Experimental wind tunnel testing of a new multidisciplinary morphing
wing model
MICHEL JOEL TCHATCHUENG KAMMEGNE
Research Laboratory in Active Controls, Avionics and Aeroservoelasticity (LARCASE)
École de Technologie Supérieure, Montreal
1100 Notre Dame West, H3C 1K3, Montreal, Quebec
CANADA
[email protected] http://www.etsmtl.ca
RUXANDRA MIHAELA BOTEZ
Research Laboratory in Active Controls, Avionics and Aeroservoelasticity (LARCASE)
École de Technologie Supérieure, Montreal
1100 Notre Dame West, H3C 1K3, Montreal, Quebec
CANADA
[email protected] http://www.etsmtl.ca
MAHMOUD MAMOU
Aerodynamics Laboratory, NRC Aerospace
National Research Council Canada
1200 Montréal Road, K1A 0R6, Ottawa, Ontario
CANADA
[email protected] http://www.nrc-cnrc.gc.ca/eng/index.html
YOUSSEF MEBARKI
Aerodynamics Laboratory, NRC Aerospace
National Research Council Canada
1200 Montréal Road, K1A 0R6, Ottawa, Ontario
CANADA
[email protected] http://www.nrc-cnrc.gc.ca/eng/index.html
ANDREEA KOREANSCHI
Research Laboratory in Active Controls, Avionics and Aeroservoelasticity (LARCASE)
École de Technologie Supérieure, Montreal
1100 Notre Dame West, H3C 1K3, Montreal, Quebec
CANADA
[email protected] http://www.etsmtl.ca
OLIVIU SUGAR GABOR
Research Laboratory in Active Controls, Avionics and Aeroservoelasticity (LARCASE)
École de Technologie Supérieure, Montreal
1100 Notre Dame West, H3C 1K3, Montreal, Quebec
CANADA
[email protected] http://www.etsmtl.ca
TEODOR LUCIAN GRIGORIE
Research Laboratory in Active Controls, Avionics and Aeroservoelasticity (LARCASE)
École de Technologie Supérieure, Montreal
1100 Notre Dame West, H3C 1K3, Montreal, Quebec
CANADA
[email protected] http://www.etsmtl.ca
Advances in Mathematics and Computer Science and their Applications
ISBN: 978-1-61804-360-3 90
Abstract: - The paper presents the development of an experimental morphing wing model and its performance
evaluation by using some wind tunnel tests. The model was designed, fabricated and tested during a
multidisciplinary collaborative research project involving industrial partners, research entities and academia
from Canada and Italy. It was based on the dimensions of a full scale wing tip structure, being equipped with a
morphable flexible upper surface made from composite materials and deformed by using four miniature
electrical actuators, with an array of 32 Kulite pressure sensors to monitor the air flow behavior over the upper
surface, and with an aileron also electrical actuated. In the paper are successively exposed: 1) a short project
presentation; 2) the skin shape optimization; 3) the instrumentation of the morphing wing model and the
mechanisms used to control it; 4) the wind tunnel aerodynamic results analysis by using an infrared camera.
Key-Words: Morphing wing, Numerical optimization, Control system, Experimental model, Instrumentation,
Wind tunnel testing, Infra-red analysis
1 Research project description Today, around the world, the fuel economy is an
aim for all factors implied in the aerospace industry
field, from environmental concerns but also from
economic concerns, related to the flights costs
reduction. Having in mind that the aerodynamic
drag is among the most important determinants of
energy consumption in aircraft, one identified way
to achieve this aim is the drag reduction. Between
the recent feasible methods used to reduce the
aerodynamic drag the researchers placed the
morphing of the aircraft wings ([1]). In order to
obtain a better lift-to-drag ratio, different parts of
the wing, such as the trailing edge, leading edge and
extrados, can be morphed. From the morphing
extrados point of view, the expected result is to
delay the transition location toward the wing trailing
edge, having in this way an extension of the laminar
region on the upper surface of the wing with a direct
consequence in the decrease of the drag over an
operating range of flow conditions ([2]-[18]).
