Title: Development of CNAFT Model for Lower Flammability Limits of Hydrogen Mixtures for Severe Accident Analysis Code in Nuclear Power Plant // Proceedings of the Ninth International Seminar on Fire and Explosion Hazards: 21-26 April 2019, Saint Petersburg, Russia. Vol. 2
Creators: Jeon J.; Jung H.; Kim S. J.
Organization: Hanyang University
Imprint: Saint Petersburg, 2019
Collection: Общая коллекция
Document type: Article, report
File type: PDF
Language: English
DOI: 10.18720/SPBPU/2/k19-75
Rights: Свободный доступ из сети Интернет (чтение, печать, копирование)
Record key: RU\SPSTU\edoc\61255

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After Fukushima-Daiichi accident, predicting lower flammability limits (LFL) of hydrogen has became an ever-important task for safety of nuclear industry. Experimental identification of LFL for all mixtures in accident conditions is considerably difficult due to wide variety of mixture types. For this reason, we have been developed a calculated non-adiabatic flame temperature (CNAFT) model to facilitate prediction of LFL. The uniqueness of this model is its ability to incorporate heat loss due to radiative heat transfer from flame during propagation using the CNAFT coefficient. The CNAFT model is more consistent with the experimental results for various mixtures compared with the previous model, which relied on the calculated adiabatic flame temperature (CAFT) to predict the LFL. However, the current model does not make a reasonable prediction of LFL under mixtures containing steam. Because steam is classified as radiating species, the presence of steam in the initial condition results more radiant heat loss. Therefore, we developed the extended CNAFT model through simulation of a seven-step combustion mechanism to consider steam effect on radiant heat loss. The extended model shows the maximum relative error with experimental results for various mixture types about 13 % even for containing steam. This study suggests that extended CNAFT model can be effectively utilized for flammability prediction in severe accident analysis code.

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