Icing remains a major challenge in aviation, affecting safety, efficiency, and environmental performance. Ice accretion degrades aerodynamics, increases fuel consumption, and can create severe operational risks, making effective prevention and certification essential. As regulations evolve around Supercooled Large Droplets (SLD) and EASA CS-25 Appendix O, conventional anti-icing systems—though effective—are energy-intensive and misaligned with net-zero targets. New solutions using smart materials, optimised architectures and advanced sensing technologies offer opportunities to address these limitations.
ICE-SMART proposes a holistic strategy to mitigate icing risks in sustainable aviation by integrating smart materials, sensor networks, simulation tools and climatological analyses. The project will develop synergies between advanced coatings, piezoelectric de-icing and intelligent detection, supported by validated numerical modelling and state-of-the-art test and validation facilities. Photo-electrothermal coatings will provide localised, energy-efficient heating, while piezoelectric actuators will support active ice removal. Integrated sensor networks will deliver real-time detection and predictive capabilities, improving system responsiveness and reducing unnecessary energy use.
Advances in simulation tools and icing test facilities are reshaping certification processes, enabling more accurate modelling of complex icing phenomena and reducing reliance on costly flight tests. ICE-SMART will also analyse climatologies and trends of atmospheric icing conditions, with focus on SLD and related hazard areas, using ERA5 reanalysis data and airborne observations. Together, these innovations support the development of more efficient and environmentally responsible aircraft systems.
Reproducing freezing rain and other SLD conditions in wind tunnels remains technically challenging, resulting in limited ability to test in fully representative conditions. Current experimental facilities and CFD tools struggle to capture SLD‑specific physics, and the scarcity of high‑quality, shared datasets restricts validation of both numerical models and test methodologies. As part of the ICE-SMART project, the participating icing wind tunnel of the RTA will improve its prototype solution for simulating 'freezing rain' (FZRA) SLD capabilities. This will enable it to switch between different certification relevant icing conditions without the need for costly IWT modifications and resulting downtime. This is an effective way for the industry to quickly identify, evaluate and improve the impact of different icing situations on their technologies as de-icing systems, ice sensors and indirect ice detection systems. This will accelerate the development of de-icing technologies significantly. Using large icing wind tunnels to test 1:1 scale models offers significant advantages in developing this technology. Additionally, high-quality 3D scans of the resulting ice accretion will be used to collect unique validation data on SLD “freezing rain” and import it into the existing 'icing' database. This will ultimately serve to further develop the necessary numerical tools. Further fidelity is gained by the application of AI methods to enhance the 3D temporal and spatial resolution.
