With a strive to develop light-weight material for automotive and aerospace applications, aluminum-based hybrid nanocomposites (AHNCs) were manufactured utilizing the compocasting approach in this study. Chopped carbon fibers (CFs) are reinforced along with different weight fractions of nanoclay (1–5%) in the matrix of AA6026 forming AHNCs. The AHNCs specimens were examined by microstructural analysis, mechanical characterization, fatigue, and corrosion strength as per ASTM guidelines. Electroless plating method is adopted for coating CFs with copper to improve the wettability with matrix. SEM pictures of manufactured composites reveal thin inter-dendritic aluminum grains with precipitate particle of eutectic at intergranular junctions, as well as nanoclay particles that have precipitated in the matrix. Tensile strength (TS) rises with inclusion of nanoclay up to a maximum of 212.46 MPa for 3% nanoclay reinforcement, after which the TS is reduced due to non-homogeneity in distribution, agglomeration and de-bonding of nanoparticles. Similarly, micro-hardness increases with addition of 3% nanoclay after which it decreases. Higher energy absorption was achieved with 3% nanoclay reinforced hybrid and a significant improvement in flexural strength was obtained. With addition of both CFs and nanoclay, the fatigue strength of the hybrid composite tends to increase due to flexible CFs and high surface area nanoclays which strengthen the grain boundaries until 3% addition. Addition of nanoclay lowers the corrosion rate with nanoclays filling the crevices and voids in the matrix.

KAERI has been developing a new decontamination process that does not contain any organic chemicals in the decontamination solution and minimizes the use of ion exchange resin in the solution as a purifying step. The process is hydrazine based reductive metal ion decontamination for decommissioning (HyBRID) and consists of N2H4, H2SO4 and Cu+ ions. The primary system of the LWR is composed of materials with high corrosion resistance, such as stainless steel and Inconel, but among the materials, the feeder and header of the primary system of the PHWR are composed of carbon steel (SA106Gr.B) with low corrosion resistance. Therefore, when decontamination of PHWRs, attention should be paid to corrosion of carbon steel. Since Fe3O4, a contaminating oxide film formed on the surface of carbon steel dissolves faster than ferrite or chromite formed on the surface of Inconel or stainless steel, the base material is exposed to the solution and is corroded during decontamination. When a large amount of iron ions is eluted into the decontamination agent due to corrosion of carbon steel, not only the soundness of the base metal is adversely affected, but also the amount of decontamination waste increases. The purpose of this study is to develop inhibitors that can minimize corrosion of carbon steel when decontamination of PHWRs using the HyBRID decontamination process. CG, 570S and PP3 were selected as corrosion inhibitors. In addition, corrosion tests of carbon steel were conducted in the HyBRID solution with corrosion inhibitors. The best corrosion inhibitors and optimal operating conditions were selected, and HyBRID decontamination agents with corrosion inhibitors were much better in corrosion resistance than existing commercial decontamination agents.

To conduct numerical simulation of a disposal repository of the spent nuclear fuel, it is necessary to numerically simulate the entire domain, which is composed on numerous finite elements, for at least several tens of thousands of years. This approach presents a significant computational challenge, as obtaining solutions through the numerical simulation for entire domain is not a straightforward task. To overcome this challenge, this study presents the process of producing the training data set required for developing the machine learning based hybrid solver. The hybrid solver is designed to correct results of the numerical simulation composed of coarse elements to the finer elements which derive more accurate and precise results. When the machine learning based hybrid solver is used, it is expected to have a computational efficiency more than 10 times higher than the numerical simulation composed of fine elements with similar accuracy. This study aims to investigate the usefulness of generating the training data set required for the development of the hybrid solver for disposal repository. The development of the hybrid solver will provide a more efficient and effective approach for analyzing disposal repository, which will be of great importance for ensuring the safe and effective disposal of the spent nuclear fuel.

To obtain a license for a deep geological disposal repository for spent nuclear fuel, it is necessary to perform a safety assessment that quantifies the radiological impact on the environment and humans. One of the key steps in the safety assessment of a deep geological repository is the development of scenarios that describe how the repository evolves over the performance period and how events and processes affect performance. In the field of scenario development, demonstrating comprehensiveness is critical, which describes whether all factors that are expected to have a significant impact on the repository's performance have been considered. Mathematical proof of this is impossible. However, If the scenario development process is logical and systematic, it can support the claim that the scenario is comprehensive. Three primary approaches are being considered for scenario development: ‘Bottomup’, ‘Top-down’, and ‘Hybrid’. Hybrid approach provides a more systematic and structured process by considering both the FEPs (Features, Events, Processes) and safety functions utilized in the bottomup and top-down approaches. Many countries that develop recent scenarios prefer demonstrating scenario comprehensiveness using a hybrid approach. In this study, a systematic and structured scenario development process of a hybrid approach was formulated. Based on this, sub-scenarios were extracted that describe the phenomena occurring in the repository over the performance period, categorized by period. By integrating and screening the extracted sub-scenarios, a scenario describing the phenomena occurring over the entire period of disposal was developed.

