• 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.

• Nuclear Engineering and Technology
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• v.40 no.5
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• pp.349-364
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• 2008

Over the years, probabilistic risk assessment (PRA) research activities conducted at the U.S. Nuclear Regulatory Commission (NRC) have played an essential role in support of the agency's move towards risk-informed regulation. These research activities have provided the technical basis for NRC's regulatory activities in key areas; provided PRA methods, tools, and data enabling the agency to meet future challenges; supported the implementation of NRC's 1995 PRA Policy Statement by assessing key sources of risk; and supported the development of necessary technical and human resources supporting NRC's risk-informed activities. PRA research aimed at improving the NRC's understanding of risk can positively affect the agency's regulatory activities, as evidenced by three case studies involving research on fire PRA, human reliability analysis (HRA), and pressurized thermal shock (PTS) PRA. These case studies also show that such research can take a considerable amount of time, and that the incorporation of research results into regulatory practice can take even longer. The need for sustained effort and appropriate lead time is an important consideration in the development of a PRA research program aimed at helping the agency address key sources of risk for current and potential future facilities.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2011.11a
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• pp.253-257
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• 2011

본 논문에서는 설계중인 스마트원전에 대한 화재 PSA 방법과 결과 그리고 민감도분석 결과를 기술하였다. 기존 국내 원전 화재 PSA에서는 EPRI의 fire PRA implementation guide에 따라 수행해왔었다. RG 1.189에 따르면 NFPA 805를 채택하는 원전이나 신규원전은 NUREG/CR-6850 방법에 따라 화재 PSA를 수행해야만 한다. 스마트는 설계단계의 원전이기에 화재 PSA 수행위한 충분한 설계정보가 없고 스마트의 선행호기도 없다. 따라서 NUREG/CR-6850 방법을 스마트에 모두 적용할 수 없어 EPRI fire PRA implementation guid와 NUREG/CR-6850 방법을 사용하여 스마트 원전에 대한 화재 PSA를 수행하였다. 화재 PSA 결과에 중요한 영향을 미치는 요인들에 대해 민감도분석을 수행하였다.

• Proceedings of the Korean Nuclear Society Conference
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• 2005.10a
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• pp.638-639
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• 2005

• Proceedings of the KSR Conference
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• 2003.10b
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• pp.265-270
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• 2003

Though the probability of tunnel fire accident is very low, but critical fatalities are expected when it occurred. In this study the effect of critical safety parameters on tunnel fire accident are examined using probabilistic technique. Fire detection time, smoke spread velocity, passenger escape velocity, flash-over time, and emergency service arrival time are considered. In order to estimate the uncertainties of input parameters Monte Carlo simulation are used, and fatalities for each assumed accident scenarios are obtained as results. For the efficiency of iterative calculation PRA(Probabilistic Risk Analysis) code is developed in this study. As a result fire detection have large effect.

• Journal of the Korean Society for Railway
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• v.7 no.4
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• pp.302-306
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• 2004

Many long railway tunnels without emergency evacuation system or ventilation system are under construction or in-use in Korea. In the case of tunnel-fire, many fatalities are occur in current condition. Current safety level is estimated in this study, for the efficient investment on safety. But so many uncertainties in major input parameters make the safety estimation difficult. In this study, probabilistic techniques are applied for the consideration of uncertainties in major input parameters. As results of this study, accident scenarios and survival ratio under tunnel fire accident are determined for various conditions.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.87-96
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• 2020

The purpose of this paper is to develop a fire HRA (Human Reliability Analysis) procedure for full power operation of domestic NPPs (Nuclear Power Plants). For the development of fire HRA procedure, the recent research results of NUREG-1921 in an effort to meet the requirements of the ASME/ANS PRA Standard were reviewed. The K-HRA method, a standard method for HRA of a domestic level 1 PSA (Probabilistic Safety Assessment) and fire related procedures in domestic NPPs were reviewed. Based on the review, a procedure for the fire HRA required for a domestic fire PSA based on the K-HRA method was developed. To this end, HRA issues such as new operator actions required in the event of a fire and complexity of fire situations were considered. Based on the four kinds of HFE (Human Failure Event) developed for a fire HRA in this research, a qualitative analysis such as feasibility evaluation was suggested. And also a quantitative analysis process which consists of screening analysis and detailed analysis was proposed. For the qualitative analysis, a screening analysis by NUREG-1921 was used. In this research, the screening criteria for the screening analysis was modified to reduce vague description and to reflect recent experimental results. For a detailed analysis, the K-HRA method and scoping analysis by NUREG-1921 were adopted. To apply K-HRA to fire HRA for quantification, efforts to modify PSFs (Performance Shaping Factors) of K-HRA to reflect fire situation and effects were made. For example, an absence of STA (Shift Technical Advisor) to command a fire brigade at a fire area is considered and the absence time should be reflected for a HEP (Human Error Probability) quantification. Based on the fire HRA procedure developed in this paper, a case study for HEP quantification such as a screening analysis and detailed analysis with the modified K-HRA was performed. It is expected that the HRA procedure suggested in this paper will be utilized for fire PSA for domestic NPPs as it is the first attempt to establish an HRA process considering fire effects.