• Fire Science and Engineering
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• v.26 no.5
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• pp.105-110
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• 2012

The present study investigates the effects of sprinkler spray on fire driven flow characteristics in a compartment based on numerical approach. The FDS (Fire Dynamics Simulator), a widely used fire field model, was used to simulate the fire induced flow and sprinkler spray and a series of grid independence tests have been performed to obtain the optimal grid size. In order to validate the result predicted by FDS model, the calculated results were compared with experimental results of Magnone et al.. The FDS model matches quite well to experiments in temperature profile and mass flux through doorway, however, the discrepancy between the FDS model and experiments increases with increasing water discharge rate. As with previous study, the FDS calculation also shows a decrease of mass flow rate of combustion products through doorway due to the sprinkler spray. This study can contribute to optimize the sprinkler system design and verify the validity of the fire field model with sprinkler spray.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.883-890
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• 2022

Purpose: Currently, in the case of domestic fire fighting facility design, it is difficult to secure highquality manpower due to low design costs and overheated competition between companies, so there is a limit to improving the fire safety performance of buildings. Accordingly, AI-based firefighting design solutions were studied to solve these problems and secure leading fire engineering technologies. Method: Through AutoCAD, which is widely used in existing fire fighting design, the procedures required for basic design and implementation design were processed, and AI technology was utilized through the YOLO v4 object recognition deep learning model. Result: Through the design process for fire fighting facilities, the facility was determined and the drawing design automation was carried out. In addition, by learning images of doors and pillars, artificial intelligence recognized the part and implemented the function of selecting boundary areas and installing piping and fire fighting facilities. Conclusion: Based on artificial intelligence technology, it was confirmed that human and material resources could be reduced when creating basic and implementation design drawings for building fire protection facilities, and technology was secured in artificial intelligence-based fire fighting design through prior technology development.

• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.3
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• pp.118-122
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• 2010

The study presents a standard time-temperature curve to evaluate the fire performance of subway tunnel structures. The central subway section is 135km long in Korea, the fourth longest in the world. The number of subway tunnels has been increasing rapidly and fire risk is proportional to the tunnel length. However, an adequate time-temperature curve for subway tunnel fires does not exist. Therefore, we studied a proposed foreign fire design model for which the heat rate is based on the traffic, and we present an appropriate time-temperature curve for Korean subway tunnels. The ISO 834 curve was used as a fire design model and the temperature distribution in the tunnel was estimated using numerical analysis. This led to a proposal for effective measures against subway tunnel fires.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.260-267
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• 2021

In this paper, we intend to use a new mixed model of YoloV5 and DeepSort. For fire detection, we want to increase the accuracy by automatically extracting the characteristics of the flame in the image from the training data and using it. In addition, the high false alarm rate, which is a problem of fire detection, is to be solved by using this new mixed model. To confirm the results of this paper, we tested indoors and outdoors, respectively. Looking at the indoor test results, the accuracy of YoloV5 was 75% at 253Frame and 77% at 527Frame, and the YoloV5+DeepSort model showed the same accuracy at 75% at 253 frames and 77% at 527 frames. However, it was confirmed that the smoke and fire detection errors that appeared in YoloV5 disappeared. In addition, as a result of outdoor testing, the YoloV5 model had an accuracy of 75% in detecting fire, but an error in detecting a human face as smoke appeared. However, as a result of applying the YoloV5+DeepSort model, it appeared the same as YoloV5 with an accuracy of 75%, but it was confirmed that the false positive phenomenon disappeared.

• Fire Science and Engineering
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• v.32 no.4
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• pp.7-16
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• 2018

In this study, the prediction performance of design fire curves (DF) was evaluated for gas fires in a compartment by using CFAST. The CFAST simulations adopted the 2-stage DF suggested by the previous study and the Quadratic and Exponential DF suggested by Ingason. It was found by comparing the simulation and experimental results that the overall prediction performance of the design fire cures for the spatially-averaged temperature and concentrations of $O_2$ and $CO_2$ was, from the most reasonable to the most inaccurate, 2-stage DF > Quadratic DF > Exponential DF. The CFAST simulation could not predict for the difference in the spatially-averaged temperature and concentrations of $O_2$ and $CO_2$ at door and inner side locations in a compartment. The CFAST simulations also showed a limitation in the prediction of the spatially-averaged temperature at lower layer and the concentration of CO.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 1997.11a
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• pp.353-360
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• 1997

