The de-icing principle of electrode-to-ice streamers and deep learning-based calculation of ice-melting rate

Abstract

Abstract Within the aviation field, dielectric barrier discharge (DBD) plasma stands as a method utilized for de-icing purposes. This paper assesses the ice-melting capability of electrode-to-ice streamers. The methodology employed is predicated upon the phenomenon termed “thermal explosion of the vibrational reservoir”, which manifests an exponential non-linear increase in gas temperature due to the plasma’s thermal instability mechanism. Utilizing a DBD plasma actuator could provide a more comprehensive understanding of the temperature near the streamers. The ice-melting rates are evaluated by utilizing a deep learning-based target segmentation algorithm. The calculated fastest ice-melting rate Rm is ∼0.97 mm2/s on the plane of the DBD surface, and meanwhile, the highest surface temperature exceeds 200°C. The method of generating these streamers is not exclusively limited to DBD to attain a higher ice-melting rate.