The Co-60 is a radioactive material widely used in domestic and foreign medical, industrial, health and research fields. Currently, world market for the Co-60 is about 80 MCi/yr and is expected to grow to 150 MCi/yr by 2025. For the Co-60, Nordion of Canada occupies about 80% of the world market. In the case of Korea, a small amount of sources with relatively low radioactivity intensity are produced using research reactors, but most of the Co-60 is entirely dependent on imports. Accordingly, although the technical feasibility of the Co-60 production technology using the PHWR was evaluated, it was evaluated as a negative result on the additional construction of a hot cell, core management, safety analysis and economic feasibility. Canada, the main producer of the Co-60, is also conducting research on the Co-60 production technology using PWR with GE-Hitachi and Westinghouse as the number of PHWR is expected to decrease. In Korea, it is necessary to preoccupy the Co-60 production technology and auxiliary technology using the PWR by utilizing excellent technology, and active research is being conducted to secure unique nuclear power technology that does not depend on foreign countries. Therefore, in this study, the thickness and weight of the radioactive shielding required for handling (transport) of Co-60 produced using the PWR were calculated.

Attention has been paid to the source term released after Chernobyl and Three Mile Island (TMI), which were the representative accidents of nuclear power plants, and has been studied several times in order to predict and evaluate radiation source term, which can be released in the event of a virtual accident. In particular, the impact of the accident was assessed on the basis of Deterministic Safety Analysis (DSA) and after the WASH-1400, the technology of the Probabilistic Safety Assessment (PSA) was introduced, supplementing safety by taking into account the existence of uncertainty. After the Fukushima accident, a SOARCA report was published to evaluate the specific classification of each type of accident, the realistic progress of the accident, and the leakage of radioactive materials. In this paper, the evaluation methodology and results of the source term of severe accident before and after the Fukushima accident were compared, and the evaluation methods applied to domestic nuclear power plants were compared. Prior to the Fukushima accident, the behavior of the accident and source term were evaluated for Loss of Coolant Accident (LOCA), which led to design based accidents, Total Loss of Feed Water (TLOFW) followed by Station Blackout (SBO) the results were compared to Chernobyl and TMI based on the resulting data to evaluate safety and reliability. After the Fukushima accident, the Interfacing System Loss of Coolant Accident (ISLOCA) and the Steam Generator Tube Rupture (SGTR), which is classified as containment’s bypass accident, were included for predictive assessment. This is due to the analysis that the risk of cancer and early mortality are affected. MACST facilities and strategies were added to domestic nuclear power plants, and accidents with a high core damage frequency were mainly interpreted. In addition, source term was evaluated with the addition of a Basement Melt-Through (BMT) accident that had not previously been considered as a focus. As a result of the comparison of source term evaluation, accidents can be caused by a number of unidentified problems, and Korea’s experience on Level 2 and 3 has not been accumulated, making it difficult to predict the results of source term evaluation or lack of reliability.

In this study, the positions of Cs-137 gamma ray source are estimated from the plastic scintillating fiber bundle sensor with length of 5 m, using machine learning data analysis. Seven strands of plastic scintillating fibers are bundled by black shrink tube and two photomultiplier tubes are used as a gamma ray sensing and light measuring devices, respectively. The dose rate of Cs-137 used in this study is 6 μSv·h−1. For the machine learning modeling, Keras framework in a Python environment is used. The algorithm chosen to construct machine learning model is regression with 15,000 number of nodes in each hidden layer. The pulse-shaped signals measured by photomultiplier tubes are saved as discrete digits and each pulse data consists of 1,024 number of them. Measurements are conducted separately to create machine learning data used in training and test processes. Measurement times were different for obtaining training and test data which were 1 minute and 5 seconds, respectively. It is because sufficient number of data are needed in case of training data, while the measurement time of test data implies the actual measuring time. The machine learning model is designated to estimate the source positions using the information about time difference of the pulses which are created simultaneously by the interaction of gamma ray and plastic scintillating fiber sensor. To evaluate whether the double-trained machine learning model shows enhancement in accuracy of source position estimation, the reference model is constructed using training data with one-time learning process. The double-trained machine learning model is designed to construct first model and create a second training data using the training error and predetermined coefficient. The second training data are used to construct a final model. Both reference model and double-trained models constructed with different coefficients are evaluated with test data. The evaluation result shows that the average values calculated for all measured position in each model are different from 7.21 to 1.44 cm. As a result, by constructing the double-trained machine learning model, the final accuracy shows 80% of improvement ratio. Further study will be conducted to evaluate whether the double-trained machine learning model is applicable to other data obtained from measurement of gamma ray sources with different energy and set a methodology to find optimal coefficient.

