A force-free field (FFF) is determined solely by the normal components of magnetic field and current density on the entire boundary of the domain. Methods employing three components of magnetic field suffer from overspecification of boundary conditions and/or a nonzero divergence-B problem. A vector potential formulation eliminates the latter issue, but introduces difficulties in imposing the normal component of current density at the boundary. This paper proposes four different boundary treatment methods within the vector potential formulation. We conduct a comparative analysis of the vector potential FFF solvers that we have developed incorporating these methods against other FFF codes in different magnetic field representations. Although the vector potential solvers with the new boundary treatments do not outperform our poloidal-toroidal formulation code, they demonstrate comparable or superior performance compared to the optimization code in SolarSoftWare. The methods developed here are expected to be readily applied not only to force-free field computations but also to time-dependent data-driven simulations.

EU taxonomy requires to solve problems for safe management of radioactive waste and disposal of spent fuel, which is a precondition for growing demand for nuclear power plant. Currently, Korea manages about 18,000 tons of high-level radioactive waste at temporary storage facilities in nuclear power plant sites, but such temporary storage facilities are expected to become saturated sequentially from 2031. Therefore, it is necessary to secure a permanent disposal facility to safely treat high-level radioactive waste. In accordance with the second basic plan for high-level radioactive waste management in 2021, it is necessary to establish requirements for regulatory compliance for the site selection and site acquisition, investigation and evaluation, and construction for the establishment of a deep geological disposal facility. In this study, we analyzed the regulatory policies and cases of leading foreign countries related to deep geological disposal facilities for high-level radioactive waste disposal waste such as IAEA, USA, Sweden, and Finland using data analysis methodology. To analyze a large amount of textbased document data, text mining is applied as a major technology and a verification standard that secures validity and safety based on the regulatory laws described so far is developed to establish a regulatory base suitable for domestic deep geological disposal status. Based on the collected data, preprocessing and analysis with Python were performed. Keywords and their frequency were extracted from the data through keyword analysis. Through the measured frequency values, the contents of the objects and elements to be regulated in the statutory items were grasped. And through the frequency values of words co-occurring among different sections through the analysis of related words, the association was obtained, and the overall interpretation of the data was performed. The results of analyzing regulations of major foreign countries using text mining are visualized in charts and graphs. Word cloud can intuitively grasp the contents by extracting the main keywords of the contents of the regulations. Through the network connection graph, the relationship between related words can be visually structured to interpret data and identify the causal relationship between words. Based on the result data, it is possible to compare and analyze the factors to be supplemented by analyzing domestic nuclear safety case and regulations.

The growth characteristics according to temperature conditions were investigated in the breeding room of the Sericulture & Entomology Experiment Station for Oriental garden crickets(Teleogryllus emma Ohmachi et Matsuura) and Modeagali-crickests(Loxoblemmus doenitzi Stein) collected from the lawns of Byeonsan-myeon, Buan-gun, Jeollabuk-do. The temperature conditions were 6 treatments from 15°C to 40°C at 5°C intervals using a multi-incubator, and the development period and mortality rate by age were compared using the 28°C breeding room conditions as a control. For T. emma, the higher the temperature, the shorter the total development period was, and the same trend was observed for the growth period by age stage. However, at low temperatures of 15°C and 20°C, all died after the third instar, and at high temperatures above 35°C, all died during development. At 25°C and 30°C, they developed normally, and the mortality rate was about 25%. The L. doenizi had the same tendency as the T. emma, with the higher the temperature, the shorter the development period. The total development period was 57.7 days at 25°C, which was similar to the T. emma's 55.9 days, and the mortality rate was the lowest at 44% at 25°C.

Silene fissipetala Turcz., which is native to Continental China and Taiwan, was newly found in Chungcheongnam-do, Korea. S. fissipetala is similar to the related taxa S. antirrhina L., S. armeria L., and S. koreana Kom. in that it has glutinous zones. However, S. fissipetala is distinguished from the congeneric species by the presence of laciniate at the petals. The species grows on slopes and roadsides, suggesting that it is likely to have been introduced through the installation of green sites and road construction. A precise description, photographs, voucher specimens and a key to related taxa are provided.

Tritium is a radioactive isotope of hydrogen with a half-life of about 12.3 years, and it is commonly found in the environment as a result of the production of Nuclear Power Plants. The World Health Organization (WHO) has established guidelines for the permissible levels of tritium in drinking water. The guideline value for tritium in drinking water is 10,000 Bq/L. It is important to note that the guideline value for tritium is not a legal limit, but rather a recommendation. National and local authorities may establish legal limits that are more restrictive than the WHO guideline value based on local conditions and risk assessments. The Australia and Finland have set a limit for tritium in drinking water at 76,103 Bq/L and 30,000 Bq/L respectively, which is more than three to seven times higher compare to guideline value of WHO. The United States Environmental Protection Agency (EPA) has set a maximum contaminant level (MCL) for tritium in drinking water at 20,000 picocuries per liter (pCi/L), which is equivalent to 740 Bq/L. The Health Canada has set a guideline value for tritium in drinking water at 7,000 Bq/L. Assuming drinking water corresponding to each tritium limit (or guideline value) for one year, the expected exposure dose is 0.01 mSv to 1 mSv. It means that the tritium in drinking water below the limits or guideline value does not pose a significant risk to human health.

