• Tunnel and Underground Space
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• v.12 no.2
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• pp.92-98
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• 2002

In this study reduced-scale experiments were conducted to analyze smoke movement in tunnel fire with jet fan, The 1/20 scale experiments were carried out under the froude scaling using gasoline pool fire range from 6.6 to 12.5 cm in diameter with total heat release rate from 0.714 to 4.77 kW. In the case of fires under the 2.5kW, backlaying was reduced about 40cm and smoke was effectively controled in downstream of the fan when operating the fan. The smoke layer was moved down and the ceiling temperature was decreased compared to that of without fan case in upstream of the fan, but the temperature in the lower part of the tunnel was increased.

• Journal of computational fluids engineering
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• v.13 no.4
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• pp.8-12
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• 2008

Heat/smoke detectors are installed in most subway platforms in Korea to detect fire. Subway platform is divided by smoke-control zones for efficient smoke-control. Once the detectors detect heat or smoke, the smoke-control ventilation system in the platform and concourse is activated according to the smoke-control ventilation mode. Smoke-control mode during fires in Korean subway platforms is that the smoke zones operate by exhausting smoke while other zones in the platform and in the concourse which is the upper floor of the platform operate by supplying air or stopping any ventilation. This study is conducted to evaluate performance of passengers' evacuation for various smoke control modes in the subway station. Distribution of smoke and heat due to fire on the platform is analyzed by using Fire Dynamics Simulator(FDS V 4.06) of NIST. Various smoke-control ventilation modes and locations of fire are considered. Evacuation and movement of passengers within the platform is simulated by building EXODUS V.4.0.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.276-279
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• 2008

Heat/smoke detectors are installed in most subway platforms in Korea to detect fire. Subway platform is divided by smoke-control zones for efficient smoke-control. Once the detectors detect heat or smoke, the smoke-control ventilation system in the platform and concourse is activated according to the smoke-control ventilation mode. Smoke-control mode during fires in Korean subway platforms is that the smoke zones operate by exhausting smoke while other zones in the platform and in the concourse which is the upper floor of the platform operate by supplying air or stopping any ventilation. This study is conducted to evaluate performance of passengers' evacuation for various smoke control modes in the subway station. Distribution of smoke and heat due to fire on the platform is analyzed by using Fire Dynamics Simulator(FDS V 4.06) of NIST. Various smoke-control ventilation modes and locations of fire are considered. Evacuation and movement of passengers within the platform is simulated by buildingEXODUS V 4.0.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1342-1347
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• 2011

Advantages of the deeply underground subway are underground space efficiency, high speed, decrease of noise and vibration. However, when fire occurs in the deeply underground subway station, large casualties are occurred like Daegu subway station fire due to the increase of evacuation distance. In this study, a numerical analysis was performed by using the fire and evacuation analysis program FDS+EVAC for smoke movement and evacuation in Beotigogae station among the deeply underground subway station. Heat release rate of carriage fire was set 10MW and the fire growth rate was ultrafast. As a result, the smoke move to the exit at 1085 second. The total evacuation time took 956 second.

• Fire Science and Engineering
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• v.13 no.4
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• pp.20-29
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• 1999

This paper describes the smoke filling process of a fire field model based on a self-developed SMEP(Smoke Movement Estimating Program) code to the simulation of fire induced flows in the two types of atrium space containing a ceiling heat flux. The SMEP using PISO algorithm solves conservation equations for mass, momentum, energy and species, together with those for the modified k- epsilon turbulence model with buoyancy term. Compressibility is assumed and the perfect gas law is used. The results of the calculated upper-layer average temperature and smoke layer interface height has shown reasonable agreement compared with the zone models. The zone models used are the CFAST developed at the Building and Fire Research Laboratory NIST U.S.A. and the NBTC one-room of FIRECALC developed at CSIRO, Australia. The smoke layer interface heights that are important in fire safety were not as sensitive as the smoke layer temperature to the nature of ceiling heat flux condition.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1319-1324
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• 2007