Source localization technique using acoustic emission (AE) has been widely used to track the accurate location of the damaged structure. The principle of localization is based on signal velocity and the time difference of arrival (TDOF) obtained from different signals for the specific source. However, signal velocity changes depending on the frequency domain of signals. In addition, the TDOF is dependent on the signal threshold which affects the prediction accuracy. In this study, a convolutional neural network (CNN)-based approach is used to overcome the existing problem. The concrete block corresponding to 1.3×1.3×1.3 m size is prepared according to the mixing ratio of Wolseong low-to-intermediate level radioactive waste disposal concrete materials. The source is excited using an impact hammer, and signals were acquired through eight AE sensors attached to the concrete block and a multi-channel AE measurement system. The different signals for a specific source are time-synchronized to obtain TDOF information and are transformed into a time-frequency domain using continuous wavelet transform (CWT) for consideration of various frequencies. The developed CNN model is compared with the conventional TDOF-based method using the testing dataset. The result suggests that the CNN-based method can contribute to the improvement of localization performance.

본 연구는 조사료 원료인 마늘 껍질의 사료적 가치와 메탄 발생량을 조사하기 위해 in vitro 발효 실험을 수행하였다. Garlic husk를 제외하고 국내에서 널리 사용되는 4가지 조사료 원료(Oat hay, Annual ryegrass, Timothy, Tall fescue)를 실험의 처리구로 구성하였다. In vitro 48 시간 발효 후 건물 소화율, 섬유소 소화율, 암모니아태 질소, 휘발성 지방산, pH, 메탄 발생량을 평가하였다. 가스 발생량은 3, 6, 9, 12, 24, 36 및 48 시간에 각각 측정되었다. 최종 가스 발생량에서 Oat hay가 유의적으로 가장 높았다(p<0.01). Garlic husk는 처리구 중 가장 높은 메탄 발생량을 나타내었다(p<0.01). Garlic husk의 건물 소화율은 Oat hay보다 유의적으로 낮았지만 Annual ryegrass, Timothy, Tall fescue보다 높았다(p<0.01). 섬유소 소화율은 Annual ryegrass에서 가장 낮았다(p<0.01). 총 휘발성 지방산 생성량은 Oat hay에서 가장 높았고(p<0.01), Garlic husk, Timothy, Tall fescue는 유사하였다. 본 연구의 in vitro 발효 성상과 메탄 발생량을 고려할 때, Garlic husk는 국내 주요 조사료를 대체할 영양적 가치를 포함하고 있으나 메탄 저감 효과는 미미할 것으로 추정된다.

PURPOSES : Steel deck bridges are the preferred structural type for reducing dead load, and the use of thin-layer asphalt concrete with excellent adhesion to the steel deck and excellent deformation followability is increasing for bridge pavements. However, because these materials are constructed at a high temperature of 240 °C or higher to maintain high fluidity during construction, excessive thermal deformation and stress may be temporarily induced in the steel deck. Therefore, the stability of the structure must be assessed by considering the environmental conditions of the site during pavement construction. Herein, a method is presented for estimating the heat source equation, in which conduction and convection effects are removed using temperature measurement data, for modeling U-rib using plate elements. The validity of the study is assessed by deriving the equivalent heat source equation using the temperature data measured from the underside of the steel deck while constructing a 40-mm-thick goose asphalt concrete pavement layer on a 12-mm-thick steel deck. In addition, the practicality is verified by performing heat transfer and thermal stress analyses. METHODS : By comparing the temperature data measured during the construction of high-fluidity asphalt concrete with the results of repeated heat transfer numerical analysis, heat source data without field conduction and convection conditions are obtained. Subsequently, a heat source equation suitable for the heat source data is derived using the least-squares method. RESULTS : The results of the heat transfer analysis using the equivalent heat source equation calculated using the presented method are almost consistent with the measured temperature data. In addition, the behavioral characteristics of the structure that matches the behavior of the actual structure can be derived through thermal stress analysis, which considers heat conduction and convection to adjacent members. CONCLUSIONS : Even when the steel deck and U-rib member are modeled as plate elements, thermal effect analysis can be performed reasonably while considering field conditions.

