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Analysis and Design of a Small-Scale Wingtip-Mounted
Pusher Propeller
Tom C. A. Stokkermans∗, Sebastiaan Nootebos†and Leo L. M. Veldhuis‡
Delft University of Technology, 2629 HS Delft, The Netherlands
The wingtip-mounted pusher propeller, which experiences a performance benefit from the
interaction with the wingtip flowfield, is an interesting concept for distributed propulsion. This
paper examines a propeller design framework and provides verification with RANS CFD sim-
ulations by analysing the wing of a 9-passenger commuter airplane with a wingtip-mounted
propeller in pusher configuration. In the taken approach, a wingtip flowfield is extracted from
a CFD simulation, circumferentially averaged and provided to a lower order propeller analysis
and optimisation routine. Possible propulsive efficiency gains for the propeller due to installa-
tion are significant, up to 16
%
increase at low thrust levels, decreasing to approximately 7.5
%
at the highest thrust level, for a range of thrust from 5
%
up to 100
%
of the wing drag. These
gains are found to be independent of propeller radius for thrust levels larger than 30
%
of the
wing drag. Effectively, the propeller geometry is optimized for the required thrust and to a
lesser degree for the non-uniformity in the flowfield. Propeller blade optimization and instal-
lation result in higher profile efficiency in the blade root sections and a more inboard thrust
distribution.
Nomenclature
b=Wing span, m
CD=Drag coefficient
CL=Lift coefficient
Cp=(p−p∞)/q∞pressure coefficient
CQ=Q/ρ∞n2D5
ptorque coefficient
CT=T/ρ∞n2D4
pthrust coefficient
c=Chord, m
Dp=Propeller diameter, m
D=Wing drag, N
hi=Average cell size of grid i, m
J=V∞/(nDp)advance ratio
L=Wing lift, N
n=Propeller rotational speed, s−1
P=Shaft power, W
p=Static pressure, Pa
Q=Torque, Nm
Q0=Torque distribution, Nm ·m−1
q=Dynamic pressure, Pa
Rp=Propeller radius, m
Rp,ref=Reference XPROP propeller radius, m
r=
Radial coordinate in propeller reference frame, m
T=Thrust, N
T0=Thrust distribution, N ·m−1
U∗
s=
Standard deviation of a fit based on theoretic order
of convergence
Uφ=Estimated discretization uncertainty
V=Velocity, m ·s−1
x=Axial coordinate, m
y=Vertical coordinate, m
y+=Dimensionless wall distance
z=Lateral coordinate, m
α=Angle of attack, deg
β=Blade pitch angle, deg
ηp=TV∞/Ppropeller propulsive efficiency
ρ=Density, kg ·m−3
ϕ=Propeller blade phase angle, deg
φi=Numerical solution obtained using grid i
ω=Vorticity, s−1
Subscripts
0=Extrapolated
0.7Rp=Radial coordinate, in which r/Rpis equal to 0.7
a=Axial
c=Chord based
iso =In isolated condition
h=Hub
k=Kink
p=Propeller
r=Root
t=Tangential, tip
∞=Freestream
∗
Ph.D. Candidate, Flight Performance and Propulsion Section, Faculty of Aerospace Engineering, AIAA Member, t.c.a.stokkermans@tudelft.nl.
†M.Sc. Graduate, Flight Performance and Propulsion Section, Faculty of Aerospace Engineering
‡Full Professor, Head of Flight Performance and Propulsion Section, Faculty of Aerospace Engineering, AIAA Member.
1
I. Introduction
Today’s research on propellers is driven by their potential for reduced fuel consumption compared to turbofan
propulsion. Not only the high propulsive efficiency of the propeller itself, but also its location on the airframe can
enhance the overall efficiency of the aircraft. Wingtip-mounted propellers have been envisaged for their favorable
interaction effects. For the tractor propeller variant, the interaction of the wing with the slipstream results in a reduction
of the wing induced drag if the rotation direction of the propeller is opposite to that of the wingtip vortex [
1
–
3
]. The
pusher propeller variant experiences a reduction in shaft power due to the swirling vortex inflow from the wingtip in
case the propeller rotates against the direction of the wingtip vortex [
2
,
4
–
6
]. Moreover, the modification of the wingtip
vortex may reduce wing induced drag as well. Yet, the ingestion of the non-uniform inflow field may result in a noise
penalty for the pusher variant. Adverse aeroelastic effects due to the large weight of an engine at the tip of a wing and
the large yawing moment arm of the thrust vector in case of a one-engine-inoperative condition have prevented the
application of wingtip-mounted propellers up to now. However, the emergence of electric propulsion in aircraft allows
almost penalty-free downscaling of the propeller due to the scale independence of the electric motor [
7
]. This makes it
possible to distribute the propulsion for instance through a hybrid-electric architecture, and enables to scale down the
wingtip-mounted propeller like proposed in the SCEPTOR concept [8].
a) Modified Learfan 2100 b) Modified Tecnam P2012 Traveller
Fig. 1 Impression of airplane concepts with small-scale wingtip-mounted pusher propellers.
