• Nuclear Engineering and Technology
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• v.47 no.1
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• pp.11-25
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• 2015

The accident at Japan's Fukushima Daiichi nuclear power plant in March 2011, caused by an earthquake and a subsequent tsunami, resulted in a failure of the power systems that are needed to cool the reactors at the plant. The accident progression in the absence of heat removal systems caused Units 1-3 to undergo fuel melting. Containment pressurization and hydrogen explosions ultimately resulted in the escape of radioactivity from reactor containments into the atmosphere and ocean. Problems in containment venting operation, leakage from primary containment boundary to the reactor building, improper functioning of standby gas treatment system (SGTS), unmitigated hydrogen accumulation in the reactor building were identified as some of the reasons those added-up in the severity of the accident. The Fukushima accident not only initiated worldwide demand for installation of adequate control and mitigation measures to minimize the potential source term to the environment but also advocated assessment of the existing mitigation systems performance behavior under a wide range of postulated accident scenarios. The uncertainty in estimating the released fraction of the radionuclides due to the Fukushima accident also underlined the need for comprehensive understanding of fission product behavior as a function of the thermal hydraulic conditions and the type of gaseous, aqueous, and solid materials available for interaction, e.g., gas components, decontamination paint, aerosols, and water pools. In the light of the Fukushima accident, additional experimental needs identified for hydrogen and fission product issues need to be investigated in an integrated and optimized way. Additionally, as more and more passive safety systems, such as passive autocatalytic recombiners and filtered containment venting systems are being retrofitted in current reactors and also planned for future reactors, identified hydrogen and fission product issues will need to be coupled with the operation of passive safety systems in phenomena oriented and coupled effects experiments. In the present paper, potential hydrogen and fission product issues raised by the Fukushima accident are discussed. The discussion focuses on hydrogen and fission product behavior inside nuclear power plant containments under severe accident conditions. The relevant experimental investigations conducted in the technical scale containment THAI (thermal hydraulics, hydrogen, aerosols, and iodine) test facility (9.2 m high, 3.2 m in diameter, and $60m^3$ volume) are discussed in the light of the Fukushima accident.

• Korean Journal of Construction Engineering and Management
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• v.8 no.3
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• pp.106-115
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• 2007

The size and length of road tunnels have been gradually expanded as industry developed. Consequently, the risk has been increased. The decision making process for ventilation system for road tunnels involves a large amount of information on economic feasibility, construction methods, and safety etc. In situation where systematically structured decision making process is unavailable, almost decisions about ventilation systems are made based on engineers' private knowledge and experiences. Procedure and criteria to choose the best optimized ventilation system among many alternatives are proposed, breaking away from the economic dependency-oriented decision making. This paper presents a Multi-Attribute Utility Theory and AHP based function with which planners can calculate overall utility of each alternative. It is anticipated that the effective use of the proposed methodology for decision making on ventilation systems ould be able to reduce the likelihood of the occurrence of potential safety risks as well as increase the overall ventilation performance.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.2
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• pp.202-209
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• 2014

In this paper, a developed device for detecting target's location and avoiding collision is proposed. Velocity and acceleration model of target are derived to estimate target's information, i.e. position, velocity and acceleration considering process and measurement noise. Kalman filtering method applied to the estimation process and its results was confirmed by simulation. The distance measurements system using laser sensor for moving target system is also developed to confirm the effectiveness of the proposed scheme. Experiments to get information of moving target with velocity and acceleration model was executed. The data with filtering and without filtering was compared by experiments. Discontinuous measured data was changed to smooth and continuous data by Kalman filtering. It is confirmed that desired data was obtained by applying proposed scheme. UI for measuring and monitoring the target data is developed and visual and auditory alarm function is attached on the system Finally, position estimation system of moving target with good performance is achieved by low price equipments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.4322-4327
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• 2015

