Summary from the 2nd AIAA Ice Prediction Workshop

被引:0
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作者
Laurendeau, E. [1 ]
Blanchet, M. [1 ]
Zayni, K. [1 ]
Hann, R. [2 ]
Radenac, E. [3 ]
Mussa, I [4 ]
Pueyo, A. [5 ]
机构
[1] Polytech Montreal, Dept Mech Engn, Montreal, PQ H3T 1J4, Canada
[2] Norwegian Univ Sci & Technol, UAV Icing Lab, Dept Engn Cybernet, N-7491 Trondheim, Norway
[3] Univ Toulouse, ONERA, DMPE, Multiphys Dept Energy, F-31055 Toulouse, France
[4] Kingston Univ, Dept Aerosp & Aircraft Engn, London SW15 3DW, England
[5] Bombardier, Icing Aerodynam, Adv Aerodynam Dept, Dorval, PQ H4S 1Y9, Canada
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摘要
The AIAA 2nd Ice Prediction Workshop (IPW-2) assembled varied specialists to perform numerical validation benchmarks towards assessing the state-of-the-art in aircraft ice accretion simulation capabilities. The workshop committee, equally diverse, chose to focus on three experimental tests cases, two swept and one unswept wing, in various icing conditions. The first two cases were selected because of their inherent 3D nature as well as their extensive datasets, while one original unswept wing low-Reynolds-number case representative of Unmanned Aerial Vehicle provided a blank test with data acquired as the workshop developed. All cases contained important tunnel-wall effects. Geometries were supplied, structured and unstructured grids created, and available experimental datasets and flow conditions provided to workshop participants. An effort was placed in standardizing data post-processing, a challenge for 3D configurations. In addition to ice accretion, data such as pressure distribution, stagnation line location, collection efficiency, freezing fraction, heat transfer coefficient, surface temperature, ice mass, minimum and maximum cross section of ice were analyzed experimentally and/or numerically. Results from various Computational Fluid Dynamics workflows were provided by academia, research centers and industries. The data was analyzed via code-to-code and code-to-experiment comparison plots that are available publicly. The paper formally presents the test cases and present some highlights. A methodology and technology gap assessment conclude on the current state-of-the-art and presents possible future workshops directions to improve our understanding and modeling of the subject experimentally and numerically.
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