In this research the pusher variant is investigated in the context of distributed propulsion. An impression of such a
concept, combining i.e. fuselage boundary layer ingestion and wingtip-mounted pusher propellers through a hybrid
electric architecture, is shown in Fig. 1 a. A more conventional airplane layout with small-scale wingtip-mounted
pusher propellers is sketched in Fig. 1 b. The design freedom to scale propellers and to distribute propulsion, results in
a non-unique thrust requirement. For example, the propeller can be designed to balance just the induced drag of the
wing or balance the entire cruise drag of the aircraft. The resulting performance benefit of propeller installation at the
wingtip may depend on the thrust level. Hence the following research question: How does propeller scale influence the
propulsive efficiency benefit and the upstream aerodynamic loading on the wing? Up to now, only research on a full
scale wingtip-mounted pusher propeller has been performed, with a propeller not specifically designed for this task
[
4
]. The inflow to the propeller is non-uniform, especially when the propeller becomes smaller relative to the wingtip
flowfield. For a boundary layer ingestion propeller, Ref. [
9
] has shown that maximizing the propulsive efficiency gain
requires a different design to cope with the non-uniform inflow experienced on the aft fuselage. Analogue to that, the
wingtip-mounted pusher propeller may also benefit from design optimization, resulting in the second research question:
To what extent can the propulsive efficiency benefit be increased by designing the propeller for the non-uniform inflow
experienced at the wingtip?
This research, which is regarded as an extension of Ref. [
10
], gives insight in these questions by analysis of a
specific case through the following steps:
1)
CFD analyses of the wing are performed in order to quantify the wing performance and extract the wingtip
flowfield.
2)
A lower order propeller analysis and optimisation routine PROPR is established and validated for uniform inflow.
3) The wingtip flowfield is fed to PROPR for analysis and design optimization.
4)
The upstream effect of the propeller designs on the wing performance is analyzed through CFD analyses of the
wing with an actuator disk representation of the propeller.
5)
The accuracy of PROPR for the non-uniform wingtip flowfield is checked through a fully resolved propeller–wing
CFD simulation.
2
II. Computational Methods
A. RANS CFD Simulations
Four different types of RANS CFD simulations were performed in order to establish the wing performance and wingtip
flowfield, to estimate the upstream effect of the propeller on the wing and to verify the accuracy of PROPR:
•Isolated wing simulations
•Isolated propeller simulations
•Wing simulations with actuator disk propeller representation
•A propeller–wing simulation
The wing used for these simulations was derived from the Tecnam P2012 Traveller [
11
], a twin-prop 9-passenger
commuter airplane with a maximum take-offmass of 3600
kg
. Only the wing was taken into account, without the
original propeller and nacelles. A sketch of the wing is shown in Fig. 2 a. A minimum radius nacelle was added at
the tip of the wing, extending aft of the trailing edge to accommodate a propeller in pusher configuration. The nacelle
radius was kept equal to the propeller hub radius
Rh
. Hence, so far there is no provision to accommodate an electric
motor. The wing parameters are given in Table 1 and are partly based on Ref. [12].
a) Wing model with nacelle and spinner. b) XPROP propeller model.
y
x
z
ypxp
zp
xp
Rp
Rh
n
yp
0.21b
0.29b
cr = ck
ct
Fig. 2 Isometric view of the wing and TU Delft research propeller XPROP.
The propeller in the isolated propeller and propeller–wing simulations is the 6-bladed XPROP propeller, shown in
Fig. 2 b, a research propeller from Delft University of Technology typical for turboprop airplanes. An extensive grid
study and experimental validation for this propeller was performed in Ref. [
13
], and the same propeller grid density
was used in this research. The spinner was modified to convert it into a pusher propeller. The propeller was used in its
original size with a radius of
Rp,ref =
0
.
2032 m and hub radius of
Rh=
0
.
23
Rp,ref
. Simulations were also performed
with proportionally scaled versions of smaller and larger size.
Table 1 Wing model parameters.
Parameter Value
Span b13.55 m
Root and kink chord cr,ck2.06 m
Tip chord ct1.38 m
c/4 sweep, dihedral, twist 0◦
Root and kink airfoil NACA23015
Tip airfoil NACA23012
Cruise speed 80 m/s
Cruise altitude 3048 m
Cruise angle of attack 3◦
Cruise lift coefficient ≈0.35
3
Symmetry BC Pressure
outlet BC
Pressure
farfield BC
OD
ID
WD
PD SD
OD:
ID:
WD:
PD:
SD:
Outer Domain
Inner Domain
Wing Domain
Propeller Domain
Slipstream Domain
15cr
cr
y
x
5cr
20cr
Fig. 3 Computational domain and boundary conditions for the wing simulations.
