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This is chapter 6 of the State of Environmental Science in Svalbard (SESS) report 2022. Uncrewed aerial vehicles (UAVs), or drones, have become an established tool for a wide range of scientific applications. Today, UAVs are used for example for mapping geomorphic features, glaciers, and heritage sites, counting reindeer, atmospheric measurements, sea ice monitoring and in many other ways. However, the technology is still relatively new and there is a substantial untapped potential for using UAVs for scientific goals. This report’s main focus is to highlight practical issues related to planning and conducting fieldwork in Svalbard, as well as storing and sharing drone-based datasets. One of the key challenges in the field is related to a lack of standardised data storage and metadata requirements. This means that many datasets are not adequately described and/or archived so they are publicly available This means that drone-based data can often not be reused, for example for long-term monitoring studies. The practical recommendations about planning and conducting fieldwork with UAVs in Svalbard is intended to help and guide scientists to become more successful in conducting drone missions. Svalbard has several special challenges related to its remoteness, high latitude, and fauna. Recommendations are given on how SIOS can strengthen and expand scientific drone applications in Svalbard. The recommendations are intended to make it easier to conduct more complex missions in Svalbard and to train and fund new users. Furthermore, it is recommended to create a forum for scientists to discuss drone-related issues, e.g. to develop community standards for data.

In-flight icing on unmanned aerial vehicles is a severe hazard and imposes limits on the operational envelope. Icing has been shown to lead to substantial aerodynamic performance losses on lifting surfaces and propellers. To quantify the performance loss of the propeller in icing conditions, this study proposes a model that describes the performance of a fixed-wing UAV propeller in icing conditions. For the development of this model, experiments in an icing wind tunnel have been performed to evaluate the performance loss of the propeller in different icing conditions. From the thrust and torque measurements, a model for the transient performance of a propeller in icing conditions has been developed. The model calculates thrust and torque as a function of the temperature, liquid water content, advance ratio, and the rotation rate of the propeller. This model contains an estimator for the ice accumulation on the propeller, the ice shedding forces of the propeller, and the performance of the iced propeller. This model can for example be used to estimate the flight performance of UAVs in icing conditions. It could also be applied for path and mission planning tools, autopilot, flight simulators, performance-based ice detection and the design of ice protection systems.

A problem that unmanned aerial vehicles (UAV) operators face when dealing with in-flight icing conditions is a reliable way to assess icing severity risk. This paper aims to develop an icing severity index that looks at the combined effect of icing performance degradation on wings and propellers for a specific UAV. The index developed in this paper will provide UAV operators with an easier way to assess icing risk. Icing severity indices for the wings and propeller are computed separately to highlight the individual contributions of power increase. Combining them yields the unified icing severity index. To develop the unified icing severity index, a focus is put on the power consumption increase resulting from aerodynamics performance degradation that is due to ice. The wings and propeller will be subject to different icing conditions specified by median volume diameter (MVD), and temperature. Two propeller rotation rates are also tested for each of these icing conditions. The tests are performed through computer simulations using a pre-existing simulation framework. Each condition will yield the power consumption from these simulations, where the UAV will fly the same straight path. These parameters are compared against the baseline, clean condition, to yield an index. Results from a case-study show significant differences in power consumption between different icing conditions. The ice affects performance degradation on the wing and propeller differently depending on ice type. The propeller degradation is the least severe for glaze ice and the worst for the rime ice case. The wing degradation is the least severe for rime ice case and worst for the glaze ice case. Combining the wing and propeller degradation show 8 times increase in power consumption for rime ice compared to clean condition in the worst case.

This is chapter 3 of the State of Environmental Science in Svalbard (SESS) report 2020 (https://sios-svalbard.org/SESS_Issue3). The polar regions are among the most sensitive areas of the Earth and changes in the Arctic have global consequences. Therefore, more and better Arctic research is needed, and unmanned vehicles are an important tool in this research. This report provides a review of research conducted with unmanned vehicles in Svalbard. That includes vehicles that travel in air, on water and underwater. The main focus is on unmanned aerial vehicles (UAVs). UAVs are well-suited for Arctic research for several reasons. The Arctic regions lack high vegetation and big settlements, making them ideal for aerial observations. UAVs can access glaciers, mountains, and other difficult areas. They are cheaper and have a lower environmental impact than manned flights. Svalbard has an international research infrastructure and frequent flight connections, making it a hotspot for Arctic research. However, there are several challenges to the use of unmanned vehicles in the Arctic. These include magnetic interference, low temperatures, harsh weather conditions, and wildlife. Most optical sensors cannot be used during the dark season between October and February. This review shows that the researchers using unmanned vehicles in Svalbard can be divided into two groups: basic and advanced users. The majority of researchers today are basic users. They use off-the-shelf UAVs to enhance their fieldwork. The most common application is mapping. A minority of the researchers are advanced users. This group includes users of unmanned marine vehicles and fixed-wing UAVs.