Improper backfill materials and compaction controls under pipelines have become one of the major causes of failure in many sewage pipeline systems. A study on backfill materials and compaction controls has been considered for a long time. However, structural supporters under the pipe were recently concerned because of pipeline repair and maintenance. This paper presents a prefabricated plastic foundation for supporting a sewage pipe system and increasing the performance function of the pipes. Several analytical models for the plastic foundations were investigated using finite-element program, ABAQUS, for checking safety. Comparing with the results of analyses, some of economic design sections based on the sizes of pipe diameters, 600mm, 700 and 600mm, were evaluated. These results could be applied to a pipeline system with a prefabricated plastic foundation with respect to pipe diameters and buried depths.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.5
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• pp.182-189
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• 2021

VPS(Void Plywood Slab System, VPS) has optimized the shape of the hollow material. In addition, it has a function to prevent the floating of the hollow material and the separation due to the working load. In this study, the punching shear capacity of flat plate was performed using Void Plywood Slab System with form work panel proposed in the previous study. As a result of the test, the strength of the VSPS specimen in which the hollow material was placed beyond 2.0 times the column width from the loading point was reduced by 9.4% compared to the reference specimen. However, the strength value was about 1.57 times higher than the design value suggested by KBC 2016. It was found that there was no change in stiffness compared to the reference specimen until shear failure occurred in the VSPS specimen in which the hollow material was placed. It can be seen that this experiment is being destroyed by shear as the flexural reinforcing bars are sufficiently reinforced.

• Journal of Advanced Navigation Technology
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• v.22 no.2
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• pp.133-140
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• 2018

In recent years, model-based design techniques have been used as a way to support cost reduction and safety certification in the development of avionics systems. In order to support performance analysis and safety analysis of aircraft and avionics equipment (item) using model based design, we developed a multi-domain simulation environment that inter-works with heterogeneous simulators. We present a multi-domain simulation environment that can verify air data computers and integrated multi-function probes at the aircraft level. The model was developed by Simulink and the flight simulator X-Plane 10 was used to verify the model at the aircraft level. Avionics model functions were tested at the aircraft level and the air data errors of the model and flight simulator were measured within 0.1%.

• Geomechanics and Engineering
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• v.31 no.4
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• pp.339-352
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• 2022

Studying slope stability is an important branch of civil engineering. In this way, engineers have employed machine learning models, due to their high efficiency in complex calculations. This paper examines the robustness of various novel optimization schemes, namely equilibrium optimizer (EO), Harris hawks optimization (HHO), water cycle algorithm (WCA), biogeography-based optimization (BBO), dragonfly algorithm (DA), grey wolf optimization (GWO), and teaching learning-based optimization (TLBO) for enhancing the performance of adaptive neuro-fuzzy inference system (ANFIS) in slope stability prediction. The hybrid models estimate the factor of safety (F_S) of a cohesive soil-footing system. The role of these algorithms lies in finding the optimal parameters of the membership function in the fuzzy system. By examining the convergence proceeding of the proposed hybrids, the best population sizes are selected, and the corresponding results are compared to the typical ANFIS. Accuracy assessments via root mean square error, mean absolute error, mean absolute percentage error, and Pearson correlation coefficient showed that all models can reliably understand and reproduce the F_S behavior. Moreover, applying the WCA, EO, GWO, and TLBO resulted in reducing both learning and prediction error of the ANFIS. Also, an efficiency comparison demonstrated the WCA-ANFIS as the most accurate hybrid, while the GWO-ANFIS was the fastest promising model. Overall, the findings of this research professed the suitability of improved intelligent models for practical slope stability evaluations.

• Geomechanics and Engineering
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• v.37 no.4
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• pp.307-321
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• 2024