The RANS equations for compressible flow were used with a 2
nd
order accurate scheme in ANSYS
r
Fluent 18.1
[
14
], a commercial, unstructured, finite volume, cell-centered solver. For the propeller–wing simulations time-dependent
solutions were found by a 2
nd
order backward Euler scheme with a time step equivalent to 2
deg
of propeller rotation.
Discretization of the advection term was done with an upwind scheme using the Barth–Jesperson boundedness principle
[
15
]. For the equation of state, an ideal gas was assumed and Sutherland’s law was used to predict the corresponding
dynamic viscosity. Standard atmospheric conditions at the cruise altitude were assumed. The turbulence model was
selected based on the findings of Kim and Rhee [
16
], who tested several turbulence models to simulate the wingtip
vortex of an isolated wing. The eddy viscosity model in their research that best agreed with experimental data in terms
of static pressure and axial velocity in the wingtip-vortex core was the Spalart–Allmaras (SA) one-equation model [
17
]
with modification proposed by Dacles-Mariani et al. [
18
] to prevent build-up of turbulence viscosity in vortex cores.
Therefore, this model was selected for the current research. Values for the inlet turbulence quantities were based on the
recommendations by Spalart and Rumsey [
19
], which resulted in an eddy viscosity ratio of 0
.
21044 for the SA model.
In order to fully resolve the boundary layer, the y+value on the no-slip walls of the model was less than one.
The computational domain and boundary conditions for the wing simulations are shown in Fig. 3. The outer
dimensions of the domain were chosen to be sufficiently large with respect to the wing chord, in order to minimize the
influence of the boundary conditions on the flow properties near the wing. At the domain inlet, a total-pressure jump
with respect to the undisturbed static pressure was set to reach the cruise speed. Furthermore, the undisturbed total
temperature was specified. At the domain outlet, the static pressure was prescribed to be on average equal to undisturbed
static pressure. On the outboard side of the domain, a Riemann-invariant pressure farfield condition was specified
with a Mach number, static pressure and static temperature complying with the inlet conditions. On the inboard side
side, a symmetry boundary condition was imposed. The wing, nacelle, propeller and spinner were modeled as no-slip
walls. The computational domain was divided in several domains for refinement of the grid. The propeller domain (PD)
was connected to the other domains through sliding mesh interfaces to allow grid rotation for simulation of propeller
motion. This domain could be replaced by a domain without propeller blades for the isolated wing simulations and
wing simulations with actuator disk representation of the propeller. The actuator disk model described in Ref. [
20
] was
used, requiring the propeller blade radial distribution of thrust and torque as input. Grids were constructed by means
of ANSYS
r
Meshing. For regions adjacent to no-slip walls, the unstructured grid was made up of a triangular wall
mesh, followed by layers of semi-structured prismatic elements of the inflation layer. For the remainder of the domain
tetrahedral elements were used. Grid density in the whole domain was controlled by wall refinement of all no-slip walls,
volume refinement of the domains, a 1
st
layer thickness of the inflation layers, and growth rates of the inflation layers
and the remainder of the grid. Grid study results for the isolated wing are shown in Section III.
The computational domain and boundary conditions for the isolated propeller simulations are described in Ref. [
13
].
Since the wake of a propeller with axisymmetric nacelle is cyclic with the number of the blades, only a single blade was
modeled in a wedge shaped domain with appropriate boundary conditions. The movement of the propeller and spinner
was simulated with a rotating reference frame.
4
B. Propeller Analysis and Optimisation Routine: PROPR
To perform quick propeller analyses and to aerodynamically design the propeller for optimized performance, a
PRopeller analysis and OPtimisation Routine named PROPR was set up based on XROTOR [
21
]. The software program
uses discrete line vortices forming a semi-rigid wake to iteratively determine the induced velocities and has been used
before by Refs. [
9
,
22
–
25
] for both uniform and non-uniform inflow. XFOIL [
26
] was selected for airfoil analyses. All
details of PROPR are described in Ref. [
10
]. Twenty radial sections were used to define the propeller geometry and
provide XROTOR with airfoil data. Each radial section was supplied with the correct non-uniform flowfield. Fully
turbulent flow for the airfoil data was assumed to allow comparison with the fully turbulent CFD simulations and to
increase stability of running XFOIL in an optimization framework. The non-linear part of the lift curve was modified
using an empirical model by Snel et al. [
27
] to correct two dimensional data for three dimensional rotational effects.
Comparison of PROPR results with validation data is provided in Section IV.
III. Isolated Wing Analysis
CFD analyses of the wing were performed at 3
deg
angle of attack to represent a cruise condition. A grid dependency
study was performed to estimate the discretization uncertainty and to select an appropriate grid density. All refinements
were varied systematically, except for the inflation layer, which was kept constant in line with Roache [
28
]. To estimate
discretization uncertainty, the least-squares version of the grid convergence index (GCI) proposed by Eça and Hoekstra
[
29
] was applied, with the alteration of using only the theoretical order of the solver of 2 to estimate the extrapolated
grid results. Table 2 gives an overview of the grid sizes and wing lift and drag found for each grid. Table 3 presents the
extrapolated lift and drag
φ0
, the standard deviation of the fit based on the theoretical order of convergence
U∗
s
and the
estimated discretization uncertainty
Uφ
for grid 2. The uncertainty of 0
.
