• Title/Summary/Keyword: safety net

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High-efficiency deep geological repository system for spent nuclear fuel in Korea with optimized decay heat in a disposal canister and increased thermal limit of bentonite

  • Jongyoul Lee;Kwangil Kim;Inyoung Kim;Heejae Ju;Jongtae Jeong;Changsoo Lee;Jung-Woo Kim;Dongkeun Cho
    • Nuclear Engineering and Technology
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    • v.55 no.4
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    • pp.1540-1554
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    • 2023
  • To use nuclear energy sustainably, spent nuclear fuel, classified as high-level radioactive waste and inevitably discharged after electricity generation by nuclear power plants, must be managed safely and isolated from the human environment. In Korea, the land area is limited and the amount of high-level radioactive waste, including spent nuclear fuels to be disposed, is relatively large. Thus, it is particularly necessary to maximize disposal efficiency. In this study, a high-efficiency deep geological repository concept was developed to enhance disposal efficiency. To this end, design strategies and requirements for a high-efficiency deep geological repository system were established, and engineered barrier modules with a disposal canister for pressurized water reactor (PWR)-type and pressurized heavy water reactor type Canada deuterium uranium (CANDU) plants were developed. Thermal and structural stability assessments were conducted for the repository system; it was confirmed that the system was suitable for the established strategies and requirements. In addition, the results of the nuclear safety assessment showed that the radiological safety of the new system met the Korean safety standards for disposal of high-level radioactive waste in terms of radiological dose. To evaluate disposal efficiency in terms of the disposal area, the layout of the developed disposal areas was assessed in terms of thermal limits. The estimated disposal areas were 2.51 km2 and 1.82 km2 (existing repository system: 4.57 km2) and the excavated host rock volumes were 2.7 Mm3 and 2.0 Mm3 (existing repository system: 4.5 Mm3) for thermal limits of 100 ℃ and 130 ℃, respectively. These results indicated that the area and the excavated volume of the new repository system were reduced by 40-60% compared to the existing repository system. In addition, methods to further improve the efficiency were derived for the disposal area for deep geological disposal of spent nuclear fuel. The results of this study are expected to be useful in establishing a national high-level radioactive waste management policy, and for the design of a commercial deep geological repository system for spent nuclear fuels.

Analysis of Infrared Characteristics According to Common Depth Using RP Images Converted into Numerical Data (수치 데이터로 변환된 RP 이미지를 활용하여 공동 깊이에 따른 적외선 특성 분석)

  • Jang, Byeong-Su;Kim, YoungSeok;Kim, Sewon;Choi, Hyun-Jun;Yoon, Hyung-Koo
    • Journal of the Korean Geotechnical Society
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    • v.40 no.3
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    • pp.77-84
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    • 2024
  • Aging and damaged underground utilities cause cavity and ground subsidence under roads, which can cause economic losses and risk user safety. This study used infrared cameras to assess the thermal characteristics of such cavities and evaluate their reliability using a CNN algorithm. PVC pipes were embedded at various depths in a test site measuring 400 cm × 50 cm × 40 cm. Concrete blocks were used to simulate road surfaces, and measurements were taken from 4 PM to noon the following day. The initial temperatures measured by the infrared camera were 43.7℃, 43.8℃, and 41.9℃, reflecting atmospheric temperature changes during the measurement period. The RP algorithm generates images in four resolutions, i.e., 10,000 × 10,000, 2,000 × 2,000, 1,000 × 1,000, and 100 × 100 pixels. The accuracy of the CNN model using RP images as input was 99%, 97%, 98%, and 96%, respectively. These results represent a considerable improvement over the 73% accuracy obtained using time-series images, with an improvement greater than 20% when using the RP algorithm-based inputs.

