Time-Resolved Spray Characterization via Unified Optical Flow and Binarization Technique

Details

• Creators:
  Brien, Casey J. ; Kang, Kyungrae ; Wood, Eric J. ; Yoon, Joshua ; Mayhew, Eric J. ; Kastengren, Alan ; Kweon, Chol-Bum M. ; Lee, Tonghun
• Corporate Creators:
  United States. Department of Transportation. Federal Aviation Administration. Center of Excellence for Alternative Jet Fuels and Environment ; University of Illinois at Urbana-Champaign
• Corporate Contributors:
  United States. Department of Transportation. Federal Aviation Administration. Office of Environment and Energy
• Subject/TRT Terms:
  ASCENT Chemical Dispersions Chemical Sprays Flammability Image Processing Machine Learning
• Publication/ Report Number:
  j.fuel.2025.137433
• DOI:
  https://doi.org/10.1016/j.fuel.2025.137433
• Resource Type:
  Journal Article
• Right Statement:
  Open Access; https://creativecommons.org/licenses/by/4.0/
• Geographical Coverage:
  United States
• Corporate Publisher:
  Elsevier
• Abstract:
  This work leverages an unsupervised machine learning and advanced image processing techniques to characterize the breakup of fuel sprays in a small-scale combustor under reacting conditions, providing valuable insights into near-nozzle flow phenomenology. The proposed methodology integrates an improved optical flow model on a convolutional neural network to extract flow vectors with a binarization technique to assess droplets’ size and shape across the region of interest. The velocimetry approach demonstrates superior performance compared to a state-of-the-art optical flow model when applied to high-speed X-ray phase contrast spray images, achieving more accurate and reliable flow predictions. Moreover, breakup processes are quantified by breakup length and sphericity in accordance with velocity estimations, allowing a more complete characterization of the flow. This study establishes a robust methodology for analyzing spray morphology and primary breakup in compact combustors, contributing valuable means of understanding and optimizing fuel spray behavior in advanced combustion systems.
• Content Notes:
  This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license https://creativecommons.org/licenses/by/4.0/. Please cite this article as: Casey J. O’Brien, Kyungrae Kang, Eric J. Wood, Joshua Yoon, Eric K. Mayhew, Alan Kastengren, Chol-Bum M. Kweon, Tonghun Lee, Time-resolved spray characterization via unified optical flow and binarization technique, Fuel, Volume 407, Part C, 2026, 137433, ISSN 0016-2361, https://doi.org/10.1016/j.fuel.2025.137433.
• Format:
  PDF
• Funding:
  13-C-AJFE-UI-051
• Collection(s):
  Federal Aviation Administration Federal Highway Administration
• Main Document Checksum:
  urn:sha-512:69829b00cdab83b49ed064fe0e1bd7d518d7e9e4bb632641993518a6ca2459e95bdd1937df8eed7ade9b84947334d6701831e2e14ed3b57b2180825a027cbb93
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/89780/dot_89780_DS1.pdf
• File Type:
  [PDF - 5.27 MB ]