The research presented in this present paper was
done within the framework of the international
CRIAQ MDO505 Morphing Wing project. The
participants in this project were Ecole de
Technologie Superieure (ETS), Ecole Polytehnique
and University of Naples ‘Federico II’ as academia
research partners, the Canadian National Research
Council (CNRC) and the Italian Aerospace
Research Center (CIRA) as research center partners
and Bombardier Aeronautique, Thales Avionic and
Alenia Aermacchi as the industry partners.
This project was performed as a continuation of
the CRIAQ 7.1 project on adaptive upper-surface
wing concept. In this project a real wing structure
was considered and designed following structural
and materials optimizations based on new
aerodynamic optimization constraints and new
morphing skin control challenges, using an
electrical actuation system along with classical and
adaptive ailerons. The novelty of the project
consisted in its multidisciplinary approach, where
structure, aerodynamics, control and experimental
design were combined to design and manufacture an
active morphing wing demonstrator and test it under
subsonic wind tunnel conditions ([3]-[18]).
The layout and the position of the morphing
upper skin on a typical aircraft wing are presented in
Fig. 1 ([19]), while the structural elements of the
developed model, e.g. spars, ribs, actuator positions
inside the wing box, are shown in Fig. 2 ([19]).
Fig. 1 The layout and the position of the morphing upper
skin on a typical aircraft wing ([19])
Fig. 2 Structural elements of the developed model ([19])
Advances in Mathematics and Computer Science and their Applications
ISBN: 978-1-61804-360-3 91
The wing model was based on the dimensions of
a full scale wing tip structure. Therefore, the span
and chord of the model match the dimensions found
on a real aircraft wing tip, 1.5 m span and 1.5 m root
chord with a taper ratio of 0.72. To this a leading
and trailing edge sweep angle of 8° was added for a
better representation. High grade industry steel and
aluminum alloy material were used for the
manufacturing of different internal structure
elements. The adaptive upper surface, made from
carbon fiber composite materials, was positioned
between 20% and 65% of the wing chord, and it was
specifically designed and optimized to meet
aeronautical industry requirements. The flexible
skin design and optimization were performed trying
to match as close as possible the aerodynamically
optimized upper surface shapes ([19]).
Speed, Reynolds number, angle of attack and
aileron deflection number were some of the
parameters that determined the actuator control of
the skin deformation. Two actuation lines, each
comprised of two electrical actuators, were installed
at 37% and 75% of the wing’s span. Each actuator
has the ability to operate independently from the
others. On each actuation line, the actuators were
positioned at 32% and 48% of the local wing chord.
2 The skin shape optimization An in-house developed genetic algorithm was
applied to the problem of airfoil upper-surface
morphing ([20]). The problem objective was to
search the optimum shapes for an airfoil through
local thickness modifications with the aim to
improve the upper surface flow and thus the
aerodynamic performances of the airfoil.
Vertical displacements for the actuators were
determined from the genetic optimization of the
wing airfoil. The optimization gave the
displacement values for one pair of actuators
situated at 37% of the wing span, while the
displacements for the second pair of actuators were
calculated as a linear dependence.
The airfoil on which the optimization was carried
and which represents the base airfoil of the wing
model original shape is shown in Fig. 3.
Fig. 4 presents a schematic of the optimization
process which was an iterative one, needing several
interactions between genetic algorithm parameters,
objective function, aerodynamic solver and shape
reconstruction using spline interpolation ([21],
[22]). The aerodynamic analysis was done by using
the open source XFoil aerodynamic solver allowing
both inviscid and viscous calculation ([23]). It
includes also the estimation of the boundary layer
parameters, including the transition position, and
airfoil geometry modification functions, such as
airfoil refinement and flap deflection ([24]).