국내외 매년 지속적으로 증가하는 대기오염의 상당량이 선박에서 배출되고 있으며, 이러한 선박에서의 배출량을 감축하기 위 해 정부는 환경규제를 강화하고 해양대기환경 개선을 위해 「환경친화적 선박의 개발 및 보급 촉진에 관한 법률」을 제정 및 시행하여 친환경 에너지를 동력원으로 사용하는 환경친화적 선박을 보급하여 해양오염 저감 기술이 개발되도록 하고 있다. 환경친화적 선박의 기 술은 최근 순수 전기추진 내지는 전기복합 추진체계까지 진화하고 있으나, 선박의 안전한 운용을 위한 검사 및 설비기준 등 관련제도의 정비는 이를 못 따라가는 실정으로, 특히 국내 연안선박의 다수를 차지하는 어선에 대한 제도는 정비가 시급한 시점이다. 이번 연구를 통 해 어선에의 전기복합 추진체계 등의 적용을 위해 핵심기자재인 배터리, 전력변환장치 등을 정의하고 이에 필요한 안전기준을 진단, 마련 하여 친환경 어선의 도입과 보급을 위해 관련된 산업을 지원할 수 있도록 최소한의 안전기준안을 마련하고자 한다.

세계적으로 온실가스 및 대기 오염물질 배출 저감을 위한 환경 규제가 점점 강화되고 있는 가운데, 국내에서도 ‘2030 친환경 관공선 전환 계획’을 수립하여 선박의 온실가스 배출량 저감 기술 개발과 친환경 소형 연안선박 건조 및 실증 사업을 추진하고 있다. 이에 따라 본 연구에서는 연안 선박의 전기복합 추진을 위한 핵심 기자재인 기어박스의 설계에 대한 연구를 수행하였다. ROMAX 소프트웨어를 활용하여 전동기 구동, 엔진 구동, 엔진 구동 발전 등 다양한 운전 모드에서 기어의 강도와 치물림 상태를 확인하고, 치형 수정 최적화를 수행하였다. 또한 위상 최적화 기법을 이용하여 기어박스 하우징의 경량화 및 최적화를 수행하였다.

This experiment was conducted to confirm the possibility of preparing Sorghum×sudangrass hybrid artificial hay using far-infrared rays in Korea. The machine used in this experiment is a drying device based on far-infrared rays, and is designed to control temperature, air flow rate, far-infrared radiation amount, and air flow speed. The Sorghum×sudangrass hybrids harvested in late September were wilted in the field for one day, and a drying test was performed on them. Conditions for drying were performed by selecting a total of 7 conditions, and each condition induced a change in radiation amount in a single condition (42%) and two steps (4 treatments) and three steps (2 treatments). The speed of the air flow in the device was fixed at 60 m/s, and the run time was changed to 30, 60, and 90 minutes. The average dry matter (DM) content was 82.84%. The DM content was 59.94 and 76.91%, respectively, in drying conditions 1 and 3, which were not suitable for hay. In terms of drying rate, it was significantly higher than 80% in the 5, 6 and 7 treatment, and power consumption was slightly high with an average of 5.7 kw/h. As for the feed value according to each drying condition, the crude protein (CP) content increased as the drying time increased, and there was no significant difference between treatments in ADF, NDF, IVDMD and TDN content. In terms of RFV, treatment 1, which is a single condition, was significantly lower than the complex condition. Through the above results, it was determined that the drying conditions 4 and 5 were the most advantageous when considering the drying speed, power consumption, and quality.

A bending experiment was conducted to verify the structural performance of the U-flange truss hybrid bean using rebars or steel pipes to reinforce the upper compression zone. As a result of evaluating the bending strength of the truss hybrid beam according to the Structural Design Standard (KDS 14 2020: 2022) by introducing the lattice member as a tensile resistance element, the following conclusions were obtained. Considering the lattice element as a tensile resistance element, the nominal bending strength was increased by 38.57 to 47.90 kN.m. As a result of reviewing the experiment as to whether the flexural member has proper ductility, it was found that it is desirable to place appropriate rebars, steel quality plans, and lateral restraints on the upper and lower parts of the hybrid beam to have sufficient ductility ratio.