복, 유효토심 등과 같은 보조자료와 CART기법을 이용한 새로운 추정기법을 제시하였다. 먼저 신뢰성 높은 토양 수분 관측자료를 가진 용담댐 유역(4개 지점)에 대하여 토양수분을 추정하여 적용 가능성을 분석하였다. 3개 지점(부귀, 상전, 천천2)의 토양수분 관측치는 토양수분 추정 모형 수립에 사용하였으며, 검증에 1개 지점(계북2)이

This study is designed to assess the priority order of the chemicals to cause to generate occupational diseases in order to understand the fundamental data required for the preparation of health protective measure for the workers dealing with chemicals. The 41 types of 51 ones of chemicals to cause to generate the national occupational diseases were selected as the study objects by understanding their domestic use or not, and their occupational diseases' occurrence or not among 110,608 types of domestic and overseas chemicals. To assess their priority order the sum of scores was acquired by understanding the actually classified condition based on a perfect score of physical riskiness(90points) and health toxicity(92points) as a classification standard by GHS, the priority order on GHS riskiness assessment, GHS toxicity assessment, GHS toxic․riskiness assessment(sum of riskiness plus toxicity) was assessed by multiplying each result by each weight of occupational disease's occurrence. The high ranking 5 items of chemicals for GHS riskiness assessment were turned out to be urethane, copper, chlorine, manganese, and thiomersal by order. Besides as a result of GHS toxicity assessment the top fives were assessed to be aluminum, iron oxide, manganese, copper, and cadium(Metal) by order. On the other hand, GHS toxicity․riskiness assessment showed that the top fives were assessed to be copper, urethane, iron oxide, chlorine and phenanthrene by order. As there is no material or many uncertain details for physical riskiness or health toxicity by GHS classification though such materials caused to generate the national occupational diseases, it is very urgent to prepare its countermeasure based on the forementioned in order to protect the workers handling or being exposed to chemicals from health.

The effects of high-resolution wind profiler (HWP) data on the wind distributions were evaluated in two different coastal areas during the study period (23-26 August, 2007), indicating weak-gradient flows. The analysis was performed using the Weather Research and Forecasting (WRF) model coupled with a three-dimensional variational (3DVAR) data assimilation system. For the comparison purpose, two coastal regions were selected as: a southwestern coastal (SWC) region characterized by a complex shoreline and a eastern coastal (EC) region surrounding a simple coastline and high mountains. The influence of data assimilation using the HWP data on the wind distributions in the SWC region was moderately higher than that of the EC region. In comparison between the wind speed and direction in the two coastal areas, the application of the HWP data contributed to improvement of the wind direction distribution in the SWC region and the wind strength in the EC region, respectively. This study suggests that the application of the HWP data exerts a large impact on the change in wind distributions over the sea and thus can contribute to the solution to lack of satellite and buoy data with their observational uncertainty.

이 연구의 목적은 2007년 개정 교육과정에서 통합 신설된 기술ㆍ가정 교과의 ‘전자 기계 기술’ 단원을 위한 로봇 수업자료를 개발하고, 적용하여 그 효과를 알아보는데 있다. 이 연구를 수행하기 위한 수업자료의 개발과정은 ADDIE 모형에 의한 분석(Analysis), 설계(Design), 개발(Development), 실행(Implementation), 평가(Evaluation) 이다. 개발된 수업자료는 한국교육과정평가원의 학습콘텐츠 개발지침의 평가준거에 의거하여 전문가 집단에게 평가받았으며, 학습자에게 실제 적용하여 그 효과를 알아보았다. 이 연구의 결과를 요약하면 다음과 같다. 첫째, 수업자료는 한국교육과정평가원의 교수·학습 콘텐츠 개발모형의 준거와 ADDIE 모형에 의한 활동들을 구성하여 5가지 측면으로 준거를 구성하였다. 연구의 절차는 분석, 설계, 개발, 실행, 평가의 5단계로 진행하였다. 둘째, 개발된 수업자료는 레고 마인드스톰을 수업교재로 활용한 학습 지도안, 학습 활동지, PPT, 수업교재 안내서이며, 이 수업자료를 통해 실제 수업에 적용하였다. 셋째, 실제 수업에 적용해 본 결과 학습자들은 로봇에 많은 흥미를 나타냈으며, 전체적으로 수업만족도가 높은 것으로 분석되었다. 넷째, 수업자료를 전문가 집단에 의해 효과를 검증한 결과 상당수 평가 영역에서 그 효과가 높은 것으로 분석되었고, 효과가 낮은 영역과 개선을 위한 서술형 의견을 반영하여 수업자료를 개선하였다.