• Proceedings of the Korea Institute of Fire Science and Engineering Conference
• /
• 2003.04a
• /
• pp.279-284
• /
• 2003

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.11 no.6
• /
• pp.703-710
• /
• 2018

Although various efforts have been made every year to reduce electric fire accidents such as accident analysis and inspection for electric fire accidents, there is no effective countermeasure due to lack of effective decision support system and existing cumulative data utilization method. The purpose of this study is to develop an algorithm for predicting electric fire based on data such as electric safety inspection data, electric fire accident information, building information, and weather information. Through the pre-processing of collected data for each institution such as Korea Electrical Safety Corporation, Meteorological Administration, Ministry of Land, Infrastructure, and Transport, Fire Defense Headquarters, convergence, analysis, modeling, and verification process, we derive the factors influencing electric fire and develop prediction models. The results showed insulation resistance value, humidity, wind speed, building deterioration(aging), floor space ratio, building coverage ratio and building use. The accuracy of prediction model using random forest algorithm was 74.7%.

• Safety and Health at Work
• /
• v.8 no.1
• /
• pp.42-48
• /
• 2017

Background: As one of the most frequently occurring accidents in a chemical plant, a fire accident may occur at any place where transfer or handling of combustible materials is routinely performed. Methods: In particular, a jet fire incident in a chemical plant operated under high pressure may bring severe damage. To review this event numerically, Computational Fluid Dynamics methodology was used to simulate a jet fire at a pipe of a compressor under high pressure. Results: For jet fire simulation, the Kemeleon FireEx Code was used, and results of this simulation showed that a structure and installations located within the shelter of a compressor received serious damage. Conclusion: The results confirmed that a jet fire may create a domino effect that could cause an accident aside from the secondary chemical accident.

• Journal of the Semiconductor & Display Technology
• /
• v.23 no.1
• /
• pp.110-116
• /
• 2024

Despite the continuous advancement of science and technology, fire accidents continue to occur without decreasing over time, so there is a constant need for a system that can accurately detect fires at an early stage. However, because most existing fire detection systems detect fire in the early stage of combustion when smoke is generated, rapid fire prevention actions may be delayed. Therefore we propose an early fire detection system that can perform early fire detection at a reasonable cost using LSTM, a deep learning model based on multi-gas sensors with high selectivity in the early stage of decomposition rather than the smoke generation stage. This system combines multiple gas sensors to achieve faster detection speeds than traditional sensors. In addition, through window sliding techniques and model light-weighting, the false alarm rate is low while maintaining the same high accuracy as existing deep learning. This shows that the proposed fire early detection system is a meaningful research in the disaster and engineering fields.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.40 no.4
• /
• pp.147-153
• /
• 2017

The mortality rate in industrial accidents in South Korea was 11 per 100,000 workers in 2015. It's five times higher than the OECD average. Economic losses due to industrial accidents continue to grow, reaching 19 trillion won much more than natural disaster losses equivalent to 1.1 trillion won. It requires fundamental changes according to industrial safety management. In this study, We classified the risk of accidents in industrial complex of Ulju-gun using spatial analytics and data mining. We collected 119 data on accident data, factory characteristics data, company information such as sales amount, capital stock, building information, weather information, official land price, etc. Through the pre-processing and data convergence process, the analysis dataset was constructed. Then we conducted geographically weighted regression with spatial factors affecting fire incidents and calculated the risk of fire accidents with analytical model for combining Boosting and CART (Classification and Regression Tree). We drew the main factors that affect the fire accident. The drawn main factors are deterioration of buildings, capital stock, employee number, officially assessed land price and height of building. Finally the predicted accident rates were divided into four class (risk category-alert, hazard, caution, and attention) with Jenks Natural Breaks Classification. It is divided by seeking to minimize each class's average deviation from the class mean, while maximizing each class's deviation from the means of the other groups. As the analysis results were also visualized on maps, the danger zone can be intuitively checked. It is judged to be available in different policy decisions for different types, such as those used by different types of risk ratings.

• Fire Science and Engineering
• /
• v.28 no.6
• /
• pp.90-98
• /
• 2014

Lately accidents of harmful chemical substance in korea were repeatedly replaying. We studied problems and preparation plan in 2008 years~2014 years through analysis cases of harmful chemical substance. Leakage of chemical substance's accident situation shows that leakage in the workplace is the most 10 cases, accounting for 58.6% is the largest proportion in 2009. Leakage according to explosion accounting for 50% (5 cases) in 2004, 25% (4 cases) in 2007 and 33.3% (4 cases) in 2011 has very irregular change. Therefore, A major cause of accidents is lack of safety management. Harmful chemical substance showed various aspects, high residual substance and non-visible characteristic so response and recovery was easy. And the second damage to move a distance causes environment pollution. So a mutual-assistance system and integrated system of related organization have to build and expert of chemical incident response and therapist of chemical substance response have to establish to do efficient and rapid response.

