The need for the development of sustainable, efficient, and green radioactive waste disposal methods is emerging with the saturation of spent nuclear waste storage facilities in the Republic of Korea. Conventional radioactive waste management methods like using cement or glass have drawbacks such as high porosity, less chemical stability, high energy consumption, carbon dioxide production, and the generation of secondary wastes, etc. To address this gigantic issue of the planet, we have designed a study to explore the potential of alternative materials having easy processability, low carbon emissions and more chemical stability such as ceramic (hydroxyapatite, HAP) and alkali-activated materials (geopolymers, GP) to capture the simulated radioactive cobalt ions from the contaminated water and directly solidify them at low temperatures. Physical and mechanical properties of HAP alone and 15wt% GP incorporated HAP (HAP-GP- 15) composite were studied and compared. The surface of both materials was fully sorbed with an excess amount of Co(II) ions in the aqueous system. Co(II) sorbed powders were separated from aqueous media using a centrifuge machine operating at 5,000 RPM for 10 minutes and dried at 100°C for 8 hours. The dried powders were then placed in stainless steel molds, and shaped into cylindrical pellets using a uniaxial press at a pressure of 1 metric ton for 1 minute. The pellets were sintered at 1,100°C for 2 hours at a heating rate of 10°C/min. Following this, the water absorption, density, porosity, and compressive strength of the polished pellets were measured using standard methods. Results showed that HAP has a greater potential for decontamination and solidification of Co(II) due to its higher density (2.65 g/cm3 > 1.90 g/cm3), less open porosity (16.2±2.9% < 42.4 ±0.9%) and high compressive strength (82.1±10.2 MPa > 6.9±0.8 MPa) values at 1,100°C compared to that of HAP-GP-15. Nevertheless, further study with different constituent ratio of HAP and GP at various temperatures is required to fully optimize the HAP-GP matrix for waste solidifications.

A comprehensive understanding of actinide coordination chemistry and its structure is essential in many aspects of the nuclear fuel cycle, such as fuel reprocessing, waste management, reactor safety, and non-proliferation efforts. Managing radioactive waste generated during the nuclear fuel cycle has recently become more important, accordingly increasing the importance of designing appropriate waste forms and storage solutions for long-term waste disposal. Compared to the increase in the need for understanding the chemistry of major radioactive elements, the information on the local structure of the radioactive elements, especially actinides, remains unknown. To probe this issue, X-ray absorption fine structure (XAFS) can be applied. By analyzing the EXAFS (extended X-ray absorption fine structure) and XANES (X-ray absorption near edge structure), the local structure around atoms can be determined. However, the radioactive properties of the nuclides hindered the measurement of EXAFS and XANES, due to the difficulties of preparation, containment, and transfer of the sample. To measure the EXAFS of various compounds regarding the back-end nuclear fuel cycle, laboratory-based EXAFS (hiXAS, HP spectroscopy) has been introduced which can measure the EXAFS and XANES at the energy range of 5-18 keV. Compounds of Copper (Cu foil, CuO samples), Zirconium (Zr foil), and Europium (Eu2O3) were used for the verification of the laboratory -based EXAFS at a given energy range. The measured EXAFS spectrum of various compounds exhibit good agreement with the theoretical data, showing an R-factor of less than 0.02. It was found that each graph has a first peak corresponding to 2.55Å for Cu foil (Cu-Cu), 1.93Å for CuO samples (Cu-O), 3.23Å for Zr foil (Zr-Zr), and from 2.32Å to 2.34Å for Eu2O3 (Eu-O), which agree well with other values from the literature. From the result, it can be implied that this equipment can be used especially in the back-end nuclear fuel cycle field to enhance the understanding of local structure in radiochemistry.

