科学研究

Prof. Alidad Amirfazli obtained his Ph.D. from Toronto University Mechanical Engineering Department and worked in York University Mechnical Engineering Department as the founding Chair since 2013. He was inducted into the Royal Society of Canada (RSC) College of New Scholars, Artists, and Scientists in 2014, and served as the first President. Prof. Amirfazli has been the recipient of the Martha Cook Piper Research prize, Killam Annual Professorship, and Petro-Canada Young Innovator Award. In 2025, He was recipient of the King Charles III Coronation Medal in recognition of his scientific contributions and service to the RSC. He is the Editor for the Advances in Colloid and Interface Science (IF=19.3). He has published in excess of 250 papers with an h-index of 55 and 11,353 citations.

内容摘要：

Aircraft icing occurs when supercooled water droplets impinge and freeze on an aircraft surface. Depending on the atmospheric conditions, the ice accretion can be classified as rime, glaze, or SLD ice. The accumulation of ice significantly degrades aerodynamic performance, which may lead to stall or loss of control. Larger droplets pose a greater risk because their higher inertia allows them to travel farther aft along the wing, potentially forming irregular ridges that disrupt airflow even over protected surfaces. The impact dynamics of supercooled droplets, including splashing, spreading, rebounding, and freezing, have been extensively studied through experiments and simulations. Machine learning (ML) offers a powerful approach for understanding these complex processes. By modeling the intricate relationships between droplet behavior and key parameters such as contact angle, Weber number, and surface roughness, ML enables the development of more accurate predictive models than traditional methods. This capability provides deeper insight into the underlying physics of aircraft icing.

联系人：工程师通用技术科教平台，张子琛

编辑：袁晓慧