• Journal of the Korean Society of Safety
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• v.26 no.4
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• pp.102-110
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• 2011

For decreasing of the casualties and designing of the smoke control systems in the ultra high-rise building, the programs for analysis of smoke control were developed for prediction of smoke spread and distributions of pressure and temperature in building fire situation. In this study, coupling algorithm between mass and enthalpy conservations was modified for improving the applicability of the CAU_ESCAP which program can consider the energy transfer. The fire situation in ultra high-rise building was applied by using the modified CAU_ESCAP. Results of pressure difference predicted by modified CAU_ESCAP are higher than results of ASCOS as stack effect is generated due to the increasing of stairway temperature. Moreover, theoretically, the result of the neutral plane is more accurate than the result of ASCOS, in fire situation of ultra high-rise building.

• Korean Journal of Hazardous Materials
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• v.6 no.2
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• pp.23-29
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• 2018

The fire and explosion properties necessary for waste, safe storage, transport, process design and operation of handling flammable substances are lower explosion limits(LEL), upper explosion limits(UEL), flash point, AIT( minimum autoignition temperature or spontaneous ignition temperature), fire point etc., An accurate knowledge of the combustion properties is important in developing appropriate prevention and control measures fire and explosion protection in chemical plants. In order to know the accuracy of data in MSDSs(material safety data sheets), the flash point of phenol was measured by Setaflash, Pensky-Martens, Tag, and Cleveland testers. And the AIT of phenol was measured by ASTM 659E apparatus. The explosion limits of phenol was investigated in the reference data. The flash point of phenol by using Setaflash and Pensky-Martens closed-cup testers were experimented at $75^{\circ}C$ and $81^{\circ}C$, respectively. The flash points of phenol by Tag and Cleveland open cup testers were experimented at $82^{\circ}C$ and $89^{\circ}C$, respectively. The AIT of phenol was experimented at $589^{\circ}C$. The LEL and UEL calculated by using Setaflash lower and upper flash point value were calculated as 1.36vol% and 8.67vol%, respectively. By using the relationship between the spontaneous ignition temperature and the ignition delay time proposed, it is possible to predict the ignition delay time at different temperatures in the handling process of phenol.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.617-623
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• 2023

Among the fire incidents in Korea over the past decade, building fires are the most common, and property and human casualties are the most common. However, the existing fire fighting system does not only inform the location of emergency exits and guide safe routes to help casualties evacuate smoothly. A system was proposed to help successful evacuation by distinguishing vertical and horizontal characteristics using spatial characteristics. In this study, an effective evacuation system was proposed by predicting fires using temperature detection sensors and smoke sensor values, and calculating the optimal evacuation path through the Dijkstra algorithm.

• Journal of the Korean Society of Safety
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• v.38 no.6
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• pp.60-71
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• 2023

The purpose of this study is to propose a quantitative toxicity endpoint distance suitable for the initial response of firefighters by comparing and analyzing the commonly applied toxic level of concern (T-LOC), specifically emergency response planning guidelines (ERPG), acute exposure guideline levels (AEGL), and immediately dangerous to life or health (IDLH). This is to protect the fire brigade, which responds to toxic chemical accidents first during the golden time. Using areal locations of hazardous atmospheres, a damage prediction program, the amount of leakage for both acidic and basic substances, along with the endpoint distance, were analyzed for alternative accident and worst-case accident scenarios. The results showed that the toxicity endpoint distance, serving as a compromise between Level-3 and Level-2 of T-LOC, was longer than ERPG-3 and shorter than ERPG-2 with IDLH, while its values were analyzed in the order of ERPG-2, AEGL-2, IDLH, AEGL-3, and ERPG-3. It is suggested that the application of IDLH in an emergency (red card) and ERPG-2 endpoint distance in a non-emergency (non-red card) can be utilized for the initial response of the fire brigade.

• International Journal of Contents
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• v.12 no.1
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• pp.49-53
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• 2016

"Hahoe Village" in Andong region is an UNESCO World Heritage Site. It should be protected against various disasters such as fire, flooding, earthquake, etc. Among these disasters, flooding has drastic impact on the lives and properties in a wide area. Since "Hahoe Village" is adjacent to Nakdong River, it is important to monitor the water level near the village. In this paper, we developed a hydrological modelling using multi-layer perceptron (MLP) to predict the water level of Nakdong River near "Hahoe Village". To develop the prediction model, error back-propagation (EBP) algorithm was used to train the MLP with water level data near the village and rainfall data at the upper reaches of the village. After training with data in 2012 and 2013, we verified the prediction performance of MLP with untrained data in 2014.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.11
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• pp.2812-2822
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• 2000

