Preprints
https://doi.org/10.5194/egusphere-2026-800
https://doi.org/10.5194/egusphere-2026-800
18 Mar 2026
 | 18 Mar 2026
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

Investigation of supercooled water droplet sticking efficiency during power transmission line icing using digital holography

Pu Zhang, Dengxin Hua, Jiang Cheng, Jingjing Liu, Xiang Xu, Yitong Miao, and Jun Wang

Abstract. Transmission line icing severely threatens the safety of the power grid. Accurate prediction of the sticking efficiency (the proportion of supercooled droplets that remain on the conductor after impact, excluding bouncing and splashing) is critical for preventing and mitigating icing disasters. Traditional prediction models for sticking efficiency typically exhibit significant errors under complex conditions (e.g. varying wind speeds and precipitation intensities), thereby limiting their practical applications. To overcome this drawback, a multi-stage coupled model based on coaxial digital holography was proposed, in which supercooled droplet diameters, velocities, and collision angles were precisely measured. These measurements were integrated into a multi-stage framework that couples droplet impact dynamics and thermodynamics to compute the sticking efficiency, thereby overcoming the accuracy limitations of existing models in complex environments. Experimental results show that the new model’s prediction errors remain below 3.5 % across a range of conditions, which is a significant improvement over traditional models, underscoring its enormous potential in engineering applications.

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Pu Zhang, Dengxin Hua, Jiang Cheng, Jingjing Liu, Xiang Xu, Yitong Miao, and Jun Wang

Status: open (until 22 Apr 2026)

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Pu Zhang, Dengxin Hua, Jiang Cheng, Jingjing Liu, Xiang Xu, Yitong Miao, and Jun Wang
Pu Zhang, Dengxin Hua, Jiang Cheng, Jingjing Liu, Xiang Xu, Yitong Miao, and Jun Wang

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Short summary
Ice forming on power lines during freezing rain can cause serious damage to electricity networks. To better predict this risk, we studied how supercooled water droplets hit, stick to, and freeze on power lines. Using a new optical measurement method and laboratory experiments, we built a more accurate prediction model. Our results show that icing can be predicted much more reliably, which can help improve early warning and protection of power grids.
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