The Longitudinal Study on the Factors of Catastrophic Health Expenditure Among Disabled Elderly Households (장애노인 가구의 과부담 보건의료비 결정요인에 관한 종단적 연구)

  • Roh, Seung-Hyun
    • Korean Journal of Social Welfare
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    • v.64 no.3
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    • pp.51-77
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    • 2012
  • This study examines the scale of occurrence of Catastrophic Health Expenditure, and identifies the factors influencing Catastrophic Health Expenditure among disabled elderly households. Catastrophic Health Expenditure is defined by when the households' health care spending out of ability to pay exceeds 10%, 20%, 30%, and 40%. This study used the 2008, 2009, and 2010 surveys of the Panel Survey of Employment for the Disabled(PSED) to explore how gender, age, spouse, the level of education, the degree of disability, the type of disability, disability duration, subjective health status, chronic disease, the number of household members, the proportion of disabled households, the proportion of working households, the proportion of aged households, the type of poverty, household income, net asset, determine Catastrophic Health Expenditure among disabled elderly households. The study examines the frequency of Catastrophic Health Expenditure with 726 households, and conducted the panel logit model. The empirical results show that Catastrophic Health Expenditures are significantly related to age, spouse, the type of disability, subjective health status, chronic disease, the number of households, the proportion of disabled households, the proportion of aged households, the type of poverty. This study showed that the health care safety net in South Korea was insufficient for disabled elderly households and that a policy should be established in ordered to protect disabled elderly households from occurrence of Catastrophic Health Expenditure.

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The Study on the Estimation of Optimal Debt Ratio in Korean Agricultural Corporations (한국 농업법인의 적정부채비율 추정을 위한 실증연구)

  • Kim, Woo-Seok;Seo, Beom;Im, In-Seob
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.4
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    • pp.135-142
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    • 2017
  • This study employs an analytical mathematical model to estimate the optimal debt ratio of Korean agricultural corporations, more sensitive to the government debt ratio policy compared to other industries, and the estimation of the optimal debt ratio based on objective data. The analytical model utilizes the equation for ROE, with the debt ratio as an independent variable, and related parameters include ROS, TAT, and NFCL. Regarding the NFCL, the optimal debt ratio standard is defined as the debt ratio that maximizes the ROE by analytical procedures such as adding an equation concerning the debt ratio and a linearity relationship to the analytical model, and from these equations, a quadratic equation with the debt ratio as an independent variable describes the ROE. This methodemploys fourteen years of corporate data. Results show that 138% of debt ratio is the optimal debt ratio to increase the ROE of the corporations, which implies that the existing debt ratio of Korean agricultural corporations is higher than optimal. Consequently, it is required for authorities to change future debt ratio policies in view that the purpose of debt ratio management is to maintain safety and increase profitability.Management should emphasize characteristics of the specific industry rather than standardized judgements based on numerical indexes.

Binary classification of bolts with anti-loosening coating using transfer learning-based CNN (전이학습 기반 CNN을 통한 풀림 방지 코팅 볼트 이진 분류에 관한 연구)

  • Noh, Eunsol;Yi, Sarang;Hong, Seokmoo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.2
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    • pp.651-658
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    • 2021
  • Because bolts with anti-loosening coatings are used mainly for joining safety-related components in automobiles, accurate automatic screening of these coatings is essential to detect defects efficiently. The performance of the convolutional neural network (CNN) used in a previous study [Identification of bolt coating defects using CNN and Grad-CAM] increased with increasing number of data for the analysis of image patterns and characteristics. On the other hand, obtaining the necessary amount of data for coated bolts is difficult, making training time-consuming. In this paper, resorting to the same VGG16 model as in a previous study, transfer learning was applied to decrease the training time and achieve the same or better accuracy with fewer data. The classifier was trained, considering the number of training data for this study and its similarity with ImageNet data. In conjunction with the fully connected layer, the highest accuracy was achieved (95%). To enhance the performance further, the last convolution layer and the classifier were fine-tuned, which resulted in a 2% increase in accuracy (97%). This shows that the learning time can be reduced by transfer learning and fine-tuning while maintaining a high screening accuracy.

