An Experimental Study on the Effects of Adverse Weathers on the Flight Performance of an Unmanned-Aerial-System (UAS)

Iowa State University Capstones, Theses and Graduate Theses and Dissertations Dissertations

2021

An experimental study on the effects of adverse weathers on the flight performance of an Unmanned-Aerial-System (UAS)

Muhammad Ahmad Siddique Iowa State University

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An experimental study on the effects of adverse weathers on the flight performance of an Unmanned-Aerial-System (UAS)

Muhammad Ahmad Siddique

A thesis submitted to the graduate faculty

in partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE

Major: Aerospace Engineering

Program of Study Committee: Hui Hu, Co-Major Professor Abdelkhalik Ossama Omar, Co-Major Professor Ali Jannesari

The student author, whose presentation of the scholarship herein was approved by the program of study committee, is solely responsible for the content of this thesis. The Graduate College will ensure this thesis is globally accessible and will not permit alterations after a degree is conferred.

Iowa State University

Ames, Iowa

2021

DEDICATION

I would like to dedicate this work to my parents, whose unwavering support and love throughout my life allowed me to accomplish wonders.

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TABLE OF CONTENTS

Page

ACKNOWLEDGMENTS ...... iv

ABSTRACT ...... vi

CHAPTER 1. INTRODUCTION ...... 1 1.1 Types of weather conditions ...... 8 1.2 Aircraft Icing ...... 10 1.3 Effects of wind ...... 13 1.4 Wind estimation ...... 15

CHAPTER 2. DESIGN AND DEVELOPMENT OF THE UAS...... 18 2.1 Selection of vehicle type ...... 18 2.2 Air frame ...... 18 2.3 Avionics ...... 20 2.4 Propulsion ...... 21 2.5 Communication and Tracking ...... 21 2.6 Cameras ...... 23 2.7 Sensors ...... 24 2.8 Data Acquistion Unit ...... 26

CHAPTER 3. FLIGHT TESTING ...... 29 3.1 UAS test experimentation site selection ...... 29 3.2 Experimental mission design ...... 29 3.3 Weather station ...... 31 3.4 Type of data to be collected ...... 32

CHAPTER 4. CALM CONDITIONS ...... 34 4.1 Calm condition flight ...... 34 4.1.1 Results ...... 39

CHAPTER 5. WINDY CONDITIONS ...... 51 5.1 Windy condition flight ...... 51 5.1.1 Results ...... 52

CHAPTER 6. ICING CONDITIONS ...... 63 6.1 Icing condition flight ...... 63 6.1.1 Results ...... 65

CHAPTER 7. COMPARISON OF RESULTS AND DISCUSSION OF FINDINGS ...... 81

CHAPTER 8. CONCLUSIONS AND RECOMMENDATIONS ...... 96 8.1 Recommendations for future work ...... 97

REFERENCES ...... 99 v

ACKNOWLEDGMENTS

I would like to express my sincerest gratitude to my advisors, Dr. Hui Hu and Dr. Ossama

Abdelkhalik, for their guidance, support and patience throughout the course of this research without whom this research work would not be possible. I would also like to thank my committee member, Dr. Ali Jannesari for his insightful comments and suggestions on my research.

Furthermore, I would like to extend a special thanks to my colleague Mr. Nianhong Han, whose technical insight helped me throughout my research work. I would also like to thank my colleagues in the Advanced Flow Diagnostics and Experimental Aerodynamics Laboratory, Mr.

Ramsankar Veerakumar, Mr. Haiyang Hu, Mr. Zichen Zhang, Mr. Chukwudum Eluchie, and Ms.

Abigayle Moser for their many fruitful discussions and assistance around the lab. I would also like to thank department faculty and staff, Mr. James Benson and Mr. Andrew Jordan, for their help with experimental facilities and Mrs. Marisa Mendoza for her constant assistance throughout my graduate program.

Finally, I would like to thank my parents and my brothers Dr. Talal Siddique, Mr. Azhar

Siddique and Dr. Nasir Siddique whose firm support and motivation helped me throughout the toughest phases of my graduate studies. Last, but not the least, I want to also offer my appreciation to my friends for staying by my side and making my experience at Iowa State University an unforgettable one. vi

ABSTRACT

An experimental UAS was developed to study the effects of adverse weathers, including icing and strong winds, on the UAS flight performance. Sensors were integrated on board the UAS to take in-situ, time-resolved measurements of atmospheric parameters, including temperature, humidity, pressure, wind direction and speed, during the flight. The measurement results of the atmospheric parameters were correlated with the UAS altitude data, and the UAS power consumption data to elucidate the underlying physics for a better understanding of the effects of the adverse weathers on the flight performances.

Test flights were fully autonomous between takeoff and landing. The experimental portion of the flight had fixed geolocation and trajectories in the designed missions. The flights resulted in comparison of circular loiter data between calm, windy and icing conditions. Variations in the

UAS power consumption were investigated during different segments of each flight. Glaze ice accretion was found to result in the malfunction of pitot static tube causing the loss of air speed data. Furthermore, wing leading edge and propeller icing resulted in rapid increase in the power consumption. It was discovered that ice accretion caused the greatest power consumption during the flight. Then, windy condition had the second highest power consumption with strong headwinds. Power consumption also spiked when turning against crosswinds from an initial tailwind condition. Iced propeller and vertical tail were preserved for the 3D scanning in the laboratory to quantify the 3-D shapes of the accreted ice structures. While the glaze icing on the

UAS propeller resulted in the formation of ice horns and ridges, the main wing of the UAS had mostly leading-edge icing with the formation of runback rivulets on the suction side. Total power consumption in calm, windy and icing conditions during fixed loiter was found to be 10.5 kW,

24.2 kW and 36.1 kW, respectively. The findings derived from the present study highlight the vii importance of developing effective strategies to ensure safer and more efficient UAS operation under adverse weather conditions.

CHAPTER 1. INTRODUCTION

Mankind has used two types of flying systems to date – manned and unmanned. Examples of manned systems are Apollo Lunar capsule, Space shuttle orbiter, SpaceX Dragon crew module,

Boeing 787 Dreamliner commercial aircraft and Bell Jetranger helicopter. Examples of unmanned flying systems include Voyager spacecrafts, MQ-9 Reaper fixed wing combat system, RQ-4

Global Hawk fixed wing surveillance aircraft and DJI Phantom quadcopter. Unmanned aerial systems (UAS) or unmanned aerial vehicles (UAVs) are also commonly known as drones. In recent years, unmanned aerial system (UAS) has seen an increase in interest and development in a multitude of applications. UAS can be manual, semi-autonomous or fully autonomous. Remotely piloted aircraft system (RPAS) is a type of UAS that can be flown manually and requires a trained pilot to operate it much like a real aircraft or helicopter, except the pilot is on the ground. Semi- autonomous UAS such as DJI Phantom are stabilized by autopilot and have an ability to self-fly but with the aid of the pilot input. Fully autonomous systems are less common but are more recently becoming popular. With the aid of machine vision, obstacle sensing and avoidance, path planning, advanced Artificial Intelligence, and improved navigation aids, UAS are becoming fully autonomous from take-off till landing. These systems operate on a pre-planned mission, launched, and monitored through a ground control station. The UAS in this case flies completely on its own, and can detect, and avoid obstacles and perform path planning on its assigned mission smartly enough to be classified as autonomous. Due to the multitude of applications opening for the UAS in global skies, safety and reliability of operations is a primary concern, while they are integrated into existing airspace operations. During flight, manned aircraft can suffer from inflight icing hazards. The critical areas of such aircraft are windshields leading to poor visibility, the engine air intake vane getting damaged from icing, wings and propeller suffering from lift force and thrust 2 deterioration. Air data probes may also get iced and give false readings to sensors. Similar to manned aircraft, the wings, air data probes, propeller and air intake are affected by icing in the

UAS. The manned aircraft usually have ice protection systems, whereas UAS usually lack an ice mitigation strategy. Figure 1-1 shows the vulnerable regions of manned and unmanned aircrafts systems.

Figure 1-1. Comparison of manned and unmanned aircraft vulnerabilities [1]

Manned aircraft usually fly faster (greater than 200 kmph) than unmanned aircraft. The manned aircraft are large in size compared to the UAS and are powered by liquid fuel engines, whereas unmanned systems often are powered by lithium batteries. Materials used in UAS are lightweight carbon fiber, composites, wood, and foam, whereas manned aircraft are made of various metals such as aluminum, and titanium. UAS payload capacity is significantly lower than manned aircraft usually. UAS operate at low Reynold’s numbers of the order of 105 since they fly slower whereas manned aircraft have a higher Reynold’s number of the order of 108. The UAS are often hand launched, catapulted or in some cases use a runway takeoff, whereas manned aircraft almost always takeoff from runway. UAS have a higher autonomy compared to manned aircraft.

Due to the need for life support systems on manned aircraft, they are large and heavy. The UAS, on the other hand, do not require such equipment. For this reason, the UAS are cheaper, lighter, and safer to operate. Table 1-1 highlights some of the key differences between manned and unmanned aircraft systems. 3

Table 1-1 Comparison of Manned and Unmanned aircraft systems

Manned Aicraft Unmanned Aircraft Flight speed Fast (>200 km/hr) Slow (upto 100 km/hr) Size Large Small Fuel Gasoline Lithium batteries Material Aluminum, Titanium, Metal alloys Carbon fiber, Composites, Balsa wood, Foam Payload Large, > 100 kg Small, < 20 kg Reynold's no. High (~10^8) Low (~10^5) Launch type Runway Catapult, runway, handlaunch Weight >1000 kg < 50 kg Autonomy Low High

Flying in harsh weather poses a threat for anything that relies on atmosphere. One of the challenges associated with flying harsh weather conditions is icing. This is especially common in cold climates. Icing can also occur in clouds and during freezing rain. There are various ways in which icing is known to cause problems. On aircraft pitot tube, icing blockage can result in malfunction of air data system and false air speed readings confusing the pilot. This can jeopardize the reliability of autopilot and even manual flying capability. Icing on the engine (e.g., inlet guide vane in jet engines) can cause wear and damage as well. However, two types of icing are of great interest as they lead to most severe icing related accidents - propeller icing and wing leading edge icing. Figure 1-2 shows the propeller icing and Figure 1-3 shows the wind leading edge icing.

Figure 1-2. Propeller icing (Source: ff4EuroHPC) 4

Figure 1-3 Wing leading edge icing (Source: Flight Safety Foundation)

Various theoretical and laboratory studies have been conducted on propeller and wing leading edge icing. Liu et al. studied the aerodynamic performance degradation on UAS propellers due to ice accretion. It captured the reduction in thrust and increase in power consumption under icing conditions [2]. Propeller icing was studied on a full scale turboprop aircraft propeller in a icing wind tunnel at McKinley Climatic Center [3]. Runback ice accretions from supercooled large droplets (SLDs) on airfoils have been studied on full scale wing section mounted in wind tunnel.

According to Broeren et al., formation of horn like features degraded the greatest amount of aerodynamic performance during the SLD accretions. The relative size of glaze icing which exists upstream of the horns has a high influence on airfoil performance reduction [4]. Waldman et al. used the Icing Wind Tunnel to conduct an in-depth investigation into the high-speed ice accretion process resulting various types of rivulets aft of airfoil leading edge. Changing wind speeds affected the water deposition rate or ice accumulation rate and that affected the spacing and area of the rivulets formed [5]. Valarezo et al. studied effects due to the small leading edge ice on single element and multielement airfoils, including tails [6]. Liu et al. studied the various ice accretions under changing wettability conditions on propellers in the icing wind tunnel [7] using the phase 5 lock technique. NACA conducted inflight testing of a manned aircraft to study the degradation effects due to propeller icing [8]. Shek et al. conducted a theoretical study for ice accretion around a propeller blade using 2D simulation and analysis [9]. Temperature, moisture, and droplet size are key factors influencing the icing conditions. The liquid water content is the mass of water in the given volume of air. This combined with moisture droplet diameter is an important factor in determining conditions relevant to icing types. Li et al. studied same airfoil shapes but with different materials such as composites and metals to investigate how the different thermal conductivities affected ice accretion for materials used in UAS structures [10]. It was discovered that heat transfer in composites is not uniform as in metal airframes used on large, manned aircraft.

Al-masri et al. studied ice formation process on pitot tube probes and investigated the ice mitigation to prevent the occurrence of errors in air speed data. Typical ice protection systems use heating elements or boots under the aircraft skin. Hybrid technique of using heating with the use of anti-icing liquid coating was observed to have better performance and energy efficiencies in melting the ice on pitot tube [11]. Conventionally, hydrophilic wind turbine blades are entirely heated to perform de-icing. This is extremely costly when considering the power consumption requirements. Gao et al. utilized a hybrid technique. Application of superhydro-/ice-phobic coating to the entire rotor blade first and then heating only 5-10% of the blade front provided significantly large energy savings with desired de-icing results [12]. Further techniques include innovations in heating mechanisms developed to mitigate icing. One study used DBD plasma actuators near the leading edge of the aircraft to study its effect on leading edge icing. Kolbakir et al. found that using streamwise layout of the actuators helped eliminate icing more efficiently [13]. Under icing conditions UAS may experience loss of stability and control. Winter et al. validated previously developed models to study the effects of iced flying wing UAS. Longitudinal stability of the flying 6 wing was severely affected during flight [14]. Improvements are desired in aircraft performance and safety and therefore ice mitigation is one of the aspects in this scenario. Hann et al. studied the negative effects of different ice formations on unmanned aircraft lift and drag curves using numerical simulations [15]. One study conducted on a NACA23012 airfoil showed that spanwise ridge icing had the greatest deterioration on aerodynamic performance, following by horn ice and runback ice, respectively [16].