Several methods have been developed to predict the rupture time of the boiler tubes in thermal power plant. However, existing life prediction methods give very conservative value at operating stress of power plant and rupture strain cannot be well estimated. Therefore, in this study, rupture time and strain prediction method accounting for creep, corrosion and heat transfer is newly proposed and compared with the current research results. The creep damage evolves by continuous cavity nucleation and constrained cavity growth. The corrosion damage evolves by steam side and fire side corrosion. The results showed good correlation between the theoretically predicted rupture time and the current research results. And rupture strain may be well estimated by using the proposed method.

• Fire Science and Engineering
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• v.28 no.6
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• pp.52-57
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• 2014

The present study suggests the fundamental method for the prediction time of the fire origin by analyzing the combustion phenomenon of inflammable material in the building structure. The heat release rate (HRR) with time variant is evaluated for the interphone as a inflammable material, which is opted from the fire incidents in the stairwell. the fire dynamics simulator (FDS ver. 6.1) is applied in order to analyze the difference of the smoke inflow time to the downstair from the fire event area with various fire pattern. The results show that the maximum inflow time difference for the case of the interphone made from ABS materials is about 4.93 times with the input conditions of heat flux values and the environment in the FDS for the fixed stairwell which composed of total volume $291.3m^3$, floorage $23.3m^2$ and the height of each floor 2.5 m. This research can be practical information for the application method of simulation scheme with experimental data to the fire Identification.

• Fire Science and Engineering
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• v.29 no.2
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• pp.73-78
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• 2015

Fire in the risk management subject belongs to high risk disaster which accompanies personnel and materiel loss. So, management of disaster and safety is required to include fire prevention activities, fire risk prediction and investment of safety management expense. Combustion toxicity is required by gas toxicity test (KS F 2271), to minimize human damage. In this study, gas toxicity test were experimented with regard to urethane sample (Depth 5~25 mm) to obtain basic data. Fire effluent exposing to experimental animal were analyzed by FT-IR (Fourier transform infrared spectroscopy). Combustion toxicity index Lethal Fractional Effective Dose ($L_{FED}$) of ISO 13344 was calculated. According to the result of calculating Lethal Concentration 50% ($LC_{50}$) based on $L_{FED}$, $LC_{50}$ of urethane sample containing certain level of fire load is confirmed as $118{\sim}129g/m^3$. Through this study, applicability of this method was confirmed for fire risk assessment. This method can provide information to predict human damage by toxicity combustion gas for securing safety.

• Fire Science and Engineering
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• v.32 no.3
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• pp.76-87
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• 2018

This study describes the damage effects modeling for a quantitative prediction about the hazardous distances from pressurized chlorine saturated liquid tank, which has two-phase leakage. The heavy gas, chlorine is an accidental substance that is used as a raw material and intermediate in chemical plants. Based on the evaluation method for damage prediction and accident effects assessment models, the operating conditions were set as the standard conditions to reveal the optimal variables on an accident due to the leakage of a liquid chlorine storage vessel. A model of the atmospheric diffusion model, ALOHA (V5.4.4) developed by USEPA and NOAA, which is used for a risk assessment of Off-site Risk Assessment (ORA), was used. The Yeosu National Industrial Complex is designated as a model site, which manufactures and handles large quantities of chemical substances. Weather-related variables and process variables for each scenario need to be modelled to derive the characteristics of leakage accidents. The estimated levels of concern (LOC) were calculated based on the Gaussian diffusion model. As a result of ALOHA modeling, the hazardous distance due to chlorine diffusion increased with increasing air temperature and the wind speed decreased and the atmospheric stability was stabilized.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.109-126
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• 2023

Early detection of forest fires is essential in preventing large-scale forest fires. Predicting forest fires serves as a vital early detection method, leading to various related studies. However, many previous studies focused solely on climate and geographic factors, overlooking human factors, which significantly contribute to forest fires. This study aims to develop forest fire prediction models that take into account human, weather and geographical factors. This study conducted a comparative analysis of four machine learning models alongside the logistic regression model, using forest fire data from Gangwon-do spanning 2003 to 2020. The results indicate that XG Boost models performed the best (AUC=0.925), closely followed by Random Forest (AUC=0.920), both of which are machine learning techniques. Lastly, the study analyzed the relative importance of various factors through permutation feature importance analysis to derive operational insights. While meteorological factors showed a greater impact compared to human factors, various human factors were also found to be significant.