期刊
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
卷 47, 期 47, 页码 20662-20675出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijhydene.2022.04.172
关键词
Scramjet engine; Hydrogen fuel; Dynamic characteristics; Cavity flame holder; OH-PLIF
资金
- National Natural Science Foundation of China [62175053]
This study investigates the combustion and oscillation behaviors in a hydrogen-fueled cavity-stabilized scramjet combustor using a high-speed PLIF technique. The spatial distribution of the flame structure under different fuel injection conditions is studied. The results reveal the shift in flame peak position downstream of the cavity with increasing injection pressure. The dynamic characteristics of flames under different flow conditions are analyzed, and the correlation between flame features and hydrogen injection conditions is obtained.
It is vital to analyze the flame characteristics and identify the flame states efficiently in scramjet. Flame combustion and oscillation behaviors in a hydrogen-fueled cavity-stabilized scramjet combustor have been investigated in this study. A 500 Hz high-speed PLIF (planar laser-induced fluorescence) technique with a 20-cm-wide view field is introduced to characterize the combustion flow. The spatial distribution of the flame structure under different fuel injection conditions is studied. The results indicate that the position of the flame peak shifted downstream of the cavity when increasing the injection pressure to a high level. The dynamic characteristics of flames under different flow conditions are analyzed, and the correlation between flame features and hydrogen injection conditions is obtained. These flame features include the vertical range, the flow direction position of the peak flame, the flow direction position of the centroid, the vertical position of the centroid, the flame area, and the flame circumference. For the present cases, the flame of 4.0 Mpa is more unstable than that of 1.5 Mpa under any flow conditions. Moreover, an experiment based on feature extraction results shows that the KNN (K-nearest neighbor) classifier could achieve high accuracy for flame state recognition in this scramjet combustor. (C) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
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