Many researches have been performed to analyze the smoke movement in tunnel fires by using field model. Recently, FDS(Fire Dynamics Simulator) v.4, which is one of the field model and developed from NIST(National Institute of Standards and Technology), is widely used. In tunnel fires, FDS can show detail results in local point, but it has difficulties in boundary condition and taking long computing time as the number of grid increases. So, there is a need to use alternative method for tunnel fire simulation. A zone model is different kind of CFD method and solves ordinary differential equation based on conservation and auxiliary equations. It shows good macroscopic view in less computing time compared to field model. In this study, therefore, to confirm the applicability of CFAST in tunnel fire analysis, numerical simulations using CFAST are conducted to analyze smoke movement in longitudinal ventilation reduced-scale tunnel fires. Then the results are compared with experimental results. The differences of temperature and critical velocity between numerical results and experimental data are over $30^{\circ}C$ and 0.9m/s, respectively. These values are out of error range. It shows that CFAST 6.0 is hard to be used for tunnel fire simulation.

• Journal of IKEEE
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• v.24 no.4
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• pp.1148-1155
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• 2020

Fire must be extinguished as quickly as possible because they cause a lot of economic loss and take away precious human lives. Especially, the detection of smoke, which tends to be found first in fire, is of great importance. Smoke detection based on image has many difficulties in algorithm research due to the irregular shape of smoke. In this study, we introduce a new real-time smoke detection algorithm that reduces the detection of false positives generated by irregular smoke shape based on faster r-cnn of factory-installed surveillance cameras. First, we compute the global frame similarity and mean squared error (MSE) to detect the movement of smoke from the input surveillance camera. Second, we use deep learning algorithm (Faster r-cnn) to extract deferred candidate regions. Third, the extracted candidate areas for acting are finally determined using space and temporal features as smoke area. In this study, we proposed a new algorithm using the space and temporal features of global and local frames, which are well-proposed object information, to reduce false positives based on deep learning techniques. The experimental results confirmed that the proposed algorithm has excellent performance by reducing false positives of about 99.0% while maintaining smoke detection performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.149-154
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• 2014

Detection performance of fire detection in the outdoor depends on weather conditions, the shadow by the movement of the sun, or illumination changes. In this paper, a smoke detection in conjunction with a robust background estimate algorithm to environment change in the outdoor in daytime is proposed. Gaussian Mixture Model (GMM) is applied as background estimation, and also, statistical characteristics of smoke is applied to detect the smoke for separated candidate region. Through the experiments with input videos obtained from a various weather conditions, the proposed algorithms were useful to detect smoke in the outdoor.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1740-1746
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• 2008

The present study performed numerical investigation to analyze the smoke behavior in the rescue station by using the commercial CFD code (FLUENT Ver 6.3). The present study adopted a 10MW ultrafast mode for simulation, and it also used the MVHS(Modify Volumetric Heat Source) model modified from the original VHS(Volumetric Heat Source) model in order to treat the product generation and the oxygen consumption under the stoichiometric state. In addition, the present simulation includes the species conservation equation for the materialization of heat source and the estimation of smoke movement. From the results, the smoke flows are moving along the ceiling because of thermal buoyancy force and as time goes, the smoke gradually moves downward at the vicinity of the entrance. Moreover, without using ventilation, it is found that the smoke flows no longer spread across the cross-passages because the pressure in the non-accident tunnel is higher than that in the accident tunnel.

• Fire Science and Engineering
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• v.11 no.4
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• pp.3-14
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• 1997

The smoke filling process for the atrium space containing a fire source is simulated using two types of deterministic fire model : Zone model and Field model. The zone model used is the CFAST(version 1.6) model developed at the Building and Fire Research Laboratories, NIST in the USA. The field model is a self-developed frie field model based on Computational Fluid Dynamic (CFD) theories. This article is focused on finding out the smoke movement and temperature distribution in atrium space which is cubic in shape. For solving the liked set of velocity and pressure equation, the PISO algorithm, which strengthened the velocity-pressure coupling, was used. Since PISO algorithm is a time-marching procedure, computing time si very fast. A computational procedure for predicting velocity and temperature distribution in fire-induced flow is based on the solution, in finite volume method and non-staggered grid system, of 3-dimensional equations for the conservation of mass, momentum, energy, species and so forth. The fire model i.e Zone model and Field model predicted similar results for clear heights and the smoke layer temperature.