• Journal of Forest and Environmental Science
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• v.33 no.2
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• pp.113-121
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• 2017

In flight particulate matter particularly emissions generated by incomplete combustion processes has become a subject of global concern due to the health problems and environmental impacts associated with them. This has compelled most countries to set standards for coarse and fine particles due to their conspicuous impacts on environment and public health. This contribution therefore explores forest fire emissions and how its particulates affects air quality, damage to vegetation, water bodies and biological functions as architects for lung diseases and other degenerative illnesses such as oxidative stress and aging. Soot was collected from simulated forest fire using a clean glass surface and carefully transferred into amber vials for analysis. Volatile components of soot were collected over 10 mL dichloromethane and analyzed using a QTOF Premier-Water Corp Liquid Chromatography hyphenated to a mass selective detector (MSD), and Gas Chromatograph coupled to a mass spectrometer (GC-MS). To characterize the size and surface morphology of soot, a scanning electron microscope (SEM) was used. The characterization of molecular volatiles from simulated forest fire emissions revealed long chain compounds including octadec-9-enoic acid, octadec-6-enoic acid, cyclotetracosane, cyclotetradecane, and a few aromatic hydrocarbons (benzene and naphthalene). Special classes of organics (dibenzo-p-dioxin and 2H-benzopyran) were also detected as minor products. Dibenzo-p-dioxin for instance in chlorinated form is one of the deadliest environmental organic toxins. The average particulate size of emissions using SEM was found to be $11.51{\pm}4.91{\mu}m$. This study has shown that most of the emissions from simulated forest fire fall within $PM_{10}$ particulate size. The molecular by-products of forest fire and particulate emissions may be toxic to both human and natural ecosystems, and are possible precursors for various respiratory ailments and cancers. The burning of a forest by natural disasters or man-made fires results in the destruction of natural habitats and serious air pollution.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2008.11a
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• pp.490-494
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• 2008

We simulated a forest fire which was occurred in Yangyang area on 2005 and compared a results between two different weather conditions(real weather condition and mean weather condition since 1968) using FARSITE, which is a forest fire spread simulator for preventing and predicting fire in USDA. And, we researched a problem in the transition for introducing, so we serve the basic method for prevention and attacking fire. In the result, severe weather condition on 2005 effected a forest fire behavior. The rate of spread under real weather condition was about 4 times faster than mean weather condition. Damaged area was about 10 time than mean weather condition. Therefore, Climate change will make a more sever fire season. As we will encounter to need for accurate prediction in near future, it will be necessary to predict a forest fire linked with future wether and fuel condition.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.2
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• pp.137-143
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• 2008

In the present study, a forest fire spread was simulated with a three-dimensional, fully-transient, physics-based, computer simulation program. Physics-based fire simulation is based on the governing equations of fluid dynamics, combustion and heat transfer. The focus of the present study is to perform parametric study to simulate fire spread through flat and inclined wildland with vegetative fuels like trees or grass. The fire simulation was performed in the range of the wind speeds and degrees of inclination. From the results, the effect of the various parameters of the forest fire on the fire spread behavior was analyzed for the future use of the simulation in the prediction of fire behavior in the complex terrain.

• Asian Journal of Atmospheric Environment
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• v.3 no.1
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• pp.1-8
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• 2009

Enhancement of aerosol optical thickness (AOT) and surface aerosol mass concentration in Korea for an active forest fire episode in Northeast Asia were estimated by Community Multi-scale Air Quality (CMAQ) model. MODIS/TERRA remote detects of fires in Northeast Asia for May 2003 gave a constraint for estimation of wildfire emissions with an NDVI distribution for recent five years. The simulated wildfire plumes and enhancement of AOT were evaluated and well resolved by comparing multiple satellite observations such as MODIS, TOMS, and others. Scatter plots of observed daily mean aerosol extinction coefficient versus $PM_{10}$ concentration in ground level in Korea showed distinctively different trends based on the ambient relative humidity.

• Journal of the Korea Safety Management & Science
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• v.24 no.4
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• pp.125-134
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• 2022

Forest fires in Korea usually start in the fall and occur every year until spring. Most wildfires are human resources that combine topographical characteristics and carelessness, and failure to respond in the initial stage and lack of cleanup are spreading to large-scale wildfires. In order to prevent these wildfires, active cooperation from the public is essential. As can be seen from recent wildfires, the attention of the public is needed above all else because large-scale wildfires in Korea are occurring due to the people's negligence. If a wildfire spreads and becomes large, it causes damage to life and property, and the damage is irreversible. In this study, various methods were used to prevent forest fires and improve initial suppression ability. In order to minimize damage, the model analyzed by the 119 Special Rescue Team in Gangwon, Chungcheong and nearby forest fires was analyzed on the combustion progress and wind direction by time period. The propagation speed by the wind direction was simulated. Until now, most of the wildfires have been extinguished by firefighting, but I hope that the Forest Service will take the lead and maintain coordination with related organizations.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1273-1283
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• 2022