49% and 3
.
10% for the lift and drag coefficient
respectively was deemed acceptable for this study.
Table 2 Overview of grids and resulting isolated wing performance.
Grid No. of cells hi/h1CL[-] CD[-]
4 8,561,478 1.82 0.3434 0.01638
3 16,315,794 1.47 0.3440 0.01622
2 32,756,863 1.16 0.3447 0.01600
1 51,424,220 1.00 0.3452 0.01585
Table 3 Grid extrapolation results and estimated discretization uncertainties for grid 2.
CLCD
φ00.3458 0.01568
U∗
s(%) 0.08 0.57
Uφ(%) 0.49 3.10
From the solution on grid 2 the flowfield that was fed to PROPR was extracted from the propeller plane, the plane
where the propeller will be installed. The flowfield at the wingtip is visualised in Fig. 4 by means of streamtraces and
the wingtip vortex is shown by an axial vorticity isosurface. On the isosurface and the propeller plane the velocity
magnitude is plotted and on the wing surface the pressure coefficient distribution is shown. In Fig. 5 this flowfield
at the propeller plane is given for the left wingtip as seen from behind, by means of contour plots of the axial and
tangential velocity components. These velocity components are most relevant for the propeller aerodynamic loading
and, together with the propeller rotational speed and propeller induced velocities, determine the local blade section
angle of attack and dynamic pressure. The tangential velocity component is defined positive in the rotation direction of
the propeller, which is running counterclockwise for the left propeller when seen from behind. In PROPR, the inflow
flowfield is radially varying but assumed to be circumferentially constant. Therefore a circumferential average of this
flowfield was taken, which will impact the resulting propeller response as follows: In the axial velocity contour plot
the reduced velocity in the wake of the wing is clearly visible and its effect on the propeller will be averaged. In the
tangential velocity plot a region of strong negative velocity and a region of positive velocity can be observed which
have an opposite effect on the propeller. These regions will also be circumferentially averaged in a net negative velocity.
5
(V − V∞) / V∞
−0.40
−0.35
−0.30
−0.25
−0.20
−0.15
−0.10
−0.05
0.00
0.05
Cp
−1.25
−1.00
−0.75
−0.50
−0.25
0.00
0.25
0.50
0.75
1.00
axial vorticity isosurface at ωx = −900 s-1
propeller plane
Fig. 4 Visualisation of wingtip flowfield and pressure coefficient distribution on the wing surface.
−0.4 −0.2 −0.0 0.2−0.4 −0.3 −0.2 −0.1 0.0
(Va − V∞) / V∞Vt / V∞
zp
yp
Rp,ref
zp
yp
Rp,ref
Fig. 5 Contour plots of axial and tangential velocity components at the propeller plane behind the left wingtip.
The dashed line shows the propeller disc area for the reference XPROP propeller.
The resulting propeller designs for this flowfield are presented in Section V and the consequence of circumferential
averaging will be further discussed in Section VII.
IV. Isolated Propeller Analysis
To establish confidence in PROPR, two comparisons were made. The first was with in-house windtunnel data of
the XPROP propeller in uniform flow. In Fig. 6 a comparison is presented of the thrust and torque coefficient versus
advance ratio for
V∞=
30 m/s. Although at high advance ratios a significant deviation starts to appear for both thrust
and torque coefficient, in the region of interest where
CT
is higher, the match with the experimental data is satisfactory.
The second comparison was made with a CFD model of the isolated propeller from Ref. [
13
]. In Fig. 7 the thrust
and torque distribution over a propeller blade are plotted for both PROPR and the CFD model for
V∞=
30 m/s and an
advance ratio of
J=
0
.
74. This corresponds to a thrust of 16% of the isolated wing drag. The integrated loading is
overestimated by PROPR with 4
.
5% and 7
.
6% in thrust and torque respectively. The shape of the thrust and torque
distribution from PROPR and the CFD model are very similar except for at the tip of the blade. The local rise in thrust
and torque in the CFD model due to the tip vortex is not captured in the PROPR results because of the single lifting line
representation of the blade. Considering that in these comparisons acceptable agreement was found, a design study was
performed with PROPR. This is presented in the next Section V.
6
0.35
0.00
0.30
0.25
0.20
0.15
0.10
0.05
−0.05
Thrust coefficient CT
0.50 0.75 1.00 1.25 1.50
PROPR
Experiment
0.06
0.00
0.05
0.04
0.03
0.02
0.01
Torque coefficient CQ
Advance ratio J
0.50 0.75 1.00 1.25 1.50
Fig. 6 Propeller performance from PROPR and inhouse windtunnel test for V∞=30 m/s and β0.7Rp=30◦.