Molten chloride salts have received considerable research attention as potential nuclear fuel and coolant candidates for molten salt reactors. However, there are several challenges, especially for structural materials due to the selective dissolution of chromium (Cr) in the molten chloride salts environment. Understanding the compatibility of uranium (U), which is used as nuclear fuel in molten salt reactors, with Cr in molten chloride salts is critical for designing the molten salt reactor structure. Therefore, in this study, the cyclic voltammetry (CV) was used to investigate the electrochemical behaviors of U and Cr. The diffusion coefficients and formal potentials were obtained. The electrochemical properties of uranium and chromium were investigated by CV in molten NaCl-MgCl2 salt at 600°C. Tungsten rods for working and counter electrode, and Ag/AgCl for reference electrode were utilized in this experiment. UCl3 made from the chemical dissolution of U rods and CrCl2 (Sigma-Aldrich, 99.99%) were used. Diffusion coefficients (D) of U and Cr were calculated by measuring reduction peak current of U3+/U and Cr2+/Cr from CV curves and using the Berzins-Delahay equation; D (U3+/U) = 3.0×10-5 cm2s-1 and D (Cr2+/Cr) = 3.3×10-5 cm2s-1. The formal potentials were also calculated by using the reduction peak potential obtained from CV results; E0’ (U3+/U) = -1.173 V and E0’ (Cr2+/Cr) = -0.321 V. The ionization tendency was investigated by comparing each reduction peak potential. The reduction peak potential Ep,c was increasing order of Ep,c (U3+/U) < Ep,c (Cr2+/Cr) < Ep,c (U4+/U3+). It can be seen that in the presence of U4+ and Cr metals, the Cr in the alloy can dissolve into Cr2+, but in the presence of U3+ and Cr metals, the Cr in the alloy does not dissolve into Cr2+. By analyzing the CV curve, diffusion coefficients and formal standard potentials were obtained. The result of comparing reduction peak potentials suggests that the nuclear fuel using U4+ should be inhibited to prevent the selective dissolution of Cr.

The ultimate objective of deep geological repositories is to achieve complete segregation of hazardous radioactive waste from the biosphere. Thus, given the possibility of leaks in the distant future, it is crucial to evaluate the capability of clay minerals to fulfill their promising role as both engineered and natural barriers. Selenium-79, a long-lived fission product originating from uranium- 235, holds significant importance due to its high mobility resulting from the predominant anionic form of selenium. To investigate the retardation behaviors of Se(IV) in clay media by sorption, a series of batch sorption experiments were conducted. The batch samples consisted of Se(IV) ions dissolved in 0.1 M NaCl solutions, along with clay minerals including kaolinite, montmorillonite, and illite-smectite mixed layers. The pH of the samples was also varied, reflecting the shift in the predominant selenium species from selenious acid to selenite ion as the environment can shift from slightly acidic to alkaline conditions. This alteration in pH concurrently promotes the competition of hydroxide ions for Se(IV) sorption on the mineral surface as the pH increases and impedes the selective attachment of selenium. The acquired experimental data were fitted through Langmuir and Freundlich sorption isotherms. From the Freundlich fit data, the distribution coefficient values of Se(IV) for kaolinite, montmorillonite, and illite-smectite mixed layer were derived, which exhibited a clear decrease from 91, 110, 62 L/kg at a pH of 3.2 to 16, 6.3, 12 L/kg at a pH of 7.5, respectively. These values derived over the pH range provide quantitative guidance essential for the safety assessment of clay mineral barriers, contributing to a more informed site selection process for deep geological repositories.

This program aims to build a specialized and converged educational platform for the training of students in the back-end nuclear fuel cycle and cultivate integrated human resources encompassing majors, generations, and fields. To achieve this, we have established an infrastructure for integrated education and training in the radiochemistry and back-end nuclear fuel cycle and operated specialized educational courses linked with special lectures, experimental practices, and field trips. Firstly, to construct an integrated educational and training infrastructure for the back-end nuclear fuel cycle, we formed a committee of experts from both inside and outside the institution and built an advanced radiochemistry laboratory equipped with physical and chemical analysis instruments. Through a comprehensive educational program involving theory, experiments, and discussions, we have established an integrated curriculum across adjacent majors and interdisciplinary studies. We also operate short-term education and experimental training programs (e.g., summer and winter schools for the back-end nuclear fuel cycle). Secondly, the program has connected leading researchers domestically and internationally, as well as the next generation of scholars. The program offers long-term educational opportunities and internships targeting both undergraduate and graduate students. To support this, we continuously offer expert colloquiums and individual research internships. Through regular committee meetings and workshops, we focus on nurturing the integrated talents necessary for the back-end nuclear fuel cycle. Through this program, students from various fields are being trained as competent integrated human resources capable of addressing various issues in the back-end nuclear fuel cycle. It is expected that this will enable us to supply specialized technical personnel in the back-end nuclear field in line with mid-to-long-term demands.

