• Fire Science and Engineering
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• v.23 no.5
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• pp.96-102
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• 2009

Forest fire ignition and spread characteristics are needed as basic data in fire management. Slope aspect of ignition point, spread direction, and wind direction at that time were analyzed and regression equations were proposed for predicting burned area, fire perimeter, head spread rate, and flank spread rate using combustion time using 101 forest fires broken out between 2007 and 2009 spring. 57% forest fires of investigated numbers were ignited in south, southwest, and southeast aspects and 68% of forest fires were spreaded to east, southeast, and northeast influenced by westerly wind. About 11.8ha forest was burned and 0.5km fire perimeter increase was predicted per hour. Head and flank spread rate were calculated 0.13km and 0.05km, respectively.

• Journal of Korean Society of Forest Science
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• v.90 no.6
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• pp.781-787
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• 2001

The spread rate of forest fire was analyzed on Samcheok forest fire that broke out on April 7, 2000 in Kunduck-Myun, Samcheok-City, Kangwon-Province and lasted for about 9 days. The spatial database including topography, overstory species distribution, micro-climate, daily fire front lines for the area was built using GIS and the daily spread pattern was investigated to determine a multiple regression equation to estimate forest fire spread rate. The results of the investigation showed that, on the first day, the forest fire spreaded out extremely fast up to 12.3m/min at about 10 a.m. until noon. After that, the forest fire spread rate fluctuated and slowed down as low as below 1m/min and quenched on April 15. The daily area-based spread rate along the fire spread line got to the peak of about 5,700ha on April 11, of which spread rates were recorded as 2.84m/min in the first half and 1.10m/min in the second half. Also, it was found that slope aspect, wind velocity and % area distribution of Pinus densiflora are the major factors affecting the spread rate of forest fire in this area.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.4
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• pp.75-79
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• 2008

As Information Technology developed, Information requirement has been went higher. In the field of GIS(Geographic Information System) more information is processed more quickly and accurately. Especially, quick analysis of forest fire information (topography, ignition point, weather condition, etc.) over a wide area is essential in order to minimize victim, environmental damage, and economical damage, decide course of evacuating, estimate a fire spread course, and attack resource arrangement. We determined a fire spread distance at each unit time through an experiment with various slope degrees and distinction of flat, upslope and downslope. For the tests on the upslope, as the slope increased, the rate of spread increased. On the downslope in contrast with the upslope, as the slope increased, the rate of spread decreased. We analyzed a spread rate of forest fire on each slope as the method classified upslope(+) and downslope(-) using the results obtained from the experiment. Consequently, the proposed method is able to be used to effectively support the attack of forest fire by providing accurate predictions of fire spread.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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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%.

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.4
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• pp.213-217
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• 2003

Forest fire spread and intensity were modeled as a function of wind and fuel. Spread rate and intensity of forest fire were related to weight and thickness of forest fuel beds and to wind speed. Forest fire spread rate and fire intensity were differentiated according to wind speed. Rapid wind speed causes a faster forest fire spread rate and greater fire intensity than does slow wind speed. Relative burning time of the fire from beginning to end in the model was 161 sec at a wind speed of 0.5 m/sec and 146 sec at 1m/sec on the model. Average forest lire spread rate was 0.014 m/sec at a wind speed of 0.5 m/sec and 0.020 m/sec at 1m/sec. Average fire intensity was 0.183 ㎾/m at a wind speed of 0.5 m/sec, 0.259 ㎾/m at 1m/sec. Fire intensity was greater when forest fire spread rate was rapid.

• Journal of the Korea Safety Management & Science
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• v.9 no.2
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• pp.49-57
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• 2007

This Study is to suggest a method of effect evaluation of forest fire on governor station in shrub land. Theoretically, to evaluate effects of forest fire, it is combined that Spread Rate of Forest Fire, Flame Model, and Thermal Radiation Effects Model; i.e. a travel time of forest fire is calculated by Spread Rate of Forest Fire, fire-line intensity is calculated by Flame Model, and effects of fire-line intensity is affected by Thermal Radiation Effects Model. With the aforementioned method, we could carry out the effect evaluation of forest fire on governor station in shrub land and could distinguish scenarios to need protection plan from all scenarios.

• Fire Science and Engineering
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• v.23 no.1
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• pp.15-20
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• 2009

For the effective management of forest fire, understanding of regional forest fire patterns is needed. In this paper, forest fire ignition and spread characteristics were analyzed based on forest fire statistics. Fire occurrences, burned area, rate of spread, and burned area per fire between 1991 and 2007 were parameterized for the cluster analysis, which results were displayed using GIS to detect spatial patterns of forest fire. Administrative districts such as cities and counties were classified into 5 clusters by fire susceptibility. Metropolitan areas had fire characteristics that were infrequent, slow rate of spread, and small burned area. However, 4 cities and counties showing fast rate of spread, and large burned area, in the eastern regions of Taeback Mountain range, were the most susceptible areas to forest fire. The next vulnerable cities and counties were located in the West and South Coast area.

• Fire Science and Engineering
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• v.34 no.1
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• pp.11-17
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• 2020

As performance-based design (PBD) has a direct impact on evacuation safety assessments, designing fire scenarios based on real fire tests is essential. To improve the reliability of the PBD for fire safety in multiplexes, information on fire behavior, such as heat release rate (HRR) and fire spread rate, are provided in this study by conducting a standard fabric flammability test. To this end, several chairs were arranged in a pattern that resembled a theater-style seating. The peak HRR and heating value per unit mass for each chair ranged from 415 kW to 988 kW and 15.2 MJ/kg to 23.8 MJ/kg, respectively. The heating values per unit mass of the new and old chairs were 23.6 MJ/kg and 16.7 MJ/kg, respectively. As the quantity of plastic and cushioning materials in the new chairs was more than that of the old ones, the new chairs were more vulnerable to fire hazards. Furthermore, when the chairs were arranged in a line, the fire spread rate was observed to be 0.39-0.42 m/min, regardless of the ignition location. Finally, a fire growth curve showing the peak HRR and fire spread rate was also demonstrated.

• Fire Science and Engineering
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• v.22 no.2
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• pp.63-69
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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-D 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-D 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 a prediction of an approximately 10% upward tendency under wind velocity conditions of 1 to 2m/s, and of an approximately 20% downward tendency under those of 3m/s.

• Journal of the Korean Wood Science and Technology
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• v.30 no.3
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• pp.18-25
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• 2002

Research to discuss the fire performance of materials requires tools for measuring their burning characteristics and validated fire growth models to predict fire behavior of the materials under specific tire scenarios using the measured properties as input for the models. In this study, burning characteristics such as time to ignition, weight loss rate, flame spread, heat release rate, total heat evolved, and effective heat of combustion for four types of wood-based materials were evaluated using the cone calorimeter and inclined panel tests. Time to ignition was affected by not only surface condition and specific gravity of the tested materials but also the type and magnitude of heat source. Results of weight loss rate, measured by inclined panel tests, indicated that heat transfer from the contacted flame used as the heat source into the inner part of the specimen was inversely proportional to specific gravity of material. Flame spread was closely related with ignition time at the near part of burning zone. Under constant and severe external heat flux, there was little difference in weight loss rate and total heat evolved between four types of wood-based panels. More applied heat flux caused by longer ignition time induced a higher first peak value of heat release rate. Burning characteristics data measured in this study can be used effectively as input for fire growth models to predict the fire behavior of materials under specific fire scenarios.