Natural uranium-contaminated soil in Korea Atomic Energy Research Institute (KAERI) was generated by decommissioning of the natural uranium conversion facility in 2010. Some of the contaminated soil was expected to be clearance level, however the disposal cost burden is increasing because it is not classified in advance. In this study, pre-classification method is presented according to the ratio of naturally occurring radioactive material (NORM) and contaminated uranium in the soil. To verify the validity of the method, the verification of the uranium radioactivity concentration estimation method through γ-ray analysis results corrected by self-absorption using MCNP6.2, and the validity of the pre-classification method according to the net peak area ratio were evaluated. Estimating concentration for 238U and 235U with γ-ray analysis using HPGe (GC3018) and MCNP6.2 was verified by 􀟙-spectrometry. The analysis results of different methods were within the deviation range. Clearance screening factors (CSFs) were derived through MCNP6.2, and net peak area ratio were calculated at 295.21 keV, 351.92 keV(214Pb), 609.31 keV, 1120.28 keV, 1764.49 keV(214Bi) of to the 92.59 keV. CSFs for contaminated soil and natural soil were compared with U/Pb ratio. CSFs and radioactivity concentrations were measured, and the deviation from the 60 minute measurement results was compared in natural soil. Pre-classification is possible using by CSFs measured for more than 5 minutes to the average concentration of 214Pb or 214Bi in contaminated soil. In this study, the pre-classification method of clearance determination in contaminated soil was evaluated, and it was relatively accurate in a shorter measurement time than the method using the concentrations. This method is expected to be used as a simple pre-classification method through additional research.

Since high-level radioactive wastes contain long-lived nuclides and emit high energy, they should be disposed of permanently through a deep geological disposal system. In Korea, the first (2016.07) and the second (2021.12) basic plans for the management of high-level disposal systems were proposed to select sites for deep geological disposal facilities and to implement business strategies. Leading countries such as Finland, Sweden and France have developed and applied safety cases to verify the safety of deep geological disposal systems. By examining the regulatory status of foreign leading countries, we analyze the safety cases ranging from the site selection stage of the deep geological disposal system to the securing of the permanent disposal system to the investigation, analysis, evaluation, design, construction, operation, and closure. Based on this analysis, we will develop safety case elements for long-term safety of deep geological disposal systems suitable for domestic situation. To systemically analyze data based on safety cases, we have established a database of deep geological disposal system regulations in leading foreign countries. Artificial intelligence text mining and data visualization techniques are used to provide database in dashboard form rather than simple lists of data items, which is a limitation of existing methods. This allows regulatory developers to understand information more quickly and intuitively and provide a convenient interface so that anyone can easily access the analyzed data and create meaningful information. Furthermore, based on the accumulated bigdata, the artificial intelligence learns and analyzes the information in the database through deep learning, and aims to derive a more accurate safety case. Based on these technologies, this study analyzed the legal systems, regulatory standards, and cases of major international leading countries and international organizations such as the United States, Sweden, Finland, Canada, Switzerland, and the IAEA to establish a database management system. To establish a safety regulation base suitable for the domestic deep geological disposal environment, the database is provided as data to refer to and apply systematic information management on regulatory standards and regulatory cases of overseas leading countries, and it is expected that it will play a key role as a forum for understanding and discussing the level of safety of deep geological disposal system among stakeholders.

The development of Features, Events, and Processes (FEPs) and scenarios, which consider the longterm evolution of repository, is underway, along with the construction of input data and a model database for the adaptive process-based total system performance assessment framework, APro. PAPiRUS serves as an integrated information processing platform, enabling users to seamlessly access, search, and extract essential information. To enhance data usability, it is crucial to establish well-structured metadata for each dataset. Regarding FEPs, individual FEPs consist of extensive text-based data and sets of other short textual data. To enhance the searchability of these FEPs, precise keywords must be assigned to each FEP. For user convenience, the PAPiRUS FEP database contains several FEPs not only the long-term evolution FEPs developed by KAERI but also thousands of FEPs form the databases such as NEA PFEPs and Posiva FEPs. Generating keywords for thousands of FEPs proves to be a labor-intensive task. Consequently, this study explores natural language processing techniques for keyword analysis to boost the productivity of the keyword generation process. Specifically, we employ Generative Pretrained Transformer (GPT) models for keyword extraction. Our test results for keyword extraction demonstrate that, although not flawless, providing suitable prompts yields sufficiently useful keyword sets. We identified several optimal prompts and developed an Excel-based program to derive keywords from the existing FEP database using these prompts. By using the outcomes of this study, initial versions of keyword sets for thousands of FEPs can be rapidly produced and subsequently refined through expert review and editing. The generated keywords will serve as metadata within PAPiRUS.

