The decommissioning of domestic Nuclear Power Plants (NPPs) in Korea is expected to begin with the Kori-1, which was permanently shutdown in 2017. In addition, Wolsong-1 has been also permanently shutdown, and another type will be the decommissioning project following Kori-1. KHNP is promoting operation and decommissioning projects as the owner of NPPs, and the Central Research Institute (CRI) has been developing a Final Decommissioning Plan (FDP) for the decommissioning license document. The FDP consists of 11 major chapters in the order of overview of the project, characteristic evaluation, safety assessment, radiation protection, decontamination & dismantlement activities, waste management, etc. The contents described in each chapter are individual chapters, but there are also parts that consider the connection with other chapters. The CRI, which develops the FDP for the first decommissioning project in Korea, has spent a lot of time and effort considering this and has been proceeding through trial and error until the present stage. Therefore, this study aims to explain the current status of FDP, a license document for domestic decommissioning projects, and the link between major input data in major chapters. It can be said that System, Structure, and Components (SSCs) subject to dismantling are considered as the scope of FDP. Chapters that perform estimations on these dismantling targets may include safety assessments, exposure dose assessments for workers and residents, and waste inventory assessments. Therefore, an important part of performing the estimation works is to consider the entire scope of decommissioning activities, and as a way, it can start from data based on the inventory data. After generating the inventory data, the waste treatment classification for the inventory is designated by reflecting the results of the characterization. In addition, for cost estimation, the cost of decommissioning project is predicted by inputting some data (i.e., UCF) such as work process, number of workers, and time required for each item with data reflected in quantity and characterization. After that, based on these inventory, characterization, and UCF data, accident scenarios and industrial safety evaluation are performed for the safety assessment. The worker exposure dose is estimated by considering the dose rate of the workspace with these data. In the case of the amount of waste, the final amount of waste is estimated by considering the factors of reduction and decontamination. In summary, the main estimation contents of FDP are evaluated by adding elements required for the purpose of each chapter from data combined with inventory, characterization, and UCF, so the contents of these chapters are based on the logic of considering the entire scope of decommissioning in common.

Nowadays, artificial intelligence model approaches such as machine and deep learning have been widely used to predict variations of water quality in various freshwater bodies. In particular, many researchers have tried to predict the occurrence of cyanobacterial blooms in inland water, which pose a threat to human health and aquatic ecosystems. Therefore, the objective of this study were to: 1) review studies on the application of machine learning models for predicting the occurrence of cyanobacterial blooms and its metabolites and 2) prospect for future study on the prediction of cyanobacteria by machine learning models including deep learning. In this study, a systematic literature search and review were conducted using SCOPUS, which is Elsevier’s abstract and citation database. The key results showed that deep learning models were usually used to predict cyanobacterial cells, while machine learning models focused on predicting cyanobacterial metabolites such as concentrations of microcystin, geosmin, and 2-methylisoborneol (2-MIB) in reservoirs. There was a distinct difference in the use of input variables to predict cyanobacterial cells and metabolites. The application of deep learning models through the construction of big data may be encouraged to build accurate models to predict cyanobacterial metabolites.

처분시설의 개발과정에서 안전성평가 문서관리는 체계적인 품질활동이 수반되어야 하며, 본 논문에서는 중·저준위 방사 성폐기물 처분시설의 건설단계에 보완된 부지특성, 지하수특성, 최종설계내용 및 모니터링 입력데이터를 포함하여 Safety Case를 위한 안전성평가 입력데이터 품질보증체계를 설명하였다. 현장/실험결과데이터, 실제 설계데이터 및 적치계획, 콘 크리트 물성데이터, 지하수, 기상, 지진에 대한 현장 모니터링데이터, 생태계데이터 및 핵종재고량데이터를 입력데이터 결 정원칙에 따라 선별하고 안전성평가에 적용할 수 있는 데이터 관리체계를 확보하였다. 이는 향후 처분시설 안전성평가의 데 이터 불확실성 저감 및 안전성 증진에 기여할 것으로 판단된다.

PURPOSES : The travel times of expressway buses have been estimated using the travel time data between entrance tollgates and exit tollgates, which are produced by the Toll Collections System (TCS). However, the travel time data from TCS has a few critical problems. For example, the travel time data include the travel times of trucks as well as those of buses. Therefore, the travel time estimation of expressway buses using TCS data may be implicitly and explicitly incorrect. The goal of this study is to improve the accuracy of the expressway bus travel time estimation using DSRC-based travel time by identifying the appropriate analysis period of input data. METHODS : All expressway buses are equipped with the Hi-Pass transponders so that the travel times of only expressway buses can be extracted now using DSRC. Thus, this study analyzed the operational characteristics as well as travel time patterns of the expressway buses operating between Seoul and Dajeon. And then, this study determined the most appropriate analysis period of input data for the expressway bus travel time estimation model in order to improve the accuracy of the model. RESULTS: As a result of feasibility analysis according to the analysis period, overall MAPE values were found to be similar. However, the MAPE values of the cases using similar volume patterns outperformed other cases. CONCLUSIONS: The best input period was that of the case which uses the travel time pattern of the days whose total expressway traffic volumes are similar to that of one day before the day during which the travel times of expressway buses must be estimated.