The modeling on fire safety assessment for a tall and narrow atrium is carried out using a reduced and full scale atrium models based on the performances of flow behavior in and near comer fire and smoke ventilation system. The comer (or wall) effects on the flame behavior considering air entrainment into a flame was evaluated theoretically and experimentally. Temperature, upward velocity, inlet air velocity, and pressure difference between the atrium space and atmosphere were measured systematically in a reduced scale model. The performance of the modeling to estimate temperature rise and natural air ventilation volume was verified based on the experimental results. Smoke filling rate from a model fire source set at the center of a tall and narrow atrium is fastest in the other cases in which fire source set in or near a corner. This suggested that the centering of the fire source is acceptable as the fire source position to assess the fire safety design for a tall and narrow atrium.

• Fire Science and Engineering
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• v.32 no.2
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• pp.7-16
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• 2018

In this study, the previous design fire curve for fire simulation was modified and re-suggested. Numerical simulations with the FDS and CFAST were performed for the n-heptane and n-octane pool fires in the ISO 9705 compartment to evaluate the prediction performances of the previous 1-stage and modified 2-stage design fire curves. The numerical results were compared with the experimental temperature and concentrations of $O_2$ and $CO_2$. The FDS and CFAST simulations with the 2-stage design fire curve showed better prediction performance for the variation of temperature and major species concentration than the simulations with 1-stage design fire curve. Especially, the simulations with the 2-stage design fire curve agreed with the experimental temperature more reasonably than the results with the 1-stage design fire curve. The FDS and CFAST simulations showed good prediction performance for the temperature in the upper layer of compartment and the results with the FDS and CFAST were similar to each other. However, the FDS and CFAST showed poor and different prediction performance for the temperature in the lower layer of compartment.

• Fire Science and Engineering
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• v.33 no.3
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• pp.112-120
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• 2019

To improve the reliability of a safety assessment using a fire simulation in domestic PBD, the evaluation method of ASET considering the uncertainties of the input parameters and numerical model of fire simulation was carried out. To this end, a cinema and officetel were selected as the representative fire spaces. The main results were as follows. Considering the uncertainty of the heat release rate, which has the greatest effect on the major physical quantities presented in the life safety standard, significant changes in temperature, CO, and visibility occurred. In addition, when the bias factors reflecting the uncertainty of the numerical model were applied, there were no significant changes in temperature and CO concentration. On the other hand, the visibility was increased considerably due to the low prediction performance of smoke concentration in FDS. Finally, the reason why the physical quantity determining the ASET in domestic PBD is mainly visibility was discussed, and the application of uncertainty of the input parameters and numerical model in a fire simulation was suggested for an accurate ASET evaluation.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.377-386
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• 2021

The A60 class deck penetration piece is a fire-resistant system installed on a horizontal compartment to prevent flame spreading and protect lives in fire accidents in ships and offshore plants. This study deals with approximate optimization using discrete variables for the fire resistance design of an A60 class deck penetration piece using different surrogate models and a genetic algorithm. Transient heat transfer analysis was performed to evaluate the fire resistance design of the A60 class deck penetration piece. For the approximate optimization of the piece, the length, diameter, material type, and insulation density were applied to discrete design variables, and temperature, productivity, and cost constraints were considered. The approximate optimum design problem based on the surrogate models was formulated such that the discrete design variables were determined by minimizing the weight of the piece subjected to the constraints. The surrogate models used in the approximate optimization were the response surface model, Kriging model, and radial basis function-based neural network. The approximate optimization results were compared with the actual analysis results in terms of approximate accuracy. The radial basis function-based neural network showed the most accurate optimum design results for the fire resistance design of the A60 class deck penetration piece.

• Proceedings of KOSOMES biannual meeting
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• 2006.11a
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• pp.283-289
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• 2006

This study is a preparation for the application of FSA (Formal Safety Assessment) to the fire safety of ships. FSA is the new-fashioned methodology proposed to prevent ships from the accidents. To make a base of the fire safety assessment about ship's fire protection design and Classification Society rule, statistical informations for the fire safety engineering are investigated. From results, the necessity of new criterion for ship's fire safety design, the need to study the human behavior in the evacuation from fire, and the development of new fire progress model considering special situations in ships are acknowledged.