• 반도체디스플레이기술학회지
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• 제20권3호
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• pp.161-166
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• 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.

• 한국화재소방학회:학술대회논문집
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• 한국화재소방학회 2012년도 춘계학술발표회 초록집
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• pp.397-399
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• 2012

• Safety and Health at Work
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• 제11권3호
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• pp.322-334
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• 2020

Background: Spontaneous combustion of coal is one of the factors which causes direct or indirect gas and dust explosion, mine fire, the release of toxic gases, loss of reserve, and loss of miners' life. To avoid these incidents, the prediction of spontaneous combustion is essential. The safety of miner's in the mining field can be assured if the prediction of a coal fire is carried out at an early stage. Method: Adularya Underground Coal Mine which is fully mechanized with longwall mining method was selected as a case study area. The data collected for 2017, by sensors from ten gas monitoring stations were used for the simulation and prediction of a coal fire. In this study, the fuzzy logic model is used because of the uncertainties, nonlinearity, and imprecise variables in the data. For coal fire prediction, CO, O₂, N₂, and temperature were used as input variables whereas fire intensity was considered as the output variable.The simulation of the model is carried out using the Mamdani inference system and run by the Fuzzy Logic Toolbox in MATLAB. Results: The results showed that the fuzzy logic system is more reliable in predicting fire intensity with respect to uncertainties and nonlinearities of the data. It also indicates that the 1409 and 610/2B gas station points have a greater chance of causing spontaneous combustion and therefore require a precautional measure. Conclusion: The fuzzy logic model shows higher probability in predicting fire intensity with the simultaneous application of many variables compared with Graham's index.

• 한국화재소방학회논문지
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• 제34권3호
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• pp.35-42
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• 2020

성능위주 소방설계(PBD)의 안전성 평가 과정에서 화재모델링의 신뢰성 확보를 위해서는 화재감지기 작동시간의 정확한 예측성능이 요구된다. 본 연구는 대표적 화재모델인 FDS에 적용되는 정온식 열감지기의 주요 입력인자인 감지기 작동온도와 RTI의 측정을 목표로 한다. 이를 위해 화재감지기 실험 장치인 Fire detector evaluator (FDE)가 적용되었으며, 제품 인지도 조사를 통해 선정된 국내 10종의 정온식 감지기가 고려되었다. 결과적으로 감지기의 제조사별로 작동온도와 RTI는 상당한 차이가 있는 것으로 확인되었으며, 측정된 DB가 적용된 FDS의 감지기 작동시간은 보다 정확한 예측이 가능함을 확인하였다. 최종적으로 신뢰성이 확보된 정온식 열감지기의 작동온도와 RTI의 DB가 제공되었다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.186-188
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• 2005

Because forest fire changes the direction according to the environmental elements, it is difficult to predict the direction of it. Currently, though some researchers have been studied to which predict the forest fire occurrence and the direction of it, using the remote detection technique, it is not enough and efficient. And recently because of the development of the sensor technique, a lot of In-Situ sensors are being developed. These kinds of In-Situ sensor data are used to collect the environmental elements such as temperature, humidity, and the velocity of the wind. Accordingly we need the prediction technique about the environmental elements analysis and the direction of the forest fire, using the In-Situ sensor data. In this paper, as a technique for predicting the direction of the forest fire, we propose the correlation analysis technique about In-Situ sensor data such as temperature, humidity, the velocity of the wind. The proposed technique is based on the clustering method and clusters the In-Situ sensor data. And then it analyzes the correlation of the multivariate correlations among clusters. These kinds of prediction information not only helps to predict the direction of the forest fire, but also finds the solution after predicting the environmental elements of the forest fire. Accordingly, this technique is expected to reduce the damage by the forest fire which occurs frequently these days.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년도 춘계학술대회논문집
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• pp.80-83
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• 2008

