A tensile test is performed to obtain the mechanical property data of the spent fuel cladding. In general, the elastic modulus, elongation, yield stress, tensile stress, etc. are obtained by axial tensile test of cladding attaching an extensometer. However, due to the limitation in the number of specimens for spent nuclear fuel that can be made, the ring tensile test (RTT) whose required length of the specimen is short is mainly performed. In the case of RTT, an extensometer or strain gauge cannot be attached because the gauge part of the specimen is formed around the cladding and is short. In addition, since a load is applied in the radial direction of the cladding, a curved portion of the circular cladding is spread out and becomes straight, and then the cladding is tensioned. For this reason, it is difficult to obtain the stress-strain curve directly from the RTT results. Isight, which is used to identify the optimization design parameters, was used to build an optimization process that minimizes the difference between the RTT and the analysis to estimate the material property. For this, the elastic modulus, plastic strain, and the radius of the RTT jig were taken as fixed variables. As variables, isotropic hardening data and plastic stress were taken. The objective function was taken as the minimization of the area difference of the load-displacement curve obtained from the tests and analysis, of the difference in the magnitude of the maximum reaction force, and of the difference in the location where the maximum reaction force occurred. Optimization workflow was configured in the following order. First, using the calculator component, plastic stress design variables were created. Next, ABAQUS was placed to perform analysis using design variables, and the reaction force or displacement was calculated. After that, the reaction force was calculated considering the 1/4 symmetry condition using the script component. After that, the data matching component performed quantitative comparison of test and analysis data. Finally, by utilizing the exploration component, the plastic stress design variable that minimizes the difference in the objective function was obtained by automatically changing six optimization algorithms. In this paper, the constructed optimization process and the obtained plastic stress by applying it to the SUS316 RTT results are briefly described. The established optimization process can be utilized to obtain mechanical property from the results of the cladding RTT of spent nuclear fuel or new material.

The buffer is a critical barrier component in an engineered barrier system, and its purpose is to prevent potential radionuclides from leaking out from a damaged canister by filling the void in the repository. No experimental parameters exist that can describe the buffer expansion phenomenon when Kyeongju bentonite, which is a buffer candidate material available in Korea, is exposed to groundwater. As conventional experiments to determine these parameters are time consuming and complicated, simple swelling pressure tests, numerical modeling, and machine learning are used in this study to obtain the parameters required to establish a numerical model that can simulate swelling. Swelling tests conducted using Kyeongju bentonite are emulated using the COMSOL Multiphysics numerical analysis tool. Relationships between the swelling phenomenon and mechanical parameters are determined via an artificial neural network. Subsequently, by inputting the swelling tests results into the network, the values for the mechanical parameters of Kyeongju bentonite are obtained. Sensitivity analysis is performed to identify the influential parameters. Results of the numerical analysis based on the identified mechanical parameters are consistent with the experimental values.

For spent nuclear fuel transferred to dry storage facilities, it is difficult to apply safeguards approaches and long-term integrity verification due to the structural characteristics of the facility. There is a need to check the integrity of the nuclear fuel assembly before transferring it to a dry storage facility and are need to provide information on whether there are any defects. At the Korea Institute of Nuclear Nonproliferation and Control, as a non-destructive testing technology for ensuring Continuity of Knowledge (CoK) of the dry storage facilities, a methodology for reconstructing images by neutron tomographic technique from spent nuclear fuel using a He-4 gas scintillation detector was presented. It is thought that the He-4 gas scintillation detector-based technology can be used to verify the defect of the nuclear fuel assembly. This methodology must be accompanied by accurate neutron measurements. The place where the technique was conducted is surrounded by a concrete wall. Concrete contains water molecules, which can affect neutron measurements. In this study, reconstruction images based on neutron measurements and MCNP simulations are compared to verify the effects of the concrete. Neutron measurements were performed by measuring Cf-252 neutron sources in a 1/10 lab-scale TN- 32 cask with six He-4 gas scintillation detectors as an array. Neutron sources are fixed at each point in the cask, and the He-4 detector array is rotated from 0° to 360° at 10° intervals to reconstruct the image using the filtered back-projection (FBP) method. Also, in MCNP reconstructed images, there are two versions depending on whether concrete wall. The source image and ring shape were found in the measurement-based thermal neutron reconstruction image, which was similar to the simulation image that considering the concrete effects. On the other hand, in the simulation reconstruction image without the concrete, only the shape of the source was found. Thus, the effect of concrete should be considered when performing the neutron tomographic techniques using He-4 gas scintillation detectors.