Recently, forest fires have frequently occurred due to climate change, leading to human and property damage every year. The forest fire monitoring technique using remote sensing can obtain quick and large-scale information of fire-damaged areas. In this study, the Gangneung and Donghae forest fires that occurred in March 2022 were analyzed using the spectral band of Sentinel-2, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI) to classify the affected areas of forest fires. The U-net based convolutional neural networks (CNNs) model was simulated for the fire-damaged areas. The accuracy of forest fire classification in Donghae and Gangneung classification was high at 97.3% (f₁=0.486, IoU=0.946). The same model used in Donghae and Gangneung was applied to Uljin and Samcheok areas to get rid of the possibility of overfitting often happen in machine learning. As a result, the portion of overlap with the forest fire damage area reported by the National Institute of Forest Science (NIFoS) was 74.4%, confirming a high level of accuracy even considering the uncertainty of the model. This study suggests that it is possible to quantitatively evaluate the classification of forest fire-damaged area using a spectral band and indices similar to that of the Compact Advanced Satellite 500 (CAS500-4) in the Sentinel-2.

• Journal of Korean Society of Forest Science
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• v.100 no.1
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• pp.70-78
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• 2011

In this study, we develop a fire stochastic simulation model by season based on the historical fire data in Korea. The model is utilized to generate sequences of fire events that are consistent with Korean fire history. We employ a three-stage approach. First, a random draw from a Bernoulli distribution is used to determine if any fire occurs for each day of a simulated fire season. Second, if a fire does occur, a random draw from a geometric multiplicity distribution determines their number. Last, ignition times for each fire are randomly drawn from a Poisson distribution. This specific distributional forms are chosen after analysis of Korean historical fire data. Maximum Likelihood Estimation (MLE) is used to estimate the primary parameters of the stochastic models. Fire sequences generated with the model appear to follow historical patterns with respect to diurnal distribution and total number of fires per year. We expect that the results of this study will assist a fire manager for planning fire suppression policies and suppression resource allocations.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.116-130
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• 2019

In South Korea, forest fire occurrences are increasing in size and duration due to various factors such as the increase in fuel materials and frequent drying conditions in forests. Therefore, it is necessary to minimize the damage caused by forest fires by appropriately providing the probability of forest fire risk. The purpose of this study is to improve the Daily Weather Index(DWI) provided by the current forest fire forecasting system in South Korea. A new Fire Risk Index(FRI) is proposed in this study, which is provided in a 5km grid through the synergistic use of numerical weather forecast data, satellite-based drought indices, and forest fire-prone areas. The FRI is calculated based on the product of the Fine Fuel Moisture Code(FFMC) optimized for Korea, an integrated drought index, and spatio-temporal weighting approaches. In order to improve the temporal accuracy of forest fire risk, monthly weights were applied based on the forest fire occurrences by month. Similarly, spatial weights were applied using the forest fire density information to improve the spatial accuracy of forest fire risk. In the time series analysis of the number of monthly forest fires and the FRI, the relationship between the two were well simulated. In addition, it was possible to provide more spatially detailed information on forest fire risk when using FRI in the 5km grid than DWI based on administrative units. The research findings from this study can help make appropriate decisions before and after forest fire occurrences.

• Transactions on Electrical and Electronic Materials
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• v.9 no.4
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• pp.143-146
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• 2008

In this study the thermal impact characteristics by forest fire are extensively investigated using temperature controlled ovens. The test conditions for thermal impact damage are simulated according to the characteristics of natural forest fire. The test pieces are suspension porcelain insulators made by KRI in 2005 for transmission lines. In the thermal impact cycle tests with $300\;^{\circ}C$ thermal impact gradient (-70 to $230\;^{\circ}C$), cycling in 10 minute periods, no critical failures occurred in the test samples even with long cycle times. But in tests with thermal impact gradient from room temperature to $200-600\;^{\circ}C$, cycling in 10 to 30 minute periods, there were critical failures of the porcelain insulators according to the thermal impact gradient and quenching method. In the case of thermal impact by forest fire, it was found of that duration time is more important than the cycling time, and the initiation temperature of porcelain insulator failures is about $300\;^{\circ}C$, in the case of water quenching, many cracks and fracture of the porcelain occurred. It was found that the thermal impact failure is closely related to the displacement in the cement by thermal stress as confirmed by simulation. It was estimated that the initiation displacement by the thermal impact of $300\;^{\circ}C$ is about 0.1 %. Above 1% displacement, it is expected that the most porcelain insulators would fail.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.114-114
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• 2010

산불에 노출되는 경우 열충격으로 작용하는 패턴과 특성을 검토하여 가속열화시험에 반영하는 것이 필요하다. 본 연구에서는 산불환경을 모의하여 복합열화시험을 실시하기위해 복합가속열화 챔버를 구축하였다. 온도는 주로 $200^{\circ}C$에서 최대 $1000^{\circ}C$까지 변화를 주면서 예비시험과 본시험 실하였다.