180
Thrust distribution T´ (N / m)
Radial coordinate r / Rp
0.2 0.3
PROPR
CFD
160
140
120
100
80
60
40
20
00.4 0.5 0.6 0.7 0.8 0.9 1.0
14
Torque distribution Q´ (Nm / m)
0.2 0.3
12
00.4 0.5 0.6 0.7 0.8 0.9 1.0
10
8
6
4
2
Fig. 7 Blade loading distributions from PROPR and CFD model for V∞=30 m/s, β0.7Rp=30◦and J =0.74.
7
V. Propeller Design Study
In this section the design optimization results from PROPR for a propeller placed in the wingtip flowfield are
discussed. The different propeller designs are given in Table 4. The original XPROP propeller was tested in isolated and
installed condition. The XPROP propeller was also optimized for minimum power in terms of blade pitch distribution
and chord distribution, keeping the airfoil sections the same. This was done for isolated and installed conditions,
denoted isoOpt and insOpt respectively. The former was tested both in isolated and installed conditions, while the latter
was only tested in installed conditions. Note that these optimizations were performed for each thrust level separately
and that for each thrust level the performance is given for optimum operating conditions in terms of β0.7Rpand J.
Table 4 Overview of different propeller geometries used in design study.
Propeller name Description
XPROP-iso Original XPROP propeller operating in isolated condition
isoOpt-iso Optimized for isolated condition, operating in isolated condition
XPROP-ins Original XPROP propeller operating in installed condition
isoOpt-ins Optimized for isolated condition, operating in installed condition
insOpt-ins Optimized for installed condition, operating in installed condition
0.10 0.14 0.17 0.21 0.24 0.27 0.31 0.34 0.38 0.41
Propulsive efficiency ηp (%)
100
90
80
70
100
95
90
85
Power P / Piso (%)
XPROP-iso
isoOpt-iso
XPROP-ins
isoOpt-ins
insOpt-ins
80
0.44 0.48
Thrust over drag ratio T / Diso
Fig. 8 Propeller optimization results showing the propulsive efficiency and power versus the thrust to wing
drag ratio at constant radius Rp/Rp,ref =1.00 for isolated and installed conditions.
A. Propeller Optimization for Constant Radius
First, a design sweep was performed for a range of thrust levels, keeping the propeller radius equal to that of the
original XPROP propeller
Rp,ref
. In Fig. 8 the propeller performance is shown for a range of design thrust levels with
respect to the isolated wing drag
T/Diso
. The propulsive efficiency
ηp=TV∞/P
is plotted, as well as the relative power
required with respect to the XPROP-iso propeller
P/Piso
. Dashed lines refer to performance in isolated conditions, solid
lines indicate installed propeller performance. Put in perspective, the wing induced drag is about 40% of the total wing
drag in this condition, so a range of thrust levels is plotted from 25% up to 115% of the wing induced drag.
8
A number of trends can clearly be observed: The propulsive efficiency decreases with increasing design thrust in both
the isolated and installed cases. This is expected since the propeller radius was kept constant. The possible efficiency
gains due to installation and optimisation of the propeller are significant. Comparing insOpt-ins with XPROP-iso results,
up to 20% increase in efficiency is achieved at lower design thrust levels by the combined effect of optimisation and
installation, decreasing to approximately 10% and remaining constant at higher thrust levels. Although a more fair
comparison is that of the insOpt-ins with the isoOpt-iso propeller, both optimised for their respective flowfield. Then,
an efficiency increase up to 15% remains at the lowest thrust level, decreasing to 9% at the highest thrust level.
Looking at the power plot, the effectiveness of geometrical optimization in both isolated and installed conditions
at low and high thrust levels is clearly visible. This effect diminishes at more average thrust levels, as the XPROP
propeller is apparently designed for those thrust levels. The reduction in required power is significant when installing
the propeller, even for the XPROP with non-optimized geometry. Reductions up to 20% are achieved when comparing
insOpt-ins with XPROP-iso results, although looking at the most fair comparison with the isoOpt-iso propeller, a bit
lower maximum power reduction of up to 15% is found. Note that the installed propeller with optimized geometry for
isolated conditions (isoOpt) yields almost identical power reductions compared to the installed propeller with optimized
geometry for installed conditions (insOpt). Thus, effectively the propeller geometry is optimized for the required
thrust level and to a lesser degree for the non-uniformity in the flowfield. Only at the very high design thrust levels of
T/Diso ≥0.42 a noticeable difference in performance between the two different optimized propellers is observed.
With increasing thrust, the power reduction due to installation converges quickly to a nearly constant value, meaning
that the effective power reduction that can be achieved by installation of the propeller almost does not change with thrust
requirement. One would expect that the effective power reduction would decrease with increasing propeller design
thrust, as there is only a finite amount of energy to be ‘extracted’ from the wingtip flowfield present in the installed case.