A 1.8 μm thick polycrystalline diamond (PCD) thin film layer is prepared on a Si(100) substrate using hot-filament chemical vapor deposition. Thereafter, its thermal conductivity is measured using the conventional laser flash analysis (LFA) method, a LaserPIT-M2 instrument, and the newly proposed light source thermal analysis (LSTA) method. The LSTA method measures the thermal conductivity of the prepared PCD thin film layer using an ultraviolet (UV) lamp with a wavelength of 395 nm as the heat source and a thermocouple installed at a specific distance. In addition, the microstructure and quality of the prepared PCD thin films are evaluated using an optical microscope, a field emission scanning electron microscope, and a micro-Raman spectroscope. The LFA, LaserPIT-M2, and LSTA determine the thermal conductivities of the PCD thin films, which are 1.7, 1430, and 213.43 W/(m·K), respectively, indicating that the LFA method and LaserPIT-M2 are prone to errors. Considering the grain size of PCD, we conclude that the LSTA method is the most reliable one for determining the thermal conductivity of the fabricated PCD thin film layers. Therefore, the proposed LSTA method presents significant potential for the accurate and reliable measurement of the thermal conductivity of PCD thin films.

흰점박이꽃무지 (Protaetia brevitarsis seulensis) 유충의 대체사료인 한약재 부산물 발효원인 유용미생물 (Effective microorganism, EM)과 느타리버섯 종균 (Oyster mushroom fungi, OM)을 비교하였다. 각 발효된 사료의 영양성분을 비 교한 결과, 조회분을 제외한 조단백, 조지방, 조섬유 함량이 OM 발효사료에서 높게 나타났다. 각 발효된 사료로 사육된 흰점박이꽃무지 유충의 영양성분을 비교한 결과 차이가 관찰되지 않았다. 각 발효사료별 흰점박이꽃무지 유 충의 생체중을 주별 비교 분석한 결과, 3주차 관찰시기부터 EM과 OM을 이용한 사료에서 흰점박이꽃무지 유충 평균중량이 유의하게 높았다. 유충 사육 시 생존율은 발효사료의 경우 동일하게 96.7%이나, 비발효사료의 경우 9.8%로 매우 낮았다. 본 실험결과, 흰점박이꽃무지의 생육에 먹이 원의 발효는 꼭 필요했으며, OM은 EM을 대체할 수 있는 흰점박이꽃무지 대체사료의 발효원으로 더 안정적이었다.

MMBR system has been suggested as a promising system to resolve harvesting problems induced from low settling efficiency of microalgae. And recently, a lot of research on reducing fouling at the MMBR system has investigated focused on EPS in many cases. EPS of microalgae mainly consists of polysaccharides and protein components, and is produced through photosynthesis and nitrogen-carbon metabolic pathways. Especially, P-EPS is one of major compounds which occur membrane fouling phenomenon, as its hydrophobic protein components cause floc formation and cake layer accumulation. And it is already known that almost every microalgae can metabolize P-EPS or Chl-a when nitrogen sources as a substrate is insufficient or exhausted situation. With the above backgrounds, uptake rates of P-EPS or Chl-a by Scenedesmus quadricauda according to the type of carbon source and nitrogen concentration were evaluated in order to verify correlation between carbon source vs P-EPS production, and indeed Scenedesmus quadricauda uses P-EPS or Chl-a when the amounts of nitrogen sourc es in the feed is not satisfied. As a result, it was shown that P-EPS and Chl-a production were increased proportional to nitrogen concentration under organic carbon condition. And especially, the amo unts of P-EPS and Chl-a in the cell were diminished with the nitrogen source becomes insufficient or exhausted. Because P-EPS accelerates fouling at the MMBR system, P-EPS degradation by Scenedesmus quadricauda in order to get nitrogen source may contribute to reducing fouling. About a affects of N-consumed Chl-a to the MMBR fouling, more survey is needed. On the contrary, considering the purpose of MMBR system of this study, i.e. harvesting useful high value microalgae efficiently feeding adequate industrial process wastewater, it seems like difficult to maintain satisfied metabolic activity and to harvest with high yield rate using nitrogen-poor MMBR feed.