국내 심부지질환경조건을 반영한 처분안전성 평가에 필요한 입력자료를 제공하기위해, 그 동안 국내 지하시험시설(KURT)환경조건에서 많은 실험을 수행해 왔다. 안전성평가코드에 사용되는 많은 입력변수 들 중 중요성이 부각되는 입력변수들을 선정하여, 각 변수별로 수집한 자료를 통계처리를 하여 값 분포 특성을 기술하고, 외국자료 값과 비교평가를 통해 값의 타당성을 검토하였다. 다룬 입력변수로서 용기물 성분야에서 용기수명, 초기파손률을, 완충재물성분야에서는 핵종용해도, 완충재의 공극률, 밀도, 확산계 수, 핵종분배계수를, 암반 및 원계영역에서는 수리전도도, 지하수유속, 핵종분배계수, 확산깊이, 암반균 열폭, 주지하수유동통로까지 거리, 핵종이동오염운의 너비 등이다.

방사성폐기물 처분 연구 사업이 법률적인 인허가 뿐만이 아니라 일반 국민의 동의를 얻기 위해서는 처분 사업의 안전성에 대한 신뢰성 획득이 중요하며 이를 위해 투명하게 공개될 수 있는 종합 성능 평가 (TSPA, Total System Performance Assessment)의 수행 이 필요하다. 본 연구에서는 처분 성능 평가의 투명성 증진을 위한 방안의 하나로 처분 종합 성능 평가 전 과정에 대해 품질 보증 원칙을 도입하여 평가 관련 전체 업무에 관한 신뢰성 향상을 꾀하고자 하였다. 이를 위해 처분 종합 성능 평가 수행의 다섯 단계인 (1) 기획, (2) 연구 수행 , (3) 문서화, (4) 내부 검토, (5) 독자적인 외부 검토 과정에 T2R3의 품질 보증 원칙을 적용한 인터넷 기반의 Cyber R&D Platform이 개발되었다. 인터넷을 기반으로 하는 본 시스템의 개발을 통해 안전성 평가 관련 모든 참여자들은 평가 전 과정에서 투명성이 유지된 데이터들에 쉽게 접근하여 이를 이용할 수 있다 Cyber R&D Platform은 안전성 평가를 위한 시나리오 개발 관련 데이터인 FEP 목록과 관련 시나리오 정보, 관련 시나리오 도출 과정 및 평가 체계 등을 체계적으로 구축한 FEAS (FEp to Assessment through Scenario development)프로그램과 안전성 평가에 필요한 입력 데이터들을 분류, 저장해 놓은 PAID (Performance Assessment Input Data) 프로그램, 그리고 이러한 자료들을 품질 보증 원칙과 절차에 의한 승인 과정을 통해 입력, 저장할 수 있는 품질 보증 시스템으로 구성되어 있으며 이를 통합 운영함으로써 도출된 데이터들의 신뢰성을 높이고자 하였다. 향후 연구에서는 Cyber R&D Platform과 평가 software와의 통합 운영으로 웹 기반 시스템에 대한 한 번의 접속만으로 안전성 평가 관련 모든 정보를 확인, 이용할 수 있도록 할 것이다.

Recently, spatial data integration for geoscientific application has been regarded as an important task of various geoscientific applications of GIS. Although much research has been reported in the literature, quantitative assessment of the spatial interrelationship between input data layers and an integrated layer has not been considered fully and is in the development stage. Regarding this matter, we propose here, methodologies that account for the spatial interrelationship and spatial patterns in the spatial integration task, namely a multi-buffer zone analysis and a statistical analysis based on a contingency table. The main part of our work, the multi-buffer zone analysis, was addressed and applied to reveal the spatial pattern around geological source primitives and statistical analysis was performed to extract information for the assessment of an integrated layer. Mineral potential mapping using multi-source geoscience data sets from Ogdong in Korea was applied to illustrate application of this methodology.