The characteristics of the spread of a forest fire are generally related to the attributes of combustibles, geographical features, and meteorological conditions, such as wind conditions. The most common methodology used to create a prediction model for the spread of forest fires, based on the numerical analysis of the development stages of a forest fire, is an analysis of heat energy transmission by the stage of heat transmission. When a forest fire breaks out, the analysis of the transmission velocity of heat energy is quantifiable by the spread velocity of flame movement through a physical and chemical analysis at every stage of the fire development from flame production and heat transmission to its termination. In this study, the formula used for the 1-dimensional surface forest fire behavior prediction model, derived from a numerical analysis of the surface flame spread rate of solid combustibles, is introduced. The formula for the 1-dimensional surface forest fire behavior prediction model is the estimated equation of the flame spread velocity, depending on the condition of wind velocity on the ground. Experimental and theoretical equations on flame duration, flame height, flame temperature, ignition temperature of surface fuels, etc., has been applied to the device of this formula. As a result of a comparison between the ROS(rate of spread) from this formula and ROSs from various equations of other models or experimental values, a trend suggesting an increasing curved line of the exponent function under 3m/s or less wind velocity condition was identified. As a result of a comparison between experimental values and numerically analyzed values for fallen pine tree leaves, the flame spread velocity reveals has a error of less than 20%.

• 방재기술
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• 통권10호
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• pp.19-26
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• 1991

This reoprt intended to apprehend the principle for combustible phenomena in the environments and the prediction of its hazard in the virtual fire. So we first explained the basic machanism for the combustion, and discovered the tendency of the conbustion in the condition of the environmental factors(Humidity, Wind, Temperature) by means of some sxperiments about the wood as example.

• 한국화재소방학회논문지
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• 제15권2호
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• pp.46-52
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• 2001

To evaluate the usability of compartment fire models for predicting sprinkler response time, fire experiment was conducted and measured sprinkler response time. The experimental data was compared with zone model "FASTLite"and field model "FDS"and field Model "SMARTFIRE" A Compartment fire conducted in a 2.4 m by 3.6 m by 2.4 m ISO 9705 room and measured H.R.R was approximately 100.3 kW. In test, Sprinkler activation temperature used is $72^{\circ}c$ and responded at 198s. The output of FASTLite, SMARTFIRE and, FDS for this fire scenario were 209s, 183s, and 192s, respectively. As a results, prediction using FDS model approached to that of test very closely and other models showed good approximated results also.

• 한국화재소방학회논문지
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• 제21권1호
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• pp.51-59
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• 2007

본 연구에서는 대구에 위치한 G 지하생활공간을 대상으로 화재하중에 따른 화재성상을 분석하였다. 화재성상 예측시 화재온도나 화재지속시간을 좌우하는 인자인 화재하중 및 환기계수를 파악하기 위하여, 현장방문을 통하여 가연조건을 조사하고 실의 용도별 가연조건에 대하여 각 재료의 단위발열량을 이용하여 화재하중을 산정하였다. 또한, 산정된 실의 화재하중을 변수로 화재성상분석을 위한 6가지 모델의 축소실험을 행하고 화원의 시간에 따른 온도변화와 화원의 온도상승으로 인한 공간내부로의 열유동 분포를 중심으로 화재성상을 분석하였다.

• 한국화재소방학회논문지
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• 제28권5호
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• pp.44-51
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• 2014

본 연구에서는 건축물에서의 성능기반 화재안전 설계 시에 사용되는 구획공간에서의 화재 성상 분석을 위해서 사무실 공간을 대상으로 하여 $2.4(L){\times}3.6(W){\times}2.4(H)m$의 크기의 구획 Mock-up을 제작하고 구획 내부에는 화재하중 $18.74kg/m^2$을 적용하여 책상, 의자, 컴퓨터 등과 같은 실제 가연물을 배치하여 화재실험을 실시하였다. 화재실험 결과, 구획 공간의 내부 중앙에서는 394~408 s 사이에 $600^{\circ}C$에 도달하였고 구획 입구 모서리에서는 404~420 s 사이에 $600^{\circ}C$에 도달하였다. 본 연구에서는 화재실험을 통해 측정된 온도변화 데이터를 BFD 곡선에 적용하여 화재시 구획 공간내의 온도변화 예측 기법을 분석하고자 하였으며, 화재실험을 통해 BFD 곡선 인자는 최대온도 $900^{\circ}C$, 최대온도 도달시간 7분과 형태계수 1.5로 결정하였다. BFD 곡선에 적용된 사무실 공간의 시간에 따른 온도 곡선은 화재초기에 빠르게 상승한 이후에 약 9분경 이후에 감소하는 형태를 나타내고 있다.