• Korean Journal of Fisheries and Aquatic Sciences
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• v.30 no.1
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• pp.158-160
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• 1997

Food poisoning accident occurred on May, 1996 at Oepo, Geoje County, Kyeongnam Province, Korea, and two persons were died within a few hours after ingestion of the soup prepared with wild mussel, Mytilus edulis, harvested on the sea rock. Paralytic shellfish poisons (PSP) were elucidated as the responsible toxins for the food poisons accident because the wild mussels caught after three days at the near place from the accident contained high toxicity of PSP ranged $650\~1000MU/g$ of edible meat by mouse bioassay. Gonyautoxin-1+4 $(42.7\%)$ and C1+C2 $(40.0\%)$ were detected as the major toxins in the mussels by fluorometric HPLC method. Although, the poison extracted out with drip during freezing and thawing, and the toxicity gradually decreased by boiling for 20 minutes, over 30 MU/g of toxins remained in the soup and meat, which indicated that they could be able to make food poisoning.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.254-257
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• 2018

In this paper, we implement the mobile application for disaster and safety accident response that can be easily accessed through smart phones to prevent the loss of life and poor awareness of safety to the increased number of disasters and accidents. A few of related mobile applications for accident response are served, and the most of them have the manual interfaces. In this paper, we implement the mobile application for scenario of the disaster such as earthquake and safety accident that can occur in daily life. It is organized in a form of a clear action option with user-friendly visual characters and can be used regardless of age group.

• The Korean Journal of Emergency Medical Services
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• v.4 no.1
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• pp.95-100
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• 2000

This is a study to evaluate the effects of the safety of ambulance driving and traffic accidents and to provide statistic information for the various factors to reduce the ambulance traffic accidents. The major instruments of this study were Korean Self-Analysis Driver Opinionnaire. This Questionnaire contains 8 items which measure drivers' opinions or attitudes: driving courtesy, emotion, traffic law, speed, vehicle condition, the use of drugs, high-risk behavior, human factors. The total of 145 divers were investigated ambulance drivers in Taejon City and others(6 City) from 2000. 5. July to 2000. 11. July. The data were analyzed by the path analysis - with SPSS and AMOS package program. The result are as follows : 1. It have suggested that risk factors of ambulance traffic accident much affected with emotion and speed control on safety ambulance driving(Y(Accident) = $0.88{\times}1$(Emotion Control) + $0.92{\times}2$(Speed) - $0.46{\times}3$(Traffic Law)+E). 2. It have suggested that risk factors of ambulance traffic accident much affected with emotion and speed control on safety ambulance driving(Y(Accident) = $0.398{\times}1$(Emotion Control) + $0.500{\times}2$(Speed) - $0.263{\times}3$(Traffic Law)+E) by coefficiecial structural analysis.

• Nuclear Engineering and Technology
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• v.47 no.2
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• pp.139-147
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• 2015

Recently, severe accidents in nuclear power plants (NPPs) have become a global concern. The aim of this paper is to predict the hydrogen buildup within containment resulting from severe accidents. The prediction was based on NPPs of an optimized power reactor 1,000. The increase in the hydrogen concentration in severe accidents is one of the major factors that threaten the integrity of the containment. A method using a fuzzy neural network (FNN) was applied to predict the hydrogen concentration in the containment. The FNN model was developed and verified based on simulation data acquired by simulating MAAP4 code for optimized power reactor 1,000. The FNN model is expected to assist operators to prevent a hydrogen explosion in severe accident situations and manage the accident properly because they are able to predict the changes in the trend of hydrogen concentration at the beginning of real accidents by using the developed FNN model.

• Journal of Korean Institute of Fire Investigation
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• v.11 no.1
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• pp.1-8
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• 2008

The purpose of this paper is to report gas fire accident based on classification of the major gas fire causes (including handling mistakes, inferior goods, etc.), fire classifications (fire, explosion, leakages, etc.), damage levels(1st, 2nd, 3rd, 4th grade levels), casualties (death, serious wound, slight injury) since gas fire has been generated according to growth of gaseous fuel consumption on home and enterprises with various accident causes. Among gaseous fuels, LPG facility can be c1assified as gas container, pressure regulator, gas hose, interim valve, combustion port. Any fire or any explosion can be caused from handling mistakes, inferior goods on each parts as stated above. Exact gas fire causes shall be identified based on previous case studies on similar fires with consideration of lesson learns.