In this study, a drop analysis of metallic disposal containers for radioactive wastes is performed according to accident scenarios at the disposal site. The weight of the disposal container is about 8 tons, and the ingot-type wastes are loaded in the disposal container. To simulate the floor of the disposal site as the impact target, the reinforced concrete pad is modeled. High impact energy of the disposal container due to their heavy weight and high drop height causes excessive deformation and failure of the concrete target having relatively weak strength. Dynamic growth of cracks due to such failures causes penetration and delamination of concrete. Since the impact force delivered to the container strongly depends on the failure of the concrete pad, it is important to properly simulate the failure of the concrete in the drop analysis. A material erosion method can be used to simulate the concrete failure. In the case of applying erosion based on the finite element method (FEM), the element is deleted when the element exceeds a certain criterion, which causes material and energy loss problem. To solve this problem, mesh-free methods such as smoothed particle hydrodynamics (SPH) can be commonly used, but the mesh-free method has the disadvantage of incurring high numerical cost. Therefore, an adaptive method combining SPH and FEM-based SOLID elements is used for concrete target modeling to simulate excessive deformation and failure of the concrete target. In the adaptive coupling method of SPH and SOLID, the concrete target is first modeled as a solid element. When the damage of concrete exceeds the failure criterion, the solid element is eroded and the SPH element replacing the solid element is activated. Since the activated SPH element continues to participate in the impact, the problem of loss of materials and energy can be effectively solved. In this way, analysis results consistent with actual physical phenomena can be obtained.

Waste that contains or is contaminated with radionuclides arises from a number of activities involving the use of radioactive material. Such activities include the operation and decommissioning of nuclear facilities; the use of radionuclides in medicine, industry, agriculture, research and education. Radioactive waste must be safely disposed in a radioactive waste repository for the protection of public health and the environment. In order to safely dispose of radioactive waste in a repository, it is important to derive an optimal predisposal management scenario because radioactive waste must be processed (i.e. processing (pretreatment, treatment and conditioning), storage and transport) for satisfying waste acceptance criteria (WAC). Optimal scenario of predisposal management of radioactive waste is derived for considering the balancing of exposures of workers and/or those of members of the public, the short term and long term risk implications of different waste management strategies, the technological options available and the costs. However, existing studies for deriving the optimal scenario of predisposal management of radioactive waste have evaluated only the radiation dose of workers and public within given scenarios using fixed value, or have derived optimal single process (i.e. decontamination) of predisposal management using Multi-Attribute Decision Making (MADM) methodology. In this study, optimal predisposal management scenario is derived by evaluating exposures of workers using system dynamics (SD) technique. Radiation dose assessment SD model was modeled using VENSIM® code developed by VENTANA systems Inc.. SD Model has the advantage of being able to respond flexibly when decision makers want to change input data and it has the advantage of being able to track dynamically changing phenomena and visually confirm interdependence. After that, based on the SD model derived from this study, evaluations of exposures of public, cost, and technicality will be added to be utilized when establishing an optimal scenario of predisposal management of radioactive waste considering multi attribute.

Various models have been proposed to describe the swelling behavior of buffer in high level waster repository. One of the most notable models, the Barcelona Basic Model (BBM), is a mechanical model that simulates the behavior of unsaturated ground and is widely applied to soils that undergo large expansion due to water. Among the BBM parameters of Kyeongju bentonite, which is found in Korea, there are no experimental data for parameters that describe the unsaturated state. Such hydromechanical properties should be characterized through experimental programs. However, such experiments are highly complicated and require long periods of time to produce an unsaturated state through different methods according to the suction range. Although there are several studies in which geotechnical parameters were obtained through a back analysis instead of direct experiments, few studies have employed machine learning methods for the identification of geotechnical parameters. In this study, instead of direct experiments, the results of a relatively simple swelling pressure experiment was compared to the numerical analysis results to propose a method of determining some of BBM parameters. Influential factors were identified by a sensitivity analysis and the values of the factors were estimated using an artificial neural network and optimization method. The obtained parameters were applied to the numerical model to estimate the swelling pressure growth, which was subsequently compared to the experimental value. As a result, it was found that there was no significant difference between the two swelling values.

Molten salt immersion technique has been tested with several Sr oxides, SrZrO3, SrMoO4 and U2SrOy, and MgCl2 based molten salts for the Sr nuclide separation. Reaction time, temperature, and salt composition were varied to effectively separate Sr in chloride forms. ICP-OES, XRD, and SEM analysis were conducted for the conversion efficiency and structure and morphology analysis. It is confirmed that all experiments of SrZrO3 with MgCl2 at 800°C for reaction time 5, 10, 20 hours showed higher conversion efficiency than 99% and in LiCl-KCl-MgCl2 and NaCl-MgCl2 molten salts at 500°C or 600°C, conversion efficiency higher than 97% was obtained. SrMoO4 in MgCl2 immersion experiments for 10 hours showed higher conversion efficiency than 99% when the molar ratio of salt/oxide powder is 7. U2SrOy was also tested with MgCl2 molten salt at 800°C and higher efficiency than 99% and mainly MgUO4 were produced as a reaction product.

In this paper, among the W-S-R relationship methods proposed by Lee, et. al., (2020) to produce rain-based rain information in real time, we tried to produce actual rain information by applying machine learning techniques to take into account the effects of wiper operation. To this end, rain sensor proposed the Graded Descent and Threshold Map method for pre-processing the cumulative value of the difference before and after wiper operation by utilizing four sensitive channels for optical sensors developed by Kim Byung-sik (2016) and using rain sensor data produced by five rain conditions in indoor artificial rainfall experiments. This method is the method of producing rainfall information by calculating the average value of the Threshold according to the rainfall conditions and channels, creating a Threshold Map corresponding to the grid 4 (channel) x 5 (thinking of rainfall information) and applying Optima Rainfall Intensity among the big data processing techniques. For the verification of these proposed findings, the application was evaluated by comparing the rainfall observations with the methods presented by Lee, et. al., (2020).

