• Fire Science and Engineering
• /
• v.23 no.2
• /
• pp.36-40
• /
• 2009

This paper presents research about the development of electrical fire cause classification in order to improve the reliability of electrical fire statistics and to collect electrical fires data efficiently. The incorrect and biased knowledge for electrical fires changed the classification of certain types of fires, from non-electrical to electrical. It is convenient and required to develop the standardized form that makes, in the assessment of the cause of electrical fires, the fire investigators directly ticking the appropriate box on the fire report form or making an assessment of a text description. In this study, newly developed electrical fire cause classification structure, which is well-defined hierarchical structure so that there are not any relationship or overlap between cause categories, is suggested. Also the suggested classification structure can be used for electrical fire investigation and statistics, which minimizes the mistake that diagnose non-electrical fires into electrical ones.

• Fire Science and Engineering
• /
• v.18 no.4
• /
• pp.1-15
• /
• 2004

The following matters were confirmed through the analysis of property losses due to fires in Korea, the U.S., and Japan. 1. Korean statistics on property losses are not the most detailed of the three centuries, and they have a lot of limitations to analyze the actual condition of property losses due to fires. 2. The percentage which takes up property losses due to fires in GDP is on the decrease in the U.S. and Japan, but increase in Korea. In addition, from 1994, it has occupied almost the same rate in Korean ad compared with the U.S. and Japan. 3. When inflation are taken into consideration, property losses due to fires in the U.S. and Japan have decreased, but in Korea, they have increased except for the recent 2 years.

• The Korean Journal of Ecology
• /
• v.23 no.2
• /
• pp.125-129
• /
• 2000

Gunung Gede Pangrango National Park is one of the Long-term Ecological Research Site in Indonesia. In the late 1997, the fires have burnt and destroyed nearly 300 ha forest in this park. and G. Masigit was the largest burnt area (250 ha) of nine locations of hot spot recognized. Undergrowth vegetation got the most severe impacts. Almost undergrowth vegetation in various location were totally burnt. However, within three months following burning new seedlings such as Omalanthus populneus, Macaranga, Trema orientalis and Eupatorium appeared in the forest floor- The number of mycoflora recorded in burnt forest was interestingly increased in post forest fires site. Forest fires in G. Masigit had also affected the wild life population and diversity. For example, the number of bird species and the number of soil insects in burnt forest was significantly reduced. The forest fires had also great impact on soil. such as on soil organic contents, bulk density, colour, consistency, permeability and the activity of soil microorganisms.

• Fire Science and Engineering
• /
• v.11 no.4
• /
• pp.15-23
• /
• 1997

A series of measurements and visualization to investigate the extingushiment of water sprays with pool fires is presented. Fire source is a small-scale pool burner with methanol, ethanol and gasoline. Measurements of temperature, O2, CO2, and CO concentrations along the plume centerline are carried out to observe pool structures without water sprays. Visualization by the Ar-ion laser sheet flow pattern of droplets of the sprays above the pool fires. It is observed than in the case of methanol and ethanol, water sprays continuously penetrate into the center of fuel surfaces. The gasoline pool fire allows intermittent penetration of water sprays because of pulsating characteristics of the gasoline flame. To evaluate the cooling effect of the fuel surface by the sprays, the temperature was measured at the fuel surface. As soon as the mists reach the fuel surface of methanol and ethanol, the temperatures of the fuel surface decrease rapidly below the boiling point, and then the fires are extinguished. Due to the application of mist upon the gasoline fire, though the fuel temperature decrease abruptly at the time of the injection, such a repid decrease do not continue till the extinction point.

• Fire Science and Engineering
• /
• v.30 no.1
• /
• pp.12-16
• /
• 2016

Propane fires of 1000 to 3000 kW in the ISO 9705 fire room were simulated using FDS to study the problem of decreasing temperature with increasing fire size. A criterion is proposed for under-ventilated fires. The computed temperature at 2000 kW and above was lower than that at 1500 kW. The heat release rate was limited by a lack of oxygen in the simulation. It was found that the heat release rate can therefore be a criterion for under-ventilated fires in simulations. Fires of 1700 kW and above in the ISO 9705 fire room are predicted to be under-ventilated.

