Rotor Blade Optimization and Flight Testing of a Small UAV ...

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Rotor Blade Optimization and Flight Testing of a Small UAV Rotorcraft

Journal: Journal of Unmanned Vehicle Systems

Manuscript ID juvs-2017-0005.R2

Manuscript Type: Article

Date Submitted by the Author: 12-Mar-2019

Complete List of Authors: Kotwicz Herniczek, Mark; Carleton University Faculty of Engineering and Design, Mechanical and Aerospace EngineeringJee, Dustin; Carleton University Faculty of Engineering and Design, Mechanical and Aerospace EngineeringSanders, Brian; Carleton University Faculty of Engineering and Design, Mechanical and Aerospace EngineeringFeszty, Daniel; Carleton University Faculty of Engineering and Design, Mechanical and Aerospace Engineering

Keyword: UAV, Rotorcraft, BEMT, Optimization

Is the invited manuscript for consideration in a Special

Issue? :Not applicable (regular submission)

https://mc06.manuscriptcentral.com//juvs-pubs

Journal of Unmanned Vehicle Systems

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Rotor Blade Optimization and Flight Testing of a Small UAV Rotorcraft

Mark Kotwicz Herniczek ∗

Research Associate

Dustin Jee

Research Associate

Brian Sanders

Research Associate

Daniel Feszty

Adjunct Professor

Department of Mechanical and Aerospace Engineering, Carleton University

Ottawa, ON, Canada

Abstract

Rotor blade optimization with blade airfoil Reynolds numbers between 100,000 and 500,000 - characteristic of small

single-rotor Unmanned Aerial Vehicles (UAV) - was performed for hover using Blade Element Momentum Theory

(BEMT) and demonstrated via flight tests. BEMT was used to test various airfoil profiles and rotor blade shapes

using airfoil data from 2D computational fluid dynamics simulations with Reynolds numbers representative of the

blade elements. Selected blade designs were manufactured and flight tested on a Blade 600X single main-rotor UAV

(671 mm blade radius) to validate the theoretical results. The parameters considered during the optimization process

were the rotor frequency, radius, taper ratio, twist, chord length, airfoil profile and blade number. The best of the

improved blade designs increased the figure of merit, a measure of rotor efficiency, from 0.31 to 0.68 and reduced power

consumption by 54%. Reducing the rotational frequency accounted for 45% of the improvement in power consumption,

while the taper ratio and blade number accounted for 25% and 17% respectively. The blade twist and airfoil profile only

had a minor effect on the power consumption, contributing 7% and 6% to the improvement. The rotor diameter and

root chord were kept identical to the original rotor and hence had no contribution. The presented results could serve as

useful guidelines to single-rotor UAV manufacturers and operators for increasing endurance and payload capabilities.

Nomenclature

Cd section drag coefficient

Clα section lift-curve slope

CP rotor power coefficient

CT rotor thrust coefficient

F Prandtl’s tip-loss function

FM figure of merit

kx longitudinal linear induced inflow coefficient

ky lateral linear induced inflow coefficient

LD section lift coefficient

P rotor power (Pinduced + Pprofile)

∗Corresponding author (email: [email protected])

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Q rotor torque

r non-dimensional radial distance

R blade radius

Re Reynolds number

T rotor thrust

vi induced velocity

vtip tip velocity

y+ non-dimensional wall distance

Ω rotor rotational frequency

αTPP tip path plane angle of attack

λ total rotor inflow ratio through disk

λh rotor inflow ratio in hover

λi induced rotor inflow ratio

µx advance ratio parallel to tip path plane

µz advance ratio perpendicular to tip path plane

σ rotor solidity

1 Introduction

The use of Vertical Takeoff and Landing (VTOL) vehicles for Unmanned Aerial Vehicle (UAV) missions has grown

exponentially in recent years. Although rotorcraft with fixed pitch rotors - such as quadcopters - have become extremely

popular in the last few years, they are best suited for hover dominated missions with relatively small payloads. For

missions requiring heavier payloads and longer endurance, single-rotor vehicles with controllable blade pitch are more

efficient and thus better suited (Leishman 2006).

The market for single main-rotor UAVs has remained widely divided between the military and commercial sectors,

especially in terms of performance and cost. Military rotorcraft are typically designed for heavier payloads (within the

range of 30 - 200 kg) and are unavailable to the public. On the other hand, commercial single-rotor UAV operators

often utilize smaller, less expensive rotorcraft with lighter payloads (2-10 kg) - many of which are based on off-the-shelf

radio controlled (RC) helicopters with a rotor radius of around 1 m. For these missions the key components of the

UAV - such as the rotor and the drive system - are typically reused in unchanged form. However, commercial RC

helicopter rotors have not been designed for maximizing mission requirements critical for commercial UAV operators,

such as range, endurance or payload. Instead, they have been developed with the primary purpose of conducting short

duration high-performance aerobatic flights. To allow for aerobatic flight a symmetrical airfoil and very high RPM is

necessary, qualities that don’t align with the extended periods of hover typically seen in commercial UAV missions. As

will be demonstrated later in this paper, the endurance of a typical RC helicopter used for UAV missions is only 5-8

minutes long while its hovering efficiency - expressed in terms of the Figure of Merit (FM) - is only around 30%. This

is in sharp contrast to the 80% value observed for manned helicopters (Leishman 2006).

There are a number of differences between typical single-rotor UAVs and manned helicopters that explain these

discrepancies. The rotor blades used in typical unmanned rotary vehicles experience a much smaller Reynolds number

compared to full-scale manned helicopters due to their smaller size. This results in a reduction of the maximum lift-to-

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drag ratio and an early onset of stall (Selig et al. 1995, Anyoji et al. 2014, Kotwicz Herniczek et al. 2016). Additionally,

while full-scale manned helicopters often feature twisted, tapered blades with cambered airfoils, most UAV blades have

no twist, taper nor any airfoil camber. Furthermore, no evidence has been found in the literature that the currently

applied blade number or the rotational frequency of rotors has been optimized for single-rotor UAVs.

