Modeling In-Flight Ice Accretion Under Uncertain Conditions

Gori, Giulio; Congedo, Pietro Marco; Maître, Olivier Le; Bellosta, Tommaso; Guardone, Alberto

doi:10.2514/1.c036545

Cited by 23 publications

(8 citation statements)

References 47 publications

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“…Parameters which strongly influence the final ice shape are displayed in Figs. 15. It shows that the mesh sensitivity and number of multi-step time intervals have a greater influence on glaze ice shapes.…”

Section: Case-241 242mentioning

confidence: 94%

“…Additionally it has been utilized for the optimization of heat fluxes in uncertain cloud environments [14]. To that end, PoliMIce has also be utilized to investigate Uncertainty Quantification (UQ) in icing conditions [15]. The aim of this work is to further validate the PoliMIce ice accretion software using the test cases from the 1 st AIAA Ice Prediction Workshop.…”

Section: Introductionmentioning

confidence: 99%

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Assessment of the PoliMIce toolkit from the 1st AIAA Ice Prediction Workshop

Morelli

Bellosta

Donizetti

et al. 2022

AIAA AVIATION 2022 Forum

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This paper presents the Politecnico di Milano Icing Research Group's contribution to the 1 st AIAA Ice Prediction Workshop. A collection of two-and three-dimensional test cases to predict the collection efficiency and ice accretion are simulated using the PoliMIce ice accretion software suite. Test cases include the prediction of the collection efficiency on a three-elementairfoil and on a full-scale horizontal swept tail plane. Additionally, test cases for the simulation of ice shapes on a NACA23012 airfoil and on swept wings with varying degrees of sweep angle are assessed. The numerical predictions are evaluated and compared to high quality experimental measurements taken from the NASA Glenn Icing Research Tunnel. In general the numerical predictions compare favourably with the experimental measurements. Key droplet impingement characteristics including the collection efficiency peak and impingement limits are captured. Meanwhile distinctive ice features of rime and glaze ice regimes are depicted in the simulations. However, there remains scope for further improvement of models as highlighted by the more challenging test cases such as the three-element-airfoil and the test cases which produce glaze ice shapes with large horns.

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Section: Case-241 242mentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Assessment of the PoliMIce toolkit from the 1st AIAA Ice Prediction Workshop

Morelli

Bellosta

Donizetti

et al. 2022

AIAA AVIATION 2022 Forum

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“…The reliability and accuracy of the three-dimensional, unsteady modelling techniques is also of genuine concern due to a high level of uncertainty in aircraft icing. Gori et al investigated 6 the uncertainties of in-flight icing conditions under Appendix-C icing conditions [26]. Their work investigated the influence of parameters including the AoA, MVD, and LWC on the final ice shapes.…”

Section: Ice Predictionmentioning

confidence: 99%

Numerical Investigation of Ice Formation on a Wing with Leading-Edge Tubercles

Morelli

Beretta

Guardone

et al. 2023

Journal of Aircraft

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“…Gori et al [14] conducted a study to understand and quantify the effects of parameter uncertainties on the numerical modeling of in-flight icing shapes, proposing a non-linear approach for the propagation of the uncertainties. To the authors' knowledge, no applications of Uncertainty Propagation techniques for the analysis and design of Thermal IPS are available in the open literature.…”

Section: Introductionmentioning

confidence: 99%

Robust Optimization of a Thermal Anti-Ice Protection System in Uncertain Cloud Conditions

Gallia¹,

Gutiérrez²,

Gori³

et al. 2024

Journal of Aircraft

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This paper presents a framework for the robust optimization of the heat flux distribution for an anti-ice electrothermal ice protection system under uncertain conditions. The considered uncertainty regards a lack of knowledge concerning the characteristics of the cloud, i.e., the liquid water content and the median volume diameter of water droplets, and the accuracy of measuring devices, i.e., the static temperature probe. Uncertain parameters are modeled as random variables, and two sets of bounds are investigated. A forward uncertainty propagation analysis is carried out using a Monte Carlo approach exploiting a surrogate models. The optimization framework relies on a gradient-free algorithm (mesh adaptive direct search), and two different objective functions are considered, namely, the 95 quantile of the freezing mass rate and the statistical frequency of the fully evaporative operating regime. The framework is applied to a reference test case, revealing a potential to improve the heat flux distribution of the baseline design. A new heat flux distribution is proposed, and it presents a more efficient use of the thermal power, increasing flight safety even at nonnominal environmental conditions.

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Modeling In-Flight Ice Accretion Under Uncertain Conditions

Cited by 23 publications

References 47 publications

Assessment of the PoliMIce toolkit from the 1st AIAA Ice Prediction Workshop

Assessment of the PoliMIce toolkit from the 1st AIAA Ice Prediction Workshop

Numerical Investigation of Ice Formation on a Wing with Leading-Edge Tubercles

Robust Optimization of a Thermal Anti-Ice Protection System in Uncertain Cloud Conditions

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