Besides study on aircraft icing, effects of wind on the aircraft fuel consumption are also important. Crosswinds are challenging to navigate and costly when it comes to fuel or power consumption. For this reason, aircrafts consider crosswind models when designing optimal flight path and trajectories. The climate change has driven airlines to consider minimizing fuel consumption to minimize environmental effects and save costs. Huang et al. studied the aircraft climbing models after takeoff to improve the overall flight efficiency. Crosswind models were integrated in simulations to provide realistic estimations of results. Conventionally aircrafts level off soon after climbing and then continue to climb and repeat this strategy until they reach the cruising altitude. It was found that instead of conventional takeoff and continuous climbing under after takeoff until reaching cruise altitude could improve fuel consumption. However, this does not include any other type of wind related phenomena or weather conditions beside crosswinds alone [17]. When an aircraft needs to navigate and turn, it is ideal when the turn is inertially coordinated. In no wind scenario, turning at maximum bank angle and minimum radius turn can provide a smooth circular turn. However, under windy conditions this is not easy to achieve. This is particularly an issue during autonomous waypoint navigation, where pilot experience, intuition and skills are not available. The sensory system of the aircraft must fully learn to work with the winds on its own. In fixed type of wind, it may still be possible navigate a smooth and stable flight 7 path, however in turbulent and unsteady winds it is a different challenge. Figure 1-4 shows that the blue circle represents a fully coordinated smooth turn by the aircraft under zero wind. In the second case, there is a 5 m/s wind blowing from south-west and the aircraft attempts to make a full 360 degrees turn which ends up being uncoordinated, as seen by the green trajectory. At a higher wind of 10 m/s, this turn becomes much more challenging as the circle gets squeezed and distorted by crosswinds.

Figure 1-4. Turning schemes under different winds

Overshooting or undershooting the desired loiter waypoint in tight airspace or narrow envelope is a challenge under windy conditions. Look ahead distance may be considered to initiate the turn a little in advance or adjust it according to the approaching waypoints [18]. 8

Recent innovations in UAS propulsion have led to new techniques for increasing the range of the unmanned aerial systems. Hybrid electric propulsion system (HEPS) is one the key new technologies being studied to enhance the flight time for small unmanned aerial systems that are severely restricted by energy source due to limited space and payload capacities. One study based on simulation concluded that use of HEPS led to 6.5% conservation of fuel in the UAVs.

Furthermore, the designed mission waypoints to flown by UAS are optimized by tweaking parameters [19].

1.1 Types of Weather conditions

Most of our planetary atmospheric flight takes place in the lowest layer called Troposphere, which is bounded by tropopause. The layers of atmosphere above the tropopause form the upper atmosphere. Earth’s weather exists in the lower atmosphere or Troposphere. This is where most of the activity also takes place. Commercial airliners fly within this layer. Clouds and winds exist in this layer that also include weather phenomena such as rain, hurricane, and thunderstorms.

Temperature in troposphere decreases with altitude above mean sea level till the tropopause which is located at 10 km height. Figure 1-5 shows the structure of atmosphere where commercial aircrafts generally fly. 9

Figure 1-5. Earth’s Lower Atmosphere (Credit: Randy Russell, UCAR)

Aircrafts flying in tropopause must consider their safety when under inclement weather.

Temperature, pressure, humidity, air density and winds are properties of weather that can generate forces which are dangerous or favorable for flight.

There are different types of weather that exist in this layer. These include rain, snow, fog, winds, thunderstorms, ice storms, snowstorms, hurricanes, tornados, derechos, and microburst etc.

Most of the time, weather forecast predict weather it is advisable to fly under the given conditions or to stay grounded. Commercial aviation is a massive and busy industry. Any impacts from weather can greatly affect human transportation. Therefore, aircraft systems are built to withstand different weather types and mitigation techniques are applied against possible challenges. 10

With the emergence of low-cost small Unmanned Aerial Systems, airspace has got a new addition and complexity in the sky. This requires integration of weather models into UAS control strategies and to ensure safety of the aerial system as well as people and infrastructure on the ground. Malfunction or performance inefficiency of the UAS whether caused by weather or other effects is undesirable.

Heavy rain and hail, for instance, can increase the drag on aircraft wings, disrupting smooth airflow and resulting in reduced lift. This can cause performance degradation. Moreover, flying in snow and fog poses low visibility risk. Icing conditions can also cause low visibility and loss of lift forces due to change of shape of the airfoil and propeller. Strong winds can result in instability and increased power consumption. Supercooled large water (SLD) droplets can exist certain clouds and result in rapid ice buildup. Wind shear and turbulence can cause airspeed changes that can be detrimental for safe flight. Snow at low temperature may be crystallized and dry enough not to stick to the aircraft, but snow closer to freezing temperature may be more wet and experience a phase change. If the surfaces are colder than the wet snow under freezing temperature, the wet snow will freeze on impact and cause ice formation which is very dangerous as it can change the shape of wings and propeller, reducing lift and thrust forces. The aircraft will have to increase the power to stay aloft, and it may struggle to fly, eventually crashing if the ice buildup continues.

Freezing rain is a similarly dangerous phenomenon. Therefore, several of these weather conditions are the challenges that need to be understood for UAS.

1.2 Aircraft Icing

Clear (or Glaze) Icing is the type of icing that forms between 0 to -10 degrees Celsius temperature, in the presence of large water droplets. The ice gradually solidifies rather than 11 immediately freezing. It often results from freezing rain or cumuliform clouds. It is translucent in appearance, denser and hard to break.

Rime Icing forms at -15 to -20 degrees Celsius from small water droplets. It conforms to the shape of the airfoil and has a rough and milky white appearance. It is generally easy to remove.

Mixed Icing is a combination of clear and rime ice with a mushroom like build up that is rough.

It can form from wet snow with both liquid and frozen particles. This type of icing usually forms between -10 and -15 degrees Celsius. Figure 1-6 shows the structure of the three types of icing.

Clear icing the most dangerous type as it is hard to see and can form horn and ridge like structures. There is also runback rivulet icing that results from the liquid water to flow over the suctions surface of the airfoil. Figure 1-7 shows the different types of ice occurrence in aircrafts.

Furthermore, supercooled large droplets (SLDs) can result from temperature inversion or collision- coalescence effects. These can exist in a large temperature range of 0 to -40 degrees Celsius.

Whenever there is a chance of ice occurrence, it is best to avoid it by not flying through it, even if the aircraft has ice protection system or some sort of mitigation in place. 12

Figure 1-6. Types of icing (Source: Aviation Weather)

Figure 1-7. Icing Conditions [20] 13

The ice formation may affect different areas of an aircraft and all of them may not have effective ice protection. Overall, results from in-flight ice accretion are detrimental to flight. The weight of the accumulated ice buildup leads to aircraft getting heavier. The irregular change of shapes can reduce lift forces. The increase in surface area and shape increases drag. Ice on the propeller and engine parts can reduce thrust or air intake, resulting in a very inefficient and dangerous flight condition resulting in stall. Figure 1-8 shows the effects of ice accretion on an aircraft. Ice formation may also block the pitot static tube and malfunction instruments that rely on correct air speed data for flight.

Figure 1-8. Effects of Aircraft Icing (Source: Aviation Weather)

1.3 Effects of wind

Winds in the lower atmosphere form a gradient in the boundary layer with the planetary surface. Due to friction effects of the terrain features, wind is zero on the ground. From there, it has a gradient and increases towards higher altitudes. The shape of this gradient can be different over urban areas, land, and water. The global wind speed at high altitudes will be the same or 14 stable, however close the surface winds will slow down and become more turbulent. The wind over water is less disturbed than the one over land, where z0 is the roughness value, as can be seen in Figure 1-9. This must be considered in the plan of low level UAS flights. As the UAS are small both in size and payload capacity, they are usually less stable and less durable to operate in strong winds. Careful mission planning must be done to ensure the UAS is not lost or damaged.

Figure 1-9. Change in surface winds with height [21]

Windy weather includes various challenges in flying. Wang et al. investigated the effects of winds on UAS flight [22]. Wind shear is the most dangerous windy condition experienced during take offs and landings. Microbursts are downdrafts that occur under thunderstorms. They create wind shear and are also most dangerous during take offs and landings. Turbulence can occur at any altitude for several reasons. It can originate from wind shear or from wake vortices or around structures and terrain, such as mountains and trees etc. It is, therefore, desirable to understand windy condition and icing condition effects on UAS flight. Currently, no similar study exists in using an airborne Unmanned Aerial System under natural atmospheric conditions to understand the negative effects of the weather. As the demand for UAS increases, so will the requirements to be safe. This experimental study will aim to develop first of its kind state-of-the-art experimental 15

Unmanned Aerial System to investigate the effects of in-flight icing and strong winds. This study will serve as a basis for development of mitigation strategies for a safer UAS operations both on ground and in the air.

1.4 Wind estimation

Wind estimation can be done using standard GNSS module (GPS/GLONASS/Beidou/Galileo), and pitot static tube. The GNSS provides ground speed of the aircraft, while the pitot static tube gives the indicated airspeed. The true airspeed can be obtained after calibrations. The wind vector triangle method is commonly used to fuse the IMU (Inertial Measurement Unit) data with the EKF

(extended Kalman filter), that can output the wind velocity and direction. The problem is usually simplified, and the horizontal component of the wind vector is estimated. For a more accurate estimation of wind vector, a multi-hole pressure probe can be used. However, in this study, only pitot-static tube was used to estimate the horizontal component of the wind during flight. There are no angle of attack and side slip angle vanes to measure them directly. Therefore, these quantities are estimated by the EKF which fuses various flight information including Euler angles and accelerometer data. The aircraft true heading is different than airspeed vector and actual flight path angle, hence different quantities are measured in different coordinate frames and then transformed into a single coordinate frame for vectorial calculations.

In the wind vector triangle, the airspeed vector and the wind vector are positioned head to tail, as shown in Figure 1-10. The ground speed vector is in the direction of the aircraft ground track or course, whereas the true airspeed vector relative to the aircraft is defined using angle of attack and side slip angles. If the green ground vector is vg, the blue airspeed vector is va and the red wind vector is vw, then the wind vector is obtained as the vector difference of ground speed and true airspeed. The airspeed vector is measured in aerodynamic coordinate frame, which needs to be 16 transformed into a fixed reference frame, such as the Earth-Centered-Earth-Fixed (ECEF) coordinate system, as in Figure 1-11.

Figure 1-10. Wind vector triangle

After that, the ground vector and the transformed airspeed vectors can be subtracted to obtain the wind vector, as shown by the following equation.

W B RB is the coordinate transformation from wind frame to aircraft body frame and RI is the coordinate transformation from body frame to ground frame.

Figure 1-11. Coordinate systems for wind measurement 17

The GNSS/GPS compass provides all three velocity components. The wind vector is shown to have three components in x, y and z directions. However, only the horizontal wind speed is determined during flight, as the airspeed is measured horizontally using the pitot static probe [23]–

[26].

CHAPTER 2. DESIGN AND DEVELOPMENT OF THE UAS

The UAS is designed for the purpose of studying the negative effects of weather on the aircraft.

As winds interact with the aerodynamics of a flying object, therefore an aerodynamic system is a suitable one to study.

2.1 Selection of vehicle type

Fixed wing aircraft can utilize its aerodynamic design in an efficient way compared to helicopter or multirotor, that are more complicated and spend a lot of energy in staying airborne.

Fixed wing design experiences two modes of icing that are of critical importance (Main wing leading edge icing and propeller icing). There are also other forms of icing that can be detrimental to flight such as pitot tube icing. To study these effects, fixed wing type aircraft is considered.

2.2 Air Frame

Because the purpose of this study is not to design an aircraft from scratch, but to rather use it to study adverse weather and its affects. Experimental techniques developed in Icing Wind Tunnel can be applied to mitigate effects of aircraft icing. A COTS (commercial-off-the-shelf) kit of

Sonicmodell Skyhunter fixed wing aircraft was purchased. The specifications of the model are tabulated in Table 2-1.

The maximum flying weight of the aircraft is recommended as 3.5 kg by the manufacturer.

Currently designed aircraft has a total weight of 2.8 kg which is well under this MTOW (Maximum

Take-off Weight) limit. Depending on the battery used, it is possible to fly more than 100 minutes on the aircraft model. Figure 2-1 shows the aircraft model being tested in wind tunnel after full assembly.

