This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
UAV Icing: Experimental Validation Data for Predicting ice Shapes at Low Reynolds Numbers
Technical Paper
2023-01-1372
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
Icing is a severe hazard to aircraft and in particular to unmanned aerial vehicles (UAVs). One important activity to understand icing risks is the prediction of ice shapes with simulation tools. Nowadays, several icing computational fluid dynamic (CFD) models exist. Most of these methods have been originally developed for manned aircraft purposes at relatively high Reynolds numbers. In contrast, typical UAV applications experience Reynolds numbers an order of magnitude lower, due to the smaller airframe size and lower airspeeds. This work proposes a set of experimental ice shapes that can serve as validation data for ice prediction methods at low Reynolds numbers. Three ice shapes have been collected at different temperatures during an experimental icing wind tunnel campaign. The obtained ice shapes represent wet (glaze ice, −2 °C), mixed (−4 °C), and dry (rime ice, −10 °C) ice growth regimes. The Reynolds number is between Re=5.6…6.0×105, depending on the temperature. The ice shapes were digitized with structure-from-motion, a photogrammetric method that builds 3D models from 2D image sequences. In addition, ice weight measurements and ice density approximations are available. This validation dataset is used in the 2nd AIAA Ice Prediction Workshop (IPW) as a base case scenario. The IPW is a recurring activity that aims to compare different 3D icing CFD methods about their ability to predict ice shapes. Overall, this work is adding a much-needed validation case for low Reynolds number icing, which will aid in the verification and development of ice prediction models.
Authors
Topic
Citation
Hann, R., Müller, N., Lindner, M., and Wallisch, J., "UAV Icing: Experimental Validation Data for Predicting ice Shapes at Low Reynolds Numbers," SAE Technical Paper 2023-01-1372, 2023, https://doi.org/10.4271/2023-01-1372.Also In
References
- Hann , R. and Johansen , T. 2020
- Hann , R. 2020
- Gao , M. , Hugenholtz , C.H. , Fox , T.A. , Kucharczyk , M. et al. Weather Constraints on Global Drone Flyability Scientific Reports 2021 1 13 https://doi.org/10.1038/s41598-021-91325-w
- Goyal , R. 2018
- Shahab , H. 2019 https://doi.org/10.4324/9781351212991-4
- Hann , R. UAV Icing: Challenges for Computational Fluid Dynamic (CFD) Tools International Conference on Computational Fluid Dynamics (ICCFD11) 2022
- Laurendeau , E. , Bourgault-Cote , S. , Ozcer , I.A. , Hann , R. et al. Summary from the 1st AIAA Ice Prediction Workshop AIAA AVIATION 2022 Forum https://doi.org/10.2514/6.2022-3398
- Hann , R. and Müller , N. https://doi.org/doi:10.18710/5XYALW
- Tiihonen , M. , Jokela , T. , Makkonen , L. , and Bluemink , G. VTT Icing Wind Tunnel 2.0 Winterwind Conference 2016
- Hann , R. UAV Icing: Ice Accretion Experiments and Validation SAE Technical Paper 2019-01-2037 2019 https://doi.org/10.4271/2019-01-2037
- Jokela , T. , Tiihonen , M. , and Karlsson , T. Validation of Droplet Size in the VTT Icing Wind Tunnel Test Section Winterwind Conference 2019
- Kaikkonen , V.A. , Molkoselkä , E.O. , and Mäkynen , A.J. Droplet Size Distribution and Liquid Water Content Monitoring in Icing Conditions with the ICEMET Sensor Proceeding International Workshop on Atmospheric Icing of Structures 2019
- Kaikkonen , V.A. , Molkoselkä , E.O. , and Mäkynen , A.J. A Rotating Holographic Imager for Stationary Cloud Droplet and Ice Crystal Measurements Optical Review 27 2020 205 216
- SAE International 2015
- Westoby , M.J. , Brasington , J. , Glasser , N.F. , Hambrey , M.J. et al. ‘Structure-from-Motion’photogrammetry: A Low-Cost, Effective Tool for Geoscience Applications Geomorphology 179 2012 300 314
- Betlem , P. , Birchall , T. , Ogata , K. , Park , J. et al. Digital Drill Core Models: Structure-from-Motion as a Tool for the Characterisation, Orientation, and Digital Archiving of Drill Core Samples Remote Sensing 12 2020 330
- Broeren , A.P. , Potapczuk , M.G. , Lee , S. , Malone , A.M. et al. Ice-accretion test results for three large-scale swept-wing models in the NASA Icing Research Tunnel 8th AIAA Atmospheric and Space Environments Conference 2016 3733
- Li , L. , Liu , Y. , Zhang , Z. , and Hu , H. Effects of Thermal Conductivity of Airframe Substrate on the Dynamic Ice Accretion Process Pertinent to UAS Inflight Icing Phenomena International Journal of Heat and Mass Transfer 131 2019 1184 1195 https://doi.org/10.1016/j.ijheatmasstransfer.2018.11.132