Session: Research Posters

Paper Number: 167852

Characterization of Snow Accretion on Superhydrophobic Surfaces Using High-Speed Imaging for Ice Prevention Strategies 

The accumulation of snow and ice on exposed surfaces presents significant operational challenges across multiple industries, including aerospace, transportation, and energy systems. The efficiency of passive anti-icing and de-icing strategies depends on a thorough understanding of the fluid-solid interaction mechanisms governing snowflake behavior upon impact. This study investigates the impact dynamics and accretion characteristics of snowflakes on superhydrophobic surfaces (SHS) using high-speed imaging at 3000 frames per second (fps), with the goal of improving ice prevention strategies through surface engineering.

Snowflake behavior upon impact is influenced by several parameters, including flake morphology, impact velocity, temperature, and surface wettability. Experiments were conducted in a controlled icing tunnel environment, where natural-like artificial snowflakes were generated and directed toward superhydrophobic test surfaces. Snowflake diameters ranged from 0.50 to 1.41 mm, with impact velocities measured between 1.05 and 2.59 m/s. Contact times varied between 0.67 and 6.67 ms, depending on the kinetic energy of the snowflake and its interaction with the surface. High-speed imaging at 3000 fps allowed for precise visualization and analysis of impact dynamics, enabling detailed tracking of bouncing, adhesion, and fragmentation.

Two distinct post-impact behaviors were identified: bouncing and partial adhesion. Snowflakes smaller than 1.40 mm and impacting at velocities below 2.90 m/s primarily rebounded from the surface with minimal adhesion, whereas larger or faster snowflakes exhibited partial fragmentation or accretion. The dominant energy dissipation mechanism was dependent on impact dynamics, with lower-energy impacts favoring elastic recovery and higher-energy impacts leading to deformation and increased contact area, promoting adhesion.

To quantify these effects, a dimensionless contact time (DCT) parameter was introduced to characterize the interaction between snowflakes and superhydrophobic surfaces. DCT was found to be strongly correlated with energy dissipation, impact velocity, and flake size, providing a predictive framework for assessing surface performance in ice-prone environments. Lower DCT values were associated with shorter contact durations and minimal adhesion, indicating a greater likelihood of bouncing and reduced snow accumulation. This approach enables a systematic evaluation of passive anti-icing surfaces under various environmental conditions.

The findings from this study contribute to the fundamental understanding of multiphase flow dynamics in fluid-solid interactions, particularly in cold environments where phase transitions and adhesion mechanics play a critical role.

These insights have direct implications for the design and implementation of superhydrophobic coatings and surface treatments in aerospace and transportation applications, where ice accumulation can lead to significant safety and performance concerns. By understanding the governing mechanisms of snowflake impact behavior, next-generation passive anti-icing technologies can be developed to enhance efficiency and reliability.

This research advances the study of fluid mechanics, multiphase flows, and experimental fluid dynamics, providing key insights into snowflake impact behavior and energy dissipation mechanisms.

Presenting Author: Ehsan K. B. Nejad University of Toledo

Presenting Author Biography: I am a Research Assistant in the Department of Mechanical, Industrial, and Manufacturing Engineering at the University of Toledo. My research focuses on experimental and computational investigations of surface interactions with environmental elements, particularly in the study of superhydrophobic surfaces for snow and ice mitigation. I utilize high-speed imaging, computational fluid dynamics (CFD), and machine learning techniques to analyze droplet and snowflake impact dynamics, with applications in aerospace, transportation, and renewable energy systems.

My work includes developing predictive models for impact behavior and optimizing surface performance under extreme environmental conditions. I specialize in experimental fluid dynamics, surface engineering, and impact mechanics, contributing to the advancement of anti-icing and de-icing technologies. In addition to research, I actively participate in mentoring students, publishing findings in peer-reviewed journals, and presenting at national and international conferences to share insights and advancements in fluids engineering and surface science.

Authors:

Ehsan K. B. Nejad University of Toledo
Hossein Sojoudi University of Toledo