• Journal of the Korean Society for Railway
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• v.7 no.3
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• pp.180-185
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• 2004

The present study investigates the effect of fire growth model on fire development characteristics in a carriage. The parallel processing version of FDS code is used to simulate the fire driven flow in a carriage and two types of fire growth model which are flame spread model and t$^2$ model are examined for the same geometrical condition. The heat release rates(HRR) of both model are similar each other until 30 s after ignition, but the flame spread model predicts 5 times higher than those of the t$^2$ fire model during the quasi-steady fire period. Maximum heat release rate in the case of flame spread model reaches about to 12 MW at 100 s after fire ignition. Also, various database of fire properties for combustible materials and more elaborate combustion model considering the flame spreading phenomena are required for better predictions of fire development characteristics using numerical simulation.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2941-2959
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• 2022

The fire brigade non-suppression probability model is a major factor that should be considered in evaluating fire-induced risk through fire probabilistic risk assessment (PRA), and also uncertainty is a critical consideration in support of risk-informed performance-based (RIPB) fire protection decision-making. This study developed an optimal integrated probabilistic fire brigade non-suppression model considering uncertainty of parameters based on the Bayesian Markov Chain Monte Carlo (MCMC) approach on electrical fire which is one of the most risk significant contributors. The result shows that the log-normal probability model with a location parameter (µ) of 2.063 and a scale parameter (σ) of 1.879 is best fitting to the actual fire experience data. It gives optimal model adequacy performance with Bayesian information criterion (BIC) of -1601.766, residual sum of squares (RSS) of 2.51E-04, and mean squared error (MSE) of 2.08E-06. This optimal log-normal model shows the better performance of the model adequacy than the exponential probability model suggested in the current fire PRA methodology, with a decrease of 17.3% in BIC, 85.3% in RSS, and 85.3% in MSE. The outcomes of this study are expected to contribute to the improvement and securement of fire PRA realism in the support of decision-making for RIPB fire protection programs.

• Journal of the Korean Society of Safety
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• v.31 no.5
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• pp.187-194
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• 2016

A single fire event within a fire area can cause multiple initiating events considered in internal events probabilistic safety assessment (PSA). For an example, a fire event in turbine building fire area can cause a loss of the main feed-water and loss of off-site power initiating events. This fire initiating event could result in special plant responses beyond the scope of the internal events PSA model. One approach to address a fire initiating event is to develop a specific fire event tree. However, the development of a specific fire event tree is difficult since the number of fire event trees may be several hundreds or more. Thus, internal fire events PSA model has been generally constructed by modifications of the pre-developed internal events PSA model. New accident sequence logics not covered in the internal events PSA model are separately developed to incorporate them into the fire PSA model. Recently, many fire PSA models have fire induced initiating event fault trees not shown in an internal event PSA model. Up to now, there has been no analytical comparative study on the constructions of fire events PSA model using internal events PSA model with and without fault trees of initiating events. In this study, the changing process of internal events PSA model to fire events PSA model is analytically presented and discussed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.4
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• pp.242-249
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• 2004

This study was conducted to develop a forest fire occurrence model using meteorological characteristics for the practical purpose of forecasting forest fire danger. Forest fire in South Korea is highly influenced by humidity, wind speed, and temperature. To effectively forecast forest fire occurrence, we need to develop a forest fire danger rating model using weather factors associated with forest fire. Forest fore occurrence patterns were investigated statistically to develop a forest fire danger rating index using time series weather data sets collected from 8 meteorological observation centers. The data sets were for 5 years from 1997 through 2001. Development of the forest fire occurrence probability model used a logistic regression function with forest fire occurrence data and meteorological variables. An eight-province probability model by was developed. The meteorological variables that emerged as affective to forest fire occurrence are effective humidity, wind speed, and temperature. A forest fire occurrence danger rating index of through 10 was developed as a function of daily weather index (DWI).

