Time-resolved spray characterization via unified optical flow and binarization technique

Casey J. O’Brien; Kyungrae Kang; Eric J. Wood; Joshua Yoon; Eric K. Mayhew; Alan Kastengren; Chol-Bum M. Kweon; Tonghun Lee

doi:10.1016/j.fuel.2025.137433

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Time-resolved spray characterization via unified optical flow and binarization technique

Journal article

Open access

Peer reviewed

Time-resolved spray characterization via unified optical flow and binarization technique

Casey J. O’Brien, Kyungrae Kang, Eric J. Wood, Joshua Yoon, Eric K. Mayhew, Alan Kastengren, Chol-Bum M. Kweon and Tonghun Lee

Fuel (Guildford), Vol.407, p.137433

03/01/2026

DOI: https://doi.org/10.1016/j.fuel.2025.137433

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Abstract

Image velocimetry

Liquid combustor

Spray atomization

ASCENT

Machine Learning

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. •Improved unsupervised machine learning enables accurate velocity estimations.•Spray characteristics for six fuel mass flow rates of a conventional jet fuel are visualized under reacting conditions.•Time-resolved droplet size, sphericity, velocity, and breakup length are obtained simultaneously.

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Title: Time-resolved spray characterization via unified optical flow and binarization technique
Creators: Casey J. O’Brien - University of Illinois Urbana-Champaign
Kyungrae Kang - University of Illinois Urbana-Champaign
Eric J. Wood - Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
Joshua Yoon - University of Illinois Urbana-Champaign
Eric K. Mayhew - DEVCOM Army Research Laboratory
Alan Kastengren - Argonne National Laboratory
Chol-Bum M. Kweon - DEVCOM Army Research Laboratory, Aberdeen Proving Ground, MD 21005, USA
Tonghun Lee - University of Illinois Urbana-Champaign
Publication Details: Fuel (Guildford), Vol.407, p.137433
Academic Unit: Alternative Jet Fuel
Publisher: Elsevier Ltd
Grants: 13-C-AJFE-UI-051, Federal Aviation Administration (United States, Washington) - FAA
Identifiers: 99901364590401842
Language: English
Resource Type: Journal article