Table 2-1. Specification of the selected airframe

Specification Detail Brand Name Sonicmodell Item Name Skyhunter Wingspan 1800mm Length 1400mm (adjustable) Wing Area 36dm/3.9ft2 (Mainwing Area) Max Flying Weight 3.0-3.5kg Color White Material EPO+Carbon Fiber CG 1/3 of wing from leading edge

Figure 2-1. Fully prepared experimental aircraft in wind tunnel testing

The skyhunter FPV airplane has a wingspan of 1.8 m approximately. It is made of lightweight and durable EPO foam with carbon fiber enforcements, high strength fuselage and wing. The large wingspan makes the aircraft stable and suitable for long flight in different weather conditions.

Sufficient interior space enables the model to carry a large number of equipment and different battery sizes for long flights. The nose of the aircraft has an intuitive design with an easy to remove canopy cover and versatile elements that make things easy to mount. Due to the modular nature of 20 the design, it is easy to disassemble for transportation. Center of gravity of the aircraft can be re- adjusted by using the tail booms. Different size of motors can be mounted on the aircraft to provide sufficient thrust to fly under all kinds of weather which are of interest.

2.3 Avionics

At the heart of the UAS is the HolyBro Durandal open-source flight controller running PX4

FMU (Flight management unit) software. The hardware includes a powerful 480 MHz STM32H7 microcontroller and an IMU (Inertial measurement unit). It houses two MEMS (Micro- electromechanical systems) accelerometers and gyroscopes, a magnetometer and a barometer. It also comes with a GPS/GLONASS dual GNSS receiver with its own separate magnetometer.

Therefore, there is redundancy in sensor readings in case of signal interference or if one device malfunctions. The flight controller takes inputs from its sensors and recognizes all important parameters about the vehicle in flight. All the controllers, such as ESC (electronic speed controllers and servos) are connected via PWM (pulse width modulation) to the controller board. The

Durandal sends the control signals to adjust motor rpm or servo angle to command actuator

(elevator, aileron, or rudder) output. This is the overall mechanism of the flight controller, which acts as a brain for the UAS. Figure 2-2 shows the flight controller board.

Figure 2-2. Autopilot/Flight Controller (HolyBro Durandal) 21

2.4 Propulsion

The UAS must have a powerplant to power it. In this study, an electric brushless DC motor is used as the powerplant. The E-flite Power 32 motor is a high torque 200 g, 770 Kv motor working with a 60A ESC (electronic speed controller).

Figure 2-3 Power 32 motor (left), APC 12x7 inch propeller (center) and 4S LIPO battery (right)

Kv is the RPM of the motor per volt without any load. For the chosen motor E-flite Power 32 for the UAS, the estimated RPM is 770KV x 14.8V = 11,396 RPM. In addition, RPM test was performed using tachometer and National Instruments DAQ in the laboratory. It was found that the motor with propeller on, had usually operated in 3000 to 9000 RPM range. To reduce the RPM requirement to generate the amount of thrust, a propeller with large diameter and smaller pitch is used. APC 12x7 inch propeller, Power 32 motor and 4S LiPo battery are shown in Figure 2-3. A high discharge rate of 100C can help in rapid power requirements during windy or extreme icing events, therefore the battery shown in the figure is chosen for the aircraft. It is a 5200 mAh battery.

2.5 Communication and tracking

The Spektrum DX7S RC transmitter offers a control range of about 1 km line of sight with the aircraft. This is used to control and fly the aircraft in case if there is a malfunction or emergency intervention of the pilot is required. Manual takeover should be a safety option. The different 22 modes of the aircraft operation are programmed on RC transmitter. These modes are mission mode, stabilized mode, auto home return and land mode and there is also an emergency kill switch.

The kill switch cuts off motor power to cause a controlled crash or to prevent propeller damage upon landing.

For long range control of the UAS from computer-based ground control station, RFD900+ radio module is used. It has an approximate range of greater than 40 km. The telemetry and control of the aircraft are both communicated via the RFD. It is a reliable design and has strong signals with the large antennas. Figure 2-4 shows the transmitter and telemetry module.

Figure 2-4. Spektrum Dx7s RC Transmitter (left) and RFD900+ Long Range Telemetry (right)

Tracking of the UAS is done by using long range 4G/LTE cellular technology based on sim card. It is the same type of sim connection which is used for telecommunications for regular phone usage. However, for this study there are no phone calls or text messages but only data usage required. The green board is the raspberry pi 3B+ companion computer that is run with Linux Operating system. The usb LTE dongle is connected to the companion 23 computer via usb port and acts as a communication source. The companion computer is able to control the UAS using the Qgroundcontrol software which is the same ground control station which is also run using standard laptop or computer to fly the aircraft. For a visual reference, binoculars are also used to track the UAS.

Figure 2-5. Raspberry Pi 3B+ (left), LTE Dongle with sim card (center) and Binoculars (right)

2.6 Cameras

Unmanned systems do not have humans on board and while they are operating remotely, it is helpful to have visual reference of what the aircraft sees. Besides this requirement, additional requirements could require sensory payloads that collect certain type of information. Some of these sensors generally include electro-optical/infra-red cameras, thermal cameras, multispectral cameras, and hyperspectral cameras.

For this study, only two types of optical cameras were used. One is the low latency Caddx

Ratel 1200TVL FPV (First-person view) camera used for real-time live view from the UAS during flight. The second is the SQ11 cube camera. The purpose of SQ11 was to observe the leading-edge ice accretion. A special adapter was designed, and 3D printed to house the SQ11 on top of propeller hub for propeller icing observation as well. To observe the wing leading edge ice formation, the

SQ11 camera was embedded in the cockpit cover of the aircraft. Figure 2-6 shows the two types 24 of cameras. The size of the cube camera is 23 mm x 23 mm x 23 mm, and its weight is 14 g including the battery. The 12 MP camera records continuously HD video of 50-100 minutes on an

SD card.

Figure 2-6. SQ11 cube camera (left) and Caddx Ratel 1200 TVL First-Person View (FPV)

camera (right)

2.7 Sensors

An RTD (Resistance based Temperature Detector) is a sensor that responds to temperature variations. It is considered an accurate measurement device temperature increases as the resistance of the sensor increases. The resistance vs temperature relationship is well known and is repeatable over time. An RTD is a passive device. Due to its lowest response time in the order of few seconds to a minute, it was decided to discontinue using it for real-time temperature data collection onboard the UAS.

A high response K-type thermocouple with MAX31855 thermocouple amplifier are selected to be used for temperature measurements due to its high response time and adequate accuracy. The thermocouple is mounted under the wing in a location, where it is in a shade during flight, to avoid being under direct solar radiation that produce errors in results. BME280 pressure and humidity sensor is an industry grade sensor by Bosch. It is exposed to atmosphere but protected by a mesh from direct contact with rain or snow. The temperature, humidity and pressure sensors are shown 25 in Figure 2-7. Durandal autopilot itself uses a high resolution and high response MS5611 barometer with an operating range of 10 to 1200 mbar at -40 to +85 °C.

Figure 2-7. BME280 (left) and MAX31855 amplifier with K-type thermocouple (right)

Fixed wing airplanes navigate using GPS compass which provides a reference for ground speed. However, an aircraft flies relative to wind and it is therefore important to know air speed information. For this reason, the UAS is equipped with a digital airspeed sensor. The sensor is connected to a pitot static tube at its total and static pressure ports by tubing. This sensor is connected with I2C protocol to the Durandal flight controller, where it feeds the air speed information to the autopilot as an input during flight. Figure 2-8 shows the pitot static tube in a 3D

Figure 2-8. PX4 Digital Air speed sensor and Pitot Static tube printed mount with the airspeed sensor. The air speed information is also fused with other variables of vehicle dynamics to estimate wind speed and direction. 26

2.8 Data Acquisition Unit

At the start of development, the UAS data acquisition was built using Arduino uno as shown in Figure 2-9. This setup was tested both with K-type thermocouple and an RTD based temperature sensor for giving two temperature readings. Humidity and pressure sensor were also used. The system was powered by a 9V cell for standalone operation. It used a 500mW 915Mhz telemetry module for relaying the data real time to the ground control station during flight. There were few drawbacks of this setup due to which it was abandoned.

Figure 2-9. First generation of DAQ setup

First, the range of telemetry at 500 mW power was limited to around 300 m. Also, the RTD temperature response was slow, and it was decided to abandon its usage. The 9V cell did not last very long during extreme cold winter flights. Long range LTE based DAQ design was more 27 feasible as it would combine both the tracking of the UAS and the data acquisition in one. The raspberry pi computer was therefore used and powered directly by the LiPo battery used for flight.

In the winter flights, to keep the LiPo battery performance optimum, it was covered with lightweight air activated handwarmers, which improved the overall operation reliability. As cold temperature is known to deplete battery charge faster, it was helpful to keep it warm during flight.

The airplane fuselage was made of EPO foam material which acted as an insulator material to keep electronics inside the aircraft dry and at an optimum temperature.

To observe the icing on propeller, a special 3D printed camera mount was designed and printed as shown in Figure 2-10. It was directly mounted on top of propeller screw instead of the standard spinner nut. The mount was test at full motor RPM in the laboratory to make sure it was balanced during the RPM test.

Figure 2-10. Camera mount for propeller icing

The UAS used only ailerons and elevator to steer and fly. Due to its twin tail design, it did not require rudder for yaw control. After assembly, the flight controller was mounted approximately as close to the CG of the aircraft as possible. Figure 2-11 and Figure 2-12 shows the location of various sensors in the aircraft. 28

Figure 2-11. UAS sensor setup

Figure 2-12. Cameras and sensors

CHAPTER 3. FLIGHT TESTING

3.1 UAS Test and experimentation site selection

The test site was chosen out of cities and population for safety reasons. The site was on the

Iowa State University’s BioCentury Research Farm (BCRF). It was ideally chosen as away from airports and in open agricultural lands that belonged to Iowa State University. Terrain on this site is vastly flat, which offers a clear path for takeoff, loiter and landing. There is a low traffic gravel road that conveniently provided access to the site under all-weather scenarios, including snowstorms. The experiments are always conducted with at least two researchers and additionally with the assistance of four other undergraduate students when required. Due to this, each person has a task assigned. The pilot-in-command always has the full control and visual sight of the UAS during the mission. Assistants help setup the equipment, provide photography or reporting on air traffic in the area.

3.2 Experimental mission design

The UAS flight is planned based on the weather conditions. Takeoff and landing particularly consider wind speed and direction. It is understood that wind gradient exists during flights. If the winds are 0 on the ground, they may be higher with respect to elevation. Most of the times the winds at the chosen site were northerly (blowing from 0-10° towards south). Other times winds were either easterly (100°) or north-westerly (310°) at the chosen site. Rarely, winds were southerly (170°).

Takeoff and landing were done into the wind. This was necessary to reduce the distance required as the ground speed is slower, while utilizing the relative airspeed due to oncoming wind.

Crosswind landings and takeoffs were avoided to prevent instability. The double boom UAS, did not have a rudder control with the vertical stabilizers. During crosswind landings or take offs, it is 30 helpful to have a rudder at lower speeds to rotate the aircraft toward relative wind as much as possible. This technique is used by pilots to prevent aerodynamic stall.

Initially during the study, various flight schemes had been flown such as rectangular patterns at fixed altitude and rectangular patterns with increasing altitude. Finally, it was decided to collect data during loiter circles. It is more appropriate because the aircraft can fix the height at each altitude and just change direction continuously relative to wind. This configuration eliminated the variation between sharp turns and level flight conditions of rectangular patterns. Another key reason to select circular loiters is to account for changes in wind direction during the flight.

Furthermore, during every new mission on a different day, different wind directions require adjusting the rectangular pattern accordingly. While takeoff and landing runs still require to be aligned with the wind direction, the loiter portion of the flight can remain the same during each mission. Therefore, experimental data is focused on the loiter part of the flight and not the takeoff and landing which are difficult to fix. During loiter the UAS maintains the turn throughout experimental data collection to fly a circular pattern of pre-defined radius. The radius during loiters had been set as 100 m. This was done based on trial and error after observing the effort required by UAS to maintain a tight turning pattern while circling. To prevent instability and stall experienced during extreme tight turns, the maximum roll angle was limited to 40°. Similarly, it was observed during test flights that a steep climb rate led to aerodynamic stall that required manual takeover of the UAS to land safely. To prevent this during autonomous missions, maximum climb rate of the UAS was limited to 5 m/s. Maximum roll during climb out was set to

25°. This limit was applied to ensure enough lift was present during the climb while avoiding aggressive navigation before reaching a safe altitude. 31

As the experimental loiters are fixed in 3D space, it is possible to study the variation in power consumption based on wind speed and direction or other weather conditions. Depending on these conditions, the loiter time may vary from one mission to another. Overall, the UAS was intended to complete a loiter turn in around one minute, allowing sufficient time to collect one set of temperature, humidity, pressure, and wind data for that particular altitude level. Given the response time of the sensors used, this time is also sufficient for readings to stabilize. After 60 seconds,

UAS climbs by 30 m and completes another loiter turn for 60 seconds. The process is repeated until reaching the ceiling altitude of 120 m. After that, the UAS returns in the same manner by descending every 30 m and loitering for 60 seconds duration. If for a certain weather condition, the time to complete one circle was greater than 60 seconds, then the experimental observation and analysis included that time instead of 60 seconds. In such a case, the UAS mission was designed in such a way as to ensure that it completes one full circle. The data analysis is, therefore, from start of a loiter circle to its finish point. The ascent and descent portions of the loiter are used to compare variations in temperature, pressure and humidity based on altitude change. Also, wind

(increasing with height due to boundary layer gradient) and power consumption (increasing due to decreasing air density and pressure) may change. The constant altitude loiter is useful to focus on variation in power consumption during ice accretion or winds. Depending on tailwind, headwind or crosswind, the UAS power consumption variation is studied throughout the loitering flight pattern.

