본 연구는 전문가 기반형 모델(Habitat Suitability Index)의 한계로 지적되는 주관적 기준, 통계분석의 부재 등과 통계기반형 모델(MaxEnt)의 한계로 지적되는 현장검증, 전문가 의견 반영 등의 극복을 위하여 각각의 모델을 개발하여 통합하는 방식으로 핵심서식지를 도출하였다. 핵심서식지 발굴을 위해 문헌분석 및 공간분석자료를 바탕으로 전문가 심층면담을 진행하였고, 전문가 자문과 GIS 도면 구축 가능성을 고려하여 모델을 개발하였다. 주요 환경변수는 식생대, 임상, 임분밀도, 연평균 강수량, 유효토심으로 선정되었다. 그 결과 현재 나도승마가 분포하고 있는 16지점 중 15지점이 핵심서식지로 나타났으며, 개발된 모델은 약 93.75%의 높은 정확도를 가지고 있는 것으로 나타났다. 하지만 전체 연구대상지의 약 27.8%가 핵심서식지로 나타남에 따라, 추후 서식변수 및 공간자료 정밀화를 통한 모델의 고도화가 필요할 것으로 판단된다. 따라서 높은 등급으로 확인된 서식지라도 대상종의 서식유무 파악을 위한 현장검증은 필수적으로 수행되어야 한다. 하지만, 이러한 한계에도 불구하고 HSI와 MaxEnt의 상호보완적 활용은 생물종의 분포와 서식지 이용 특성을 통하여 적합 서식지를 예측하고, 신규 서식지 발굴 및 대체서식지 선정 등 다양한 방면으로 활용 가능할 것으로 판단된다.

After the major radioactivation structures (RPV, Core, SG, etc.) due to neutron irradiation from the nuclear fuel in the reactor are permanently shut down, numerous nuclides that emit alpha-rays, beta-rays, gamma-rays, etc. exist within the radioactive structures. In this study, nuclides were selected to evaluate the source term for worker exposure management (external exposure) at the time of decommissioning. The selection of nuclides was derived by sequentially considering the four steps. In the first stage, the classification of isotopes of major nuclides generated from the radiation of fission products, neutron-radiated products, coolant-induced corrosion products, and other impurities was considered as a step to select evaluation nuclides in major primary system structures. As a second step, in order to select the major radionuclides to be considered at the time of decommissioning, it is necessary to select the nuclides considering their half-life. Considering this, nuclides that were less than 5 years after permanent suspension were excluded. As a third step, since the purpose of reducing worker exposure during decommissioning is significant, nuclides that emit gamma rays when decaying were selected. As a final step, it is a material made by radiation from the fuel rod of the reactor and is often a fission product found in the event of a Severe accident at a nuclear power plant, and is excluded from the nuclide for evaluation at the time of decommissioning is excluded. The final selected Co-60 is a nuclide that emits high-energy gamma rays and was classified as a major nuclide that affects the reduction of radiation exposure to decommissioning workers. In the future, based on the nuclide selection results derived from this study, we plan to study the evaluation of worker radiation exposure from crud to decommissioning workers by deriving evaluation results of crud and radioactive source terms within the reactor core.

Dry active wastes (DAWs) are combustible waste generated during the operation and decommissioning of nuclear facilities, and are known to be generated in the amount of approximately 10,000 to 40,000 drums (based on 200 L) per unit. It consists of various types of protective clothing, paper, and plastic bags, and is stored in radioactive waste storage facilities. Therefore, reducing the volume of DAWs is an important issue in order to reduce storage costs and utilize the limited space of waste storage facilities. Heat treatment such as incineration can dramatically reduce the volume of waste, but as the waste is thermally decomposed, CO2, a global warming gas, is generated and there is a risk of emissions of harmful gases including radionuclides. Therefore, a heat treatment process that minimizes the generation of CO2 and harmful gases is necessary. One of the alternatives to incineration is to carbonize DAWs, dispose of carbonized materials below the release standard as non-radioactive waste, and selectively separate and stabilize inorganic components, including radionuclides, from carbonized DAWs. In this study, 13 types of DAWs generated from nuclear power plants were selected and their thermal decomposition characteristics were investigated to design a heat treatment process that replaces incineration. As a result of TGA analysis, the temperature at which thermal decomposition of each waste begins is 260-300°C for cotton, 320-330°C for paper, 315-420°C for synthetic fiber, 350°C for latex gloves. The mass of most samples decreased to less than 1 % of the initial weight after heat treatment, and dust suit and latex gloves had residues of 13.83% and 13.71% of the initial mass, respectively. The metal components of the residue produced after heat treatment of the sample were analyzed by EDS. According to the EDS results, cotton contains Ca and Al, paper contains Ca, Al and Si, synthetic fiber contains Ca, Cu and Ti, latex gloves contain Ca and Mg. Additionally, ICP analysis was performed to quantify the inorganic components. These results are expected to be applicable to the processing of DAW generated at nuclear facilities in the future.