Because of the limited maximum thrust that can be delivered by the XPROP propeller it is not possible to investigate the
effective power decrease at even higher thrust levels for the current propeller radius. The experimental work done by
Patterson et al. [
4
] gives already an indication of the power reduction found at higher thrust levels, considering that the
size of that propeller and its thrust relative to the wing was much larger. At similar lift coefficient the power reduction
was found to be 14%, although this was for a non-optimized propeller design. Considering that this is of similar order
to what was found in this study thus far, it may be that over a larger thrust range this relative power reduction stays
more or less constant. To confirm this, in Section V.C the higher thrust regime up to a thrust equal to the cruise drag of
the wing will be investigated with larger radius propellers.
B. Blade Loading and Geometry Changes Due to Optimization
The resulting changes in the propeller blade loading and geometry due to optimization and installation are discussed
for two different design thrust levels:
T=
0
.
21
Diso
and
T=
0
.
39
Diso
. First, the results from optimization of the XPROP
propeller with
T=
0
.
21
Diso
are discussed. In Fig. 9 the blade pitch angles, chord fractions, the profile efficiency and
thrust distribution over the entire blade radius are shown. It is seen that the chord distribution of the insOpt and isoOpt
propellers are nearly identical, even though the insOpt propeller was subjected to the non-uniform wingtip flowfield
during optimization. In both cases, the chord lengths were reduced by as much as 40% compared to the XPROP
propeller. A slight increase in blade pitch angle in the root sections is observed. Both the optimized isoOpt and insOpt
propellers show significantly higher efficiency in the root sections. Presence of the non-uniform inflow enables further
efficiency gains. Combined, this leads to a higher local profile efficiency for the insOpt propeller, especially for the
root sections (
r/Rp<
0
.
4). A clear trend is visible in the thrust distribution over the blade. Geometry optimization
of the XPROP propeller causes the thrust distribution to shift inboard towards the root. Furthermore, the maximum
value decreases. The same behavior to an even greater extent is observed when investigating the insOpt propeller. The
combination of higher profile efficiency and the production of thrust there where the profile efficiency is higher makes
this the most efficient propeller of the three.
Second, the optimization results with
T=
0
.
39
Diso
are discussed. In Fig. 10 it is seen that the local blade chord
lengths are increased in both the isoOpt and insOpt propeller designs compared to the original XPROP propeller. This
geometry change due to optimization shows a reverse trend than what was seen for the lower design thrust in Fig. 9,
where the chord fractions were decreased due to optimization. The local blade pitch angle is higher for both the isoOpt
and insOpt propeller design, as was the case for the propellers optimized for
T=
0
.
21
Diso
. Also the improvements in
local efficiency are similar, except for at the tip. Note that the efficiency of the XPROP propeller is relatively low in the
tip region (
r/Rp>
0
.
85) due to tip stall. Optimization of the propeller geometry reduces this tip stall and the overall
efficiency distribution is again an almost ideal constant distribution. Finally, again an inboard shift in thrust distribution
is observed for the optimized propeller geometries.
9
Radial coordinate r / Rp
0.2 0.4 0.6 0.8 1.0 0.2 0.4 0.6 0.8 1.0
Profile efficiency (%)
100
80
60
40
20
200
150
100
50
0
T´ (N / m)
Blade pitch angle β (deg)
20
30
40
50
60
70
Chord c / Rp
0.20
0.15
0.10
0.05
XPROP-iso
isoOpt-iso
insOpt-ins
Fig. 9 Propeller blade loading and geometry changes due to optimization for T =0.21Diso.
Radial coordinate r / Rp
0.2 0.4 0.6 0.8 1.0 0.2 0.4 0.6 0.8 1.0
Profile efficiency (%)
100
80
60
40
20
200
100
0
T´ (N / m)
Blade pitch angle β (deg)
20
30
40
50
60
70
Chord c / Rp
0.20
0.15
0.10
0.05
XPROP-iso
isoOpt-iso
insOpt-ins
300
400
Fig. 10 Propeller blade loading and geometry changes due to optimization for T =0.39Diso.
10
C. Propeller Optimization with Varying Radius
The performance of the propeller placed in the wingtip flowfield was also investigated for propeller radii different
from the XPROP propeller. The radius was varied between 0
.
75
−
1
.
50
Rp,ref
, where
Rp,ref
is the radius of the XPROP
propeller. A design thrust range up to
T=Diso
was analysed for the largest radius propeller. The hub dimension was
kept constant and was not scaled with propeller radius. In this analysis the performance of the propeller optimized
for installed condition and operating in installed condition, insOpt-ins, was compared to a propeller of equal radius
optimized for isolated condition operating in isolated condition, isoOpt-iso. This is the most fair comparison since
both propellers are optimised for their respective flowfield. The propeller performance results are given in Fig. 11 as
a function of thrust level. For any given thrust level, the propulsive efficiency
ηp
increases with increasing propeller
radius for all propeller designs. This is a straight forward result since, with increasing radius and equal thrust, more
mass is accelerated by the propeller but with a lower velocity increase. The corresponding advance ratio is also higher
for larger radii propellers due to the large reduction in required rotational speed n.