Although full scale rotor optimization has been widely studied (Hassan & Charles 1997, Allen & Rendall 2001,

Tatossian & Nadarajah 2011, Leishman & Ananthan 2008, Lee et al. 2010, Leishman 2009, Lee & Kwon 2006) and

low Re airfoils have been developed for aircraft using discrete methods (Selig & Guglielmo 1997, Pfenninger & Vemuru

1988), research regarding small-scale UAV rotor optimization and the manufacturability of those rotors is not evident

in the literature. Some research has been performed at the Micro Air Vehicle (MAV) scale (Bohorquez et al. 2010),

however, the range of Reynolds numbers in this paper are an order of magnitude higher and thus the optimized

rotor blades are likely to be very different. Research has also been published for scaled co-axial rotors, however, the

aerodynamics and optimization involved also differ significantly (Prior & Bell 2011).

The purpose of this paper is therefore to examine whether the efficiency of a 600-class UAV (600 mm nominal rotor

radius), representative of a standard commercial single-rotor UAV, can be improved while maintaining cost-effective

manufacturability of the optimized blades. The paper aims to demonstrate these improvements computationally as

well as through flight tests. UAV developers and operators may be able to use results from this paper to increase the

performance of small (approx. 1 m rotor diameter), single-rotor UAVs.

2 Methodology

The Blade 600X single-rotor UAV (Figure 1), with a rotor radius of 671 mm, was chosen as the test platform due to

the popularity of this category (600–800 class) of aircraft among UAV operators. A 600-class helicopter was selected

instead of the more common 700-800 class helicopters due to its greater ease of use, lower price-point and comparable

the aerodynamics to the 700-800 class rotors.

The main technical parameters of the Blade 600X are shown in Table 1. The stock blades use a NACA 0012 airfoil

and do not feature any twist or taper.

The baseline performance of the UAV was determined through flight testing. A computational method was then

developed by using Computational Fluid Dynamics (CFD) for airfoil section data generation and Blade Element

Momentum Theory (BEMT) for blade optimization. The use of CFD was necessitated by the lack of low Reynolds

number 2D airfoil data needed for the BEMT optimization routine. The CFD method was validated using low Reynolds

number wind tunnel data for the NACA 6409 airfoil from Selig et al. (1995), while the BEMT code was validated using

test cases provided by Leishman (2006) as well as by comparing it to the baseline flight test data. This computational

method was then used to arrive at new rotor geometry and rotor frequency optimized for endurance and range.

Once the new blade geometry had been defined, the design was assessed to ensure the complexity of the geometry did

not surpass the capabilities of the manufacturing process and Finite Element Analysis (FEA) was used to evaluate the

feasibility of the structural design. The vetted design was then manufactured and flight tested using an instrumented

Blade 600X UAV. In the following sections, details of the CFD method, the BEMT code utilized, as well as the UAV

instrumentation and flight test results are described. Blade optimization was also performed for forward flight, however,

these results are presented to a limited extent due to the scope of the paper, which focuses on demonstrating efficiency

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improvements in hovering flight.

3 2D Airfoil Data Development

Since BEMT discretizes the rotor blade into two dimensional elements, 2D airfoil data for blade sections along the rotor

at the corresponding Reynolds and Mach numbers is required to yield accurate results. For a rotor with a 671 mm

radius and 2,000 RPM, the tip speed is only around Mach 0.4 (at standard sea level conditions), while the Reynolds

number along the blade varies between 0 at the root and 500,000 at the tip. Although there have been significant

efforts to produce airfoil data for Reynolds numbers within this range (Selig et al. 1995, 1996, Lyon et al. 1998, Selig

& McGranahan 2004, Williamson et al. 2012), low Reynolds number airfoil data remains very limited relative to data

suited for full-scale helicopter applications, i.e. in a range between 3 million and 9 million. Since an airfoil’s stall

characteristics and flow behaviour can differ significantly at low Reynolds numbers, use of CFD was necessary to

generate the relevant data.

CFD simulations were performed using ANSYS CFX and the airfoil geometry was modeled in ANSYS ICEM. Only

an overview of the key findings regarding verification and validation are provided here; refer to Kotwicz Herniczek et al.

(2016) for further details of the CFD validation.

For the verification and validation of the method, a set of test cases from Selig et al. (1995) consisting of a NACA

6409 airfoil exposed to a freestream with a Mach number of 0.03 (corresponding to a Reynolds number of 200,000)

was chosen. The outcome of this process was the identification of a minimum density mesh for the simulations, which

consisted of 92,014 elements (61,092 nodes) and a first spacing off the wall of 0.001c (y+ ∼ 0.5). It was found that the

best comparison with experiment was obtained when a transitional Shear Stress Transport (SST) turbulence model

was used, suggesting that the flow transitioned from a laminar to turbulent regime near the trailing edge of the airfoil.

These numerical parameters were used for all simulations presented in this paper, and served as an input to the BEMT

optimization routine.

3.1 Low Reynolds Number CFD Data for Selected Airfoils

The Blade 600X UAV uses a symmetric NACA 0012 airfoil. While appropriate for aerobatic flights for which the Blade

600X was designed, this airfoil is not ideal for flight missions typical of commercial UAVs, such as high payload hover or

forward flight. Since the blades operate at low Reynolds number (<500,000) and low Mach number (<0.4) conditions,

airfoils that are used on the blades of full-size helicopters are equally sub-optimal.

The following airfoils, shown in Figure 2, were selected to be tested and used during the blade optimization process:

E387, S7055, NACA 0012, NACA 0009, NACA 2409, NACA 4409, NACA 6409 and NASA RC(4)-10. The first two

airfoils, E387 and S7055, are sailplane airfoils for which experimental airfoil data is available in a study by Selig et al.

(1995) at the University of Illinois at Urbana-Champaign. The four NACA series airfoils with 9% thickness and camber

varying from 0 to 6% (similar thickness and camber to low Reynolds number airfoils) were selected to explore the

potential of using standard NACA airfoils for low Reynolds number applications. Thicknesses below 9% were not

considered owing to blade manufacturing, balancing, and stiffness concerns. The last airfoil, NASA RC(4)-10, is used

on full-size helicopters and was chosen for comparison purposes.

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Low Reynolds number lift and drag data produced by CFD for the five NACA series airfoils considered are included

in Figures 3a and 3b. As expected, a thinner airfoil will have a lower drag coefficient but will experience stall earlier.