Class Classification and Validation of a Musculoskeletal Risk Factor Dataset for Manufacturing Workers (제조업 노동자 근골격계 부담요인 데이터셋 클래스 분류와 유효성 검증)

  • Young-Jin Kang;;;Jeong, Seok Chan
    • The Journal of Bigdata
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    • v.8 no.1
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    • pp.49-59
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    • 2023
  • There are various items in the safety and health standards of the manufacturing industry, but they can be divided into work-related diseases and musculoskeletal diseases according to the standards for sickness and accident victims. Musculoskeletal diseases occur frequently in manufacturing and can lead to a decrease in labor productivity and a weakening of competitiveness in manufacturing. In this paper, to detect the musculoskeletal harmful factors of manufacturing workers, we defined the musculoskeletal load work factor analysis, harmful load working postures, and key points matching, and constructed data for Artificial Intelligence(AI) learning. To check the effectiveness of the suggested dataset, AI algorithms such as YOLO, Lite-HRNet, and EfficientNet were used to train and verify. Our experimental results the human detection accuracy is 99%, the key points matching accuracy of the detected person is @AP0.5 88%, and the accuracy of working postures evaluation by integrating the inferred matching positions is LEGS 72.2%, NECT 85.7%, TRUNK 81.9%, UPPERARM 79.8%, and LOWERARM 92.7%, and considered the necessity for research that can prevent deep learning-based musculoskeletal diseases.

Kidney Tumor Segmentation through Semi-supervised Learning Based on Mean Teacher Using Kidney Local Guided Map in Abdominal CT Images (복부 CT 영상에서 신장 로컬 가이드 맵을 활용한 평균-교사 모델 기반의 준지도학습을 통한 신장 종양 분할)

  • Heeyoung Jeong;Hyeonjin Kim;Helen Hong
    • Journal of the Korea Computer Graphics Society
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    • v.29 no.5
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    • pp.21-30
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    • 2023
  • Accurate segmentation of the kidney tumor is necessary to identify shape, location and safety margin of tumor in abdominal CT images for surgical planning before renal partial nephrectomy. However, kidney tumor segmentation is challenging task due to the various sizes and locations of the tumor for each patient and signal intensity similarity to surrounding organs such as intestine and spleen. In this paper, we propose a semi-supervised learning-based mean teacher network that utilizes both labeled and unlabeled data using a kidney local guided map including kidney local information to segment small-sized kidney tumors occurring at various locations in the kidney, and analyze the performance according to the kidney tumor size. As a result of the study, the proposed method showed an F1-score of 75.24% by considering local information of the kidney using a kidney local guide map to locate the tumor existing around the kidney. In particular, under-segmentation of small-sized tumors which are difficult to segment was improved, and showed a 13.9%p higher F1-score even though it used a smaller amount of labeled data than nnU-Net.

History of Disease Control of Korean Ginseng over the Past 50 Years (과거 50년간 고려인삼 병 방제 변천사)

  • Dae-Hui Cho
    • Journal of Ginseng Culture
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    • v.6
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    • pp.51-79
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    • 2024
  • In the 1970s and 1980s, during the nascent phase of ginseng disease research, efforts concentrated on isolating and identifying pathogens. Subsequently, their physiological ecology and pathogenesis characteristics were scrutinized. This led to the establishment of a comprehensive control approach for safeguarding major aerial part diseases like Alternaria blight, anthracnose, and Phytophthora blight, along with underground part diseases such as Rhizoctonia seedling damping-off, Pythium seedling damping-off, and Sclerotinia white rot. In the 1980s, the sunshade was changed from traditional rice straw to polyethylene (PE) net. From 1987 to 1989, focused research aimed at enhancing disease control methods. Notably, the introduction of a four-layer woven P.E. light-shading net minimized rainwater leakage, curbing Alternaria blight occurrence. Since 1990, identification of the bacterial soft stem rot pathogen facilitated the establishment of a flower stem removal method to mitigate outbreaks. Concurrently, efforts were directed towards identifying root rot pathogens causing continuous crop failure, employing soil fumigation and filling methods for sustainable crop land use. In 2000, adapting to rapid climate changes became imperative, prompting modifications and supplements to control methods. New approaches were devised, including a crop protection agent method for Alternaria stem blight triggered by excessive rainfall during sprouting and a control method for gray mold disease. A comprehensive plan to enhance control methods for Rhizoctonia seedling damping-off and Rhizoctonia damping-off was also devised. Over the past 50 years, the initial emphasis was on understanding the causes and control of ginseng diseases, followed by refining established control methods. Drawing on these findings, future ginseng cultivation and disease control methods should be innovatively developed to proactively address evolving factors such as climate fluctuations, diminishing cultivation areas, escalating labor costs, and heightened consumer safety awareness.