개인별 신체 특성을 나타내는 가상피팅모델을 이용하여 제공되는 가상 착용 서비스는 웹을 기반으로 한 인터넷 의류 쇼핑의 흥미를 더해준다. 본 연구의 연구자들은 2000년과 2002년에 개발된 미국의 가상피팅모델과 국내에서 개발되었던 가상피팅모델의 개발 기술의 특성과 변화를 분석하였다. 연구결과는 가상피팅모델의 구축을 위해서는 인체의 치수, 형태, 얼굴의 특징들에 관한 정보 입력이 필요하며, 이때 요구되는 정보는 미국과 한국의 사이트에서 차이가 있음을 밝혔다. 미국의 사이트는 정면이나 측면의 실루엣에 대한 정보의 입력이 요구되는 반면 한국의 사이트는 더 많은 인체 치수 관련 정보를 요구하였다. 2000년에 개발되었던 한국의 가상피팅모델은 길고 좁은 프로포션으로 표현되어 사실적인 표현이 부족하였던 반면 2002년 미국에서 개발한 가상피팅모델은 다양한 인종의 특성을 반영하며, 그래픽 기술의 발전으로 사실적으로 표현된 가상피팅모델을 제공하는 것으로 나타났다.

I - BUILDS는 기존의 CAD 프로그랩인 BUILDS와 지식베이스룹 일판된 시스템으로 통합한 컨쓸설계용 전문가 시스댐이다. 본 시스템올 구축하기 위한 노력의 일환으로 본 논문에서논 추론에 의해 발생된 데이 타 뜰 을다양한계산능력을가지 변서 특별한 업부 도 수행할 수 있게 설계된 건붙의 일팔구조셜계 시스댐인 BUILDS 의 부시스템 (BUILDS - A ) 에 이용되도록 입력파일화하기 위한 기본적인 개념을 기술한다.

In this study, we investigated the impact of different initial data on atmospheric modeling results using the Weather Research and Forecast (WRF) model. Four WRF simulations were conducted with different initialization in March 2015, which showed the highest monthly mean PM10 concentration in the recent ten years (2006-2015). The results of WRF simulations using NCEP-FNL and ERA-Interim were compared with observed surface temperature and wind speed data, and the difference of grid nudging effect on WRF simulation between the two data were also analyzed. The FNL simulation showed better accuracy in the simulated temperature and wind speed than the Interim simulation, and the difference was clear in the coastal area. The grid nudging effect on the Interim simulation was larger than that of the FNL simulation. Despite of the higher spatial resolution of ERA-Interim data compared to NCEP-FNL data, the Interim simulation showed slightly worse accuracy than those of the FNL simulation. It was due to uncertainties associated with the Sea Surface Temperature (SST) field in the ERA-Interim data. The results from the Interim simulation with different SST data showed significantly improved accuracy than the standard Interim simulation. It means that the SST field in the ERA-Interim data need to be optimized for the better WRF simulation. In conclusion, although the WRF simulation with ERA-Interim data does not show reasonable accuracy compared to those with NCEP-FNL data, it would be able to be Improved by optimizing the SST variable.

Phosphorus (P) is an essential and major nutrient for both plants and animals. However, anthropogenic P in the environment may cause severe problems such as the deterioration of water quality. Therefore, it is essential for the Korean government to manage P in the agricultural sector. The annual P budget for Korea was 46 kg P ha-1 in 2013, placing Korea in second among Organication for Economic Co-operation and Development (OECD) countries. P surplus and deficiency in agricultural lands can be estimated according to the P budget, which is one of the OECD agri-environment indicators. In the P budget, it is important to ensure consistency in the input-output data sources, in order to apply national and regional policies for the environmentally sound management of agricultural P. This study examines the impacts on the input-output data sources in the regional P budget in Korea. P budgets were between 99-145 kg-P/ha, depending on different data sources. We suggest two recommended data combinations (DC 1 and DC 2) for reliability of the data. P budgets calculated using DC 1 and DC 2 were 128 kg-P/ha and 97 kg-P/ha, respectively. According to the results, one of the core factors affecting P budgets was crop production. In this study, DC 2 was recommended rather than DC 1 in order to consider the cultivated areas for various crops. It is also necessary to analyze the sensitivity of the coefficients used in P budget in the future.

To prevent increasing instances of heat-related illnesses due to heat waves generated by climate change, a customized thermal environment index should be developed for outdoor workers. In this study, we conducted sensitivity analysis of the Masan harbor during a heat wave period (August 9th to 15th, 2013) using the MENEX model with metabolic rate and clothing-insulation data, in order to obtain realistic information about the thermal environment. This study shows that accurate input data are essential to gather information for thermophysiological indices (PST, DhR, and OhR). PST is sensitive to clothing insulation as a function of clothing. OhR is more sensitive to clothing insulation during the day and to the metabolic rate at night. From these results, it appears that when exposed to high-temperature thermal environments in summer, wearing highly insulated clothing and getting enough rest (to lower the metabolic rate) can aid in preventing heat-related illnesses. Moreover, in the case of high-intensity harbor work, quantification of allowed working time (OhR) during heat waves is significant for human health sciences.