In the nuclear fuel cycle (NFC) facilities, the failure of Heating Ventilation and Air Conditioning (HVAC) system starts with minor component failures and can escalate to affecting the entire system, ultimately resulting in radiological consequences to workers. In the field of air-conditioning and refrigerating engineering, the fault detection and diagnosis (FDD) of HVAC systems have been studied since faults occurring in improper routine operations and poor preventive maintenance of HVAC systems result in excessive energy consumption. This paper aims to provide a systematic review of existing FDD methods for HVAC systems therefore explore its potential application in nuclear field. For this goal, typical faults and FDD methods are investigated. The commonly occurring faults of HVAC are identified through various literature including publications from International Energy Agency (IEA) and American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE). However, most literature does not explicitly addresses anomalies related to pressure, even though in nuclear facilities, abnormal pressure condition need to be carefully managed, particularly for maintaining radiological contamination differently within each zone. To build simulation model for FDD, the whole-building energy system modeling is needed because HVAC systems are major contributors to the whole building’s energy and thermal comfort, keeping the desired environment for occupants and other purposes. The whole-building energy modeling can be grouped into three categories: physics-based modeling (i.e., white-box models), hybrid modeling (i.e., grey-box models), and data-driven modeling (i.e., black-box models). To create a white-box FDD model, specialized tools such as EnergyPlus for modeling can be used. The EnergyPlus is open source program developed by US-DOE, and features heat balance calculation, enabling the dynamic simulation in transient state by heat balance calculation. The physics based modeling has the advantage of explaining clear cause-and-effect relationships between inputs and outputs based on heat and mass transfer equations, while creating accurate models requires time and effort. Creating a black-box FDD model requires a sufficient quantity and diverse types of operational data for machine learning. Since operation data for HVAC systems in existing nuclear cycle facilities are not fully available, so efforts to establish a monitoring system enabling the collection, storage, and management of sensor data indicating the status of HVAC systems and buildings should be prioritized. Once operational data are available, well-known machine learning methods such as linear regression, support vector machines, random forests, artificial neural networks, and recurrent neural networks (RNNs) can be used to classify and diagnose failures. The challenge with black-box models is the lack of access to failure data from operating facilities. To address this, one can consider developing black-box models using reference failure data provided by IEA or ASHRAE. Given the unavailability of operation data from the operating NFC facilities, there is a need for a short to medium-term plan for the development of a physics-based FDD model. Additionally, the development of a monitoring system to gather useful operation data is essential, which could serve both as a means to validate the physics-based model and as a potential foundation for building data-driven model in the long term.

As the demand for nuclear power increases as a means to achieve carbon neutrality, concerns about nuclear proliferation have also grown. Consequently, significant researches have conducted to enhance nuclear non-proliferation resistance. Among these research, nuclear material attractiveness is a methodology used to evaluate how appealing a particular material is for potential use in nuclear weapons, based on the characteristics of that material. Existing nuclear material attractiveness assessments focused on materials like U, Pu, and TRU, which could be directly used in the production of nuclear weapons. However, these assessments did not consider how the properties of nuclear materials change throughout the nuclear fuel cycle, with each facility process. This study assumed a scenario of the nuclear fuel cycle of graphite reduction reactors and analyzed including enrichment facilities and PUREX. This study used the FOM (Figure-Of-Merit) method developed by LANL (Los Alamos National Laboratory) for evaluating the nuclear material attractiveness. The FOM formula consists of three parameters such as critical mass, heat content, and dose The critical mass of targe materials and the dose evaluation were conducted using the Monte Carlo N-Particle code. The heat content was calculated using the ORIGEN code embedded in the Scale code. In particular, if U-238 is dominant in the facility’s materials, such as mining and refining facilities, and critical mass evaluation is unpractical. Therefore, 1SQ (Significant Quantity) of that uranium was assumed as the critical mass value for the FOM evaluation, even though 1SQ is not identical to the critical mass As a result of this study, the attractiveness of Pu produced by PUREX among all nuclear fuel cycle facilities was 2.7616, which was the most attractive to be diverted to nuclear weapons. Through this study, it was shown that the proliferation risk of the nuclear facilities in the nuclear fuel cycle and risk of diversion among those facilities.

This study aims to classify R&D activities related to the nuclear fuel cycle using the deep learning methodology. First, R&D data of the Republic of Korea were collected from the National Science & Technology Information Service (NTIS) for the years 2021, 2022, and 2023. We use keywords such as ‘nuclear,’ ‘uranium,’ ‘plutonium,’ and ‘thorium’ to find nuclear-related R&D projects in the NTIS database. Among the numerous R&D projects found through keyword searches, overlapping and medical-related R&D projects were excluded. Finally, 495 R&D projects conducted in 2021, 430 R&D projects conducted in 2022, and 296 R&D projects conducted in 2023 were obtained for analysis. After that, Safeguards experts determine whether the R&D projects are subject to declaration under the AP. The values of the content validity index (CVI) and content validity ratio (CVR) were used to verify whether the experts’ judgments were valid. The 1,218 collected and labeled data were then divided 8:2 into training and test datasets to see if deep learning could be applied to classify nuclear fuel cycle-related R&D activities. We use the Python and TensorFlow packages, including RNN, GRU, and CNN methods. First, the collected text information was preprocessed to remove punctuation marks and then tokenized to make it suitable for deep learning. After 20 epochs of training to classify the nuclear fuel cycle-related R&D activities, the RNN model achieved 97.30% accuracy and a 5.85% error rate on the validation dataset. The GRU model achieved 96.53% accuracy and a 9.06% error rate on the validation dataset. In comparison, the CNN model achieved 94.61% accuracy and a 2.57% error rate on the validation dataset. When applying the test dataset to each model, the RNN model had a test accuracy of 83.20%, the GRU test accuracy of 82.79%, and the CNN model had a test accuracy of 85.66% for the same dataset. This study applied deep learning models to labeled data judged by various experts, and the CNN model showed the best results. In the future, this study will continue to develop an optimum deep learning model that can classify nuclear fuel cycle-related R&D activities to achieve the purpose of safeguards measures from open-source data such as papers and articles.

