Super-Cooled Large Droplet Experimental Reproduction, Ice Shape Modeling, and Scaling Method Assessment

Rocco, Edward T.; Han, Yiqiang; Kreeger, Richard E.; Palacios, José

doi:10.2514/1.j059401

Cited by 5 publications

(1 citation statement)

References 26 publications

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“…At present, ice detection facing SLD environment is a difficult point in engineering practice in the world, including the capabilities and limitations of detection equipment and engineering tools, the impact of special water droplet breakup characteristics on icing, etc. [4][5][6][7][8][9][10]. Existing studies have proposed a variety of identification technologies for SLD environment [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Research on Icing Classification Method Based on Wind Tunnel Test with Double Impact Surface Probe

Liu,

Huang,

et al. 2024

J. Phys.: Conf. Ser.

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Facing supercooled large water droplet environment, an effective ice detection method is a prerequisite to implement the avoidance strategy and get out of the icing environment of SLD as soon as possible. Fiber-optic icing sensors were arranged on the double impact surface probe. The probe was used for icing wind tunnel test. Different machine learning algorithms were used to establish the classification method of icing conditions based on multi-sensor ice thickness information fusion. An appropriate algorithm was selected for the classification method to detect icing conditions. The icing classification method based on SVM could effectively distinguish the conventional water droplet icing condition from the SLD icing condition, and it has significant potential on aviation industry application.

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