• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.3
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• pp.249-257
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• 2015

A fuel assembly consists of fuel rods composed of pellets (UO2) and a cladding tube (Zircaloy). The role of the fuel rods in the reactor is to generate heat by nuclear fission, as well as to retain fission products during operation. A simulation method using a computer program was used to evaluate the safety of the nuclear fuel rods. This computer program has been called the fuel performance code. In the analysis of a light water reactor fuel rod, the gap conductance, which depended on the distance between the pellets and cladding tube, mainly influenced the thermomechanical behavior of the fuel rod. In this work, a 3D gap element was proposed to simulate the thermo-mechanical behavior of the nuclear fuel rod, considering the gap conductance. To implement the proposed 3D gap element, a 3D thermo-mechanical module was also developed using FORTRAN90. The asymmetric characteristics of the nuclear fuel rod, such as the MPS (missing pellet surface) and eccentricity, were simulated to evaluate the proposed 3D gap element.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.842-848
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• 2022

Parametric studies of heat transfer and fluid flow are very important research of interest because the design and operation of fluid flow and heat transfer systems are guided by these parametric studies. The safety of the system operation and system optimization can be determined by decreasing or increasing particular fluid flow and heat transfer parameter while keeping other parameters constant. The parameters that can be varied in order to determine safe and optimized system include system pressure, mass flow rate, heat flux and coolant inlet temperature among other parameters. The fluid flow and heat transfer systems can also be enhanced by the presence of or without the presence of particular effects including gravity effect among others. The advanced Generation IV reactors to be deployed for large electricity production, have proven to be more thermally efficient (approximately 45% thermal efficiency) than the current light water reactors with a thermal efficiency of approximately 33 ℃. SCWR is one of the Generation IV reactors intended for electricity generation. High Performance Light Water Reactor (HPLWR) is a SCWR type which is under consideration in this study. One-eighth of a proposed fuel assembly design for HPLWR consisting of 7 fuel/rod bundles with 9 coolant sub-channels was the geometry considered in this study to examine the effects of system pressure and mass flow rate on wall and fluid temperatures. Gravity effect on wall and fluid temperatures were also examined on this one-eighth fuel assembly geometry. Computational Fluid Dynamics (CFD) code, STAR-CCM+, was used to obtain the results of the numerical simulations. Based on the parametric analysis carried out, sub-channel 4 performed better in terms of heat transfer because temperatures predicted in sub-channel 9 (corner subchannel) were higher than the ones obtained in sub-channel 4 (central sub-channel). The influence of system mass flow rate, pressure and gravity seem similar in both sub-channels 4 and 9 with temperature distributions higher in sub-channel 9 than in sub-channel 4. In most of the cases considered, temperature distributions (for both fluid and wall) obtained at 25 MPa are higher than those obtained at 23 MPa, temperature distributions obtained at 601.2 kg/h are higher than those obtained at 561.2 kg/h, and temperature distributions obtained without gravity effect are higher than those obtained with gravity effect. The results show that effects of system pressure, mass flowrate and gravity on fluid flow and heat transfer are significant and therefore parametric studies need to be performed to determine safe and optimum operating conditions of fluid flow and heat transfer systems.

• Journal of Radiation Protection and Research
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• v.39 no.1
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• pp.38-45
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• 2014

This paper describes the results of assessment of radiological dose resulting from operation of the Daedeok nuclear facilities including the HANARO research reactor, which has been performed to assure whether or not to comply with the regulation standards of the radioactive effluents releases. Based on the meteorological data and the radiation source term, the maximum individual doses were evaluated from 2010 to 2012. The atmospheric dispersion and the deposition factors of gaseous effluents were calculated using the XOQDOQ computer code. ENDOS-G and ENDOS-L code systems were also used for maximum individual dose calculation from gaseous and liquid effluents, respectively. The results were compared with the regulation standards for the radioactive effluents presented by the Nuclear Safety and Security Commission (NSSC). The effective doses and the thyroid doses of the maximum individual were calculated at the maximum exposed point in the Daedeok site, and contributions of exposure pathways to the radiological doses resulting from gaseous and liquid radioactive effluents were evaluated at each facility of the Daedeok site. As a result, the maximum exposed age was analysed to be the child group, and the operation of HANARO research reactor had a major effect more than 90% on the individual doses. The main exposure pathways for gaseous radioactive effluent were from ingestion and inhalation. The effective doses and the thyroid doses were considerably influenced by tritium and iodine, respectively. The gaseous radioactive effluents contributed more than 90% on the total doses, whereas the contributions of the liquid radioactive effluents were relatively low. Consequently, the maximum individual dose due to radioactive effluents from the nuclear facilities within the Daedeok site were less than 3% of the regulation standard over 3 years; therefore, it can be concluded that radioactive effluents from the nuclear facilities were well managed, with the radiation-induced health detriment for residents around the site being negligible.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.