Ice accretion poses substantial safety hazards for the manned and unmanned aviation industries. Its study is essential for icing events risk assessment and for the development of efficient ice protection systems. The existing ice accretion measurement techniques—casting, molding, and laser-scanning—are time-consuming, sometimes cumbersome to use, and highly expensive, while hand tracing is inexpensive, but has lower accuracy and time-consuming post-processing. This work presents two low-cost, fast, and easy-to-use measurement techniques for 2D ice accretion profiles. Both employ algorithms of automatic ice shape detection, one based on unmediated image-processing, another based on the processing of manual ice tracings. The techniques are applied to ice accretion experiments conducted in an icing wind tunnel at low Reynolds numbers, and their results are validated against ice thickness caliper measurements. A comparison of the results shows that both techniques accurately measure the leading-edge ice thickness and the 2D shape of the ice accretion profiles. One technique is faster, with higher measurement accuracy, but produces interrupted-line 2D ice profiles and requires good lighting conditions, while the other generates continuous-line 2D profiles and has no application restriction, but it is slower, with lower accuracy. A discussion is conducted, aiming to help one determine the best applications for each ice accretion measurement technique presented.
<div class="section abstract"><div class="htmlview paragraph">In-flight icing can result in severe aerodynamic performance penalties for unmanned aerial vehicles. It is therefore important to understand to which extent ice will build up on fixed-wing unmanned aerial vehicles wings and empennages, namely rudder and elevator, and how this ice will impact the aerodynamic performance and limits the flight envelope. This work investigates numerically icing effects on wing and empennage over a wide range of icing parameters. This is conducted using the icing CFD code FENSAP-ICE on the Maritime Robotics PX-31 Falk UAV. Therefore, the 2D profiles of these airfoils, which are RG-15 for the wing and SD8020 for rudder and elevator, are investigated. The investigated angles of attack are between –5° and 14° in 0.5° increments. Furthermore, the icing conditions are chosen according to the FAA CS 25 Appendix C for continuous maximum and intermittent maximum icing. A broad range of temperatures, droplet median volumetric diameters, and the corresponding liquid water contents are simulated to generate a understanding of the icing effects according to Appendix C. An automation script to enable a more effective parallel execution of the in total 142 simulations of each airfoil has been used. The results of the simulations are used to calculate the change in the lift coefficient <i>c<sub>l</sub></i>, the drag coefficient <i>c<sub>d</sub></i> and the momentum coefficient <i>c<sub>m</sub></i>, and an estimate of the total accreted ice mass.</div><div class="htmlview paragraph">The aerodynamic performance penalties are strongly dependant on the environmental conditions. For both icing envelopes, two different worst case conditions are identified. For continuous maximum this condition lies at –2 °C and a droplet size of 15 μm, for intermittent maximum at –6 °C and 20 μm. For continuous maximum conditions the maximum lift can decrease by 37%, and the drag increase by 107%. For intermittent maximum the maximum lift can decrease by 35%, and the drag increase by 103%.</div></div>
<div class="section abstract"><div class="htmlview paragraph">Atmospheric in-flight icing poses a challenge to all aircraft including unmanned aerial vehicles (UAVs). Aircraft should avoid icing conditions unless they have ways of mitigating the negative effects of icing, e.g., if they are equipped with an ice protection system (IPS). When de-icing systems are used, a certain amount of ice is allowed to accumulate before it is removed. This intercycle ice deteriorates the aerodynamics by reducing the lift, adding mass, and increasing the drag. This study combines the energy that is required to compensate for the added drag of intercycle ice shapes with the energy required for a wing IPS and compares the energy needs for different IPS operations. Two different kinds of intercycle ice shapes are simulated numerically using FENSAP-ICE, one ice shape that would accrete on an unprotected wing and one ice shape that would accrete when using a parting strip, a continuously heated element at the leading edge. The results show that both intercycle ice shapes deteriorate the aerodynamic performance of the airfoil significantly compared to a clean airfoil. Additionally, the results show that the aerodynamics deteriorate fastest in the initial stages of ice accretion, likely caused by fast horn growth and a fast transition from laminar to turbulent flow. The aerodynamic performance is combined with energy requirements of electrothermal de-icing tests in an icing wind tunnel. The results show that de-icing with a parting strip is more energy-efficient than de-icing without a parting strip and anti-icing. In addition, it is found that the energy required for the IPS on a wing is significantly larger than the energy required to compensate for the added intercycle drag. Considering these results during the development and operation of an IPS will help to improve the range and endurance of UAVs in icing conditions.</div></div>
<div class="section abstract"><div class="htmlview paragraph">Icing is a severe hazard to aircraft and in particular to unmanned aerial vehicles (UAVs). One important activity to understand icing risks is the prediction of ice shapes with simulation tools. Nowadays, several icing computational fluid dynamic (CFD) models exist. Most of these methods have been originally developed for manned aircraft purposes at relatively high Reynolds numbers. In contrast, typical UAV applications experience Reynolds numbers an order of magnitude lower, due to the smaller airframe size and lower airspeeds. This work proposes a set of experimental ice shapes that can serve as validation data for ice prediction methods at low Reynolds numbers. Three ice shapes have been collected at different temperatures during an experimental icing wind tunnel campaign. The obtained ice shapes represent wet (glaze ice, −2 °C), mixed (−4 °C), and dry (rime ice, −10 °C) ice growth regimes. The Reynolds number is between <i>Re</i>=5.6…6.0×10<sup>5</sup>, depending on the temperature. The ice shapes were digitized with structure-from-motion, a photogrammetric method that builds 3D models from 2D image sequences. In addition, ice weight measurements and ice density approximations are available. This validation dataset is used in the 2<sup>nd</sup> AIAA Ice Prediction Workshop (IPW) as a base case scenario. The IPW is a recurring activity that aims to compare different 3D icing CFD methods about their ability to predict ice shapes. Overall, this work is adding a much-needed validation case for low Reynolds number icing, which will aid in the verification and development of ice prediction models.</div></div>
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