The domestic representative nuclear fuel cycle facilities are post-irradiation examination facility (PIEF) and Irradiated Examination Facility (IMEF) at KAERI. They have regularly operated since 1991 and 1993, respectively. Due to the long period of use, the facilities are ageing, and maintenance costs are increasing every year. The maintenance methods have mainly been breakdown maintenance (BM) and partially preventive maintenance (PM). They involve replacing components that have problems through periodic inspections by on-site inspectors. However, these methods are not only uncertain in terms of replacement cycles due to worker’s deviation on the inspection results, but also make it difficult to respond accidents developed through failures on the critical equipment that confines radioactive material. Therefore, an advanced operation and maintenance studied in 2022 through all of nuclear facilities operated at KAERI. Advancement strategy in four categories (safety, sustainability, performance, innovativeness) was analyzed and their priorities according to a facility environment were determined so a roadmap for advanced operation and maintenance could be developed. The safety and sustainability are higher importance than the performance and innovativeness because facilities at KAERI has an emphasis on research and development rather than industrial production. Thus, strategy for advancement has focused even more on strengthening the safety and sustainability. To enhance safety, it has been identified that immediate improvement of aged structures, systems, and components (SSCs) through large-scale replacement is necessary, while consideration of implementing an ageing management program (AMP) in the medium to long term is also required. Facility sustainability requires strengthening operation expertise through training, education, and cultivation of specialized personnel for each system, and addressing outstanding regulatory issues such as approval of radiation environment report on the nuclear fuel processing facilities and improvement work according to fire hazard analysis. One of the safety enhancement methods, AMP, is a new maintenance approach that has not been previously applied, so it had to be thoroughly examined. In this study, an analysis was conducted on the procedure and method for introducing an AMP. An AMP for nuclear fuel cycle facilities was developed by analyzing the AMP applied to the BR2 research reactor in Belgium and modifying it for application to nuclear fuel cycle facilities. The ageing management for BR2 has the objective to maintain safety, availability and cost efficiency and three-step process. The first step is the classification of SSCs into four classes to apply graded approach. Secondly, ageing risk is assessed to identify critical failure modes, their frequency and precursors. Final step involves defining measures to reduce the ageing risk to an acceptable level in order to integrate the physical and economic aspects of ageing into a strategy for inspection, repair, and replacement. Similar approach was applied to the nuclear fuel cycle facility. Firstly, the SSCs of nuclear fuel cycle facilities have been classified according to their safety and quality classifications, as well as whether they are part of the confinement boundary. The SSCs involved in the confinement boundary were given more weight in the classification process, even if they are not classified as safety-class. A risk index for ageing was introduced to determine which prevention and mitigation measure should be chosen. By multiplying the health index and the impact index, the ageing risk matrix provides a numerical score that represents guidance on the prevention and mitigation of ageing effect. The health index is determined by combining the likelihood of failure and engineering evaluation of the current condition of SSCs, whereas the impact index is calculated by taking into account the severity of consequences and the duration of downtime resulting from a failure. This ageing management has to be thoroughly reviewed and modified to suit each facility before being applied to nuclear fuel cycle facilities.

This article examines the consequences of a significant spent fuel management decision or event in the United States, South Korea and Taiwan. For the United States, it is the financial impact of the Department of Energy’s inability to take possession of spent fuel from commercial nuclear power companies beginning in 1998 as directed by Congress. For South Korea, it is the potential financial and socioeconomic impact of the successful construction, licensing and operation of a low and intermediate level waste disposal facility on the siting of a spent fuel/high level waste repository. For Taiwan, it is the operational impact of the Kuosheng 1 reactor running out of space in its spent fuel pool. From these, it draws six broad lessons other countries new to, or preparing for, nuclear energy production might take from these experiences. These include conservative planning, treating the back-end of the fuel cycle holistically and building trust through a step-by-step approach to waste disposal.