3.3 Weather station

While weather services like AccuWeather, weather.com or Aviation Weather provide general information from closest weather stations or airports, it is beneficial to know local weather conditions at the experimental site. For this reason, a mobile weather station was procured and 32 setup on a mast. The weather station unit provided the temperature, humidity, pressure, dew point, light intensity, wind speed and direction. Before and during every flight, weather station data is collected to monitor ground level weather where the UAS was launched from. Due to wind shear and gradient present, the wind data at high altitudes is general different than what is reported by a fixed height weather station. Figure 3-1 shows the weather monitoring station on fixed on site.

Figure 3-1. Weather monitoring station

3.4 Type of data to be collected

To study the effects of negative weather, both flight data and weather data must be collected.

Various types of data are related to each other. For instance, atmospheric pressure is dependent on altitude above Earth’s mean sea level. As the altitude increases, pressure should vary. A barometer gives pressure data. Temperature is collected by using K-type thermocouple mounted under the wing. Humidity sensor is embedded in fuselage to read pressure and humidity data without getting wet. Power consumption data is collected by UAS during flight, which is instrumental in compared all data with. Air speed sensor helps provide indicated air speed of the aircraft, while on board 33

GPS compass provides navigation and ground speed data. Wind speed and direction estimates are also recorded for analysis.

During flights, various types of experiments can be conducted. Experimental data collected vertically with respect to height with all other variables changing only with respect to height can be measured (such as Temperature, Pressure, Humidity, Wind and Power consumption). In other cases, flights conducted in different times of the day can help compare variation of data temporally and diurnally. Flights conducted on calm day can be compared with flights conducted on windy, snowy, icing, and rainy days.

CHAPTER 4. CALM CONDITIONS

4.1 Calm condition flight

In this chapter, the effect of calm weather is studied on aircraft flight to set the benchmark for all other weather conditions. Calm weather in contrast with rainy, windy, or snowy weather is considered safer and easy to fly in. The clear sky means visibility is excellent. Lack of high winds indicate the aircraft experiences less drag and require a higher takeoff and landing ground speed and distance. If the weight of a UAS is heavy, it can be challenging to hand launch due to lack of sufficient relative wind. However, in this study, the UAS weight and center of gravity are well balanced. Power 32 motor along with 12x7-inch propeller provided enough thrust at take off during hand launch.

Power consumption is thought to be less affected during calm weather than during harsh weather. Calm weather is a good indicator of setting the basis for comparison with other types of weather conditions.

To perform testing under calm conditions, careful planning is done as the takeoff and landing runs are longer than windy conditions. It is ideal to use a catapult launcher or a runway takeoff. It is also necessary to ensure the pitch up elevator authority is high enough to enable the aircraft to take off safely when hand launched. In this study, all these conditions were met, and a safe hand launch was achieved.

The flight pattern for calm conditions still depends on the wind. Since the loiter point has been fixed for all experimental flights, the only thing that must be considered is the takeoff and landing direction and ground speed during takeoff and landing. If the wind is zero, it does not matter in which direction the UAS takes off or lands. However, if there is little bit of wind, it should be utilized to assist in takeoff and landing. Besides the direction of wind, another factor to consider 35 is the safety of operation. High ground speed during takeoff and landing means, if there are people or infrastructure nearby, it should be considered. In our experimental flight, there is only the researchers and the vast agricultural land on which the flights are conducted when no one is working there. The one factor that was considered during selection of direction is the terrain features. If one specific orientation of the land was relatively flat for a longer distance, then it was preferred to land there. Figure 4-1 shows the designed mission for calm weather flight. Ground weather station just before takeoff in the late afternoon indicated 1.5 mph southerly wind. The

UAS was hand launched from the empty gravel road during absent traffic. It flew in the manner as to intercept various waypoints during different phases of the mission. Six loiter waypoints for the experiment were on top of each other as shown in the figure. After descending back to the lowest loiter point of 30 degrees, the UAS followed the landing pattern to land adjacent to the home point.

Figure 4-1. Calm weather designed mission. 36

The three-dimensional trajectory of the actual flown mission is shown in Figure 4-2. Based on aviation practices that also consider air traffic and wind direction, the rectangular flight pattern with different legs was designed. From the takeoff or launch point, the UAS flies into the wind during initial climb out. This is called the upwind leg which is facing south. Then the UAS turned west by 90 degrees turn and this leg is called crosswind leg. Next the UAS turned 90 degrees right to face north. This is called the downwind leg. It was in the middle of downwind leg where the experimental loiters were designed. This is a suitable location during flight for the UAS to climb while circling and descend in the same manner. At the end of the experimental phase, the UAS exists the loiters and continued in the downwind leg to fly farther. Downwind leg is the longest leg in the rectangular pattern, and it is parallel to the runway.

Figure 4-2. Flown mission profile (3D Isometric view) 37

The UAS then exits downwind leg and turns right 90 degrees to fly eastward course. This is called the base leg, as it is used to enter the landing pattern of the aircraft. The landing pattern of the aircraft include the landing loiter, which was at the same height as 30 m and the radius of the loiter was 75 m. The base leg is parallel but opposite to the upwind leg. At the end of base leg, the aircraft turned right 90 degrees to face south to enter the final approach leg. The aircraft flies the glide slope which is a trajectory used to adjust the throttle and elevator to allow the aircraft to smoothly descend with level wings from this point at a fixed descent rate till landing the landing flare. The glide slope angle is preferred to be not steep to allow for a smooth landing. The glide slope angle in this flight was 4.5 degrees and the distance of this slope was 380 m. Depending on the speed of approach, approximately 3-5 m above the ground, the aircraft does the landing flare, which is used to slow down further by reducing power and pitching up to allow for a smooth touch down.

Figure 4-3. Side view of the mission designed for calm conditions.

Sometimes, the landing point has a different height relative to the takeoff height, as shown in

Figure 4-3 by using the side view. This must be taken into account when deciding on the landing 38 site and designing the landing phase. As seen in this mission profile, the aircraft landed slightly below the takeoff height. This is because of the variation in terrain. The approximate difference in height must be input into the landing pattern approach to allow the aircraft to flare at the correct height. If the landing height is vastly different, the aircraft could have a hard landing, or it could fail to detect touch down after flaring which would result in landing abortion and go-around. The go around is a technique used to attempt a second landing by following the flight pattern for landing again. Figure 4-4 shows the top view of the mission. It is a convenient way to visualize the rectangular pattern with Right-Hand-South landing approach pattern used in this specific mission relative to wind. The location of loiter points are visible in front of the ground control station in one direction. It is the best location to keep a visual reference in the line-of-sight on the

UAS, which is an FAA requirement for drones. Note that the x-axis here represents North in positive direction and South in negative direction. The negative y-axis represents West.

Figure 4-4. Top view of the benchmark experimental mission under calm conditions

4.1.1 Results

To take off, the aircraft throttled up to 100% and achieved the maximum power consumption during this phase of climb out. Its power consumption was 1092.66 W during this phase. Heights are measured relative to the home point at initialization. After initial take off climb out, the UAS reached the first assigned take off altitude of 15 m (waypoint 1) and lowered the throttle. Then it throttled up and continued to climb to 30 m to reach waypoint 2 during its upwind leg in the pattern.

Figure 4-5 shows the height variation during the flight.

Height 140

120

100

Relative Relative Altitude(m) 20

0 0 100 200 300 400 500 600 700 -20 Time (s)

Figure 4-5. Relative Altitude, measured from takeoff height.

Next, the aircraft made a 90 degree right turn to enter the crosswind leg and maintained 30 m altitude until it intercepted the next waypoint (number 3). Upon intercepting it, the UAS made a right 90 degree turn and entered the downwind leg. At the same time as entering, downwind leg, the UAS began climbing to 60 m altitude loiter point at a set climb rate of 3 m/s and a pitch angle of about 10 degrees. 40

The power consumption during this climb phase was 591W at 73% throttle. Due to the longer distance in this climb leg, the UAS required a lower power to climb compared to the power required at takeoff climb out. As shown by Figure 4-2, the UAS reached the periphery of the loiter circle of the loiter waypoint number 4 and entered it tangentially. Here the UAS spent approximately 60 seconds to circle around the loiter waypoint of diameter 200 m. Then, it increased the throttle by 25% and pitched up to 15 degrees to climb at a rate of 5 m/s to reach the next loiter waypoint (number 5) at 90 m altitude above the same location.

The UAS circled this waypoint for about 60 seconds collecting atmospheric data used for comparisons under all weather conditions. During the loiter point climb outs, UAS indicated airspeed (IAS) increased by 1 m/s and then returned to an average reading of about 15 m/s. This was again observed as the UAS throttled up from 53% to 80% (a 2% greater increase in throttle than previous climb), increasing power consumption by 514.28 W during the climb to 120m loiter waypoint (number 6). The climb rate was 5 m/s and pitch angle were 15 degrees as during previous climb. It was observed that the lowest ground speed was observed when the UAS heading during loiters was 140 degrees. This is also approximately indicating the direction from which wind is blowing. Figure 4-6 shows the indicated air speed and ground speed.

Power consumption at this height was 230 W and it required about 53% throttle to operate the system throughout the loiter. After completing the loiter of 120m altitude, the UAS turned down the throttle to 0% which reduced power consumption to 0 W approximately as it started to descend at a rate of 5 m/s and pitch down angle of 15 degrees.

Indicated Air speed remained roughly the same through all altitudes of the flight. It momentarily increased very slightly during ascent and descent of loiters and then settled back. 41

Speed 30 25 20 15 10

5 Speed Speed (m/s) 0 0 100 200 300 400 500 600 700 -5 -10 Time (s)

Ground Speed Indicated Air Speed

Figure 4-6. Indicated air speed and ground speed during flight.

Roll Angle 50

) °

( 10 ϕ 0 0 100 200 300 400 500 600 700 -10

-20

-30 Time (s)

Figure 4-7. Roll angle variation in calm conditions.

During the slowest ground speeds of the aircraft, the UAS also had the lowest roll angle, as it can be seen from Figure 4-6 and Figure 4-7. Pitch angle information is shown in Figure 4-8. The

UAS flew close to 0 degrees pitch during regular flight. However, during loiter ascents and descents it used a pitch angle of approximately 8 degrees and -8 degrees, respectively. 42

Pitch Angle 25 20 15 10

) °

( 0 θ -5 0 100 200 300 400 500 600 700 -10 -15 -20 -25 Time (s)

Figure 4-8. Pitch Angle in calm conditions

Aircraft heading indicated that it spent minimal time facing the relative wind due to calm conditions. It can be seen from Figure 4-9, that the curved section between two consecutive vertical lines is shrunk quite steeply. Its inflection point occurs where the UAS faces the headwind momentarily during the loiters. In other weather conditions, this slope of curves may vary.

Aircraft Heading 400 350

300

) ° ( 250 200 150

100 Heading Angle 50 0 0 100 200 300 400 500 600 700 -50 Axis Title

Figure 4-9. Aircraft heading during loiter flight under calm conditions. 43

Figures 4-10 till 4-12 indicate how the use of throttle changed power consumption, and how climb rate was associated with that phase of the flight. The sharp surges represent climbs and dips represent descent during flight.

Climb Rate 10 8 6 4 2 0 0 100 200 300 400 500 600 700

-2 Climb Climb (m/s) Rate -4 -6 -8 Time (s)

Figure 4-10. Rate of climb during experimental flight

Throttle Percentage 120

100

40 Throttle (%) 20

0 0 100 200 300 400 500 600 700 -20 Time (s)

Figure 4-11. Percentage of throttle in use during calm conditions 44

Power Consumption 1400

1200

1000

800

600

Power Power (W) 400

200

0 0 100 200 300 400 500 600 700 -200 Time (s)

Figure 4-12. Power consumption during calm weather

During the entire flight, the UAS flight battery consumption had a variation with respect to the different phases. Small dips are visible in Figure 4-13 that represent the increase in battery discharge during climbs to higher loiter altitudes. There are slight bumps in the graph that represent descent phases of the flight.

Battery Remaining 6000

5000

4000

3000

2000

1000 BatteryConsumption (mAh) 0 0 100 200 300 400 500 600 700 Time (s)

Figure 4-13. Battery consumption during full mission profile 45

Wind Direction 350

300

) °

( 250

200

150

100 WindDirection 50

0 0 100 200 300 400 500 600 700 Time (s)

Figure 4-14. Wind direction reported by the UAS.