Camber increases the maximum lift-to-drag ratio from 40 for the NACA 0012 and NACA 0009 to 47, 51 and 52 for the

NACA 2409, NACA 4409 and NACA 6409 respectively. These are are achieved at angles of attack of 8.3, 6.9, 6.3,

5.7 and 4.7 for the NACA 0012, NACA 0009, NACA 2409, NACA 4409 and NACA 6409.

4 Blade Element Theory

The concept of Blade Element Theory (BET) allows for an estimation of the performance of a rotor for both hover and

forward flight. The greatest challenge for implementing this method is to express the inflow velocity along the blade.

In hover, this can be done by combining BET with Momentum Theory, while in forward flight, semi-empirical methods

need to be involved due to the complexity of aerodynamics and blade dynamics.

4.1 Hover

Blade Element Theory discretizes the rotor blade such that each finite element can be considered as a two-dimensional

airfoil for which aerodynamic forces and moments can be determined. These sectional loads can then be integrated

over the blade span and averaged over one rotor revolution to estimate overall rotor performance (Leishman 2006).

Momentum Theory (necessary to calculate the inflow velocity, vi) models the rotor of the UAV as an infinitely thin,

one-dimensional disk and applies conservation of mass, momentum and energy to the control volume surrounding the

rotor and its wake.

Combining both methods, the non-uniform inflow (in hover) along a rotor blade can be estimated using BEMT as:

λh(r) =vi(r)

vtip=

√σClr

8F(1)

Once the inflow ratio is known, Eqs. (2) and (3), describing the discretized thrust and power of the rotor can be

integrated and used to assess rotor efficiency considering rotor twist, airfoil shape and sectional orientation.

dCT =1

2σClr

2dr (2)

dCP = dCTλh +1

2σCdr

3dr (3)

The sectional lift and drag coefficients (Cl and Cd) in the above equations are obtained from the CFD simulations

described previously.

Figure of Merit, the ratio of ideal to actual power consumption and a measure of the aerodynamic efficiency of a

helicopter can then be calculated using Eq. (4). The induced power is associated with the lift required to hover while

the profile power corresponds to the power required to overcome rotor drag. Ideal power is entirely induced in nature

but ignores losses due to non-uniform inflow, es, wake swirl and non-ideal wake contraction (Leishman 2006).

FM =Pideal

Pinduced + Pprofile=

C3/2T /√

2∑dCTλh + 1

2

∑σCdr3dr

(4)

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To improve the stability of the BEMT implementation, a relaxation scheme was applied to the iteration process

used to find the local Angle of Attack (AOA). Additionally, an initial value for the AOA was estimated by using a Clα

of 2π and equations based on the lift curve slope were used for the first iteration rather than those based on Cl. A

detailed description of the theory, assumptions and equations used in BEMT can be found in Leishman (2006).

4.2 Forward Flight

Blade motion becomes considerably more complex in forward flight with factors such as blade flapping, compressibility

effects and blade stall having a significant effect on results. Additionally, the flow can no longer be assumed to be

axisymmetric and therefore cannot be estimated using BEMT and requires discretization along the azimuthal direction.

As a result, Blade Element Theory coupled with some simplifying assumptions (including an estimation of the inflow)

need to be applied in order to obtain the performance parameters of a rotor in forward flight. Drees’ linear inflow

model, given in Eq. (5), was used to approximate the inflow in forward flight, where kx and ky are model coefficients.

The blade dynamics of a fully articulated rotor were used to approximate the dynamics of the rigid (hingeless) Blade

600X helicopter.

λi(r, ψ) = λiavg (1 + kxr cosψ + kyr sinψ) (5)

The induced inflow in forward flight can be calculated following momentum theory for forward flight developed by

Glauert (Johnson 1994):

λiavg =CT

2√µ2x + λ2

(6)

where the total inflow, λ is given by:

λ = µz + λiavg (7)

The advance ratios µx and µz quantify the incoming flow parallel and perpendicular to the rotor plane and are

defined as:

µx = V∞cosαTPP

ΩR(8)

µz = V∞sinαTPP

ΩR(9)

A detailed description of the theory, assumptions and equations used in the development of the Blade Element

Theory code used to produce the forward flight results presented in this manuscript can be found in Wiebe (2015)

5 Rotor Optimization

In the following sections, the effects of key parameters (UAV mass, rotor frequency, blade geometry, etc.) on UAV

performance are presented. All results in this section were obtained using BEMT.

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5.1 Helicopter Mass Selection

From Table 1, the baseline UAV mass is 3.84 kg. However, for the purposes of this paper, the UAV mass was fixed

to 5.0 kg, allowing for a 1.16 kg mass for instrumentation and a simulated payload representative of a high resolution

camera. At the end of the optimization process and during flight testing, the mass was varied to estimate the maximum

payload. Since the Blade 600X UAV is limited by the motor characteristics (more specifically the motor’s maximum

power) rather than blade stall, it is possible to design a rotor which increases range, endurance and FM while also

increasing maximum payload. This is attainable by reducing the power requirement of the rotor configuration through

RPM control and blade design. Since a 1.16 kg payload is typically sufficient, the blade design was optimized for

increased endurance and range with this payload in mind.

5.2 Rotor Rotational Frequency Selection

Lowering the rotational frequency of the main rotor considerably decreases the power required to hover and increases

FM. Figure 4a illustrates this relationship for the baseline rotor configuration (NACA 0012 airfoil, zero twist and

taper). One should note the baseline rotational frequency of main rotor of the UAV is recommended to be 2,000 RPM,

however, this rotational frequency is only necessary for aerobatic maneuvers and a lower rotor frequency is suitable for

regular operation.

An additional benefit of decreasing the rotor frequency is that it brings the blade AOA closer to the optimal lift-to-

drag ratio when flown with a UAV mass of 5.0 kg. This relationship is demonstrated in Figure 4b for the baseline rotor

configuration which theoretically has a maximum L/D ratio that occurs at a rotational frequency below 1,000 RPM

at an AOA of 8.3. Although minimizing the RPM to the optimal lift-to-drag ratio is desirable, a rotor frequency of

1,500 RPM was selected due to instability observed during low RPM flight testing. Loss of stability was characterized

by a slight wobble of the UAV in the pitch and roll axis for both hover and forward flight. Since flight testing was

performed indoors to avoid the time commitment of obtaining a Special Flight Operations Certificate (SFOC), further

lowering the RPM risked crashing the UAV due to the confined, low altitude nature of the flights. Reducing the rotor

frequency from 2,000 RPM to 1,500 RPM increased FM by 55% and reduced the power required to hover by 36%.

