EGU25-16460, updated on 15 Mar 2025
https://doi.org/10.5194/egusphere-egu25-16460
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Advanced Diagnostic and Forecast System of Icing Conditions for UAV Operational Safety
Satyanarayana Tani1, Helmut Paultisch1, Robin Deutsch2, Arno Fallast3, Thomas Neubauer3, Markus Kucera4, and Reinhard Puffing4
Satyanarayana Tani et al.
  • 1Institute of Microwave and Photonic Engineering, Graz University of Technology, Graz, Austria (satyanarayana.tani@tugraz.at)
  • 2AIRlabs Austria GmbH
  • 3Institut Luftfahrt, FH JOANNEUM GmbH,Graz
  • 4Pegasus Research & Development GmbH

The increasing use of Unmanned Aerial Vehicles (UAVs) across various sectors underscores the necessity for thorough testing under diverse meteorological conditions to ensure operational safety and reliability. The IFIRE project, led by AIRlabs Austria in collaboration with Pegasus Research & Development GmbH, Graz University of Technology, and FH JOANNEUM, addresses this important challenge by focusing on assessing UAV performance in adverse weather conditions, particularly in relation to icing.

The primary objective of the project is to enhance aviation safety and efficiency by integrating advanced weather diagnostic and forecasting capabilities into UAV operations. A comprehensive methodology is proposed, which includes developing a sophisticated weather forecast model, machine learning approaches, conducting flight tests to collect critical data, and evaluating natural icing conditions at the Steinalpl test site in Austria. IFIRE aims to establish new safety and reliability benchmarks for UAVs by creating a state-of-the-art flight-testing area specifically designed for natural icing conditions. The multidisciplinary consortium brings together technical, regulatory, environmental, and operational expertise to address the challenges of UAV testing in icy environments. Information on the initial phase of the project and future steps will be presented.

How to cite: Tani, S., Paultisch, H., Deutsch, R., Fallast, A., Neubauer, T., Kucera, M., and Puffing, R.: Advanced Diagnostic and Forecast System of Icing Conditions for UAV Operational Safety, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16460, https://doi.org/10.5194/egusphere-egu25-16460, 2025.