Thermal Effects on the Development, Fecundity and Life Table Parameters of Aphis craccivora Koch (Hemiptera: Aphididae) on Yardlong Bean (Vigna unguiculata subsp. sesquipedalis (L.)) (갓끈동부콩에서 아카시아진딧물[Aphis craccivora Koch (Hemiptera: Aphididae)]의 온도발육, 성충 수명과 산란 및 생명표분석)

  • Cho, Jum Rae;Kim, Jeong-Hwan;Choi, Byeong-Ryeol;Seo, Bo-Yoon;Kim, Kwang-Ho;Ji, Chang Woo;Park, Chang-Gyu;Ahn, Jeong Joon
    • Korean journal of applied entomology
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    • v.57 no.4
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    • pp.261-269
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    • 2018
  • The cowpea aphid Aphis craccivora Koch (Hemiptera: Aphididae) is a polyphagous species with a worldwide distribution. We investigated the temperature effects on development periods of nymphs, and the longevity and fecundity of apterous female of A. craccivora. The study was conducted at six constant temperatures of 10.0, 15.0, 20.0, 25, 30.0, and $32.5^{\circ}C$. A. craccivora developed successfully from nymph to adult stage at all temperatures subjected. The developmental rate of A. craccivora increased as temperature increased. The lower developmental threshold (LT) and thermal constant (K) of A. craccivora nymph stage were estimated by linear regression as $5.3^{\circ}C$ and 128.4 degree-days (DD), respectively. Lower and higher threshold temperatures (TL, TH and TH-TL, respectively) were calculated by the Sharpe_Schoolfield_Ikemoto (SSI) model as $17.0^{\circ}C$, $34.6^{\circ}C$ and $17.5^{\circ}C$. Developmental completion of nymph stages was described using a three-parameter Weibull function. Life table parameters were estimated. The intrinsic rate of increase was highest at $25^{\circ}C$, while the net reproductive rate was highest at $20^{\circ}C$. Biological characteristics of A. craccivora populations from different geographic areas were discussed.

ESTIMATION OF THE FISSION PRODUCTS, ACTINIDES AND TRITIUM OF HTR-10

  • Jeong, Hye-Dong;Chang, Soon-Heung
    • Nuclear Engineering and Technology
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    • v.41 no.5
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    • pp.729-738
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    • 2009
  • Given the evolution of High-Temperature Gas-cooled Reactor(HTGR) designs, the source terms for licensing must be developed. There are three potential source terms: fission products, actinides in the fuel and tritium in the coolant. It is necessary to provide first an inventory of the source terms under normal operations. An analysis of source terms has yet to be performed for HTGRs. The previous code, which can estimate the inventory of the source terms for LWRs, cannot be used for HTGRs because the general data of a typical neutron cross-section and flux has not been developed. Thus, this paper uses a combination of the MCNP, ORIGEN, and MONTETEBURNS codes for an estimation of the source terms. A method in which the HTR-10 core is constructed using the unit lattice of a body-centered cubic is developed for core modeling. Based on this modeling method by MCNP, the generation of fission products, actinides and tritium with an increase in the burnup ratio is simulated. The model developed by MCNP appears feasible through a comparison with models developed in previous studies. Continuous fuel management is divided into five periods for the feeding and discharging of fuel pebbles. This discrete fuel management scheme is employed using the MONTEBURNS code. Finally, the work is investigated for 22 isotope fission products of nuclides, 22 actinides in the core, and tritium in the coolant. The activities are mainly distributed within the range of $10^{15}{\sim}10^{17}$ Bq in the equilibrium core of HTR-10. The results appear to be highly probable, and they would be informative when the spent fuel of HTGRs is taken into account. The tritium inventory in the primary coolant is also taken into account without a helium purification system. This article can lay a foundation for future work on analyses of source terms as a platform for safety assessment in HTGRs.