The instabilities observed at 1,500 RPM were unexpected given that RC helicopters of similar scale have been known

to attain head speeds as low as 1000 RPM. Reasons for this behavior may include the increased mass of the helicopter

due to the simulated payload, sub-optimal tuning of the flybarless control system, or overly stiff head dampers. If

instability had not occurred, RPM would have been reduced within a margin of safety of stall conditions.

5.3 Rotor Radius Selection

A large rotor radius, coupled with low RPM is generally desirable to lower the power requirement of the vehicle. This

can be observed in Figure 4c which illustrates the effects of rotor radius on FM and required power considering the

baseline rotor configuration. Figure 4d also demonstrates that increasing the rotor radius would not be beneficial at the

given payload of 1.16 kg unless the rotor frequency is decreased below 1,500 RPM. Since increasing the rotor diameter

would require significant alteration to the frame of the UAV and instability was observed at rotor frequencies below

1,500 RPM, the original 671 mm blade length was maintained. A smaller blade radius could theoretically increase the

blade efficiency or FM by bringing the blade AOA closer to the optimal L/D ratio, however, it would also significantly

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increase the power consumption of the UAV.

5.4 Airfoil Chord Length Selection

If blade taper is not considered, a significant performance improvement can be obtained by reducing the chord length due

to the associated decrease in solidity and the shift in the blade AOA which brings it closer to the angle corresponding to

the maximum L/D ratio. However, if a taper ratio is introduced, a much less significant reduction in chord is necessary

to minimize the required power to hover. This relationship is shown in Figure 4e (NACA 0012 airfoil with no twist

operating at 1,500 RPM) where it can be observed that the optimal chord length is significantly affected by the taper

ratio. Ideally a combination of taper ratio and chord reduction would be utilized, however, reducing the chord was not

feasible considering the materials and blade balancing methods utilized for the production of the rotor (i.e. further

reduction in the chord would leave insufficient thickness at the leading edge of the rotor to add balancing ballast and

result in insufficient blade stiffness). As such, the blade root chord length was kept at 55 mm. A decrease in solidity

and a shift in the AOA was instead achieved with either taper, a reduction in the blade number (i.e. single-blade with

counterweight design), or a combination of both.

5.5 Airfoil Selection

A variety of airfoils (shown in Figure 2) were considered in order to understand the effect of thickness, camber and

shape on the lift and drag characteristics of the airfoil. As can be observed from Figures 3a and 3b, increasing the

camber shifted the lift curve slope upwards while also increasing drag. Conversely, reducing the airfoil thickness had

negligible effect on lift but significantly reduced drag (note that the camber and thickness of NACA 4-series airfoils are

specified by the first and last two digits of the airfoil name, respectively). Airfoils thinner than the NACA 4409 were

not considered to ensure sufficient blade thickness for blade balancing and structural stiffness. From the CFD studies

described earlier, the NACA 4409 and NACA 6409 airfoil were found to have the best lift-to-drag ratios, occurring at

5.7 and 4.7 respectively. Ultimately the NACA 4409 airfoil was selected for its sightly better performance at the

operating AOA of the final blade design, however, both airfoils performed similarly. Implementing the NACA 4409

airfoil into the design resulted in a 5.1% and 4.9% improvement in FM and power consumption relative to the NACA

0012.

The full-scale helicopter-specific airfoil (NASA RC(4)-10) performed poorly as expected since its transonic profile

is not designed for low speed and low RPM flight. This further emphasizes that the low Reynolds number environment

calls for special solutions for small rotorcraft UAVs.

5.6 Taper Selection

While a hyperbolic taper theoretically results in a minimal profile power by maximizing the lift-to-drag ratio (Leishman

2006), blade design was limited to a linear taper to facilitate the manufacturing and blade balancing process. For

simplicity, only a constant taper ratio along the blade was considered. Results for the NACA 4409 airfoil (no twist)

operating at 1,500 RPM for taper ratios between one (constant chord) and four are presented in Figure 4f. It should

be noted that the planform geometry was determined such that the thrust-weighted solidity of the rotor remained

constant. As expected, introducing taper reduced the required power and increased FM as the AOA approaches an

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optimal lift-to-drag ratio. From the presented results, it can be observed that the optimal taper ratio for hover is likely

greater than 4:1. The taper ratio for forward flight is generally restricted to avoid loss of lift on the retreating blade.

In this application, the tip velocity is well below the speed of sound and the forward flight speed is small (∼10 m/s).

Therefore the optimal taper ratio for forward flight is also higher than 4:1. Due to manufacturing constraints and the

limitations of materials such as wood, a taper ratio of 2:1 was chosen to avoid an overly thin tip which could fracture

during the machining process or undergo aeroelastic deformation during flight. At constant thrust-weighted solidity a

taper ratio of 2:1 improves FM and power consumption by 4.9% and 4.7%, respectively. If the weighted solidity is not

kept constant, FM is increased by 21% and power consumption is reduced by 17% (at a taper ratio of 2:1).

5.7 Twist Selection

Minimizing the induced power requires uniform inflow over the rotor disk, which is obtained with a hyperbolic twist

distribution along the blade known as ‘ideal twist’. To avoid divergence of the pitch angle at the root, linear twist is

typically used near the root while ideal twist can be used at the tip (Leishman 2006). A combination of linear and ideal

twist was considered during the optimization process. Both the root pitch angle and the location where linear twist

transitioned to ideal twist were varied. Results for hover and forward flight (presented in Figure 10) were as expected,

with hovering flight having an optimal root pitch around 30 and forward flight (10 m/s forward speed and 5 rotor

tilt) having an optimal root pitch of 10. A lower root pitch angle is desirable in forward flight to avoid loss of lift and

propulsive efficiency on the advancing blade (Leishman 2006). The optimal transition point from linear to ideal twist

for both hover and forward flight was found to be 50% of the blade length from the root. Section 10 represents results

for a rotor with a NACA 4409 airfoil with no taper and with a transition from linear to ideal twist at 50% of the blade

length operating at 1,500 RPM.