• Fire Science and Engineering
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• v.28 no.5
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• pp.23-29
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• 2014

The present study has been conducted to investigate the validity of the computational fire model and the results predicted by BRANZFIRE zone model and FDS field model are compared with a real scale fire test with spray fire in a multi-compartment. The liquid spray fires fueled with toluene and methanol are used as the fire source and the quantitative measurement of heat release rate is performed in an isolated ISO-9705 compartment with a standard door opening. The temperature field predicted by FDS model showed good agreement with the measurement in the fire room and the corridor, and BRANZFIRE model also gave acceptable result in spite of its simplicity and roughness. The mean temperature predicted by FDS model corresponds with measurement within maximum discrepancy range of 25% and the overall mean value of FDS model matched well with experimental data less than 10%. This study can contribute to establish the limitation and application scope of computational fire model and provide reference data for applying to reliable fire risk assessment.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.4
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• pp.344-350
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• 2006

The present study investigates the characteristics of fire-driven heat flows and gas concentration in a compartment fire by using the modified VHS model (MVHS). The main idea of this model is to add some source terms for combustion products and oxygen consumption to the original VHS model for providing more accurate and useful information on gas concentration distributions as well as thermal fields. It is found that the present MVHS model shows fairly good agreement with the experimental data and the eddy breakup combustion model. The tilting angle of fire plume calculated by MVHS is larger than that of EBU model because the fire source of VHS is affected by ventilating flow less than EBU. However, this discrepancy is apparently reduced in the downstream region of fire source.

• Journal of the Korea Safety Management & Science
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• v.9 no.2
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• pp.49-57
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• 2007

This Study is to suggest a method of effect evaluation of forest fire on governor station in shrub land. Theoretically, to evaluate effects of forest fire, it is combined that Spread Rate of Forest Fire, Flame Model, and Thermal Radiation Effects Model; i.e. a travel time of forest fire is calculated by Spread Rate of Forest Fire, fire-line intensity is calculated by Flame Model, and effects of fire-line intensity is affected by Thermal Radiation Effects Model. With the aforementioned method, we could carry out the effect evaluation of forest fire on governor station in shrub land and could distinguish scenarios to need protection plan from all scenarios.

• Journal of the Korean Society of Safety
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• v.13 no.1
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• pp.70-76
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• 1998

The smoke filling process for the atrium space containing a fire source is simulated using two types of deterministic fire models : 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 fire field model based on Computational Fluid Dynamics(CFD) theories. This article is focused on finding out the smoke movement and temperature distribution in atrium space which is cubic in shape. 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 the clear height and the smoke layer temperature.

• Journal of the Society of Naval Architects of Korea
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• v.44 no.2 s.152
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• pp.83-92
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• 2007

To improve the fire safety of ships, it is required to prepare the systematic design guideline for fire protection and the way of assessing fire characteristics quantitatively. The introduction of simulation technique based on fire engineering is useful to assess fire safety performance quantitatively. Fire simulation tools are currently developing with U.S.A., Europe and Japan as a leader. Most of current fire simulation tools were developed for building or inland structure. Therefore it is required validation process and development of data base to apply maritime environments. In this paper, I/O parameters of simulation tools such as CFAST and BRI2002 of zone model and FDS and KFX of field model analysed, and designed data base considering maritime environment. The fire simulation for the pool fire model of engine room and its adjacent compartments is performed and evaluated the results.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.320-324
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• 2023

As urbanization accelerates and facilities that use energy increase, human life and property damage due to fire is increasing. Therefore, a fire monitoring system capable of quickly detecting a fire is required to reduce economic loss and human damage caused by a fire. In this study, we aim to develop an improved artificial intelligence model that can increase the accuracy of low fire alarms by mixing DeepSORT, which has strengths in object tracking, with the YOLOv5s model. In order to develop a fire detection model that is faster and more accurate than the existing artificial intelligence model, DeepSORT, a technology that complements and extends SORT as one of the most widely used frameworks for object tracking and YOLOv5s model, was selected and a mixed model was used and compared with the YOLOv5s model. As the final research result of this paper, the accuracy of YOLOv5s model was 96.3% and the number of frames per second was 30, and the YOLOv5s_DeepSORT mixed model was 0.9% higher in accuracy than YOLOv5s with an accuracy of 97.2% and number of frames per second: 30.