• Journal of the Korean Institute of Gas
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• v.24 no.5
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• pp.47-55
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• 2020

Hazardous materials accidents are not limited to the leakage of the material, but if the early response is not appropriate, it can lead to a fire or an explosion, which increases the scale of the damage. However, as the 4th industrial revolution and the rise of the big data era are being discussed, systematic analysis of hazardous materials accidents based on new techniques has not been attempted, but simple statistics are being collected. In this study, we perform the systematic analysis, using machine learning, on the fire accident data for the past 11 years (2008 ~ 2018), accumulated by the National Fire Service. The analysis results are visualized and presented through text mining analysis, and the possibility of developing a damage-scale prediction model is explored by applying the regression analysis method, using the main factors present in the hazardous materials fire accident data.

• Journal of Environmental Impact Assessment
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• v.16 no.6
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• pp.495-502
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• 2007

In Korea, military authorities have neglected to consider impacts of military projects on local communities and natural environment. Moreover, local communities have had difficulties in dealing with the Ministry of National Defense (MND), which was stubborn enough not to implement environmental assessment on their projects. In this situation, recent case, "EIA of Baekgol Division's Howitzer Fire Training Site" in the Supreme Court-in which judges upheld the Higher Court's decision that the division violated the Environmental Impact Assessment law by ignoring to implement EIA-reveals that military projects can no longer forgo environmental assessment. The decision has serious ramifications on the future of Environmental Impact Assessment in military-led projects. This paper examines the proper scope of EIA in military-led projects and, more specifically, fire training site and searches for how to improve it through 'probable error,' a military training method that is applied to real 'howitzer' fire training. Probable error of the artillery field manual is nothing more than an error that exceeded as often as it is not exceeded and its scientific method was demonstrated through real fire tests in the US. Army. If it is applied to improve assessment methods about the proper scope of EIA in military 'howitzer' fire training site, 'probable error' will improve effect prediction, mitigation and reliability.

• Fire Science and Engineering
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• v.15 no.1
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• pp.7-15
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• 2001

This paper describes the smoke filling process of a fire field model based on a self-developed SMEP (Smoke Movement Estimating Program) codo to the simulation of fire induced flows in the atrium space (SIVANS atrium at Japan) containing smoke radiation effect. The SMEP using PISO algorithm solves conservation equations for mass, momentum, energy and species, together with those for the modified k-$\varepsilon$ turbulence model with buoyancy term. Also it solves the radiation equation using the discrete ordinates method. The result of the calculated smoke temperature containing radiation effect has shown a better prediction than the result calculated by only convection effect in comparison with the experimental data. This seems to come from the radiation effect of $H_2$O and $CO_2$ gas under smoke productions. Thus, the consideration of the radiation effect under smoke in fire should be necessary in order to get more realistic result. Also the numerical results indicated that the smoke layer is developing at a rate of about 0.1 m/s. It would take about 450 seconds after starting the ultra fast fire of 560 kW that the smoke layer move down to 1.5m above the escape level.

• Steel and Composite Structures
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• v.49 no.5
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• pp.533-546
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• 2023

Cost-effective solutions provided by composite construction are gaining popularity which, in turn, promotes the appearance on the market of new types of composite sections that allow not only to take advantage of the synergy of steel and concrete working together at room temperature, but also to improve their behaviour at high temperatures. When combined with high performance materials, significant load-bearing capacities can be achieved even with reduced cross-sectional dimensions. Steel-reinforced concrete-filled steel tubular (SR-CFST) columns are one of these innovative composite sections, where an open steel profile is embedded into a CFST section. Besides the renowned benefits of these typologies at room temperature, the fire protection offered by the surrounding concrete to the inner steel profile, gives them an enhanced fire performance which delays its loss of mechanical capacity in a fire scenario. The experimental evidence on the fire behaviour of SR-CFST columns is still scarce, particularly when combined with high performance materials. However, it is being much needed for the development of specific design provisions that consider the use of the inner steel profile in CFST columns. In this work, a new experimental program on the thermo-mechanical behaviour of SR-CFST columns is presented to extend the available experimental database. Ten SR-CFST stub columns, with circular and square geometries, combining high strength steel and concrete were tested. It was seen that the circular specimens reached higher failure times than the square columns, with the failure time increasing both when high strength steel was used at the embedded steel profile and high strength concrete was used as infill. Finally, different proposals for the reduction coefficients of high performance materials were assessed in the prediction of the cross-sectional fire resistance of the SR-CFST columns.