Since the majority of the flight time of rotary UAVs is usually dedicated to hovering flight, a root pitch angle of 15

was chosen for the initial blade design, resulting in a 7.6% increase in the FM and 7.1% power reduction for hovering

flight without noticeably affecting forward flight. If an RUAS operator has a mission profile consisting of mostly forward

flight, a smaller root pitch angle should be used.

5.8 Blade Tip Design Selection

Blade tip design is critical on large helicopters due to the tip speeds approaching or even exceeding supersonic speed

on the advancing blades in forward flight. However, for scaled helicopters such as the Blade 600X, which has a nominal

rotational frequency of 2,000 RPM and forward flight speed not exceeding 30 m/s, the maximum resultant tip speed

Mach number will be around Mach 0.5 (i.e. well below the critical Mach number of 0.8). Thus, the blade tip design only

has a minor impact on the aerodynamic performance of the UAV. Nevertheless, blade tip design for single main-rotor

UAVs can affect the acoustic footprint of the rotor and therefore should not be completely neglected. However, since

the BEMT code developed could not accurately predict the aerodynamics or aeroacoustics of the blade tip, a swept

back, rounded tip commonly seen in single-rotor UAVs was chosen for the blade design.

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5.9 Blade Number Selection

From BEMT and flight testing, the AOA of the stock blades (NACA 0012 airfoil, zero twist, zero taper) was observed

to be around 2-3 at 75% of the radius, depending on the RPM. This is far below the 8.3 corresponding to the optimal

lift-to-drag ratio for the NACA 0012. This was also found to be the case for the optimized blades due to manufacturing

limitations which prevented further reducing rotor solidity. A single-bladed design was therefore considered to reach

the desired AOA corresponding to the maximum L/D ratio.

Simulation results from BEMT showed that a single-bladed configuration (using the stock blades) with a UAV mass

of 5.0 kg at 1,500 RPM increased FM by 17% and reduced the power requirement by 14%. Using a single-bladed design

with the a blade that incorporates the twist, taper, and airfoil profile described in the previous sections yields even

better results. A summary of these simulation results is presented in Table 2. While the results tabulated below are

for hover, the same trend was seen for forward flight.

Since the manufactured counterweight was placed near the center of rotation it was required to be significantly

heavier than the opposing blade. To maintain a consistent total UAV weight of 5 kg the payload was reduced by 365 g

in the single-bladed design. If the payload is not reduced, operating at 5.365 kg with the single-bladed design remains

beneficial for the stock configuration but marginally increases power consumption for the optimized design, as shown

in Table 2. Ideally the center of mass of the counterweight would be further from the center of rotation such that a

smaller mass could be used.

Another advantage of a single-bladed design is that the baseline blade could be still used by UAV operators while

delivering a significant performance improvement. Thus, only the counterweight required to match the centripetal

force of the rotating blade would need to be purchased or manufactured. Although using a single blade is not feasible

at low RPM as a result of the unsymmetrical lift produced, due to the high RPM required for flight of this scale

of UAV, the blade frequency is such that stable flight can be achieved. Even at 1,500 RPM, minimal change in

stability and controllability was observed during flight testing when switching from a two-bladed to a single-bladed

rotor configuration. Changes to the vibration and noise amplitude of the UAV were not observed during flight testing

of the single-bladed rotor. This observation, however, was unexpected and is likely a result of the high gear noise and

inexpensive off-the-shelf components used to measure vibration and noise.

5.10 Optimized Blade Design

The optimized blade design, illustrated in Figure 6, features a NACA 4409 airfoil, 2:1 taper ratio, 15 root pitch angle

and a transition to ideal twist at 50% of the blade length. Cost-effectiveness and manufacturability are of utmost

importance for such low cost UAV rotorcraft and, as will be shown later, the blade shown in Figure 6 can be relatively

easily machined from wood or by other more sophisticated techniques.

Although the optimization parameters are presented individually in the sections above, all possible combinations

were considered simultaneously during the optimization routine.

5.11 Summary of Optimization Results

By compiling all the aforementioned results, the performance of each rotor configuration (Figure 7a) and the impact

of each parameter were evaluated (Figure 7b). In Figure 7a, it can be observed that the original rotor configuration

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at 2,000 RPM in a two-bladed configuration (shown as the leftmost bar in the figure) has a significantly higher power

consumption relative to all the tested rotor configurations. Note that the baseline blades refers to the stock blades

suggested by the manufacturer of the Blade 600X UAV and feature zero twist, no taper and use the NACA 0012 airfoil.

Figure 7b reflects the impact of each optimization parameter going from the leftmost (baseline blades at 2,000 RPM

with two blades) to the rightmost (optimized blade at 1,500 RPM with one blade) rotor configuration. As expected

from Figure 7a, the RPM has the largest impact on the power consumption of the UAV. The number of blades and

taper also have a large impact on the UAV performance, while blade twist and airfoil geometry only have a minor

impact on the power consumed by the rotor. Figure of Merit showed a similar trend, with the RPM (58%) and number

of blades (18%) having the largest impact on rotor efficiency, followed by taper (12.5%), twist (6%) and airfoil profile

(5%).

6 Blade Manufacturing

Four different manufacturing methods were considered during the blade fabrication process. Due to the differing

limitations of each manufacturing method, they did not all feature the same design. In particular, the fibreglass blade

featured no twist nor taper. Each method was used to prototype 1-2 sets of blades, which were then tested in a whirl

tower facility. Flight testing was performed on each of the designs with exception of the aluminum edged blade due

to manufacturing defects identified during whirl tower testing. The main features of each manufactured blade were as

follows:

1. CNC - Wooden blade dipped in epoxy with steel leading edge ballast (124.3 g)∗,†

2. CNC - Geometrically optimized non-ballasted wooden blade dipped in epoxy (58.5 g)

3. CNC - Wooden blade with aluminum leading edge (158.0 g)

4. CNC - Steel counterweight (single-blade design; 501.4 g)

5. 3D-printed skeleton wrapped in fiberglass skin (233.5 g)