• Fire Science and Engineering
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• v.19 no.3 s.59
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• pp.1-12
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• 2005

June 1, 2004, National Emergency Management Agency was established, and one of its aims is to reduce the percentage of accident occurrence and damage scale to that of developed countries in 10 years. In this paper, Korea is compared with Japan in the view of actual conditions of accident occurrence in order to compare Korea with developed countries. In the case .of Korea, traffic accidents, fire accidents, careless accidents, drowning accidents, climbing accidents occur frequently. Decreasing these accidents is a major target to reduce the accident occurrence. Also, home accidents of babies and elders who are unable to avoid dangers are frequent. Studies focusing on those related accidents are required.

• Nuclear Engineering and Technology
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• v.49 no.5
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• pp.928-940
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• 2017

An experiment using the $Prim{\ddot{a}}rkreisl{\ddot{a}}ufe$ Versuchsanlage (PKL) was performed for the OECD/NEA PKL-3 Project as a counterpart to a previous test with the large-scale test facility (LSTF) on a cold leg smallbreak loss-of-coolant accident with an accident management (AM) measure in a pressurized water reactor. Concerning the AM measure, the rate of steam generator (SG) secondary-side depressurization was controlled to achieve a primary depressurization rate of 200 K/h as a common test condition; however, the onset timings of the SG depressurization were different from each other. In both tests, rapid recovery started in the core collapsed liquid level after loop seal clearing, which caused whole core quench. Some discrepancies appeared between the LSTF and PKL test results for the core collapsed liquid level, the cladding surface temperature, and the primary pressure. The RELAP5/MOD3.3 code predicted the overall trends of the major thermal-hydraulic responses observed in the LSTF test well, and indicated a remaining problem in the prediction of primary coolant distribution. Results of uncertainty analysis for the LSTF test clarified the influences of the combination of multiple uncertain parameters on peak cladding temperature within the defined uncertain ranges.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.171-178
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• 2018

Recently, the continuing operation of nuclear power plants has become a major controversial issue in Korea. Whether to continue to operate nuclear power plants is a matter to be determined considering many factors including social and political factors as well as economic factors. But in this paper we concentrate only on the economic factors to make an optimum decision on operating nuclear power plants. Decisions should be based on forecasts of plant accident risks and large and small accident data from power plants. We outline the structure of a decision model that incorporate accident risks. We formulate to decide whether to shutdown permanently, shutdown temporarily for maintenance, or to operate one period of time and then periodically repeat the analysis and decision process with additional information about new costs and risks. The forecasting model to predict nuclear power plant accidents is incorporated for an improved decision making. First, we build a one-period decision model and extend this theory to a multi-period model. In this paper we utilize influence diagrams as well as decision trees for modeling. And bayesian statistical approach is utilized. Many of the parameter values in this model may be set fairly subjective by decision makers. Once the parameter values have been determined, the model will be able to present the optimal decision according to that value.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1246-1254
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• 2018

The importance of performing Level 3 probabilistic safety assessments (PSA) along with a general interest in assessing multi-unit risk has been sharply increasing after the Fukushima Daiichi nuclear power plant (NPP) accident. However, relatively few studies on multi-unit Level 3 PSA have been performed to date, reflecting limited scenarios of multi-unit accidents with higher priority. The major difficulty to carry out a multi-unit Level 3 PSA lies in the exponentially increasing number of multi-unit accident combinations, as different source terms can be released from each NPP unit; indeed, building consequence models for the astronomical number of accident scenarios is simply impractical. In this study, a new approach has been developed that employs the look-up table method to cover every multi-unit accident scenario. Consequence results for each scenario can be found on the table, established with a practical amount of effort, and can be matched to the frequency of the scenario. Preliminary application to a six-unit NPP site was carried out, where it was found that the difference between full-coverage and cut-off cases could be considerably high and therefore influence the total risk. Additional studies should be performed to fine tune the details and overcome the limitations of the approach.

• Journal of the Korea Safety Management & Science
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• v.22 no.1
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• pp.9-14
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• 2020

Artificial intelligence (AI) has been applied to most industries by enhancing automation and contributing greatly to efficient processes and high-quality production. This research analyzes the applications of AI-based automobile accident prevention systems. It deals with AI-based collision prevention systems that learn information from various sensors attached to cars and AI-based accident detection systems that automatically report accidents to the control center in the event of a collision. Based on the literature review, technological and institutional changes are taking place at the national levels, which recognize the effectiveness of the systems. In addition, start-ups at home and abroad as well as major car manufacturers are in the process of commercializing auto parts equipped with AI-based collision prevention technology.