This paper delves into the critical assessment of predicting sidewall displacement in underground caverns through the application of nine distinct machine learning techniques. The accurate prediction of sidewall displacement is essential for ensuring the structural safety and stability of underground caverns, which are prone to various geological challenges. The dataset utilized in this study comprises a total of 310 data points, each containing 13 relevant parameters extracted from 10 underground cavern projects located in Iran and other regions. To facilitate a comprehensive evaluation, the dataset is evenly divided into training and testing subset. The study employs a diverse array of machine learning models, including recurrent neural network, back-propagation neural network, K-nearest neighbors, normalized and ordinary radial basis function, support vector machine, weight estimation, feed-forward stepwise regression, and fuzzy inference system. These models are leveraged to develop predictive models that can accurately forecast sidewall displacement in underground caverns. The training phase involves utilizing 80% of the dataset (248 data points) to train the models, while the remaining 20% (62 data points) are used for testing and validation purposes. The findings of the study highlight the back-propagation neural network (BPNN) model as the most effective in providing accurate predictions. The BPNN model demonstrates a remarkably high correlation coefficient (R2 = 0.99) and a low error rate (RMSE = 4.27E-05), indicating its superior performance in predicting sidewall displacement in underground caverns. This research contributes valuable insights into the application of machine learning techniques for enhancing the safety and stability of underground structures.

• Research in Community and Public Health Nursing
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• v.1 no.1
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• pp.299-317
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• 1989

This study was attempted to find out the distribution of industrial nurses, analyze job performance by function and utilization state of medical dispensary among workers. The subjects for this study were 32 nurses working at industry located in Kyungpook and Taegu area. The data was collected through questionaire during the period of August 5-31, 1986, and analysed by the method of frequency and percentage. The following is the main findings of the study; 1. 72.2% of respondents was engaged in manufacturing industry, 33.3% in workplace whose regular workers was more than 2,000 workers. 67.7% in occupational health physicians was part-time system. 2. 93.1% of respondents was 20-29 years age group, 93.1% was graduates of junior nursing college, 96.6% was unmarried. 448% had 1-4 years of total working experiences. 3. For the motives which made them becomes industrial health nurse, 'good employment condition' was 62.1%. For the job satisfaction, 'moderate' was 586%. For the interest about the industrial health, 'moderate' was most frequent (58.6%). In the inservice education, 86.2% of the subjects was received education. 4. For the attitude of the dispensary and industrial nursing of employer, 'necessary' was most frequent (72.4%, 62.6%). 5. All establishment had dispensary facilities, 65.5% of them had independent dispensary. 6. In duty shift, 93.1% of respondents was working in one shift system. 41.4% of respondents was received from 250,000 won to 290,000 Won and 41.4% was belong to personnel section and 24.1% was direct controlled by general business section chief. 7. In the main health problem of their factories, 48.3% of respondents was work-environmental state, 24.1% was health education. 8. In the Dispensary budget, 60% of respondents was under 3,000 won per worker. 9. In the job performance rate by function, nursing service 73.1%, industrial health and nursing management 63.7%, environmental hygiene and safety management 54.5%, medical insurance 44.9%, welfare 38.4%. 10. Main health complaints among workers utilizing medical dispensary was 35.9% of respiratory system, 21.5% of gastro-intestinal system, 11.0% of skeletomuscular system.

• Journal of Acupuncture Research
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• v.17 no.4
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• pp.120-129
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• 2000

This study was designed to study on major components of various Bee Venom(Bee Venom by electrical stimulation in Korea; K-BV I, Bee Venom by Microwave stimulation in Korea; K-BV II, 0.5mg/ml, Fu Yu Pharmaceutical Factory, China; C-BV, 1mg/ml, Monmouth Pain Institute, Inc., U.S.A.; A-BV) using HPLC(High performance liquid chromatography). The results were summarized as follows : 1. HPLC method is useful for analysis of Bee Venom when solution rate is above 1:4000. 2. Analysis of Apamin using HPLC, the Retention time was 8.7min, and standard measurement curve was a function of y=4E+06x+21245. 3. Analysis of Melittin using HPLC, the Retention time was 29.0 min, and standard measurement curve was a function of y=4E+06x+23015. 4. Concentration of Melittin was about 297times than Apamin in K-BV I, and about 329times in K-BV II at same 1:500 solution rate, abnormally about 12 times in C-BV at 1:4000 solution rate. 5. Chinese Bee Venom using HPLC, the point from 5 to 7min(Retention time) showed a big extraordinary peak. These data from the study can be applied to establish the standard measurement of Bee Venom and prevent pure bee venom from mixing of another components. I think it is desirable to study more about safety of Bee Venom as time goes by.