In recent years, the diminishing of operation and maintenance cost using advanced maintenance technology is attracting many companies’ attention. Especially, the heavy machinery industry regards it as a crucial problem since a failure of heavy machinery requires high cost and long downtime. To improve the current maintenance process, the heavy machinery industry tries to develop a methodology to predict failure in advance and to find its causes using usage data. A better analysis of failure causes requires more data so that various kinds of sensor are attached to machines and abundant amount of product usage data is collected through the sensor network. However, the systemic analysis of the collected product usage data is still in its infant stage. Many previous works have focused on failure occurrence as statistical data for reliability analysis. There have been less works to apply product usage data into root cause analysis of product failure. The product usage data collected while failures occur should be considered failure cause analysis. To do this, this study proposes a methodology to apply product usage data into failure cause analysis. The proposed methodology in this study is composed of several steps to transform product usage into failure causes. Various statistical analysis combined with product usage data such as multinomial logistic regression, T-test, and so on are used for the root cause analysis. The proposed methodology is applied to field data coming from operated locomotive and the analysis result shows its effectiveness.

Interpreting ultraviolet-to-infrared (UV-to-IR) observations of galaxies in terms of constraints on phys- ical parameters - such as stellar mass (M*) and star formation rate (SFR) - requires spectral synthesis modelling. We investigate how increasing the level of sophistication of the standard simplifying assump- tions of such models can improve estimates of galaxy physical parameters. To achieve this, we compile a sample of 1048 galaxies at redshifts 0:7 < z < 2:8 with accurate photometry at rest-frame UV to near-IR wavelengths from the 3D-HST Survey. We compare the spectral energy distributions of these galaxies with those from different model spectral libraries to derive estimates of the physical parameters. We find that spectral libraries including sophisticated descriptions of galaxy star formation histories (SFHs) and prescriptions for attenuation by dust and nebular emission provide a much better representation of the observations than `classical' spectral libraries, in which galaxy SFHs are assumed to be exponentially declining functions of time, associated with a simple prescription for dust attenuation free of nebular emission. As a result, for the galaxies in our sample, M* derived using classical spectral libraries tends to be systematically overestimated and SFRs systematically underestimated relative to the values derived adopting a more realistic spectral library. We conclude that the sophisticated approach considered here is required to reliably interpret fundamental diagnostics of galaxy evolution.

The world energy crisis and the universal interest in comfort buildings are not only leading the thriving Passive House and Nearly Zero Energy House strategies but also encouraging the development of higher performance HVAC systems and alternative energy sources for occupants and sensible energy consumption. However, household appliances have been used to control the indoor environment such as humidifiers, dehumidifiers and air cleaners are became popular, occupants have come to rely on these appliances heavily and are overusing energy on indoor environment manage easily and quickly. In addition, the intense air tightness of current residential buildings makes possible to reduce harmful outdoor conditions but has made the indoor environment isolated from the outdoors. As well, climate change due to global warming and the urban heat island effect have broken the natural bond between humans and the environment. As high-rise, air tight buildings have become the most common residential building type in South Korea, occupants in high-rise residential buildings inevitably lose the chances to have the natural environment by the change of season to feel the warm sunlights of spring and the dry leafy smell on an autumn breeze. In this sense, regional weather data was analysed to establish comfort residential building strategies that commune with nature and o

Pig embryonic stem cells (ESC) has been suggested to become important animal model for therapeutic cloning using embryonic stem cells derived by somatic cell nuclear transfer (SCNT). However, the quality of cloned embryo and derivation rate of cloned blastocyst has been presented limits for derivation of cloned embryonic stem cell. In this study, we have tried to overcome these problems by aggregating porcine embryos. Zonafree reconstructed SCNT Embryos were cultured in micro-wells singularly (non-aggregated group) or as aggregates of three (aggregated groups) at the four cell stage. Embryo quality of the cloned embryos and attachment on feeder layer rate significantly increased in the aggregates. The aggregation of pig SCNT embryos at the four-cell stage can be a useful technique for improving the quality of pig cloned blastocyst and improvement in the percentage of attachment on the feeder layer of cloned embryos. * This work was supported by the BioGreen 21 Program (PJ0081382011), Rural Development Administration, Republic of Korea.

본 연구의 목적은 댐 관리자가 쉽게 이해할 수 있고, 실제 댐 운영 업무에 적용하기 쉬운 저수지 운영률을 도출하는 것이다. 수위 구간별 저수지 운영률은 현재의 저수지 수위가 위치하는 영역의 운영 기준에 따라 저수지를 운영하는 간단한 방법이지만, 구체적인 수위 구간의 설정이 필요한 방법이다. 이에 연구에서는 수위 구간별 운영률을 포함한 저수지 운영 모형을 개발하였고, 수위 구간별 운영률의 적절한 수위 구간을 결정하기 위해 집합체 혼합진화 알고리즘을 이용하였다. 개발된 저수지 운영 모형을 물 수급 불균형으로 인해 물 공급에 어려움을 겪고 있는 필리핀의 Angat 댐에 대하여 적용하여 수위 구간별 운영률을 도출하고, 그에 따라 기록 유입량 자료를 이용하여 Angat 댐을 모의 운영하였다. 그 결과, 모의 운영을 통해 결정된 계획 공급량 대비 용수공급 부족량과 발전량은 실제 운영 기록에 비해 각각 34.5%와 21.2% 개선되었다. 본 연구의 결과는 댐의 장기 운영률 유도에 활용되어질 수 있을 것이다.