• Fire Science and Engineering
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• v.17 no.3
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• pp.13-19
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• 2003

In this paper, numerical calculations are conducted to predict the characteristics of the heat transfer and smoke propagation in a cydodrome. The gas flow velocity and temperature around the origin of the fire is obtained by using a plume model and the turbulent flow characteristics are considered by standard $textsc{k}$-$\varepsilon$ turbulent model. In this study, the transient thermal behavior can be used for designing fire detection of large rooms.

• Journal of Mechanical Science and Technology
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• v.16 no.11
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• pp.1485-1496
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• 2002

In order to investigate the fire-induced smoke movement in a three-dimensional room with an open door, numerical and experimental study was performed. The center, wall, and corner fire plumes for various sized fires were studied experimentally in a rectangular pool fire using methanol as a fuel. The numerical results from a self-developed SMEP (Smoke Movement Estimating Program) field model were compared with experimental results obtained in this and from literature. Comparisons of SMEP and experimental results have shown reasonable agreement. As the fire strength became larger for the center fires, the air mass flow rate in the door, average hot layer temperature, flame angle and mean flame height were observed to increase but the doorway-neutral-planeheight and the steady-state time were observed to decrease. Also as the wall effect became larger in room fires, the hot layer temperature, mean flame height, doorway-neutral-planeheight and steady-state time were observed to increase. In the egress point of view considering the smoke filling time and the early spread of plume in the room space, the results of the center fire appeared to be more dangerous as compared with the wall and the corner fire. Thus it is necessary to consider the wall effect as an important factor in designing efficient fire protection systems.

• Fire Science and Engineering
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• v.13 no.2
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• pp.18-25
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• 1999

There are a lot of works for predicting smoke movement in a building experimentally and m numerically. It is Vel${\gamma}$ important to predict a smoke movement in a corridor which is c connected to adjacent spaces. A numerical analysis of smoke movement in an enclosed c corridor is perlormed by a field model. The used field model is develo야d with 3-D u unstructured meshes, PISO Algorithm and buoyant plume model. In this study, tern야~ature a and flow field, some important p하ameters such as smoke spread time, hot layer temperature, c ceiling jet velocity were compared with experimental data which were perlormed in Korea I Ins디tute of Machinery and Materials. And average velocity of ceiling jet by this study is c compared with Hinkley's formula. This paper shows a flow characteristic around the soffit a and average velocity of ceiling jet is i따luenced by geometry of corridor, heat output, and d distance from the fire source.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.5
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• pp.603-613
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• 2004

Extensive forest fires 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 sometimes transported to Korea through Mongolia and eastern China. In this study ground based radiation (visible and UV-B) data measured during May 2003 at Seoul and Kwangju were analyzed to estimate smoke aerosol impacts on solar radiation. Surface criteria air pollutants ($PM_{10}$, CO, $O_3$) data were also obtained from National Institute of Environmental Research (NIER) during smoke aerosol event period (19 May~24 May 2003). Large Aerosol Optical Depth (AOD) 1.0~3.0 was observed during this period due to the influence of the long range transport of smoke aerosol plume from the Russian fires, resulting in short-wavelength direct aerosol radiative forcing of -90~ -200W/$m^2$. These smoke aerosol plume caused decrease in surface UV-B radiation up to 80% and increase in PM_(10) concentration up to 200${\mu}g/m^3$ exceeding the 24 hour ambient air quality standard.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 1996.11a
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• pp.201-206
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• 1996

추진제 연소 기체의 연기도(degree of smoke)의 정량적 측정을 위하여 설계, 제작된 Smoke Chamber를 이용하여, 고체 추진제의 연소 기체에 대한 연기도의 측정 기법을 확립하였으며, 몇가지 유연성 및 무연성 혼합형 고체 추진제 조성들과 복기형 추진제의 연소 기체에 대하여 온·습도 조건의 변화에 따라 연기도를 측정하여 결과를 종합, 분석하였다. 그 결과, Smoke Chamber장비를 이용한 측정을 통하여 추진제 연소 기체중의 연기 생성도를 정량화 함으로써, 기후 조건과 추진제 조성에 따른 연기도의 차이를 구분할 수 있었으며, 일차 연기(primary smoke)와 이차연기(secondary smoke)의 생성 조건 및 이들의 분리 측정이 가능하다는 결론을 얻었다. 측정 파장 영역에 대한 확장을 통하여 측정 범위룰 보완한다면, Smoke Chamber System은 향후 고체 추진제의 연소 기체의 연기 특성의 파악 및 로켓 모터 plume 연구의 기초 자료 획득에 유용하게 이용될 수 있다고 판단된다.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.621-632
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• 2013

