Ice accretion on commercial aircraft operating at high Reynolds numbers has been extensively studied in the literature, but a direct transformation of these results to an Unmanned Aerial Vehicle (UAV) operating at low Reynolds numbers is not straightforward. Changes in Reynolds number have a significant impact on the ice accretion physics. Previously, only a few researchers worked in this area, but it is now gaining more attention due to the increasing applications of UAVs in the modern world. As a result, an attempt is made to review existing scientific knowledge and identify the knowledge gaps in this field of research. Ice accretion can deteriorate the aerodynamic performance, structural integrity, and aircraft stability, necessitating optimal ice mitigation techniques. This paper provides a comprehensive review of ice accretion on fixed-wing UAVs. It includes various methodologies for studying and comprehending the physics of ice accretion on UAVs. The impact of various environmental and geometric factors on ice accretion physics is reviewed, and knowledge gaps are identified. The pros and cons of various ice detection and mitigation techniques developed for UAVs are also discussed.

Ice accretion on rotary-wing unmanned aerial vehicles (RWUAVs) needs to be studied separately from the fixed-wing UAVs because of the additional flow complexities induced by the propeller rotation. The aerodynamics of rotatory wings are extremely challenging compared to the fixed-wing configuration. Atmospheric icing can be considered a hazard that can plague the operation of UAVs, especially in the Arctic region, as it can impose severe aerodynamic penalties on the performance of propellers. Rotary-wing structures are more prone to ice accretion and ice shedding because of the centrifugal force due to rotational motion, whereby the shedding of the ice can lead to mass imbalance and vibration. The nature of ice accretion on rotatory wings and associated performance degradation need to be understood in detail to aid in the optimum design of rotary-wing UAVs, as well as to develop adequate ice mitigation techniques. Limited research studies are available about icing on rotary wings, and no mature ice mitigation technique exists. Currently, there is an increasing interest in research on these topics. This paper provides a comprehensive review of studies related to icing on RWUAVs, and potential knowledge gaps are also identified.

The operational regime of Unmanned Aerial Vehicles (UAVs) is distinguished by the dominance of laminar flow and the flow field is characterized by the appearance of Laminar Separation Bubbles (LSBs). Ice accretion on the leading side of the airfoil leads to the formation of an Ice-induced Separation Bubble (ISB). These separation bubbles have a considerable influence on the pressure, heat flux, and shear stress distribution on the surface of airfoils and can affect the prediction of aerodynamic coefficients. Therefore, it is necessary to capture these separation bubbles in the numerical simulations. Previous studies have shown that these bubbles can be modeled successfully using the Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) but are computationally costly. Also, for numerical modeling of ice accretion, the flow field needs to be recomputed at specific intervals, thus making LES and DNS unsuitable for ice accretion simulations. Thus, it is necessary to come up with a Reynolds-Averaged Navier–Stokes (RANS) equation-based model that can predict the LSBs and ISBs as accurately as possible. Numerical studies were performed to assess the fidelity of various RANS turbulence models in predicting LSBs and ISBs. The findings are compared with the experimental and LES data available in the literature. The structure of these bubbles is only studied from a pressure coefficient perspective, so an attempt is made in these studies to explain it using the skin friction coefficient distribution. The results indicate the importance of the use of transition-based models when dealing with low-Reynolds-number applications that involve LSB. ISB can be predicted by conventional RANS models but are subjected to high levels of uncertainty. Possible recommendations were made with respect to turbulence models when dealing with flows involving LSBs and ISBs, especially for ice accretion simulations.