80
85
90
95
100
105
1.0
1.2
1.4
1.6
1.8
2.0
0.75Rp,ref
1.00Rp,ref
1.25Rp,ref
1.50Rp,ref
0.0 0.2 0.4 0.6 0.8 1.0
6
8
10
12
14
16
18
0.0 0.2 0.4 0.6 0.8 1.0
82
84
86
88
90
92
Propulsive efficiency ηp (%)ηp − ηp, iso (%)
Power P / Piso (%) Advance ratio J
Thrust over drag ratio T / Diso
Fig. 11 Optimization results with varying propeller radius for installed condition with insOpt-ins design com-
pared to isolated condition with isoOpt-iso design.
The gain in efficiency by installation of the propeller at the wingtip,
ηp−ηp,iso
, varies less with propeller radius.
Only for low thrust levels of less than 30% of the wing drag, significant differences occur in the efficiency gain. While
the efficiency gain decreases with thrust level, it does so at a reducing rate, decreasing to a still significant gain of 7
.
5%
when the thrust equals the wing drag
T=
1
.
00
Diso
. As discussed earlier for the optimisation results at equal radius, the
power ratio
P/Piso
seems to level offto an approximately constant value at larger thrust levels. This is also happening
for the other propeller radii, however the relative power reduction reduces for larger propeller radii, reducing to a 9%
reduction due to the wingtip flowfield for 1.50Rp.
11
VI. Actuator Disk–Wing Analysis
The upstream effect of the propeller designs on the wing performance was analyzed through CFD analyses of the
wing with an actuator disk representation of the propeller. These simulations are of similar computational cost as the
isolated wing simulations but do provide the required time-averaged upstream effect of the propeller at much reduced
computational cost compared to the fully resolved propeller–wing simulation in Section VII. In Fig. 12 the wing lift
coefficient
CL
and lift-over-drag ratio
L/D
are plotted as a function of propeller thrust for a number of cases with
varying propeller radius from Fig. 11. Results are also shown for the isolated wing.
0.0 0.2 0.4 0.6 0.8 1.0
0.3446
0.3447
0.3448
0.3449
0.3450
0.3451
0.3452
0.0 0.2 0.4 0.6 0.8 1.0
21.30
21.35
21.40
21.45
21.50
21.55
21.60 Prop off
0.75Rp,ref
1.00Rp,ref
1.25Rp,ref
1.50Rp,ref
Thrust over drag ratio T / Diso
Wing lift coefficient CL
Wing lift-over-drag ratio L / D
1.50Rp,ref no swirl
Fig. 12 Wing performance as function of propeller thrust investigated with an actuator disk.
The changes in wing lift coefficient due to propeller thrust are quite small and are only just larger than the estimated
discretization uncertainty given in Table 3. Despite this, an increasing trend in
CL
is visible with increasing propeller
thrust level. This could be explained by a slightly stronger suction over the wing due to the presence of the propeller.
Contrary to the lift coefficient, the lift-over-drag ratio decreases with increasing propeller thrust. Apparently the
propeller slightly reduces the wing efficiency. Another observation is that with increasing propeller radius, the upstream
effects of the propeller on the wing reduce. For the 1
.
50
Rp
case an additional simulation was performed where no
swirl component was introduced by the actuator disk, denoted no swirl. It shows that the swirl component has only a
minor impact on the wing loading. Thus, the reduction of swirl in the wingtip flowfield due to the propeller does not
cause a significant change in wing loading and the observed changes are mainly an effect of the axial velocity increase.
However in general, it is concluded that the upstream effect of the propeller on the wing loading is very limited for the
investigated thrust range. A closer look at the downstream interaction of the wing on the propeller is presented in the
next section.
VII. Propeller–Wing Analysis
To check the accuracy of PROPR for the non-uniform wingtip flowfield, and to investigate the unsteady behaviour
of a wingtip-mounted pusher propeller, a fully resolved propeller–wing CFD simulation was performed. The original
XPROP propeller was simulated installed on the wingtip at optimum operating condition in terms of
β0.7Rp
and
J
at a
thrust of T=0.30Diso.
In Fig. 13 a the normalized blade thrust and torque as function of blade phase angle are shown, as defined in Fig. 14
b. In addition, the mean of the thrust and torque obtained from the transient CFD simulation are shown, as well as the
thrust and torque values calculated using PROPR. As expected, the blade thrust and torque vary considerably over a
rotation due to the circumferential non-uniformities in the flowfield that were shown in Fig. 5. Following the trajectory
of the blade, clear trends are observed:
•ϕ=0◦: Initial position, blade pointing up and perpendicular to the wing surface.
•ϕ=90◦: Blade is fully outboard and subjected to the largest negative tangential velocities, thus highest thrust.
