This study introduces a numerical method to accurately depict experimental ice accretions on straight wings using two-dimensional calculations. The method employs a 2D version of the multi-step stochastic model for in-flight icing simulations, previously utilized for [1] Gent, R. W., Dart, N. P., and Cansdale, J. T., “Aircraft icing,” Philosophical Transactions of threedimensional scenarios. The robustness of the level-set front-tracking technique allows for assessing the model’s behavior as the number of steps increases, reaching up to eight. The model’s stochastic characteristics are harnessed to estimate the spanwise variability of the experimental shape by integrating various realizations obtained from identical simulation conditions. From the merged ice shape, it is possible to extract the probability field, the Maximum Combined Cross Section (MCCS), and average ice shape, facilitating comprehensive comparative analyses with experimental results. In conclusion, the suggested approach is employed to compare numerical findings with the experimental data taken from the 1st AIAA Ice Prediction Workshop.

A Two-Dimensional Multi-Step Stochastic Approach for Straight Wing Ice Accretion Analyses

Freschi, Matteo;Donizetti, Alessandro;Bellosta, Tommaso;Guardone, Alberto
2025-01-01

Abstract

This study introduces a numerical method to accurately depict experimental ice accretions on straight wings using two-dimensional calculations. The method employs a 2D version of the multi-step stochastic model for in-flight icing simulations, previously utilized for [1] Gent, R. W., Dart, N. P., and Cansdale, J. T., “Aircraft icing,” Philosophical Transactions of threedimensional scenarios. The robustness of the level-set front-tracking technique allows for assessing the model’s behavior as the number of steps increases, reaching up to eight. The model’s stochastic characteristics are harnessed to estimate the spanwise variability of the experimental shape by integrating various realizations obtained from identical simulation conditions. From the merged ice shape, it is possible to extract the probability field, the Maximum Combined Cross Section (MCCS), and average ice shape, facilitating comprehensive comparative analyses with experimental results. In conclusion, the suggested approach is employed to compare numerical findings with the experimental data taken from the 1st AIAA Ice Prediction Workshop.
2025
AIAA Aviation Forum and Ascend 2025
978-1-62410-738-2
Aerodynamic Coefficients
Computing
Flight Testing
Icing Conditions
Icing Wind Tunnel
Numerical Simulation
Reynolds Averaged Navier Stokes
Spalart Allmaras Turbulence Model
Supercooled Large Droplets
Thermodynamic Model
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1301125
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