∗For reference the weight of a stock blades is 136.4g

†Stated blade weights are for a single blade

Computer Numerically Controlled (CNC) routing and 3D printing processes were used to prototype the blades due

to their ability to produce blade geometry of arbitrary complexity. Limitations in blade geometry were therefore mainly

driven by material properties and the accuracy of the machining process. The finished blades from each manufacturing

method are shown in Figures 8a to 8d and 9a. The wooden blades without the aluminum leading edge and the 3D

printed blades required chord-wise balancing to avoid flutter while each of the designs with wood as the load bearing

material needed to be impregnated with epoxy to increase blade stiffness. Yellow birch was used for each of the wooden

blades due to its strength characteristics and availability. The wooden blades in Fig. 8a feature no twist nor taper

and were used to test the feasibility of manufacturing wooden blades. The wooden geometrically optimized blade

depicted in Fig. 8b, on the other hand, proved to be too thin at the leading edge to complete chord-wise balancing

with the manufacturing tolerances of the available equipment without risking the structural integrity of the blade. The

tip-design of the aluminum-edged blade (Fig. 8c) feature a higher taper than the design presented in Fig. 6 due to

smaller amount of taper seen in the remaining blade span. This allows for higher blade strength without a significant

loss in aerodynamic performance.

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A common requirement for each of these designs was for their fabrication cost to remain within a budget compa-

rable to the cost of the baseline UAV itself (i.e. a maximum of 1,000 CAD). This requirement prevented the use of

manufacturing methods involving custom molds or autoclave curing. It should also be noted that the manufacturing

methods presented above are primarily suitable for prototyping and would be uneconomical for large-scale production.

Further details regarding the manufacturing process used for each method can be found in Kotwicz Herniczek et al.

(2016).

Although each blade was manufactured and tested in the whirl-tower, only flight test results for the one-bladed

design (with the stock blade as the lifting surface) are included in this manuscript. This was due to a number of

setbacks during the manufacturing process: The geometrically optimized wooden epoxy-dipped blade survived whirl

tower testing, however, significant blade deformations were observed during takeoff and no flight data was captured.

The wooden aluminum-edged blade showed promising theoretical stiffness and structural strength, however, the blades

were destroyed during whirl tower testing due to incorrect epoxy application along the wood-aluminum interface.

Lastly, the fiberglass wrapped blades were created as a proof-of-concept with the hope of refining the wrapping process

to allow for more precise and complex geometry. The first iteration of these blades were hand-wrapped and given their

similar blade geometry to the stock blades, showed no improvement relative to the stock configuration. Similarly, the

steel-ballasted wooden blades featuring no twist nor taper were flight tested successfully but showed no improvement

in power consumption, as expected.

7 Whirl Tower Testing

Prior to flight testing, each blade design was tested in Carleton University’s Whirl Tower facility at maximum RPM

and maximum pitch angle. This was done to ensure the blades could sustain the highest possible tensile and bending

loads experienced during flight.

The newly designed blades and the counterweight were first subjected to an initial rotational velocity of 500 RPM

(0 collective pitch) for two minutes and then inspected for any loosening of the lead-lag axis blade attachment bolt,

structural distortion, surface cracking or other signs of fatigue. Signs of vibration caused by rotor imbalance were

carefully monitored via remote high-speed video cameras within the chamber. The blades were then subjected to

increasing RPM and pitch such that the final test (held for two minutes) consisted of rotating the blades at 2,000 RPM

at a collective pitch of 10.

8 Flight Testing

Flight testing was conducted to validate the improvements predicted by BEMT as well as to evaluate flight performance

of the manufactured blades. To eliminate variable flight conditions and to facilitate compliance with Transport Canada

regulations, the tests were performed indoors.

8.1 Apparatus

The test platform, as mentioned earlier, was the Blade 600X UAV. While the majority of the necessary components are

included with the purchase of a build kit, it is not possible to measure and record data without additional components;

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namely an electronic speed controller and data logger. The Turnigy ESC-100A Super Brain was used in conjunction

with the Turnigy USB linker to record battery power consumption and shaft RPM. A dedicated Adafruit ADXL335

triple-axis accelerometer was rigidly mounted to the frame of the UAV and connected to an Arduino Uno Microcontroller

to record vibration data, while a telemetry radio enabled real time data streaming and collection. A static pitot tube

was also mounted underneath the rotor along the tail boom to measure inflow through the disk.

8.2 Methodology

Several types of tests were performed. The first test was composed of varying the payload of the UAV and recording

the power drawn from the battery while in hover. During the second test, the RPM was varied via the Electronic Speed

Controller (ESC) while keeping the total UAV mass constant at 5.0 kg. Lastly, FM was measured using a combination

of ground and flight tests. Each test was performed in order to validate the values obtained from BEMT. Free-flight

tests were performed inside an indoor gymnasium 60 m wide by 70 m long by 11 m tall. Any interference effects were

assumed to be negligible given that the UAV was at least 4 m from any boundary surface. It should be noted that

even lower power consumption could be obtained for the flight test data at 1,500 RPM if the gearing had been altered

such that the motor could have remained at full throttle (thus eliminating the reduction in motor efficiency seen by

the motor at low–mid throttle).

8.3 Payload Test Results

During payload testing, the payload was varied from 0 kg to 3.8 kg. Only a fraction of the maximum payload was

added due to the reduced controllability of the UAV at larger payloads and the confined, indoor flight space. Figure 9b

illustrates the relationship between power and total UAV mass. Since the BEMT prediction (shown by the solid line in

Figure 9b) represents the shaft power, while the experimental flight data represents the total power consumption of the

UAV, an offset between the two power values is expected. Although the BEMT prediction is significantly lower, the

offset is consistent and an experimentally determined factor of 2.0 (which accounts for the motor efficiency and the tail

rotor power consumption) can be used to match the two results (shown by the dotted line in Figure 9b). Additional

reasons for the large offset observed are an underestimation of the coefficient of drag by the CFD simulation and the

simplifying assumptions introduced by BEMT for the calculation of the power required to hover. It should be noted,

however, that each of these possible sources of error are not expected to be significant given the successful validation of

the CFD methodology with experimental drag data and the reasonable performance of BEMT that been demonstrated

for hovering flight (Leishman 2006). Minor error is also introduced due to the conversion factor from the avionics power

draw, which does not vary with payload. The consistency of the offset in Figure 9b, however, suggests that the trend

predicted by BEMT is reasonable. The baseline UAV configuration (using two stock blades) and a rotational frequency

of 1,800 RPM was used during payload testing.

