JOURNAL ARTICLE

The fuel mixing of multi-annular extruded fuel jets in cavity flame holder at supersonic combustion chamber: Computational study.

  • Published In: International Journal of Modern Physics C: Computational Physics & Physical Computation, 2025, v. 36, n. 3. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Kamyarpour, Naser; Hosseinnejad, Farhad; Seyyedi, Seyyed Masoud; Hashemi-Tilehnoee, M. 3 of 3

Abstract

A cavity-flame holder is widely used for the injection of the fuel jet in a supersonic combustor due to high fuel residence time. This paper presents extensive results about the impacts of extruded annular multi-jets for improving fuel mixing inside the cavity flame holder. A three-dimensional model of the cavity with multiple extruded nozzles in different lengths and conditions has been examined in this study to investigate the flow and fuel mixing inside the cavity. In addition, the usage of internal air jets is investigated and extensive comparisons between the elongation of the extruded nozzle and the use of the inner air jets for better fuel distribution are done. The presented results show that the usage of both inner air jet and nozzle elongation significantly enhances the fuel distribution within the cavity flame-holder. The achieved finding confirms that the latter technique is more efficient for the fuel mixing in the combustor of a scramjet engine. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Modern Physics C: Computational Physics & Physical Computation. 2025/03, Vol. 36, Issue 3, p1
  • Document Type:Article
  • Subject Area:Engineering
  • Publication Date:2025
  • ISSN:0129-1831
  • DOI:10.1142/S012918312450195X
  • Accession Number:182210958
  • Copyright Statement:Copyright of International Journal of Modern Physics C: Computational Physics & Physical Computation is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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