Apophis is a near-Earth object with a diameter of approximately 340 m, which will come closer to the Earth than a geostationary orbit in 2029, offering a unique opportunity for characterizing the object during the upcoming encounter. Therefore, Korea Astronomy and Space Science Institute has a plan to propose a space mission to explore the Apophis asteroid using scientific instruments such as a laser altimeter. In this study, we evaluate the performance metrics of a laser altimeter using a pseudorandom noise modulation technique for the Apophis mission, in terms of detection probability and ranging accuracy. The closed-form expression of detection probability is provided using the cross correlation between the received pulse trains and pseudo-random binary sequence. And the new ranging accuracy model using Gaussian error propagation is also derived by considering the sampling rate. The operation range is significantly limited by thermal noise rather than background noise, owing to not only the low power laser but also the avalanche photodiode in the analog mode operation. However, it is demonstrated from the numerical simulation that the laser altimeter can achieve the ranging performance required for a proximity operation mode, which employs commercially available components onboard CubeSat-scale satellites for optical communications.

In this study, a chlorination technique for recycling Li2ZrO3, a reaction product of ZrO2-assisted rinsing process, was investigated to minimize the generation of secondary radioactive pyroprocessing waste. It was found that the reaction temperature was a key parameter that determined the reaction rate and maximum conversion ratio. In the temperature range of 400−600℃, an increase in the reaction temperature resulted in a profound increase in the reaction rate. Hence, according to the experimental results, a reaction temperature of at least 450℃ was proposed to ensure a Li2ZrO3 conversion ratio that exceeded 80% within 8 h of the reaction time. The activation energy was found to be 102 ± 2 kJ·mol−1·K−1 between 450 and 500℃. The formation of LiCl and ZrO2 as reaction products was confirmed by X-ray diffraction analysis. The experimental results obtained at various total flow rates revealed that the overall reaction rate depends on the Cl2 mass transfer rate in the experimental condition. The results of this study prove that the chlorination technique provides a solution to minimize the amount of radioactive waste generated during the ZrO2-assisted rinsing process.

학교소속감이 중도탈락을 막을 수 있는 중요한 변수임에도 불구하고 특히 고등학교 학생에 대한 학교소속감 연구는 그 수가 많지 않다. 아직 충분한 연구가 이루어지지 않은 분야에서 기계학습 기법을 활용하는 탐색적 연구가 학문적 기여를 할 수 있다. 본 연구의 주요 목적은 일반고 및 특성화고 학생들의 학교소속감을 예측하는 중요한 변수를 파악하는 것이다. 이를 위하여 부산교육종단 연구 2016 4차년도 데이터의 일반고와 특성화고 학생, 교사, 교장, 학교 변수를 모두 활용하였다. 구체적으로 75개 일반고 1,775명의 824개 변수 자료와 36개 특성화고 739명의 854개 변수 자료를 기계학습 기법으로 분석한 결과, 일반고와 특성화고에서 각각 20개와 21개의 학생, 교사, 학교 관련 변수가 선택되었다. 학교소속감을 개인의 심리적 차원에 초점을 맞추어 분석한 선행연구와 달리, 본 연구는 교사, 교장, 학교 변수까지 모두 모형에 투입함으로써 학교 현장에서의 변화를 꾀하였다. 기계학습 기법 중 벌점회귀모형으로 분류되는 glmmLasso를 활용하여 변수 선택 시 자료의 위계적 구조를 반영한 점 또한 연구 의의라 하겠다. 특히 특성화고 자료는 사례 수보다 변수 수가 더 많은 고차원 자료였으므로 기계학습 기법을 활용하는 것이 필수적이었다. 연구 결과를 토대로 고등학생의 학교소속감을 향상시키기 위하여 필요한 정책적 제언을 제시하고, 후속 연구주제 또한 논하였다.

2019년 초연된 최우정의 오페라 ≪1945≫는 한국 창작오페라 70년사에서 유의미한 발자취를 남긴 작품으로 평가된다. 그 바탕에는 물론 한국어로 된, 한국인의 삶과 사회가 녹아 있는 대본의 힘이 깔려있으며, 이는 관객들의 공감을 사고 보편성을 획득하게 하였다. 그러나 오페라 장르의 특성상, 무엇보다 중요한 것은 ‘음악’이다. 본 논문은 작곡가 최우정의 오페라 작곡기법을 라이트 모티브의 활용, 극적 요소를 연출하는 음악, 인용 기법과 작곡 방식의 세 가지 범주로 나누어 살펴보았다. 결과적으로, 최우정의 오페라 ≪1945≫는 ‘파편적’으로 존재하는 여러 음악재료들이 서로 유동적인 ‘절합’의 관계를 맺고 있고 수직⋅수평적 측면에서 대위적으로 직조되는 ‘다성부적 방식’으로 작곡되었음을 밝혔다.