Fig. 3 The original wing airfoil (reference airfoil)
Input 1st Generation XfoilFitness
FunctionEvaluation
Cross-Over
MutationTournamentNewGeneration
Final Generation
Yes
No
Results
Flight conditions
Genetic algorithm
parameters
Airfoil coordinates
Fig. 4 Schematics of the optimization process
The objective function was constructed based on
the desired objective of influencing the upper
surface flow of the wing with the purpose of
minimizing drag and delaying the transition from
laminar to turbulent flow for a more stable boundary
layer. The optimization objective function is
,1
4
_
__
2
3
d
TR
w
originalTr
originalTrmorphedTr
d
ifC
Upw
Up
UpUpw
CwF
(1)
where UpTr and Cd represent the transition point on
the upper surface of the airfoil and the drag
coefficient of the airfoil, and wi are the weights used
to manipulate the objective function.
The optimization was applied for several
combinations of Mach numbers (M), angles of
attack (α) and aileron deflection angles (δ). Fig. 5
presents a Monte Carlo map for one of the cases
with the optimization results plotted on it. The
Monte Carlo map shows all the possible
combinations of two actuator displacements,
essentially all the possible results, and one can plot
the optimized results on it to estimate how close the
optimization code was.
Advances in Mathematics and Computer Science and their Applications
ISBN: 978-1-61804-360-3 92
Fig. 5 Monte Carlo map with optimization results for
α=2°, M=0.2 and δ=4° flow case
3 Instrumentation of the morphing
wing model and the mechanisms used
to control it The experimental wing model contained three parts:
1) a metal part coming from the original aircraft
wing, with unmodified structure, able to sustain the
wing loads; 2) a morphing part, consisting of a
flexible skin installed on the upper surface of the
wing; and 3) an actuated aileron, designed starting
from the original one on the aircraft (Fig. 6) ([25]).
The morphing part was actuated by four similar
electric actuators, placed on two actuation lines:
Act. #1 and Act. #3 at 32% from chord, respectively
Act. #2 and Act. #4 at 48% from chord (Fig. 6). For
each of the optimized airfoils resulted four vertical
displacements corresponding to the positions of the
four actuators, stored in a database in order to be
used as reference vertical displacements for the
control system. The actuator designed controller
modified the actuators linear positions until the real
vertical displacements of the morphing skin in the
four actuation points equalled the desired vertical
displacements of the optimized airfoil resulted for a
flow condition ([25]).
Fig. 6 Wing structure and actuations lines positions
The system interfacing the remote computer and
the morphing wing experimental model was based
on the architecture presented in Fig. 7; it was
designed by using a National Instruments Real Time
(RT) Target. The feedback for the control system of
the morphing actuators was provided by four Linear
Variable Differential Transformers (LVDT) used as
position sensors and having axes parallel to the
actuators axes ([25]).
The experimental instrumentation included [25]:
1) a NI PXIe-1078, 9-Slot 3U PXI Express Chassis;
2) a NI PXIe-8135 embedded controller; 3) four NI
PXIe-4330 Data Acquisition Cards; 4) a NI PXI-
8531, 1-Port CANopen Interface for PXI; 5) a NI
PXIe-6356 Simultaneous X Series Data Acquisition
Card; 6) a SCXI-1000 rugged, low-noise chassis
that can hold up to four SCXI modules; 7) a NI
SCXI-1540 8-Channel LVDT Input Module; 8) a NI
SCXI-1315; 9) two Programmable power supplies
Aim-TTi CPX400DP.
The GUI used for the control system and data
acquisition system in the wind tunnel tests is shown
in Fig. 8, while Fig. 9 shows the Fast Fourier
Transforms (FFT) for an acquisition sequence
associated to the 32 Kulite pressure sensors
equipping the upper surface flexible skin.