Wind speed 7

WindSpeed (m/s) 1

0 0 100 200 300 400 500 600 700 -1 Time (s)

Figure 4-15. Wind speed corresponding to wind directions reported by the UAS.

Wind speed and direction remained relatively constant throughout the flight at all altitudes, according to Figure 4-14 and Figure 4-15. The average wind speed was around 5.2 m/s during the experimental portion of the flight in the loiters. METAR information was decoded and reported 7 knots (3.6 m/s). UAS reported average wind direction blowing from approximately 133 degrees. 46

This was approximately within the range of 150 degrees which was reported by METAR during the flight. There were negligible variations in the wind speed and direction throughout the experimental portion of the flight in the loiters.

DAQ Barometric Pressure 994 992 990 988 986 984

982 Pressure Pressure (hPa) 980 978 976 0 100 200 300 400 500 600 Time (s)

Figure 4-16. Pressure variation during calm weather flight

Temperature 8 7 6 5 4 3

Temperature Temperature (C) 2 1 0 0 100 200 300 400 500 600 Time (s)

Figure 4-17. Temperature change during calm conditions 47

In Figure 4-5 relative height was shown to vary during the flight. The shape of that graph when inverted looks very similar to the shape of the pressure graph as shown in Figure 4-16. The pressure is measured in hectopascal above the mean sea level. From the graph, pressure at hand launch height (approximately 1.5-2 m above ground level), was recorded as 991.5 hPa. The hand launch was done from the gravel road which is higher than the flat grassy area next to the field by 1 m.

The pressure read by the aircraft after landing is 991.8 hPa, which is slightly higher than take off point pressure. Pressure responded near real-time with height changes during flight. The lowest pressure reading of 977.5 hPa is recorded at the highest altitude of 120 m. This is a decrease in 14 hPa from takeoff height.

The temperature recorded by the UAS at launch was 4.65 °C. During the climb from takeoff till reaching the loiter point of 60 m, the temperature increased to 7.47°C. From there onwards, temperature decreased with height until reaching 120 m, as seen in Figure 4-17. During the descent, temperature increased slightly till 60 m height. After that, temperature started to decrease during descent to 30 m height and maintained it. During the final landing, temperature decreased with height until landing where it was 2.35 °C. Temperature changes may have been influenced by the cooling of the Earth closer to sunset and temperature inversion may affect how the profile of temperature varies with height.

Results from humidity data in Figure 4-18 show that humidity decreased with increase in height till reaching the loiter point of 60 m height. After that humidity increased by less than 1 % till 120 m height. After that, during the descent, humidity continued to increase until landing where the final humidity was 25.75%.

Humidity 30

Relative Relative Humidity(%) 5

0 0 100 200 300 400 500 600 Time (s)

Figure 4-18. Relative humidity in calm weather

During the entire span of the flight, temperature data was averaged at each height. It was observed that during the climb temperature overall increased till 60 m height. After that, temperature decreased till 120 m ceiling, as shown in Figure 4-19.

Average Temperature Variation 120 Climb 100 Descent 80

40 Height(m) 20

-20 0 1 2 3 4 5 6 7 8 Temperature (°C)

Figure 4-19. Time averaged change in temperature with height 49

Overall, temperature had increased during this entire ascent. On the way down, temperature followed a similar pattern, but the results appear skewed. At first there was little change in temperature during the descent to 90 m height. But after that, temperature slightly increased until reaching 60 m. Then the trend changed, and temperature started to decrease significantly more than it had increased during climb phases. The final temperature after landing was 2.65°C. This reading was 2.86°C lower than the temperature at takeoff and 3.5°C lower than the temperature at

120 m height.

Average Humidity Variation 120 Climb 100 Descent 80

40 Height(m) 20

-20 17 19 21 23 25 27 Relative Humidity (%)

Figure 4-20. Time averaged change in humidity with height

To understand the variation in humidity during entire flight duration, time averaging was done, and data plotted with respect to height. It was observed that, relative humidity decreased rapidly till 19.4% until 40 m height. After that, it started to increase until reaching 120 m ceiling, where it was 20.25%. During descent of the aircraft, humidity increased slowly by 0.43% till about 70 m height and then it increased at a faster rate till landing. The final humidity on the ground was

25.65% which is 2.16% higher than relative humidity at takeoff, as shown in Figure 4-20. 50

Overall, humidity followed a similar trend during climb and descent phases of the flight. Next, the barometric pressure readings were time-averaged at every height. Figure 4-21 shows that the pressure dropped linearly with height through the climb phase from 0 to 120 m height. The drop in pressure was from 991.605 hPa at the takeoff level to 977.492 hPa at the highest altitude reached.

The pressure also increased identically during the descent phase. The overall change in pressure during flight was by 14 hPa as reported earlier.

Average Pressure Variation 120 Climb 100 Descent 80

40 Height(m) 20

-20 976 978 980 982 984 986 988 990 992 994 Pressure (hPa)

Figure 4-21. Time averaged change in pressure with height

To conclude this chapter, calm weather provides an important result that must be comparable with flights under harsh weather. For this reason, a thorough and detailed analysis has been done in this chapter. Next chapters will discuss flights under the inclement weather with strong winds and icing conditions.

CHAPTER 5. WINDY CONDITIONS

5.1 Windy condition flight

This flight condition required careful planning. High winds and gusts put a limit on safe flying.

Based on previous test flights during the development of the UAS, higher winds were tested with time to observe the flight. The reason for doing so was to make sure that the structural integrity of the UAS will not be compromised and that it will be able to withstand and fly with enough power against the crosswinds and headwinds.

Headwinds are good to take off and land into as they reduce the takeoff and landing distance by the presence of initial relative wind. This relative wind generates lift forces that are required for flight. A stronger than usual headwind at takeoff helps lift the aircraft but requires more power due to increased drag. For this reason, E-Flite Power-32 motor was found suitable with a 12 x 7 in propeller that assisted in sufficient takeoff performance under the given payload. Strong winds were forecasted on March 15th, 2021 in the morning. So, the equipment was setup from sunrise to wait for adequate flight conditions. At 9:30 AM, ground weather station readings reported easterly winds of 10.5 mph with 16 mph gusts. This was above any wind limits flown in past. A fully charged 5200mAh 4S Lithium Polymer battery was installed to the aircraft. The raspberry-pi based

Data Acquisition Unit was activated and long-range LTE-based cellular connection was established. In case the UAS got blown away by winds or a had a fly away malfunction, LTE connection was intended to track and recover it.

At 10:17 AM, the UAS was hand launched into the wind to fly the same autonomous waypoint mission as previously designed to work with all weather conditions. During strong winds, it was observed that the UAS slightly struggled to maintain exact circular path of the loiter radius. The larger more defined red circle shows the experimental loiter flightpath. The circular shape is seen 52 slightly distorted in region A and region B as shown in the Figure 5-1. It will be discussed later that the power consumption spiked to the greatest extent in region A and then in region B. The red line is what the UAS has flown, and the light orange line represents the designed mission path.

Data was compared for one complete loiter circle, which took 81 seconds in this case.

Figure 5-1. Flight pattern of the Windy condition experiment

5.1.1 Results

After the flight, the collected data was downloaded. It was then reduced and cleaned and then processed for analysis. Figure 5-2 below shows the relative altitude variation during one complete circular shaped loiter turn at 120 m height setting.

Figure 5-3 shows that the indicated air speed remained uniform throughout the loiter. However, the ground speed increased due to tailwind and then decreased due to transition towards headwind.

The UAS climbed slightly while going from crosswind to tailwind part of the loiter and then recovered to maintain the targeted assigned altitude of 120 m. 53

Height 127 126 125 124 123 122 121 120

Relative Relative altitude(m) 119 118 117 0 10 20 30 40 50 60 70 80 90 Time (s)

Figure 5-2. Relative Altitude during the windy mission

Speed Comparison

40 Ground Speed Indicated Air Speed 35 30 25 20

15 Speed Speed (m/s) 10 5 0 0 20 40 60 80 100 Time (s)

Figure 5-3. Ground speed and indicated air speed of the UAS during windy flight.

During the phase of increased ground speed and slightly increasing altitude, the UAS was under a positive (right) roll condition as seen by the Figure. Maximum roll angle during the loiter 54 turn was observed as 37.7° at 78 second into the loiter. Towards the second half of the loiter turn, the roll angle remained relatively lower and under ±10°.

Roll Angle 45 40 35

) °

( 25 20 15

10 Roll Angle Roll Angle 5 0 -5 -10 0 10 20 30 40 50 60 70 80 90 Time (s)

Figure 5-4. Roll angle under windy condition.

Pitch 4

) 0

° ( -2

-4

Pitchangle -6

-8

-10 0 10 20 30 40 50 60 70 80 90 Time (s)

Figure 5-5. UAS Pitch angle under windy condition. 55

During most of the loiter pattern, the UAS flew under a negative pitch angle. The pitch angle fluctuated several times indicating a bumpy flight under strong winds as shown in Figure 5-5. For instance, this variation was from -1.3 to 2.3 degrees in 1 to 2 second period. The UAS heading during the loiter takes a full 360° turn as it flies in circles. Figure 5-6 shows the time the UAS spent facing a certain heading at a given instance. The graph is nearly level at 100° for most of the loiter. This indicates the UAS is seeking for relative wind (by crabbing, for example) in this direction to maximize lift forces beneficial for flight under crosswinds.

Heading 400 350

300

) ° ( 250 200 150

100 Heading Angle 50 0 0 10 20 30 40 50 60 70 80 90 -50 Time (s)

Figure 5-6. UAS Pitch angle under windy condition.

Figure 5-7 shows the aircraft flying in a crabbed manner during loiter to face the wind direction. The actual flight path is the loiter circle of 200 m diameter indicated in the white color.

The path the aircraft has flown previously is shown in the purple color. At this stage, the UAS heading is 119°, while the flight course is tangent to the loiter circle approximately. The current wind direction reported by the aircraft is 98.9° at 10.6 m/s. From the heads-up display (HUD) in 56 the top right of the Figure 5-7, it is also seen that the UAS has a positive roll angle while maintaining a zero-degree pitch in this instance.

Figure 5-7. Frequent crabbing during windy flight

The rate of climb of the UAS is used to indicate its vertical speed. During climb outs, it is an important indicator that considers the weight of the aircraft and the available power to change altitude. Usually, the engine power is adjusted along with other control inputs to achieve the desired rate of climb. To prevent aerodynamic stall, the climb rate of the UAS in this experiment was restricted to 5 m/s based on previously conducted development test flights prior to experimental flights. During the fixed altitude loiter, the UAS should ideally have a zero-climb rate. During windy conditions, this is not the case. The climb rate of the aircraft fluctuated by ±2 m/s during the entire circle. This could be in response to the varying relative wind the aircraft flew in. Figure 5-8 shows the climb rate performance during the loiter at 120 m height setting. 57

Throttle controls the power provided to the aircraft to fly. In engine powered airplanes, it controls the amount of fuel let into the engine for combustion and providing thrust.

Climb Rate 2 1.5 1 0.5 0 -0.5 -1 -1.5

Climb Climb (m/s) Rate -2 -2.5 -3 -3.5 0 10 20 30 40 50 60 70 80 90 Time (s)

Figure 5-8. Climb rate during windy flight.

Throttle 70

30 Throttle (%) 20

0 0 10 20 30 40 50 60 70 80 90 Time (s)

Figure 5-9. Throttle percentage in windy flight conditions 58

In case of electric motor, it is the current draw that is adjusted to accommodate the power requirements of the UAS. In the high wind flight, the throttle is seen to vary from 50% to 66%, just to maintain the altitude and fly with respect to the winds. This is a significant amount of variation compared to a calm weather flight, where throttle varies less abruptly. Figure 5-9 shows the percentage of throttle usage by the system during flight. Operation of throttle directly relates to the power. As the system needs to consume greater or lesser power, the autopilot commands throttle input to adjust power. Figure 5-10 shows the power consumption during flight, which is quite identical to percentage of throttle. Slight delay in power consumption may be noticed, but that is because throttle is applied first and that results in power response. The delay may be negligibly small in case of electric propulsion systems compared to gasoline powered engines.

Power Consumption 450 400 350 300 250 200

Power Power (W) 150 100 50 0 0 10 20 30 40 50 60 70 80 90 Time (s)

Figure 5-10. Power Consumption during windy flight

Various types of aircrafts use different fuels. The electric UAS uses electricity to operate. Its fuel comes from Lithium Polymer batteries that store the charge and can operate at certain voltage as an output. The milli-ampere hour (mAh) is a measure of the stored charge inside the battery that 59 it can provide for a system. The battery in use has a 5200 mAh capacity. During the flight, the battery discharge is of interest because it affects the economy of operation. Figure 5-11 shows that

461 mAh are consumed by the UAS during this flight.

Battery Remaining 2700

2600

2500

2400

2300

2200

BatteryConsumed (mAh) 2100

2000 0 10 20 30 40 50 60 70 80 90 Time (s)

Figure 5-11. Battery Consumption

The wind direction estimated using extended Kalman filter (EKF) during the flight utilizes the data from GNSS and pitot-static tube along with UAS flight dynamics. It fuses IMU data with the orientation of the UAS during flight with respect to relative wind to predict the wind direction.