• Journal of Korean Society for Atmospheric Environment
• /
• v.20 no.4
• /
• pp.437-450
• /
• 2004

Extensive forest fire activities occurred across the border in Russia, particularly east of Lake Baikal between the Amur and Lena rivers in May 2003. These forest fires released large amounts of particulates and gases into the atmosphere, resulting in adverse effects on regional air quality and the global radiation budget. Smoke pollution from the Russian fires near Lake Baikal was transported to Korea through Mongolia and eastern China. On 20 May 2003, a number of large fires were burning in eastern Russian, producing a thick, widespread pall of smoke over much of Northeast Asia. In this study, separation technique was used for aerosol retrieval application with imagery from MODIS aboard TERRA satellites. MODIS true-color image shows the location of fires and the grayish color of the smoke plumes over Northeast Asia. Aerosol optical thckness (AOT) retrieved from the MODIS data were compared with fire hot spots, ground-based radiation data and TOMS -based aerosol index data. Large AOT, 2.0-5.0 was observed on 20 May 2003 over Korea due to the influence of the long range transport of smoke aerosol plume from the Russian fires, while surface observed fine mode of aerosol size distribution increased.

• Fire Science and Engineering
• /
• v.23 no.5
• /
• pp.133-137
• /
• 2009

The Fire Dynamics Simulator (FDS), a computational fluid dynamics model for fire simulation, was applied to propylene vertical wall fires, to confirm its accuracy in simulation of vertical wall fires. The temperature profiles at the center of the burner obtained for mass loss rates per unit area in the range of $7.0{\sim}29.29g/m^2-s$ were compared with those of experiment. Comparisons of the heat flux distributions along the vertical centerline on the wall surface were made with the measurements. It was shown that the computed temperature profiles were in good agreement with the experiment. It was also noted that the peak temperature near the wall was underpredicted, the heat flux was too high compared with the measurements, and hence improvements are required for FDS in simulation of the vertical wall fires.

• Fire Science and Engineering
• /
• v.32 no.1
• /
• pp.99-107
• /
• 2018

Diesel cars employ a diesel particulate filter (DPF) to reduce the discharge of fine dust. However, cases of fires caused by DPFs have been reported in diesel cars. In this study, I examined the regulation of exhaust gas and exhaust gas recirculation in diesel cars. Then, I analyzed cases of car fires caused by DPFs, their characteristics, car fire factors related to DPFs and preventive measures, and their consideration in investigations of the causes of fires. Finally, regarding car fire investigations, this study proposed a process of proving that fires are caused by DPFs.

• Journal of Forest and Environmental Science
• /
• v.40 no.1
• /
• pp.24-34
• /
• 2024

Fire, being primarily a natural phenomenon, is impossible to control, although it is feasible to map the forest fire risk zone, minimizing the frequency of fires. The spread of a fire starting in any stand in a forest can be predicted, given the burning conditions. The natural cover of the land and the safety of the population may be threatened by the spread of forest fires; thus, the prevention of fire damage requires early discovery. Satellite data and geographic information system (GIS) can be used effectively to combine different forest-fire-causing factors for mapping the forest fire risk zone. This study mainly focuses on mapping forest fire risk in the Madikhola watershed. The primary causes of forest fires appear to be human negligence, uncontrolled fire in nearby forests and agricultural regions, and fire for pastoral purposes which were used to evaluate and assign risk values to the mapping process. The majority of fires, according to MODIS events, occurred from December to April, with March recording the highest occurrences. The Risk Zonation Map, which was prepared using LULC, Forest Type, Slope, Aspect, Elevation, Road Proximity, and Proximity to Water Bodies, showed that a High Fire Risk Zone comprised 29% of the Total Watershed Area, followed by a Moderate Risk Zone, covering 37% of the total area. The derived map products are helpful to local forest managers to minimize fire risks within the forests and take proper responses when fires break out. This study further recommends including the fuel factor and other fire-contributing factors to derive a higher resolution of the fire risk map.

• Electronics and Telecommunications Trends
• /
• v.35 no.1
• /
• pp.80-88
• /
• 2020

This paper describes the development trends and service provision examples of disaster occurrence and spread prediction technology for various disasters such as tsunamis, floods, and fires. In terms of fires, we introduce the WIFIRE system, which predicts the spread of large forest fires in the United States, and the Metro21: Smart Cities Institute project, which predicts the risk of building fires. This paper describes the development trends in tsunami prediction technology in the United States and Japan using artificial intelligence (AI) to predict the occurrence and size of tsunamis that cause great damage to coastal cities in Japan, Indonesia, and the United States. In addition, it introduces the NOAA big data platform built for natural disaster prediction, considering that the use of big data is very important for AI-based disaster prediction. In addition, Google's flood forecasting system, domestic and overseas earthquake early warning system development, and service delivery cases will be introduced.