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Modeling In-Flight Ice Accretion Under Uncertain Conditions

Authors :
Alberto Guardone
Tommaso Bellosta
Giulio Gori
Olivier Le Maitre
Pietro Marco Congedo
Uncertainty Quantification in Scientific Computing and Engineering (PLATON)
Centre de Mathématiques Appliquées - Ecole Polytechnique (CMAP)
École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
Dipartimento di Scienze e Tecnologie Aerospaziali [Milano] (DAER)
Politecnico di Milano [Milan] (POLIMI)
European Project: 722734,H2020 Pilier Excellent Science,H2020-MSCA-ITN-2016,UTOPIAE(2017)
European Project: 824310,H2020,H2020-MG-2018-SingleStage-INEA,ICE GENESIS(2020)
Source :
Journal of Aircraft, Journal of Aircraft, 2022, 59 (3), ⟨10.2514/1.C036545⟩, Journal of Aircraft, American Institute of Aeronautics and Astronautics, 2021, pp.1-15. ⟨10.2514/1.C036545⟩, Journal of Aircraft, 2021, pp.1-15. ⟨10.2514/1.C036545⟩
Publication Year :
2022
Publisher :
American Institute of Aeronautics and Astronautics (AIAA), 2022.

Abstract

International audience; In-flight ice accretion under parametric uncertainty is investigated. Three test cases are presented which reproduce experiments carried out at the NASA's Glenn Icing Research Tunnel (IRT) facility. A preliminary accuracy assessment, achieved comparing numerical predictions against experimental observations, confirm the robustness and the predictiveness of the computerized icing model. Besides, sensitivity analyses highlight the variance of the targeted outputs with respect to the different uncertain inputs. In rime icing conditions, a predominant role is played by the uncertainty affecting the airfoil angle of attack, the cloud liquid water content and the droplets’ mean volume diameter. In glaze icing condition, the sensitivity analysis shows instead that the output variability is due mainly to the ambient temperature uncertainty. Results expose a major criticality of standard uncertainty quantification techniques. The issue is inherent the approximation of the full icing model behavior in domain regions scarcely affected by ice build up. To mitigate the issue, a non-linear regression method is proposed and applied.

Details

ISSN :
15333868 and 00218669
Volume :
59
Database :
OpenAIRE
Journal :
Journal of Aircraft
Accession number :
edsair.doi.dedup.....1c154b63992522b379d9addcd1de46de
Full Text :
https://doi.org/10.2514/1.c036545