During the flight, the wind direction and wind speed are reported by the system as shown in Figure

5-12 and Figure 5-13, respectively. The system measured a maximum wind of about 11 m/s which is about 24 mph blowing from approximately 101° East. The ground reported wind direction was

100°. It is possible that due to gusts and presence of wind shear, wind direction and speed varied slightly during the flight.

Wind Direction 103 102.5

102

) ° ( 101.5 101 100.5 100

99.5 WindDirection 99 98.5 98 0 20 40 60 80 100 Time (s)

Figure 5-12. Wind Direction during windy conditions

Wind Speed 11

10.8

10.6

10.4

10.2 WindSpeed (m/s) 10

9.8 0 20 40 60 80 100 Time (s)

Figure 5-13. Wind speed during windy conditions corresponding to wind directions.

Barometer in the BME280 integrated in the UAS data acquisition system recorded a fluctuating pressure data. Due to the height variation of the UAS, as seen in Figure 5-2 earlier, the pressure data fluctuated accordingly in response. Figure 5-14 shows pressure averaged at 963.4 hPa. 61

Pressure 964.2

964

963.8

963.6

963.4

Pressure Pressure (hPa) 963.2

963

962.8 0 20 40 60 80 100 Time (s)

Figure 5-14. Pressure readings from barometer during windy conditions

Temperature is one of the most important atmospheric parameters. The K-type thermocouple mounted under the aircraft wing recorded around 0.2°C temperature that fluctuated between 0.1°C and 0.3°C. This is within the accuracy range of K-type thermocouples as ±2°C. The thermocouple response upon reaching and loitering at 120 m altitude is shown in Figure 5-15.

Temperature 0.4 0.35

0.3

C) ° ( 0.25 0.2 0.15

Temperature Temperature 0.1 0.05 0 0 20 40 60 80 100 Time (s)

Figure 5-15. Thermocouple temperature readings during windy conditions 62

Relative humidity, as reported from the Bosch BME280 sensor, is shown in Figure 5-16. The accuracy of the humidity sensor is +/-3%. An average of 88.4% humidity was observed within the accuracy range.

Humidity 88.7

88.6

88.5

88.4

88.3

Relative Relative Humidity(%) 88.2

88.1 0 20 40 60 80 100 Time (s)

Figure 5-16. Humidity sensor readings during windy conditions

CHAPTER 6. ICING CONDITIONS

6.1 Icing condition flight

Icing conditions are considered dangerous for anything that flies. Since flight is made possible by lift forces that are generated when pressure difference is developed, it is important to study the effects of icing that are known to have negative effects on lift. However, to study icing is not an easy task. Icing is hard to predict. Aviation forecasters work hard to inform pilots of potential icing risk during flight. In this study, it was attempted to use aviation weather resources to predict icing.

Various attempts were made over several months of winter to achieve any kind of icing. It was in vain till now. Ice accretion depends on multiple factors. The icing wind tunnel at the Aerospace

Engineering Department of Iowa State University’s is one of a kind in the world, where some icing conditions can be created to form ice accretion successfully. Once the process is understood, it is desired to mitigate icing. While mitigation techniques are developed in laboratory environment, they need to be tested on aircraft in real conditions.

In this study, there are two types of icing that are of interest – propeller icing and wing icing.

During colder days of the winter when the temperature dropped below -15°C, it was attempted to fly through snow and winter storms. Various cold wintry conditions were met to test fly the UAS while developing it. Freezing rain is another cause of icing. It occurs at temperatures close to freezing. Between 2 °C and -5 °C, in freezing rain type of precipitation, glaze or clear icing is ideal to be studied. However, freezing rain is also hard to predict for planning experimental flights. Only few studies are done on it. Few of the biggest organizations such as the National Aeronautics and

Space Administration (NASA) conduct aircraft icing in-flight study on manned aircraft for research. However, UAS have not been used to study icing mainly due to the magnitude of challenge involved with UAS operations and weather applications. 64

The test site for icing study was kept same as for all other sites, for the purpose of being able to compare data. Since calm and windy conditions were met with success at the set loiter waypoints. The next big challenge was to study icing. After tracking weather forecasts for long, it was decided to choose a day with high moisture and temperatures close to freezing. With overcast conditions and fog present at lower altitudes, it was planned to fly in the set waypoint mission to intercept expected conditions that could carry supercooled precipitation.

If successful, the UAS could crash due to loss of lift resulting from excessive icing. However, this was intentional since the data was being collected to study the mode of crash and the variables causing it. Even without crash, the change in lift is desired to be studied for aircraft performance under icing.

In the late afternoon on March 15th, 2021, the UAS was prepared with moderate wind for the experiment with fully charged batteries. Figure 6-1 shows the UAS prepared just before launch.

Ground weather station recorded 6.7 mph winds blowing from 110°.

Figure 6-1. Fixed wing UAS before icing flight. 65

6.1.1 Results

The UAS took off and progressed through the designed waypoints. Multiple waypoint readings were taken. However, for comparison purposes the loiter point of 120 m is used in this study. At the assigned altitude, the UAS flew with relatively stable throttle that varied 1% to 2% to adjust power. This was done to reach and maintain the setpoints of the mission. In this case, due to existence of slight wind, power required adjustments. Figure 6-2 shows the throttle adjustment during one complete circle flown. However, at 60 seconds into the loiter, throttle started increasing dramatically.

Throttle Percentage 65 64 63 62 61

60 Throttle (%) 59 58 57 0 10 20 30 40 50 60 70 80 90 Time (s)

Figure 6-2. Throttle Percentage

Power consumption varied according to throttle input from the autopilot. One of the important observations here is that, with time power consumption was increasing. According to Figure 6-3, the power consumption increased by 154 W during the loiter segment of the flight. This was a dramatic and continuous increase in power consumption, which was different from random spikes.

Power Consumption 700

600

500

400

300 Power Power (W) 200

100

0 0 10 20 30 40 50 60 70 80 90 Time (s)

Figure 6-3. Variation in power consumption

Roll 30

10 Roll Roll angle (degrees) 5

0 0 10 20 30 40 50 60 70 80 90 Time (s)

Figure 6-4. Roll angle variation during the phases of 360° loiter turn.

It was observed that during the loiter, the UAS had a varying roll angle from 5° to 26.5° as shown in Figure 6-4. The shape of this graph depends on at which orientation relative to the wind 67 the UAS reached the assigned loiter point height. This roll angle graph varies from the windy condition roll angle graph which had more extreme range of roll angle variation during the loiter.

Aircraft heading angle showed an affinity to fly facing the 100° heading as closely as possible while between the headwind and crosswind, indicating the correctness of the direction of wind from weather report at takeoff. Figure 6-5 shows the longest flight time was spent between the headings of 60° and 150°. The graph has a different shape than windy condition heading graph, where the heading angle range facing the wind was much larger and horizontal than this curved and inclined. The curved and inclined part is an indicative of more coordinated turning.

Heading 400 350

300 ) ° 250 200 150

100 Headingangle ( 50 0 0 10 20 30 40 50 60 70 80 90 -50 Time (s)

Figure 6-5. Heading angle of the aircraft

The indicated airspeed was incorrect at around -6 m/s during the entire phase of this flight, indicating malfunction of the airspeed sensor. The ground speed varied between 5 m/s and 21 m/s during the flight. The top speed of 21 m/s was observed when the UAS was flying at a heading angle of 285° which was opposite to the direction the wind was blowing from. Tailwind flight increases ground speed to maintain airspeed for flight. At about the heading of 100°, the UAS had 68 slowed down to the lowest ground speed reading of about 5 m/s. The shape of this graph is less extreme than that of the windy condition flight, where the ground speed varied more extremely going from 4.2 m/s to 33 m/s instead. Figure 6-6 shows the comparison between indicated airspeed and ground speed during the icing condition.

Speed 25 Ground Speed Indicated Air speed 20

5 Speed Speed (m/s) 0

-5

-10 0 10 20 30 40 50 60 70 80 90 Time (s)

Figure 6-6. Indicated air speed of the aircraft and the GPS-based ground speed.

Icing conditions are influenced by temperature, pressure, and humidity in addition to wind.

This is the main reason why these atmospheric parameters are collected in this aerial system in real-time. The ice accretion takes place with current conditions surrounding the aircraft. As already observed earlier, the power consumption curve had an increasing trend with respect to time. It is, therefore, important to monitor the temperature and humidity variation in the aircraft surroundings.

Figure 6-7 shows that the temperature readings were dropping in a downward trend over time, from -0.6°C to -0.85°C. There was also fluctuation in temperature data by 0.215°C due to the accuracy range of the K-type thermocouple up to +/- 2°C. However, the current temperature at this range was still under freezing and could lead to ice formation. 69

Temperature

0 10 20 30 40 50 60 70 80 90 0 -0.1

-0.2 C)

° -0.3 -0.4 -0.5 -0.6

-0.7 Temperature Temperature ( -0.8 -0.9 -1 Time (s)

Figure 6-7. K-type Thermocouple readings

Figure 6-8 shows that with time the humidity increased by about 5% and had a continuously increasing trend during the loitering flight. This indicated the presence of increasing moisture in the atmosphere, which indicated there could be significant liquid water content present.

Humidity 68

Relative Relative Humidity(%) 63

62 0 10 20 30 40 50 60 70 80 90 Time (s)

Figure 6-8. Relative humidity readings from BME280 sensor 70

The pressure variation recorded by barometer were relative to change in altitude during loitering flight. Pressure readings averaged around 961.25 hectopascals. However, there was some random noise in pressure by about 0.2 hPa as shown in Figure 6-9. This was within the accuracy range of the sensor (+/- 1 hPa).

Pressure 961.6 961.5 961.4 961.3 961.2 961.1 Pressure Pressure (hPa) 961 960.9 960.8 0 10 20 30 40 50 60 70 80 90 Time (s)

Figure 6-9. Barometric pressure from BME280 sensor

The complete mission profile is shown in Figure 6-10. The orange line indicates the designed mission. The red line indicates the trajectory of the flown mission of the UAS. This snapshot is taken at the end of the mission, when the UAS was taken back to the base station which is next to the launch point. Notice that compared to the windy day, in icing condition the aircraft flew in nearly circular path that is defined by the large red circle shown in Figure 6-10. 71

Figure 6-10. Icing Flight

Upon completing the mission, the UAS returned with iced wing as shown in the Figure 6-11.

There was a significant amount of icing observed on the leading edge of the wing, which was immediately recognizable. This image was taken by the camera embedded in the fuselage of the aircraft for detecting ice accretion. For comparison with a clean wing, the aircraft is shown in the same final approach on another day when there was no precipitation, as shown in Figure 6-12. 72

Figure 6-11. Leading edge Ice accretion observed during final approach.

Figure 6-12. Clean wing flight on a calm day on final approach 73

Figure 6-13. Ice accumulation under the wing

Most of the icing was hard, however due to warmer temperature on the ground, some thinner ice had begun melting. Detailed post flight images were captured as soon as the aircraft landed to get the best view possible. Figure 6-13 and Figure 6-14 show the icing under the wing and on the leading-edge sides. There were also runback icing rivulets visible on top surface downstream of the leading edge as shown in Figure 6-15.

Figure 6-14. Ice accumulation on the leading edge and top surface 74

Figure 6-15. Runback rivulets

It was discovered that there was significant icing on all leading edges of the aircraft including the nose. The leading edge of the red laminated horizontal stabilizer had a layer of clear ice built up with some thickness on top and bottom surface as well. The twin vertical stabilizers of the aircraft had a solid leading edge ice accretion that was not melting from touch. However, it got dislodged upon pushing it with sufficient force. Figure 6-16 and Figure 6-17 shows the ice accretion on the leading edge of the horizontal and vertical stabilizers.

Figure 6-16. Leading edge of the horizontal stabilizer

Figure 6-17. Leading edge of the vertical stabilizer 76

Icing on lifting surfaces is detrimental when it comes to providing aerodynamic forces and stable flight conditions. It creates a rough surface with disturbed flow, creating eddies and turbulence, resulting in increased drag. Without adequate ice protection system, the excessive change of shape can result in aerodynamic stall condition and crash. Icing on critical instruments can be as problematic. It was observed that the total pressure and static pressure ports of the pitot- static tube were blocked as the entire tube was iced. The rest of the surface was coarse in look and with glaze icing. Figure 6-18 shows the pitot static tube covered in clear icing.

Figure 6-18. Fully iced pitot-static tube with blocked ports

Figure 6-19. Propeller icing (leading edge view) with visible glaze iced horns. 77

The aircraft had landed safely despite the icing because the experimental mission was designed for a relatively short duration. Figure 6-19 above shows the propeller was heavily iced during flight. There are horns and ridges formed on the pressure and suction sides, which are considered to be among the most detrimental form of clear icing. The leading edge is also iced significantly to change the shape of the propeller. It is indicative of the reason power consumption could be increasing during flight. Furthermore, part of leading edge appears to have shed the ice during rapid increase in rpm or due to landing impact. The separation line is approximately half-way span wise from the blade tip. Because outer part of the blade spins faster, therefore it could have led the outer half of the blade to shed ice compared to the inner half.