CANDU Spent Fuel (CSF) dry storage system, SILO, has been operated from 1992 at Wolsung under 50 year operating license. As of 2023, this system has been operated for over 30 years and its licensed remaining operation time is less than 20 years. When it faces the final stage of operation, it has only two options; moving to a centralized away-from-reactor storage or extending its license atreactor. These two options have an inevitable common duty of confirming the CSF integrity by a “demonstration test”. Since the degradation of CSF and structural materials in the SILO are critically dependent on temperature, two important goals of the ‘DEMO test’ were set as follows. 1. Design of ‘DEMO SILO’: Development of internal monitoring technology by transforming SILO design. 2. Accurate measurement and evaluation of the three-dimensional temperature distribution in the ‘DEMO SILO’ Based on operating real commercial SILO dimension, a conceptual “DEMO SILO” design has been developed from 2022. Because, unlike with commercial Silo, ‘Demo Silo’ must be disassembled and assembled, and have penetration holes. Safety evaluation technologies like structural, thermal and radiation protection analysis also have been developed with design work. ‘Demo SILO’ should evaluate an accurate 3D temperature distribution with minimal number of thermocouples and penetration holes to avoid disruption of internal flow and temperature distribution. For this reason, a ‘Best Estimate Thermal-Hydraulics evaluation system for SILO’ is under development and it will be essential for ensuring temperature prediction accuracy. Construction of a full-scale test apparatus to validate this technology will begin in 2024. In order to supply power to many heaters and monitor temperature gradient inside of this apparatus, it has modular design concept by dividing its whole body to axial 9 sub-bodies which looks like a donut containing a basket at center position.

Micro-electronic gas sensor devices were developed for the detection of carbon monoxide (CO), nitrogen oxides (NOx), ammonia (NH3), and formaldehyde (HCHO), as well as binary mixed-gas systems. Four gas sensing materials for different target gases, Pd-SnO2 for CO, In2O3 for NOx, Ru-WO3 for NH3, and SnO2-ZnO for HCHO, were synthesized using a sol-gel method, and sensor devices were then fabricated using a micro sensor platform. The gas sensing behavior and sensor response to the gas mixture were examined for six mixed gas systems using the experimental data in MEMS gas sensor arrays in sole gases and their mixtures. The gas sensing behavior with the mixed gas system suggests that specific adsorption and selective activation of the adsorption sites might occur in gas mixtures, and allow selectivity for the adsorption of a particular gas. The careful pattern recognition of sensing data obtained by the sensor array made it possible to distinguish a gas species from a gas mixture and to measure its concentration.

Recently, the development of computer vision with deep learning has made object detection using images applicable to diverse fields, such as medical care, manufacturing, and transportation. The manufacturing industry is saving time and money by applying computer vision technology to detect defects or issues that may occur during the manufacturing and inspection process. Annotations of collected images and their location information are required for computer vision technology. However, manually labeling large amounts of images is time-consuming, expensive, and can vary among workers, which may affect annotation quality and cause inaccurate performance. This paper proposes a process that can automatically collect annotations and location information for images using eXplainable AI, without manual annotation. If applied to the manufacturing industry, this process is thought to save the time and cost required for image annotation collection and collect relatively high-quality annotation information.

Fermentation by Rhizopus spp. has been used as a traditional medicine for treating various inflammatory diseases. Allergic asthma is a chronic respiratory disease that is caused by an exaggerated immune response. This study was conducted to ascertain the anti-inflammatory effects of Rhizopus spp. fermentation extract (RU) on a mouse model of ovalbumin (OVA)-induced asthma. The animals were intraperitoneally injected OVA on day 1 and 7, followed by OVA intranasal inhalation on days 14 to 18. The animals were treated daily with RU (100 and 200 mg/kg) by oral gavage from day 18 to day 23. RU significantly decreased eosinophilia and the production of inflammatory cytokines and OVA specific immunoglobulin E in animals with asthma, along with reducing airway inflammation and mucus secretion in lung tissue. Histological changes in the lungs and levels of inflammatory mediators of allergic airway inflammation were evaluated. The regulatory effects of RU on type 2 helper T (Th2) cell activation were investigated. RU administration attenuated asthmatic changes such as inflammatory cell infiltration and mucus production, decreased the levels of Th2-related cytokines, and reduced Th2 cell activation. Administration of RU effectively reduced allergic responses in asthmatic mice, which is associated with regulating Th2 cell activation and differentiation. These results indicate that RU can attenuate the respiratory symptoms of asthma.