A flammability limit model for hydrogen-air-diluent mixtures based on heat transfer characteristics in flame propagation
Predicting lower flammability limits (LFL) of hydrogen has become an ever-important task for safety of nuclear industry. While numerous experimental studies have been conducted, LFL results applicable for the harsh environment are still lack of information. Our aim is to develop a calculated non-adi...
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Published in | Nuclear engineering and technology Vol. 51; no. 7; pp. 1749 - 1757 |
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Main Authors | , , |
Format | Journal Article |
Language | Korean |
Published |
2019
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Subjects | |
Online Access | Get full text |
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Summary: | Predicting lower flammability limits (LFL) of hydrogen has become an ever-important task for safety of nuclear industry. While numerous experimental studies have been conducted, LFL results applicable for the harsh environment are still lack of information. Our aim is to develop a calculated non-adiabatic flame temperature (CNAFT) model to better predict LFL of hydrogen mixtures in nuclear power plant. The developed model is unique for incorporating radiative heat loss during flame propagation using the CNAFT coefficient derived through previous studies of flame propagation. Our new model is more consistent with the experimental results for various mixtures compared to the previous model, which relied on calculated adiabatic flame temperature (CAFT) to predict the LFL without any consideration of heat loss. Limitation of the previous model could be explained clearly based on the CNAFT coefficient magnitude. The prediction accuracy for hydrogen mixtures at elevated initial temperatures and high helium content was improved substantially. The model reliability was confirmed for $H_2-air$ mixtures up to $300^{\circ}C$ and $H_2-air-He$ mixtures up to 50 vol % helium concentration. Therefore, the CNAFT model developed based on radiation heat loss is expected as the practical method for predicting LFL in hydrogen risk analysis. |
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Bibliography: | KISTI1.1003/JNL.JAKO201930351883204 |
ISSN: | 1738-5733 2234-358X |