To further analyze the ice accretion, dry ice was procured, and insulating foam boxes were prepared to preserve the iced specimens. The propeller was removed from the motor and carefully stored in the box with dry ice suitable to prevent further melting of the iced propeller. Because the entire aircraft or the main wing were too large to preserve for transportation, it was decided to disconnect one of the vertical tails instead and preserve it in the box as well.

These preserved specimens were taken to the Icing Wind Tunnel Laboratory’s freezer and stored for further analyses. Figure 6-20 shows the use of dry ice to store samples at the test site.

Figure 6-20. Iced propeller being storedin dry ice container 78

Figure 6-21. Iced propeller painted for 3D scanning.

To measure the mass and volume of the accumulated ice in further analysis, propeller and tail were carefully removed, and spray painted with multiple coats as shown in Figure 6-21. This was necessary to prevent laser light distortions through clear ice causing incorrect projections. HP 3D

Scan Pro software was used to stitch and align the images to create and refine the mesh. The scanning was performed by using the recommended projector and camera setup by the software manufacturers. The setup used for propeller and tail 3D scanning is shown in Figure 6-22 and

Figure 6-23. During the scan, the hub of the propeller was used to mount it on the stand with additional materials. On the stand, the lower side of the blade was not scanned since it was used to fix the propeller in dry ice insulation box damaging the icing. The second side blade which is on the upper orientation in Figure 6-22 is scanned for analysis. 79

Figure 6-22. Propeller mounted on the stand with calibration markers for 3D scanning setup.

Figure 6-23. Vertical tail being scanned using HP 3D Scan Pro. 80

From the scan results, the volume of ice accumulated on one blade of the propeller was calculated to be 1359.5 mm3. This was equivalent of a 1.2 g mass of ice accretion. The original mass of the entire propeller was 43g. Furthermore, 0.5 g of ice accretion was calculated on the right vertical stabilizer after stitching and post analysis of the images used for 3D scanning. The scanned 3D models of the clean and iced propeller and the cross-sectional analyses are shown in

Figures 6-24 and 6-25, respectively.

Figure 6-24. Propeller Ice Accretion

Figure 6-25. Cross sectional view of iced propeller blade

CHAPTER 7. COMPARISON OF RESULTS AND DISCUSSION OF FINDINGS

So far three types of flight experiments have been studied. They were conducted at same loiter point locations, same heights, and same radius. The only thing that varied between their results was type of weather condition. Individual post flight analysis was conducted in chapters 4, 5 and

6. In this chapter, the flight tests are compared with base flight conditions. Furthermore, important findings are discussed.

Calm weather flight was conducted in evening, windy condition flight was conducted during morning and icing flight was conducted during evening. Calm weather had a temperature of 5.82°C that did not require use of hand warmers to keep the LiPo batteries warm during flight. On the other hand, the windy day temperature was 0.21 °C and the icing condition temperature during flight was -1.5 °C at the loiter altitude used for study. Humidity on this day was particularly low as 20.22% compared to windy day when it was the highest at 88.36 % and icing condition humidity was 67.5 %. Atmospheric pressure in calm condition was highest as 977.45 hPa compared to other two windy and icing conditions, where the pressure was 963.34 and 961.3 hPa, respectively. Calm weather was sunny and had no clouds. The wind speed during the experiment was 5.2 m/s on calm day, the highest of 11 m/s during the windy flight and a moderate of 4.8 m/s during the icing flight.

Winds generally blew from East in the range of 100° to 145°. Furthermore, Table 7-1 and Figure

7-1 summarize the weather conditions collected from ground-based weather station at takeoff for reference.

Table 7-1. Comparison of weather parameters at takeoff from ground weather station 82

Calm Windy Icing Time Evening Morning Evening Temperature (°C) 1.5 0.3 0.3 Humidity (%) 45 94 96 Pressure (inHg) 29.29 28.87 28.81 Wind Speed (m/s) 0.6 4.5 3 Wind Direction (°) 150 100 110

Figure 7-1. Comparison of reference weather conditions

During the experimental flights, the greatest power was consumed during the icing condition.

The UAS consumed the second largest amount of power during flight under strong winds. Calm weather led to the least amount of power. The results are summarized in Table 7-2. Icing flight had a noisy power consumption just like the windy day but during the icing build up, power consumption kept increasing during the flight.

Table 7-2. Comparison of power and battery consumption in different weather conditions 83

Power (W) Battery (mah) consumed % increase Calm condition 10548 184 0 Windy condition 24248 461 130 Icing condition 36133 673 243

Calm condition appeared more fuel efficient and led to a total power consumption of 10.5 kW, while the windy condition had an intermediate total power consumption of 24.2 kW. The highest total power 36.1 kW was consumed in flight under the icing conditions. Strong winds led to an increase in power consumption by 130%. Overall increase in power consumption under a single loiter circle in icing conditions was 243%. The wind speeds and directions from ground station and UAS during flight are compared in Table 7-3 for all three flight conditions.

Table 7-3. Comparison of total power consumed during the experiment.

W.S. (Ground) UAS W.S. (Ground) UAS Wind Speed (m/s) Avg Wind Speed (m/s) Wind Direction (°) Avg Wind Direction (°) Calm 0.6 5.2 150 132.7 Icing 3 4.8 110 104 Windy 4.5 10.1 100 101.1

It is seen that at higher altitudes, the wind speeds are much larger than on the ground. The wind direction is also different at higher altitudes. However, under windy condition the wind direction on the ground and air is reported very closely to about 100 degrees.

During each flight, battery was consumed at a different rate. This makes sense because different weather conditions that led to different power consumptions would discharge the batteries or consume the fuel at different rates. Based on Figure 7-2, the greatest battery consumption is caused by flight under icing conditions shown by the red graph. Calm conditions helped conserve the battery as shown by the black line. Additionally, these comparisons show that the starting battery capacities were different for different weather conditions. Each mission was launched with 84 fully charged 5200 mAh battery. The battery had already discharged by different amounts by the time the UAS reached its experimental loiter point where this data was collected. Calm weather had the greatest battery capacity available at the start of the experimental loiter point, then the windy condition and finally the icing condition.

Figure 7-2. Comparison of battery consumption in different weather conditions

Power Consumption under Ice Accretion 1200 30 25 1000 20 800 15 10 600 5

Power Power (W) 400 0 Speed Speed (m/s) -5 200 -10 0 -15 0 50 100 150 200 250 300 350 400 Time (s)

Ground Speed Indicated Air Speed Power (W)

Figure 7-3. Power consumption during ice formation

During the ice accretion test flight, changes in power consumption are of great interest. A careful analysis of the results show that power consumption started to increase with time. It is observable from the red graph in Figure 7-3 that between 37 seconds and 233 seconds, the power consumption increased from 219.68 W to 526.35 W (about 140% increase). Such a significant increase in power consumption was followed by sudden power surge almost instantaneously that lasted for 3 seconds. The surge recorded 1043.8 W of power consumption, which is exactly a 200% increase in power consumption. Since the power consumption is increased by throttle control only, it is therefore possible that increase in throttle while loitering at fixed altitude would only be trigged by this large amount under dangerous flight conditions. These conditions are related to ice formation that compromise flight efficiency. Figure 7-3 also shows the comparison of airspeed and ground speed with the power consumption under icing. Under all flight conditions in the presence of wind, the highest and lowest ground speed coincided with an increase in power consumption which are correct in this case as well. However, there is something different than calm and windy weather flights in this case which led to the highest overall power consumption.

The only explanation for that is the decrease in aerodynamic lift forces, increase in drag, increase in weight or reduction in thrust leading to a need for an increase in propeller RPM. To continue flying the aircraft under such conditions, the autopilot signals the Electronic Speed Controller

(ESC) to speed up the propeller RPM thereby increasing the thrust. This leads to increase in power consumption. However, the ice build-up continues and if allowed for sufficient time, all aerodynamic lift forces could be diminished leading to an ultimate crash. The UAS did not have ice protection systems on its wings, however if the propeller icing accumulated significantly, it will have to keep speeding up to compensate for loss of thrust efficiency. One of the reasons the rapid surge in power may have occurred for 3 seconds duration is to shed the mass of ice. After 86 this instance, the power consumption reduced, but then again started to increase in few seconds.

Even if propeller shed the icing, it will continue to form ice on the wings and even propeller over time. Having seen the images and 3D scans of the iced propeller after landing, there was a portion of propeller leading edge that lacked icing unusually. It is highly probable that chunk of ice was shed during such a surge of power in flight.

At 283 seconds, the indicated air speed, which is always constant during flight dropped completely, as if pitot static tube stopped working or the airspeed sensor malfunctioned. From this instance onward, the airspeed went to negative. This is another consequence of glaze icing, where ice formation on total port of the pitot tube will result in negative readings. These are important findings regarding the negative effects of icing on aircraft performance. After the malfunction of air speed sensor, the UAS entered an emergency return to land mode, based on GPS compass- based navigation to land safely.

During the windy day, power varied according to various aspects of flight. During takeoff and climb outs, there is a rapid surge in power. However, due to winds and gusts, the power variation also takes place significantly. Figure 7-4 shows how the power dropped to near zero during descent from 120 m height. Comparing Figure 7-4 with Figure 7-5 shows how with increase in height, temperature dropped, and humidity increased. At the end of loiters, the temperature increased, and humidity dropped again, capturing the expected variation during the atmospheric variables in the morning. These variations can be different in evenings or late afternoons due to different temperature inversion effects. During this phenomenon, warm air and moisture rises and can lead to an increase in temperature and humidity with altitude for a certain height. 87

Power variation with Height 140 1200

120 1000 100 800 80 600

60 Height(m) 400 Power (W) 40 20 200 0 0 0 100 200 300 400 500 600 700 Time (s)

Height (m) Power Consumption

Figure 7-4. Windy day power variation with height

Moreover, some additional reasons for increases in power consumption are considered. The flight data from the calm day was studied for the entire flight duration, as shown in Figure 7-6.

Variation of atmospheric parameters 1.5 90

89 C)

° 1 88 87 0.5 86 85

0 84 Humidity(%) Temperature Temperature ( 83 -0.5 82 0 100 200 300 400 500 600 Time (s)

Temperature (°C) Humidity (%)

Figure 7-5. Windy day atmospheric parameters with height 88

Figure 7-6. Flight Data Analysis (“The big picture”)

It is observed that during climbs, the throttle and power increases rapidly, while during descent it reduces to zero. When, coupled with the ground speed, roll angle and heading angle, further understanding can be gained into flight behavior. Figure 7-7 is used for a closer look into the situation. 89

Figure 7-7. Identification of power surges in a calm weather

When investigating each second of flight data, it is helpful to start somewhere and then follow along logically, considering cause and effect approach. For instance, observable changes in throttle point to respective changes in power consumption. Figure 7-7 shows two sets of throttle and power spikes found along the green and black vertical lines. If we follow down the ladder, we see that 90 the green line intercepts the max ground speed which occurs when the UAS is flying with the approximate heading of 310°. This is when the UAS is approximately flying with tailwind and it attempts to maintain the loiter turn radius in clockwise direction. Due to the strong wind pressure encountered against the turn direction, the roll authority kicks in and the ailerons are actuated. The turn requires a high roll angle of greater than 30° every time in this situation during the flight.

Therefore, to make the turn successfully against the wind pressure which is trying to push or slip away the aircraft off the circular path, throttle increase may have been applied by autopilot.

Another observation is along the black lines, which pass through the second greatest increase in throttle and power consumption. When following down in this sequence, it exactly intercepted the minimum ground speed as marked by black squares. Next, it was discovered that the heading of the UAS during this condition was 145°. This is the direction from which wind was blowing.

Also, the roll angle in this case is smallest since the aircraft can fly level with the oncoming headwind.

Figure 7-8 shows that the flight data is smooth during calm weather. The circular shaped ground speed has a uniform curve that is constantly changing. The slowest speed part of the curve represents aircraft flying with headwind directly. Notice that the heading angle graph has a flatter section that exists relatively long time during the loiter. This section is representing the crabbing or facing of the UAS towards the headwind to increase relative air flow. Figure 7-9 shows the similar graph but for windy conditions. Here the red squares indicate information of interest. The first red square is indicating that the ground speed is relatively constant or fixed value of a significant time of the loiter in windy condition. 91

Figure 7-8. Identification of power surges in a calm weather

The roll angle is nearly zero and the heading angle is against the oncoming wind blowing from

100 degrees. Most of the times during the loiter under windy conditions, the UAS tries to crab and face the relative wind as much as possible to minimize chances of stall at lower speeds. The windy condition flight data is noisy and fluctuates. It can be hard to understand, therefore, to make clear sense of its trend, a moving average is used as shown by the red line in Fig 7-10. The red line is clearer and has reduced noise. It is used to identify the variation in power consumption at two different power and throttle increases. The higher increase in power consumption is observed when the UAS is flying with headwind, while the next highest surge in power consumption is seen when the UAS is flying with tailwind, and it attempts to turn clockwise against the pressure of the wind while flying the loiter pattern. 92

Figure 7-9. Identification of power surges in windy weather

Figure 7-10. Using Moving Average to filter out high frequency noise.

