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Development of CNAFT model for lower flammability limits of hydrogen mixtures for severe accident analysis code in nuclear power plant

Authors
Jeon JJung HKim, Sung Joong
Issue Date
Apr-2019
Publisher
Peter the Great St. Petersburg Polytechnic University
Keywords
Hydrogen; lower flammability limit; radiative heat transfer; CAFT; CNAFT
Citation
Proceedings of the ninth international seminar on fire and explosion hazards, pp.1376 - 1386
Indexed
OTHER
Journal Title
Proceedings of the ninth international seminar on fire and explosion hazards
Start Page
1376
End Page
1386
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/14194
DOI
10.18720/spbpu/2/k19-75
Abstract
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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Kim, Sung Joong
COLLEGE OF ENGINEERING (DEPARTMENT OF NUCLEAR ENGINEERING)
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