This study was conducted to investigate the correlation between the distribution chart and input data of the predicted 3-second gust and damage cost, by using the forecast field and analysis field of Regional Data Assimilation Prediction System (RDAPS) as initial input data of Korea risk assessment model (RAM) developed in the preceding study. In this study the cases of typhoon Rusa which caused occurred great damage to the Korean peninsula was analyzed to assess the suitability of initial input data. As a result, this study has found out that the distribution chart from the forecast field and analysis field predicted from the point where the effect due to the typhoon began had similarity in both 3-second gust and damage cost with the course of time. As a result of examining the correlation, the 3-second gust had over 0.8, and it means that the forecast field and analysis field show similar results. This study has shown that utilizing the forecast field as initial input data of Korea RAM could suit the purpose of pre-disaster prevention.

Linear and nonlinear models are available to simulate the effect of mine blasting and the results change by each model. Linear model can properly simulate loss of impact wave in plastic failure region based on comparison of site vibration measurement and numerical analysis iteratively. But, loss of impact wave in plastic failure region should be calibrated into input parameter of blasting pressure. A method to convert loss of impact wave into design parameter is suggested in this study.

최근 기후변화에 의한 기상이변이 발생하고 국지적 집중호우로 인한 홍수피해가 심각하게 증가하고 있다. 이러한 피해를 경감하기 위한 방법으로 정확한 홍수유출량 예측을 통한 홍수예경보 구축이 필요시 된다. 정확한 홍수유출량 예측을 위해 수문기상학적 요소와 특성인자들의 정확한 상호 연관성 규명과 공간적 변동성 해석은 강우-유출 모형에서 발생하는 불확실성을 감소시키는데 중요한 요소로 작용하게 된다. 본 연구에서는 정확한 홍수유출량을 산정하기 위한 강우-유출모형을 이용한 입력자료의 해상도에 따른 불확실성을 감소시키기 위해 강우격자 해상도와 지형인자 격자 해상도에 따라 강우-유출모형이 어떻게 반응하는지 분석하였다. 분포형 강우-유출 모형인 GRM 모형을 이용하여 내성천 및 감천 유역을 대상으로 이벤트를 산정하여 홍수유출 모의 및 검증을 실시하였다. GRM 모형 구성을 위한 입력자료(강우, DEM, 토지이용도, 토양도)의 해상도 격자크기는 500m 격자크기를 기본으로 각각 1 km, 2 km, 5 km, 10 km, 12 km 격자크기의 지형자료를 사용하여 유출모의를 실시하고 유출량 변화를 모의하였다. 입력자료별 모의결과로 DEM의 분석결과는 모든 시험유역에서 공통적으로 DEM의 격자크기가 증가할수록 첨두유량과 총유출량이 일정하게 감소하는 경향을 나타내고 있다. 나머지 입력자료로 토지이용 및 토양도에 격자크기에 따른 모의결과는 DEM과는 상반되게 일정한 경향성을 나타나지 않는 것으로 분석되었다. 특히 일정한 경향성이 나타나는 DEM의 분석결과는 DEM의 격자크기가 증가할수록 수평거리가 증가하여 경사도는 감소하는 특징으로 인해 나타나는 결과인 것으로 판단된다.

본 연구의 목적은 중소하천에서의 홍수예측을 위해 사용되는 기존의 수문학적 모형이 가지고 있는 문제점을 개선한 홍수예측 모형을 개발하는데 있다. 이를 위해 기존의 수문학적 강우-유출 모형에서 사용되는 많은 수문학적 자료 및 매개변수들의 사용 없이 오직 수위 및 강우측정 자료만을 이용하여 홍수를 예측할 수 있는 Takagi-Sugeno 퍼지 추론기법과 신경망을 연계한뉴로-퍼지홍수예측 모형을 구축하고자 하였다. 뉴로-퍼지 홍수예측 모형의 예측정확도는 입력자료

In an effort to examine the Regional Atmospheric Modeling System (RAMS ver. 4.3) to the initial meteorological input data, detailed observational data of NOAA satellite SST (Sea Surface Temperature) was employed. The NOAA satellite SST which is currently provided daily as a seven-day mean value with resolution of 0.1 o grid spacing was used instead of the climatologically derived monthly mean SST using in RAMS. In addition, the RAMS SST data must be changed new one because it was constructed in 1993. For more realistic initial meteorological fields, the NOAA satellite SST was incorporated into the RAMS-preprocess package named ISentropic ANalysis package (ISAN). When the NOAA SST data was imposed to the initial condition of prognostic RAMS model, the resultant performance of near surface atmospheric fields was discussed and compared with that of default option of SST. We got the good results that the new SST data was made in a standard RAMS format and showed the detailed variation of SST. As the modeling grid became smaller, the SST differences of the NOAA SST run and the RAMS SST43 (default) run in diurnal variation were very minor but this research can apply to further study for the realistic SST situation and the development in predicting regional atmospheric field which imply the regional circulation due to differential surface heating between sea and land or climatological phenomenon.