Power consumption and throttle under the given state of flight at assigned waypoints are summarized in Table 7-4 and Table 7-5. During windy conditions, increase in throttle and power consumption is significantly large compared to the case of calm weather. It is seen that the range of roll angle and ground speed variation is larger in windy condition than in the calm condition.

Table 7-4. Comparison of power and throttle changes in windy and calm conditions

Calm weather Windy weather

Power (W) Min Max Difference Min Max Difference

Facing the wind 218.79 W 240.64 W 21.85 W 150 W 457 W 307 W

Turning against tailwind 223.55 W 237.09 W 13.54 W 292.4 W 351.15 W 58.75 W

Throttle (%) Min Max Difference Min Max Difference

Facing the wind 53% 55% 2% 44% 66% 22%

Turning against tailwind 54% 55% 1% 52% 62% 10%

Table 7-5. Flight conditions for power and throttle change comparison

Calm weather Windy weather

G.S. (m/s) Roll (°) Heading (°) G.S. (m/s) Roll (°) Heading (°)

10.6 7.2 146 4.7 6 102

24.9 32 301 32.7 35.1 280

During the climb phases of the aircraft temperature and humidity are expected to change based on change in atmospheric condition. Temperature normally decreases with elevation. The results between the constant climb of 30 m from 90 m to 120 m altitudes above ground level were compared for calm, windy and icing conditions. Calm and icing flights were in the late afternoon, and the windy flight was in morning. Both windy and icing flights were conducted on the same day, while the calm flight was conducted approximately one week later. Temperature decreased by 0.336°C for windy conditions and by 0.391°C for icing conditions. Temperature during calm 94 conditions decreased by 0.039°C. At first, temperature decreased by 0.258°C till 111 m height and then it increased by 0.219°C towards 120 m height, as shown in Figure 7-13. It is possible that this unusual pattern existed due to effects of the temperature inversion in the lower atmosphere.

Variation in Temperature with Height 120

115

110

105

Height(m) 100

90 -2 -1 0 1 2 3 4 5 6 7 Temperature (°C)

Calm Windy Icing

Figure 7-13. Temperature variation with height

During the climb, it was observed that relative humidity increased for all three weather conditions.

The largest increase of 0.86% occurred for icing condition, as there was significant moisture in the lower atmosphere that day, which resulted in ice accretion. For windy condition, humidity increased by 0.37%. For the calm condition, humidity increased by only 0.22% only. The relative humidity on the calm day was about 20%, which is considered extremely low as the air carries low moisture.

During calm conditions, the UAS flew in relatively less windy condition compared to any other flight condition. It was observed that the wind speed changed 5.1 m/s to 5.3 m/s with an average of 5.2 m/s wind speed under calm conditions. In comparison, the wind speed on average was 10 m/s with a variation from 9.9 m/s to 10.8 m/s during the loiter. Wind directions and speeds during 95 flight were compared to weather reports and they were found within a close range. Figure 7-14 shows the comparison of wind speed and directions of the windy weather flight from the base data of calm weather.

Figure 7-14. Comparison of wind speeds and directions between calm and windy weather

conditions

CHAPTER 8. CONCLUSIONS AND RECOMMENDATIONS

Adverse weather has been a threat to the safety of people on the ground and in the aircraft during flight. Deterioration of flight performance and the expense of fuel consumption are some of the factors associated with these conditions. This study surveyed the current problems associated with manned or unmanned fixed-wing aircrafts due to inclement weather. Various atmospheric conditions were investigated which have an influence on negative effects generated.

This study details the comprehensive experimental setup and procedures developed to investigate the negative effects of weather on fixed-wing UAS. Different atmospheric conditions were studied that existed during the experimental flights. The flights were conducted in calm, windy and icing conditions. Observations were made using onboard cameras and sensors that transmitted and recorded real time data with the help of on-board Data Acquisition Unit and long- range radio telemetry. The UAS was tested extensively before collecting experimental data to ensure its safety and reliability.

The power consumption data was studied under windy and icing conditions and compared with the baseline calm weather flight. Leading edge and propeller icing were obtained. Ice accretion was observed during flight using onboard cameras. This state-of-the-art study led to understanding the limitations and severe degradation of flight performance under weather outside the laboratory environment where conditions were uncontrolled and 100% natural. Total power consumption was greatest in icing condition, then in windy condition and least in calm conditions. The power consumption in the windy conditions was further investigated in detail to study the reason for significant variations. The analysis revealed that headwind flight led to greatest power consumption. This must be due to the increased drag on aircraft by the push created on its body against the wind. The next highest power consumption was identified at the part of loiter where 97 the UAS was turning clockwise against crosswind. This was a transition phase where tailwind changed to crosswind in maintaining the fixed loiter pattern. The UAS had the highest roll angle to make this turn which would be required to withstand the large pressure of the wind on its entire body.

The results obtained from this study can lead to development of better UAS design and improvement in flight techniques that can help enhance performance and safety. A better understanding of flight under adverse weather is established. Ice accretion can be mitigated by developing and testing new techniques used to prevent or eliminate aircraft icing during flight.

8.1 Recommendations for future work

This study was conducted in calm, windy and icing conditions. Heavy rain and snow may cause increased drag or reduction in lift forces as well. In future, the effects of these conditions may be studied for comparisons. The flights may be conducted at set times of the day through all seasons of the year to understand how the diurnal cycle and the seasonal changes in weather affect flight performance. In this investigation, clear (glaze) ice formation was investigated. In future studies, rime ice and mixed ice conditions may also be investigated. Currently, a catapult launcher is being developed to assist in all-weather condition takeoffs. In future, the launcher may be utilized to help reduce power consumption at takeoff and increase safety of the mission. Current study compared data from single circle of the loiter flights. Future studies may be conducted with longer flight times. More number of flights are required with set time during the diurnal cycle to collect sufficient data for understanding local temperature inversion effects throughout all seasons.

Furthermore, higher altitudes can offer better change of atmospheric parameters and flight performance data. With the appropriate airspace authorizations, Beyond Visual Line of Sight

(BVLOS) flights may be conducted at higher altitudes and longer ranges. The superhydro-/ice- 98 phobic coatings may be applied on the aircraft propeller and wings to study the changes in ice formation and aerodynamic performance characteristics during flight.

REFERENCES

[1] L. Prince Raj, J. W. Lee, and R. S. Myong, “Ice accretion and aerodynamic effects on a multi-element airfoil under SLD icing conditions,” Aerosp. Sci. Technol., vol. 85, pp. 320–333, 2019, doi: 10.1016/j.ast.2018.12.017. [2] Y. Liu, L. Li, W. Chen, W. Tian, and H. Hu, “An experimental study on the aerodynamic performance degradation of a UAS propeller model induced by ice accretion process,” Exp. Therm. Fluid Sci., vol. 102, no. November 2018, pp. 101–112, 2019, doi: 10.1016/j.expthermflusci.2018.11.008. [3] P. Pellicano, C. Dumont, T. Smith, J. Riley, and D. Report, “Propeller Icing Tunnel Test on a Full-Scale Turboprop Engine,” Security, no. March, 2010. [4] A. P. Broeren, C. M. LaMarre, M. B. Bragg, and S. Lee, “Characteristics of SLD ice accretions on airfoils and their aerodynamic effects,” 43rd AIAA Aerosp. Sci. Meet. Exhib. - Meet. Pap., no. April, pp. 3027–3050, 2005, doi: 10.2514/6.2005-75. [5] R. M. Waldman and H. Hu, “High-speed imaging to quantify transient ice accretion process over an airfoil,” J. Aircr., vol. 53, no. 2, pp. 369–377, 2016, doi: 10.2514/1.C033367. [6] W. O. Valarezo, F. T. Lynch, and R. J. McGhee, “Aerodynamic performance effects due to small leading-edge ice (Roughness) on wings and tails,” J. Aircr., vol. 30, no. 6, pp. 807–812, 1993, doi: 10.2514/3.46420. [7] Y. Liu, L. Li, H. Li, and H. Hu, “An experimental study of surface wettability effects on dynamic ice accretion process over an UAS propeller model,” Aerosp. Sci. Technol., vol. 73, no. December, pp. 164–172, 2018, doi: 10.1016/j.ast.2017.12.003. [8] S. Library, “Govt. docs,” 1950. [9] A. Shek, “Propeller Blade Analysis,” 2019. [10] L. Li, Y. Liu, Z. Zhang, and H. Hu, “Effects of thermal conductivity of airframe substrate on the dynamic ice accretion process pertinent to UAS inflight icing phenomena,” Int. J. Heat Mass Transf., vol. 131, pp. 1184–1195, 2019, doi: 10.1016/j.ijheatmasstransfer.2018.11.132. [11] F. Al-masri, “Experimental investigation on the icing physics and anti- / de-Icing technology of an aircraft pitot probe,” 2020. [12] L. Gao, Y. Liu, L. Ma, and H. Hu, “A hybrid strategy combining minimized leading-edge electric-heating and superhydro-/ice-phobic surface coating for wind turbine icing mitigation,” Renew. Energy, vol. 140, pp. 943–956, 2019, doi: 10.1016/j.renene.2019.03.112. [13] C. Kolbakir, H. Hu, Y. Liu, and H. Hu, “An experimental study on different plasma actuator layouts for aircraft icing mitigation,” Aerosp. Sci. Technol., vol. 107, p. 106325, 2020, doi: 10.1016/j.ast.2020.106325. 100

[14] A. Winter, R. Hann, A. Wenz, K. Gryte, and T. A. Johansen, “Stability of a Flying Wing UAV in Icing Conditions,” 8th Eur. Conf. Aeronaut. Aerosp. Sci. (EUCASS). June, 2019, doi: 10.13009/EUCASS2019-906. [15] R. Hann, A. Wenz, K. Gryte, and T. A. Johansen, “Impact of atmospheric icing on UAV aerodynamic performance,” 2017 Work. Res. Educ. Dev. Unmanned Aer. Syst. RED-UAS 2017, pp. 66–71, 2017, doi: 10.1109/RED-UAS.2017.8101645. [16] S. G. Pouryoussefi, M. Mirzaei, M. M. Nazemi, M. Fouladi, and A. Doostmahmoudi, “Experimental study of ice accretion effects on aerodynamic performance of an NACA 23012 airfoil,” Chinese J. Aeronaut., vol. 29, no. 3, pp. 585–595, 2016, doi: 10.1016/j.cja.2016.03.002. [17] Q. Huang, M. Zhang, and S. Liu, “Aircraft Departure Fuel Consumption Improvement Model Based on Flight Data,” IOP Conf. Ser. Mater. Sci. Eng., vol. 688, no. 2, 2019, doi: 10.1088/1757-899X/688/2/022031. [18] J. Osborne and R. Rysdyk, “Waypoint guidance for small UAVs in wind,” Collect. Tech. Pap. - InfoTech Aerosp. Adv. Contemp. Aerosp. Technol. Their Integr., vol. 1, pp. 459– 470, 2005, doi: 10.2514/6.2005-6951. [19] J. Hung, “Investigation of methods for increasing the energy efficiency on unmanned aerial vehicles (UAVS),” Queensl. Univ. Technol., no. Thesis of Master of Engineering, 2011, [Online]. Available: http://eprints.qut.edu.au/46247. [20] A. Bureau of Meteorology, “Airframe Icing,” 2015. [21] S. E. Larsen, “The atmospheric boundary layer over land and sea: Focus on the off-shore Southern Baltic and Southern North Sea region.,” no. January 2013, p. 40, 2013, [Online]. Available: http://orbit.dtu.dk/files/60086685/South_Baltic_OFFER_phd_course_notes.pdf. [22] B. H. Wang, D. B. Wang, Z. A. Ali, B. Ting Ting, and H. Wang, “An overview of various kinds of wind effects on unmanned aerial vehicle,” Meas. Control (United Kingdom), vol. 52, no. 7–8, pp. 731–739, 2019, doi: 10.1177/0020294019847688. [23] S. Mayer, G. Hattenberger, P. Brisset, M. Jonassen, and J. Reuder, “A ‘no-flow-sensor’ wind estimation algorithm for unmanned aerial systems,” Int. J. Micro Air Veh., vol. 4, no. 1, pp. 15–29, 2012, doi: 10.1260/1756-8293.4.1.15. [24] M. Mondek, “Small UAV flight control system - Wind estimation system,” Czech Technical University in Prague, 2015. [25] C. Mallaun, A. Giez, and R. Baumann, “Calibration of 3-D wind measurements on a single-engine research aircraft,” Atmos. Meas. Tech., vol. 8, no. 8, pp. 3177–3196, 2015, doi: 10.5194/amt-8-3177-2015. [26] A. Cho, J. Kim, S. Lee, and C. Kee, “Wind estimation and airspeed calibration using a UAV with a single-antenna GPS receiver and pitot tube,” IEEE Trans. Aerosp. Electron. Syst., vol. 47, no. 1, pp. 109–117, 2011, doi: 10.1109/TAES.2011.5705663.