12
36031527022518013590450 36031527022518013590450
1.2
1.1
1.0
0.9
0.8
0.7
0.6
1.2
1.1
1.0
0.9
0.8
0.7
0.6
Propeller blade phase angle φ (deg)
Blade thrust T / TPROPR
Blade torque Q / QPROPR
CFD
PROPR
CFD mean
Fig. 13 Installed XPROP propeller blade thrust and torque evolution over a complete rotation for
T=0.30Diso.
•ϕ=
180
◦
: Blade is again perpendicular to the wing but now pointing down. Thrust delivered with inflow from
under the wing is slightly lower.
•ϕ=
270
◦
: At this angle the blade is fully immersed in the wake region of the wing, showing a clear local peak in
thrust, due to the lower axial velocity. This causes an increased angle of attack of the blade sections.
Identical trends are observed when investigating the torque evolution. The difference in mean thrust and torque
obtained between CFD and PROPR are very similar to those obtained for the isolated propeller in Section IV. The blade
thrust and torque are overestimated 3
.
3% and 4
.
0% by PROPR respectively. This provides confidence in the validity of
PROPR given these non-uniform flowfields.
To get some more insight in the blade loading evolution, in Fig. 14 a the propeller blade thrust distribution is plotted
at various blade positions as defined in Fig. 14 b. The blade distribution from PROPR is also shown. It is seen that the
thrust distribution over the blade from PROPR is nearly identical to that found in the transient CFD simulation over
blade 1. Blade 2 and 3 are subjected to the largest tangential velocity field and indeed show the highest thrust. Most
notably, these blades experience a significantly higher thrust at the root sections of the blade. Blade 5 experiences the
lowest blade loading because, as was shown in Fig. 5, the tangential velocity field at this location is near zero. A drop in
thrust near the root occurring over blade 6 is seen, because it is immersed in a flowfield with locally positive tangential
velocity. Blade 6 experiences this positive tangential velocity near the root, because it crosses the tip vortex of the wing.
This becomes clear from Fig 15, where a tangential and an axial vorticity isosurface is shown at such levels that they
identify the propeller blade tip vortices and wingtip vortex respectively. The propeller blades are at the same position as
in Fig. 14 b. It is clear that blade 6 is starting to cross the wingtip vortex.
13
1
2
3
4
5
6
Thrust distribution T´ (N / m)
Radial coordinate r / Rp
0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
100
0
50
−50
150
200
250
300
350
CFD - blade 1
CFD - blade 2
CFD - blade 3
CFD - blade 4
CFD - blade 5
CFD - blade 6
PROPR
a) Propeller blade thrust distribution comparison. b) Definition of blade positions.
yp
zp
φ
5
6
4
3
2
1
Fig. 14 Comparison of XPROP propeller blade thrust distributions at different blade positions for
T=0.30Diso.
a) Side view of vorticity isosurfaces.
b) Rear view of vorticity isosurfaces.
ωx = −900 s-1
ωt = 800 s-1
wingtip vortex
blade tip vortices
Fig. 15 Vorticity isosurfaces identifying the XPROP propeller blade tip vortices and wingtip vortex.
14
VIII. Conclusions
A design framework for wingtip-mounted pusher propellers was established and verified with RANS CFD sim-
ulations. It was found that the following approach is valid: First a wingtip flowfield was extracted from an isolated
wing simulation. Then, this flowfield was circumferentially averaged and used in a validated lifting-line based propeller
analysis and optimisation routine named PROPR for aerodynamic design optimization. The upstream effect of the
propeller on the wing performance was investigated with an actuator disk representation of the propeller in multiple
wing simulations and was found to be very limited for the tested thrust levels. This was a requirement for the taken
approach. However, a trend of increasing wing lift coefficient and decreasing lift-over-drag ratio was observed with
increasing propeller thrust, which may become significant for higher thrust levels than currently investigated. At last,
the resulting propeller performance from PROPR was in line with time-averaged propeller loading of fully resolved
propeller-wing RANS CFD simulations, providing confidence in the validity of the approach. This was despite the large
fluctuation found in the transient propeller blade loading due to circumferential non-uniformities in the inflow field.
With this design framework for wingtip-mounted pusher propellers, various conclusions on propeller design for
wingtip-mounted pusher propellers are drawn:
•
The possible propulsive efficiency gains for the propeller due to installation are significant: Up to 16% increase in
efficiency was achieved at the lowest investigated thrust level of 5% of the wing drag, decreasing with a reducing
slope to approximately 7.5% for the highest investigated thrust level of 100% of the wing drag.
•
The propulsive efficiency gain was only significantly dependent on the propeller radius for low thrust levels of
less than 30% of the wing drag.
•
It was found that effectively the propeller geometry is optimized for the required thrust level and to a lesser degree
for the non-uniformity in the flowfield.
•
Propeller blade optimization and installation result in higher profile efficiency in the blade root sections and a
more inboard thrust distribution over the blade.
Considering the propulsive efficiency benefits found in this study, wingtip-mounted pusher-propellers should be
considered for (hybrid)-electric concepts. The propeller thrust should then be a design variable, determining together
with the wing lift the resulting efficiency benefit from this aerodynamic interaction.
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