• The Journal of Bigdata
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• v.3 no.2
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• pp.71-78
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• 2018

The study is based on machine learning techniques to increase the accuracy of the forest fire predictive model. It used 14 years of data from 2003 to 2016 in Gang-won-do where forest fire were the most frequent. To reduce weather data errors, Gang-won-do was divided into nine areas and weather data from each region was used. However, dividing the forest fire forecast model into nine zones would make a large difference between the date of occurrence and the date of not occurring. Imbalance issues can degrade model performance. To address this, several sampling methods were applied. To increase the accuracy of the model, five indices in the Canadian Frost Fire Weather Index (FWI) were used as derived variable. The modeling method used statistical methods for logistic regression and machine learning methods for random forest and xgboost. The selection criteria for each zone's final model were set in consideration of accuracy, sensitivity and specificity, and the prediction of the nine zones resulted in 80 of the 104 fires that occurred, and 7426 of the 9758 non-fires. Overall accuracy was 76.1%.

• Fire Science and Engineering
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• v.16 no.2
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• pp.33-37
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• 2002

This study has investigated hydrodynamic of torque characteristics for disc of butterfly valve that is used in control for fire-protection water, The free-streamline theory is applied to predict hydrodynamic of torque characteristics. The torque characteristics of disc are corrected for the angles of attack of valve disc and surrounding velocity of flow by theoretical torque equation, and correction equation is added. The torque characteristics of disc are investigated for the ratio of hub thickness to the valve diameter. The result of prediction are shown to be successful as that show typical torque characteristics of butterfly valve. Since the velocity distribution around the disc is confirmed in a visualization, it is confirmed that the free-streamline theory can be used to predict the torque characteristics of disc.

• Fire Science and Engineering
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• v.13 no.2
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• pp.3-11
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• 1999

New examination of a predictive model for the ISO 9705 room-corner test have been m made for materials studied by L S Fire Laboratories, Italy. The ISO 9705 test subjects wall a and ceiling mounted materials to a comer ignition source of 100 kW for a duration of 10 m minutes; if flashover does not occur this is followed by 300 kW for another 10 minutes. The m materials that did not stay in place during combustion because of melting, dripping, or d distorting were simulated by an adjustment to the material's total available energy. For m mat려als that remain in place the simulation model appears to do well in its prl어ictions. A l large-s떠Ie room test results 뾰 compar벼 with the m여el’s prediction also.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2008.04a
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• pp.333-336
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• 2008

This study is the result between the variation of fuel moisture and the risk of forest fire through measuring the change of moisture containing ratio on-site and its average analysis for each diameter of surface dead fuels in the forest. The measurement was performed on six days from the day after a rainfall. The fuel moisture on-site was measured on the day when the accumulated rainfall was above 5.0mm, and the measurements was 2 times in spring. From the pine forest which were distributed around Samcheok and Donghae in Kangwondo, three regions were selected by loose, medium, and dense forest density, and the fuel moisture was measured on the ranges which are less than 0.6cm, 0.6-3.0cm, 3.0-6.0cm, and more than 6.0cm in the forest for six days from the day after a rainfall. The study showed that the moisture containing ratio converged on 3 - 4 days for surface deads fuels which diameter are less than 3.0cm and the convergence was made more than six days for ones which diameters are more than 3.0cm except the surface dead fuel of 3.0-6.0cm diameter of loose forest density.

• Fire Science and Engineering
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• v.17 no.4
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• pp.7-12
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• 2003

The heat of combustion is one of the major physical properties used to determine the fire and explosion hazards of the flammable substances. Empirical equations have been developed to pre-dict the net heats of combustion of organic halogenated compounds based on the atomic contribution method. The method developed in this study was compared with Cardozo's method and Hanley's method. As can be seen from the average absolute deviation(A.A.D.), the proposed equation was found to be best. The proposed equation may serve as an estimation scheme for the heats of combustion of the other organic halogenated compounds.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.371-374
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• 2001

This paper describes a technique that can predict electric fires by detecting a spark signal generated from operation of electric facilities. An electric fire lead a loss of life as well as huge property, therefore it is very Important to predict an electric fire and eliminate the causes of it. Electrical spark which is ranked as majority causes of electric fires has a characterized frequency bandwidthdistinguishedfrompowerfrequenry. In the experiment, various spark signals are simulated in a condition such as short circuit, flashover and surface discharge. The results showed that the monitoring of spark signals can predict electric fires.