Accretion of ice on aircraft wings can severely degrade aerodynamic performance, posing safety risks and operational challenges for both manned and unmanned aircraft. Predicting the drag increase caused by ice accretions can improve mission planning and the operation of ice protection systems. While few analytical expressions predict the drag increase of iced airfoils based on atmospheric and flight parameters, all were developed for the Reynolds numbers of manned aircraft (mostly between 1,500,000 and 15,000,000). Unmanned aerial vehicles (UAVs) typically operate at lower Reynolds numbers (typically between 250,000 and 1,000,000), requiring specialized research in icing conditions. This study compares existing drag correlations to drag increases simulated numerically with computational fluid dynamics (CFD) solver Ansys FENSAP-ICE on the wing of a small UAV. The results show a significant difference between the predicted and the simulated drag coefficients. Based on the numerical results, new predictions are developed based on the mass that has impinged on the aircraft and the freezing fraction. Using separate equations for different freezing fractions, all datapoints can be predicted within 23% of the simulated values, with an average error of less than 6%. Although the training dataset is limited, applying the equations to cases outside the original dataset still presents good predictions. Even though this study relies on numerical results without direct experimental validation, the results are promising for developing more accurate wing drag prediction methods for low-Reynolds-number cases.
Wallisch et al. (Wed,) studied this question.
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