This thesis focused on atmospheric ice accretions, aerodynamic icing penalties, and ice protection systems (IPS) on fixed-wing unmanned aerial vehicles (UAVs). The motivation for this work was to increase the knowledge about the mechanisms and effects of atmospheric in-flight icing on UAVs. These insights were directed to aid in the development of systems to mitigate the adverse effects of icing on UAVs. Therefore, this thesis aimed to answer the following questions: Why is icing on UAVs a problem? What are the specific issues of icing on UAVs? How can we predict ice accretions on UAVs? What impacts does icing have on UAVs? How can we protect UAVs from icing? And, how much energy is required for an active UAV IPS? The methods of this thesis included experimental tests and numerical simulations. Four experimental campaigns were conducted in the scope of this work. Icing wind tunnel tests were performed at Cranfield University in fall 2018 and at the facilities of the Technical Research Centre of Finland (VTT) in spring and fall 2019. Conventional wind tunnel tests with artificial ice shapes were conducted in summer 2019 in the fluid mechanics laboratory at the Norwegian University of Science and Technology (NTNU). Numerical simulations were conducted with LEWICE (2D) and FENSAP-ICE. The first objective of this thesis was to investigate the special issues related to icing on UAVs and to identify differences to icing on manned aircraft. This included technical aspects originating from disparities in airframe size, airspeed, propulsion, mission objectives, etc. Operational challenges included differences in icing environments, difficulties in icing forecasting, and path-planning. Furthermore, an overview was given over general topics related to icing detection, IPS, icing wind tunnels, and simulation methods of icing for UAVs. Also, wind turbine icing was highlighted as a research field with significant similarities and potential synergies with UAV icing. The second objective of the thesis was to collect experimental ice shapes from icing wind tunnel tests and compare them to numerical icing simulations. This work was relevant because the numerical methods used in this thesis have originally been developed for manned aircraft applications and were not validated for UAVs. One of the main concerns was the difference in the Reynolds number regime, which for UAVs is about an order of magnitude lower than for manned aircraft. The comparison between numerical and experimental ice shapes revealed significant limitations of the codes. In general, both numerical simulation tools seemed to predict lower ice masses, smaller icing limits, and smoother ice shapes. The smallest deviations occurred for rime ice, the largest for glaze, especially for LEWICE. In general, FENSAP-ICE offered better results with a sufficient level of similarity to the experimental ice shapes. LEWICE showed more limitations, especially with regards to the shape and complexity of the ice shapes. The third objective of the thesis was to investigate the effects of icing on the aerodynamic performance of UAVs. This work included a comparison of FENSAP-ICE to experiments with artificial ice shapes at low Reynolds numbers. This validation showcased the accuracy and the limitations of the numerical method, the latter which existed especially for flow conditions with large separations. Following this validation, two numerical studies were performed. One to identify the most hazardous meteorological icing conditions for UAVs, and the other to investigate the influence of airspeed and airfoil size on performance penalties. These studies showed that UAVs are more sensitive to icing conditions than manned aircraft and that the most hazardous conditions occur near the freezing point and in conditions with high water content. The fourth and final part of this thesis focused on an electrothermal IPS for UAVs and the required heat loads for anti-icing and de-icing. A numerical study using LEWICE and FENSAP-ICE was conducted to investigate the differences between running-wet and fully-evaporative anti-icing systems, showing that running-wet was more efficient. Furthermore, an experimental campaign was conducted to test anti-icing, ice detection, and autonomous operation on a UAV IPS. Another experimental study was performed focusing on determining the heat loads for anti-icing and de-icing. A variety of icing and IPS parameters were tested on two different IPS systems (conventional and parting strip). The results showed that the least energy-efficient operation of the IPS was anti-icing. De-icing was substantially more efficient, especially at low temperatures. De-icing with a parting strip was shown to be the most efficient IPS mode.

An established reduced-frequency approach leveraging time-dependent 3D CFD-ALE simulations is used to calculate the static, quasi-static and dynamic stability derivatives of a clean and severely iced flying wing UAV at two angles of attack. Together with stationary 3D simulations, a quantitative assessment of changes to the flight behaviour can be made. The method can be used for any aircraft in any icing condition with minor limitations. The results show a severe degradation to some stability derivatives, especially in static longitudinal performance, whereas others are less affected and some even improved.

This paper presents a large parameter study on meteorological conditions to investigate the aerodynamic performance degradation of UAVs for a wide range of icing conditions. The knowledge about weather influences is essential for the development of efficient icing protection. The numerical CFD simulations for ice accretion and performance evaluation were performed on the 2D airfoil RG-15, using FENSAPICE. The method is validated with literature and experimental data. The results show a significant deterioration of lift and drag for all selected icing conditions and a distinct dependency of temperature, liquid water content and ice mass on the aerodynamic performance.