2018
DOI: 10.7731/kifse.2017.31.2.052
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Assessment of the Habitability for a Cabinet Fire in the Main Control Room of Nuclear Power Plant using Sensitivity Analysis

Abstract: Numerical simulations were performed to evaluate the habitability of an operator for a cabinet fire in the main control room of a nuclear power plant presented in NUREG-1934. To this end, a Fire Dynamics Simulator (FDS), as a representative fire model, was used. As the criteria for determining the habitability of operator, toxic products, such as CO, were also considered, as well as radiative heat flux, upper layer temperature, smoke layer height, and optical density of smoke. As a result, the probabilities of… Show more

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Cited by 5 publications
(1 citation statement)
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“…To evaluate the uncertainty of various fire models used for fire risk assessment, NUREG-1824 conducted fire modeling on 340 full-scale fire experiment results [5]. Bias factors (δ) and relative standard deviations (    ) of the main physical quantities of fire models presented as this code and the verification and validation (V&V) results can be used to determine the possibility of a specific object exceeding its thermal, owing to a fire [9,10]. Furthermore, a performance-based design assessment model with improved accuracy has been proposed recently in Korea, in which the δ of the fire model is applied to fire modeling prediction results [11].…”
mentioning
confidence: 99%
“…To evaluate the uncertainty of various fire models used for fire risk assessment, NUREG-1824 conducted fire modeling on 340 full-scale fire experiment results [5]. Bias factors (δ) and relative standard deviations (    ) of the main physical quantities of fire models presented as this code and the verification and validation (V&V) results can be used to determine the possibility of a specific object exceeding its thermal, owing to a fire [9,10]. Furthermore, a performance-based design assessment model with improved accuracy has been proposed recently in Korea, in which the δ of the fire model is applied to fire modeling prediction results [11].…”
mentioning
confidence: 99%