The most important things for a forest fire detection system are the exact extraction of the smoke from image and being able to clearly distinguish the smoke from those with similar qualities, such as clouds and fog. This research presents an intelligent forest fire detection algorithm via image processing by using the Gaussian Mixture model (GMM), which can be applied to detect smoke at the earliest time possible in a forest. GMMs are usually addressed by making the model adaptive so that its parameters can track changing illuminations and by making the model more complex so that it can represent multimodal backgrounds more accurately for smoke plume segmentation in the forest. Also, in this paper, we suggest a way to classify the smoke plumes via a feature extraction using HSL(Hue, Saturation and Lightness or Luminanace) color space analysis.

• Proceedings of the Korean Society of Tobacco Science Conference
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• 2000.05a
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• pp.12-21
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• 2000

The smoke from a burning cigarette is classified as mainstream, which is the smoke inhaled by the smoker during a puff, and sidestream, which is defined by ISO 10185 as all smoke which leaves a cigarette during the smoking process other than from the butt end. Most of the sidestream smoke is generated during static burn, that is, in between puffs. The amount of sidestream smoke generated by a cigarette depends on the cigarette construction, tobacco blend, and properties of the cigarette paper, The main paper properties affecting sidestream smoke generation are: porosity, basis weight, type and amount of filler, type and amount of burn additive.Sidestream smoke is composed of a visible phase (small liquid droplets) and an invisible phase (gaseous molecules). This paper focuses on the visible portion of the sidestream smoke. Optical methods, which are based on the relationship between light scattering and density of the rising plume of smoke, have been used successfully by the industry. However, the present trend is to use gravimetric methods where the particulate matter is captured on a Cambridge(R) filter pad and weighed. The gaseous portion of the sidestream smoke, which does not contribute to the visible sidestream smoke, passes through the Cambridge filter pad.Sidestream smoke reduction is achieved by modifying certain mass transport processes occurring in a smoldering cigarette. There are four main pathways for reducing sidestream smoke: A) less tobacco burned, B) slower rate of tobacco combustion, C) more efficient trapping of smoke by the cigarette paper, and D) more complete combustion of tobacco. This paper discusses how the physical properties of paper and cigarette construction affect sidestream smoke reduction via the above four mechanisms.

• International Union of Geodesy and Geophysics Korean Journal of Geophysical Research
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• v.26 no.1
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• pp.43-58
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• 1998

The Kwinana Shoreline Fumigation Experiment (KSFE) took place at Fremantle, WA, Australia between January 23 and February 8, 1995. The CSIRO DAR LIDAR measured plume sections from near the Kwinana Power Station (KPS) stacks to up to about 5 km downstream. It also measured boundary layer aerosols and the structure of the boundary layer on some occasions. Both stages A and C of KPS were used as tracers at different times. The heart of the LIDAR system is a Neodymium-doped Yttrium-aluminum-garnet (Nd:YAG) laser operating at a fundamental wavelength of 1064 nm, with harmonics of 532 nm and 355 nm. For these experiments the third harmonic was used because the UV wavelength at 355 nm is eye safe beyond about 50 m. The laser fires a pulse of light 6 ns in duration (about 1.8 m long) and with an energy (at the third harmonic) of about 70 mJ. This pulse subsequently scattered and absorbed by both air molecules and particles in the atmosphere. A small fraction of the laser beam is scattered back to the LIDAR, collected by a telescope and detected by a photo-multiplier tube. The intensity of the signal as a function of time is a measure of the particle concentration as a function of distance along the line of the laser shot. The smoke plume was clearly identifiable in the scans both before and after fumigation in the thermal internal boundary layer (TIBL). Both power station plumes were detected. Over the 9 days of operation, 1,568 plumes scans (214 series) were performed. Essentially all of these will provide instantaneous plume heights and widths, and there are many periods of continuous operation over several hours when it should be possible to compile hourly average plume statistics as well. The results of four days LIDAR observations of the dispersion of smoke plume in the TIBL at a coastal site are presented for the case of stages A and C.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2002.05a
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• pp.95-101
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• 2002

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1195-1200
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• 2020

The DOM (: Digital Optical Method), which measures the turbidity of chimney smoke, is a method of calculating the turbidity by setting the area to be measured and the contrast area using a low-cost digital camera that can be easily obtained. However, it is difficult to measure clouds and white smoke in a cloudy sky. In this paper, we develop a background sky type model that can represent the background sky and classify the type by periodically photographing it with a digital camera to solve this problem. In addition, based on the model, we develop a filter to optimize white smoke image and prove its excellence through experiments.