• Fire Science and Engineering
• /
• v.33 no.2
• /
• pp.79-84
• /
• 2019

The use of emergency escape breathing devices (EEBD) is strongly required to protect against toxic gas or flooding caused by ship fires or accidents. Recently developed domestic EEBD products only satisfy the basic performance requirements, but no wear fit and activity performance evaluation has been done for real usage. In this study, the global level test requirements for wear comfort and activity of EEBDs were developed and the open and closed type of domestic EEBD products were evaluated. Poor visibility, longer wear time, breathing resistance, and hose obstruction in an open type and canister obstruction, weight unbalance, and an invisible black breathing bag in the closed type EEBD were estimated to be the main problems that need to be improved.

• Journal of the Society of Disaster Information
• /
• v.11 no.1
• /
• pp.135-147
• /
• 2015

Recent underground common utility tunnels are underground facilities for jointly accommodating more than 2 kinds of air-conditioning and heating facilities, vacuum dust collector, information processing cables as well as electricity, telecommunications, waterworks, city gas, sewerage system required when citizens live their daily lives and facilities responsible for the central function of the country but it is difficult to cope with fire accidents quickly and hard to enter into common utility tunnels to extinguish a fire due to toxic gases and smoke generated when various cables are burnt. Thus, in the event of a fire, not only the nerve center of the country is paralyzed such as significant property damage and loss of communication etc. but citizen inconveniences are caused. Therefore, noticing that most fires break out by a short circuit due to electrical works and degradation contact due to combustible cables as the main causes of fires in domestic and foreign common utility tunnels fire cases that have occurred so far, the purpose of this paper is to scientifically analyze the behavior of a fire by producing the model of actual common utility tunnels and reproducing the fire. A fire experiment was conducted in a state that line type fixed temperature detector, fire door, connection deluge set and ventilation equipment are installed in underground common utility tunnels and transmission power distribution cables are coated with fire proof paints in a certain section and heating pipes are fire proof covered. As a result, in the case of Type II, the maximum temperature was measured as $932^{\circ}C$ and line type fixed temperature detector displayed the fire location exactly in the receiver at a constant temperature. And transmission power distribution cables painted with fire proof paints in a certain section, the case of Type III, were found not to be fire resistant and fire proof covered heating pipes to be fire resistant for about 30 minutes. Also, fire simulation was carried out by entering fire load during a real fire test and as a result, the maximum temperature is $943^{\circ}C$, almost identical with $932^{\circ}C$ during a real fire test. Therefore, it is considered that fire behaviour can be predicted by conducting fire simulation only with common utility tunnels fire load and result values of heat release rate, height of the smoke layer, concentration of O2, CO, CO2 etc. obtained by simulation are determined to be applied as the values during a real fire experiment. In the future, it is expected that more reliable information on domestic underground common utility tunnels fire accidents can be provided and it will contribute to construction and maintenance repair effectively and systematically by analyzing and accumulating experimental data on domestic underground common utility tunnels fire accidents built in this study and fire cases continuously every year and complementing laws and regulations and administration manuals etc.

• Journal of the Semiconductor & Display Technology
• /
• v.20 no.3
• /
• pp.161-166
• /
• 2021

To prevent accidents caused by changes in the surrounding environment or other factors, various protection facilities are installed at the photovoltaic connection module. The main causes of fire are sparks due to foreign substances inside the photovoltaic connection module through high temperature rise and dew condensation in the photovoltaic connection module, and fire due to heat from the power diode. The proposed method can predict the fire by measuring flame, carbon dioxide, carbon monoxide, temperature, humidity, input voltage, and current on the photovoltaic connection module, and when the fire conditions are reached, fire alarm and power off can be sent to managers and users in real time to prevent fire in advance.

• Fire Science and Engineering
• /
• v.33 no.6
• /
• pp.72-79
• /
• 2019

Through this study, we developed a model for predicting chemical accidents lead to casualties. The model was derived from the logistic regression analysis model and applied to the variables affecting the accident. The accident data used in the model was analyzed by studying the statistics of past chemical accidents, and applying independent variables that were statistically significant through data analysis, such as the type of accident, cause, place of occurrence, status of casualties, and type of chemical accident that caused the casualties. A significance of p < 0.05 was applied. The model developed in this study is meaningful for the prevention of casualties caused by chemical accidents and the establishment of safety systems in the workplace. The analysis using the model found that the most influential factor in the occurrence of casualty in accidents was chemical explosions. Therefore, there is an urgent need to prepare countermeasures to prevent chemical accidents, specifically explosions, from occurring in the workplace.