8.4 Figure of Merit Results

Figure of Merit (FM) of the baseline and modified UAV rotor was measured via several methods: measuring the shaft

torque through the tail thrust, measuring the inflow using a pitot tube and measuring the power drawn from the

batteries during hover.

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8.4.1 Shaft-torque measurement:

Figure of merit, defined in Eq. (4), is the ratio between the ideal power and the actual power required to hover. The

ideal power in hover can be determined using momentum theory, while the actual power required to hover is equivalent

to the product of shaft torque (Q) and the rotational velocity of the shaft (Ω) as described in Eq. (10).

P = Ω ∗Q (10)

Thus, measurement of the actual power can be obtained by recording the rotational velocity of the main shaft as

well as measuring the torque along that axis. The rotational velocity can be obtained from the rotational frequency

measurement recorded by the ESC, while the torque measurement can be determined by measuring the tail thrust and

multiplying by the tail boom length. To measure the tail thrust, a ground based test stand was built to measure the

force generated by the tail rotor at the pitch and RPM setting required for the UAV to hover during free flight. The

apparatus consisted of a one-degree-of-freedom rotational platform with a force sensor connected to the tail boom. The

main rotor was tested with the main rotor blades on and the tail blades off.

8.4.2 Pitot tube measurement:

The second method used to measure the FM involved placing a pitot tube 10 cm underneath the rotor and recording

the induced velocity at different radial positions along the rotor during hover. The ideal power (required to push air

through the rotor disk if non-ideal effects such as viscous effects, 3D effects, swirl, etc. are neglected) can then be

calculated using Eq. (11).

Pideal = T ∗ vi (11)

The measured inflow velocity showed the expected trend, where the inflow is lowest near the root and increases

towards the blade tip. However, the data recorded from the pitot tube was too poor in resolution and precision to

compare to theoretical results. This was likely a result of significant vibration being transfered through the pitot tube

mount.

8.4.3 Battery power draw measurement:

Lastly, the shaft power of the UAV was estimated from the total power draw of the batteries (recorded by the ESC)

during hover. To obtain the shaft power, the measured power was divided by a factor of 2.0 (experimentally determined

during payload testing) in order to account for the motor efficiency as well as the tail rotor and avionics power

consumption.

Figure 10a shows results for the Figure of Merit calculated from the battery power consumption, the torque mea-

surement and using BEMT, with the three methods showing good agreement. Each measurement was performed under

the same conditions using two stock blades rotating at 1,800 RPM with no payload attached to the UAV.

Results presented in Figure 10b, are similar to Figure 7a introduced earlier in the paper, but include the experimental

results for the power consumption for each rotor configuration. It should be noted that the same experimentally

determined factor of 2.0 was used to match the experimental power to the value predicted by BEMT. Although the

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last two columns in Figure 10b do not have experimental results due to the manufacturing difficulties outlined in

the manuscript, the values for power consumption predicted by BEMT are expected to be reasonable due the close

agreement seen in Figures 9b, 10a and 10b.

9 Conclusions

Rotor blade optimization at Reynolds numbers between 100,000 and 500,000 (indicative of this scale of UAV rotorcraft)

was performed using Blade Element Momentum theory. BEMT was used to test various airfoil profiles and rotor blade

shapes using data provided from CFD. Using BEMT, a blade design utilizing a cambered profile, taper and twist was

developed. Selected blade designs were manufactured and flight tested on the Blade 600X UAV to validate theoretical

results. The following conclusion were made:

1. Rotor efficiency (and therefore range and endurance) can be significantly increased by reducing rotor RPM.

Reducing the RPM from 2,000 to 1,500 on the Blade 600X UAV (equipped with two stock blades) resulted in a

55% increase in the FM and 36% reduction in the power consumption.

2. Following RPM control, reducing solidity had the second largest effect on blade performance and can be achieved

with a taper ratio, smaller chord or a lower blade number. Increasing rotor radius is also generally desirable but

only if the appropriate rotor frequency can be achieved. Blade twist and airfoil selection had the lowest impact

on the performance of the UAV.

3. Using a counterweight to reduce the number of blades is an effective, simple and low-cost method to increase

rotor efficiency. On the Blade 600X UAV, a one-bladed design improved FM and power consumption by 17% and

14% respectively (at 1500 RPM using the stock blades).

4. BEMT is a fast and reasonably accurate tool to investigate blade geometry. For the Blade 600X, a NACA 4409

airfoil, 2:1 taper ratio, 15 root pitch angle and a transition to ideal twist at 50% of the blade length showed optimal

theoretical performance while maintaining manufacturability. This blade design would theoretically improve FM

by 28% and power consumption by 22% (at 1500 RPM for a two-bladed configuration).

5. Published 2D airfoil data at low and transitional Reynolds numbers (100,000 to 500,000) is limited, and CFD or

wind tunnel testing may be required to obtain accurate airfoil data (necessary for BEMT).

6. Rotor blades can be manufactured at low cost with little machinery. However, the process is time consuming,

which restricts the methods to small-scale production. The manufacturing materials and method may also limit

the range of allowable blade geometry during the optimization process.

7. Lightweight, complex and thin blade geometry leads to improved theoretical aerodynamic performance, however,

great care must be taken to ensure sufficient structural stiffness is maintained. Manufacturing tolerances must

also be considered during selection of the minimum blade thickness to ensure chord-wise balancing is feasible.

8. The results presented in this paper suggest that many UAV operators could extend the endurance and range of

their helicopters by reducing rotor RPM and that there is a market for aerodynamically optimized small-scale

UAV rotor blades. Single-bladed designs with a counterweight may also be a viable option for UAV operators

looking to improve the range and endurance characteristics of their helicopters.

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10 Acknowledgments

This work has been a part of Carleton University’s Capstone Rotorcraft initiative, supported by Bell Helicopter Textron

Canada and ING Robotic Aviation, to investigate sub-scale helicopter performance optimization.

References

Allen, C. & Rendall, T. (2001), ‘Cfd-based optimization of hovering rotors using radial basis functions for shape

parameterization and mesh deformation’, Optimization and Engineering 14(1), 97–118.