As a semi-enclosed sea, the Yellow Sea is shared by costal states such as China, South Korea and North Korea which have common interests in this maritime area. This situation requires special attention and mutual efforts for the protection and preservation of the coastal waters and marine ecosystem. The Yellow Sea contains many shipping routes, and it is potentially exposed to the risks of vessel-source pollution. This research has examined how the Yellow Sea states have implemented the International Maritime Organisation conventions relating to vessel-source pollution at the domestic level through a comparative legal study. The objective of this research is to understand current national laws of the Yellow Sea states dealing with the prevention of vessel-source pollution and to emphasize the necessity of regional efforts and cooperation to implement global regulatory instruments in order to protect and preserve the marine environment from the threats of international shipping activities.

유럽 지역은 다양한 해양오염 물질들로부터 해양환경을 보호하기 위해 특별 한 주의가 필요한 해역들이 분포되어 있다. 그동안 유럽 연합은 선박의 안전을 보장하고 선박기인 해양오염을 방지하기 위해 국제해사기구의 규범들을 효과 적으로 이행하고 있으며, 이와 더불어 유럽 연합 차원에서의 다양한 규제들을 채택해 왔다. 이러한 유럽 연합의 규범들은 선박기인 해양오염을 방지하기 위 해 채택된 국제해사기구의 규제수단의 법적 효과를 최대화하는데 공헌하고 있 다. 또한, 유럽 연합은 글로벌 해운산업에서의 영향력을 바탕으로 선박기인 해 양오염 방지를 위한 국제해사기구의 규제수단을 채택하는 의사결정과정에서 상당한 영향력을 발휘하고 있다. 선박기인 해양오염 방지에 관한 유럽 연합의 규제를 다루고 있는 본 연구는 공유해역을 가지고 있는 국가들이 어떻게 지역 협력 구축을 통해 선박기인 해양오염을 효과적으로 방지할 수 있는지에 관한 교훈을 제시하고자 한다.

4차 산업시대를 맞이하여 많은 공학 분야에서 IoT(Internet of Things)기술의 연계는 매우 중요한 쟁점이다. 최근 조선소에서도 디지털 조선, 스마트 팩토리 등의 개념을 구체화하고 있는 추세이다. 한편 자동차, 비행기 등에서 자율주행을 구현하는 연구는 매우 활발 하고 일정 부분 상용의 형태로 나타나고 있다. 본 연구는 오픈 소스 아두파일럿 기반의 FC(Flight Controller) 및 RTK(Real Time Kinematic) GPS(Global Positioning System)를 이용하여 자율 주행 임무를 수행하는 보트의 주행성에 관한 연구로서 잔잔한 호수에서 실해역 실험을 수행하였으며 보트의 임무는 특정한 지점을 자율주행한 후 홈 위치로 스스로 돌아오는 과정에 대한 조종성 평가이다. 주어진 속도에서 기 설정된 임무 궤적과 실 운항 궤적에 따른 차이를 분석하고 시스템의 보트 적용성에 대한 일련의 연구를 수행하였다. 또한 4개의 프로펠러를 가지는 OmniX 선체의 주행성을 분석하였으며 최대 48%의 주행 추적성 향상을 확인하였다.

Due to environmental pollution, regulations on existing petroleum-based fuels are increasing day by day. LNG is in the spotlight as an eco-friendly fuel that does not emit NOx or SOx, but its boiling point is -163°C, so it needs to be handled with care. Materials that can be used at the above temperature are defined by IMO through the IGC Code. Among them, 9% nickel steel has great advantages in yield strength and tensile strength under cryogenic conditions, but it is difficult to use in arc welding such as FCAW for various reasons. This study is a study to apply fiber laser welding to solve this problem. As a previous study, this study conducted a study to find a welding heat source. After performing bead on plate welding, the optimal heat source was derived by analyzing the shape of the bead and adjusting the parameters of the heat source model. In this case, by applying the multi-island genetic algorithm, which is a global optimization algorithm, not the intuition of the researcher, accurate results could be derived in a wide range.