Anyoji, M., Nonomura, T., Aono, H., Oyama, A., Fujii, K., Nagai, H. & Asai, K. (2014), ‘Computational and ex-

perimental analysis of a high-performance airfoil under low-reynolds-number flow condition’, Journal of Aircraft

51(6), 1864–1872.

Bohorquez, F., Pines, D. & Samuel, P. (2010), ‘Small rotor design optimization using blade element momentum theory

and hover tests’, Journal of Aircraft 47(1), 268–283.

Hassan, A. & Charles, B. (1997), ‘Airfoil design for helicopter rotor blades - a three-dimensional approach’, SOARTECH

34(2), 197–205.

Johnson, W. (1994), Helicopter Theory, Dover Publications, New York, NY.

Kotwicz Herniczek, M., Jee, D., Sanders, B. & Feszty, D. (2016), Rotor blade optimization and flight testing of a small

uav rotorcraft, in ‘Proc. AHS 72nd Annual Forum’.

Lee, J., Chae, S., Oh, S. & Yee, K. (2010), ‘Parametric study for hovering performance of a coaxial rotor unmanned

aerial vehicle’, Journal of Aircraft 47(5), 1517–1530.

Lee, S. & Kwon, O. (2006), ‘Aerodynamic shape optimization of hovering rotor blades in transonic flow using unstruc-

tured meshes’, AIAA 44(8).

Leishman, G. (2006), Principles of Helicopters Aerodynamics, Cambridge University, New York, New York.

Leishman, G. (2009), ‘Aerodynamic performance considerations in the design of a coaxial proprotor’, AHS 54(1).

Leishman, G. & Ananthan, S. (2008), ‘An optimum coaxial rotor system for axial flight’, AHS 53(4), 366–381.

Lyon, C., Broeren, A., Giguere, P., Gopalarathnam, A. & Selig, M. (1998), Summary of Low-Speed Airfoil Data -

Volume 3, SoarTech, Virginia Beach, Virginia.

Pfenninger, W. & Vemuru, C. (1988), ‘Design of low reynolds number airfoils: Part 1’, Journal of Aircraft 27(3), 204–

210.

Prior, S. & Bell, J. (2011), ‘Empirical measurements of small unmanned aerial vehicle co-axial rotor systems’, Journal

of Science and Innovation 1(1), 1–18.

Selig, M. & Guglielmo, J. (1997), ‘High-lift low reynolds number airfoil design’, AIAA 34(1), 72–79.

16

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Draft

Selig, M., Guglielmo, J., Broeren, A. & Giguere, P. (1995), Summary of Low-Speed Airfoil Data - Volume 1, SoarTech,

Virginia Beach, Virginia.

Selig, M., Lyon, C., Giguere, P., Ninham, C. & Guglielmo, J. (1996), Summary of Low-Speed Airfoil Data - Volume 2,

SoarTech, Virginia Beach, Virginia.

Selig, M. & McGranahan, B. (2004), Wind tunnel aerodynamic tests six airfoils for use on small wind turbines, Technical

Report NREL/SR-500-34515, National Renewable Energy Laboratory, Golden, Colorado.

Tatossian, C. & Nadarajah, S. (2011), ‘Aerodynamic shape optimization of hovering rotor blades using a non-linear

frequency domain approach’, Computers & Fluids 51(1), 1–15.

Wiebe, J. (2015), Development of a simulation and optimization framework for improved aerodynamic performance of

r/c helicopter rotor blades, Master’s thesis, Carleton University.

Williamson, G., McGranahan, B., Broughton, B., Deters, R., Brandt, J. & Selig, M. (2012), Summary of Low-Speed

Airfoil Data - Volume 5, Champaign, Illinois.

Figure 1: Standard Blade 600X UAV configuration.

Table 1: Standard Blade 600X Specifications.

Specification English MetricEmpty mass (no batteries) 6.26 lb 2.84 kgMinimum takeoff mass (no payload) 8.47 lb 3.84 kgTotal takeoff mass (with payload)∗ 11.02 lb 5.00 kgMain rotor radius† 26.42 in 671 mmMain rotor chord 2.17 in 55 mmMain rotor rotational frequency 2,000 RPMMain rotor tip Reynolds number 500,000Main rotor airfoil NACA 0012

∗The total takeoff mass was defined as 5.0 kg for the purposes of this paper, leaving 1.16 kg for various instrumentation and payload for theflight tests.†The rotor radius is taken from the center of rotation to the blade tip.

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(a) (b)

Figure 3: Lift and drag coefficient data of selected NACA airfoils (Re = 400,000; M = 0.06).

Figure 5: Variation of power consumption with root pitchangle.

Table 2: Single-bladed (with a counterweight)and double-bladed configuration BEMT resultswith a takeoff mass of 5.0 kg at 1,500 RPM.

Blade Type Blades FM Power [W]

Stock NACA 0012 2 0.48 385

Stock NACA 0012 1 0.56 330

Stock NACA 0012* 1 0.57 360

Optimized Design 2 0.62 300

Optimized Design 1 0.68 275

Optimized Design* 1 0.68 304

* Takeoff mass of 5.365 kg (payload of 1.16 kg)

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(c) (d)

(e) (f)

Figure 4: Impact of rotor parameters on performance: (a) power requirement variation with RPM; (b) variation of bladeAOA with RPM; (c) variation of FM with rotor radius at a constant payload; (d) variation of power with rotor radius ata constant payload; (e) variation of power with rotor chord at a different taper ratios; (f) variation of power with taperand RPM in hover.

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Figure 6: Manufacturing drawing of the optimized blade design.

(a) (b)

Figure 7: Results from optimization: (a) power variation with rotor configuration; (b) relative influence of optimizationparameters on power consumption.

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(a) (b)

(c) (d)

Figure 8: Two bladed designs: (a) steel-ballasted wooden blade; (b) non-ballasted, ”optimized” wooden blade; (c) hybridwooden and aluminium blade (6061-T6); (d) 3D-printed, fibreglass-wrapped blade.

(a) (b)

Figure 9: (a) Single-bladed steel counterweight design mounted on the Blade 600X with a close-up view of the counter-weight; (b) comparison of theoretical and experimental power consumption as a function of payload.

(a) (b)

Figure 10: Validation of results from optimization: (a) comparison of FM estimated from battery power draw, tail torquemeasurement and BEMT; (b) theoretical and experimental power variation with rotor configuration.

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