Fig. 7 National Instruments RT target and remote computer configurations
Maxon
motor drivesCANopen
Custom device
Wing controller
Aileron controller
Kulite processing
Custom device
(RMS, Zeroing)
Data logger
Custom device
Morphing wing model
Aileron drive
Kulite sensors signals
LVDT
sensors
signals
PressureRMS
Vizualization
Data
Status
National Instruments RT Target
CANopen Bus
Command control
morphing actuator
Data logger
command
State check
Command
control aileron
Position target
Position target
Remote computer
Advances in Mathematics and Computer Science and their Applications
ISBN: 978-1-61804-360-3 93
Fig. 8 Graphical User Interface (GUI) for wind tunnel tests
Fig. 9 Fast Fourier Transforms (FFT) for an acquisition sequence associated to the 32 Kulite pressure sensors
4 Wind tunnel testing of the wing The wind tunnel tests were performed at the 2 m x 3
m atmospheric closed circuit subsonic wind tunnel
of the National Research Council Canada.
The upper surface flexible skin was equipped
with 32 high precision Kulite piezoelectric-type
sensors ([26]) for pressure measurement on the
flexible skin to evaluate the laminar-to-turbulent
transition location. These sensors were installed in
two staggered lines (with 16 Kulite sensors on each
line), situated respectively at 0.600 m and 0.625 m
from the wing root section. In addition to the Kulite
piezoelectric sensors, at the same two spanwise
stations, 60 static pressure taps were installed (30
taps on each line), on the wing leading edge, lower
surface and aileron, thus providing complete
experimental pressure distribution around the wing
cross section at 40% of the wing span.
Fig. 10 presents the MDO 505 morphing wing
model installed in the tunnel test section, viewed
from both the leading edge (left picture) and the
trailing edge (right picture).
Advances in Mathematics and Computer Science and their Applications
ISBN: 978-1-61804-360-3 94
For capturing the transition region over the entire
wing model surface infra-red (IR) thermography
camera visualizations were performed. The wing
leading edge, its upper surface flexible skin and the
aileron interface were coated with high emissivity
black paint to improve the quality of the IR
photographs. The span-wise stations, where the two
pressure sensors lines were installed were not
painted, in order to not influence the pressure
reading quality. A Jenoptik Variocam camera, with
a resolution of 640×480 pixels, was used to measure
the surface temperatures ([27]). This camera was
equipped with 60o lens in order to capture the flow
transition on the entire upper surface of the wing.
Wind tunnel experimental testing was conducted for
all the aerodynamic optimized cases.
Fig. 11 presents an example of the IR
visualization of the wing model upper surface
transition, for one flight condition (angle of attack
1.5°, Mach number 0.2 and aileron deflection 4°
down) and for both un-morphed (left figure) and
morphed (right figure) skin shapes.
Fig. 10 MDO 505 wing model setup in wind tunnel tests
The black line from Fig. 11 represents the
average transition line on the upper surface, and its
variation as function of the span-wise position can
clearly be observed. The two dashed white lines
represent the estimated extent of the transition
region, determined as function of the chord-wise
temperature gradient existing between laminar and
turbulent regimes. The red dot corresponds to the
estimated transition in the span-wise section situated
at 0.612 m from the root section (40% of the model
span), that is half-way between the two Kulite
piezoelectric pressure sensors lines. The accuracy of
the transition detection for this section was
estimated to ± 2% of the local chord, based on the
known Kulite positions and their thermal signatures
in the images.
For this flow case the laminar region was
extended with 7.6% of the chord and the transition
region was extended as well with 3% of the chord.
On the other way, the rake drag coefficient was
reduced with 3% from the original value.
a.
b.
Fig. 11 IR visualization of the laminar-to-turbulent
transition region for α=1.5°, M= 0.2 and δ=4° down
5 Conclusions The development and experimental wind tunnel
testing of a new multidisciplinary morphing wing
model were here presented. The experimentally
Advances in Mathematics and Computer Science and their Applications
ISBN: 978-1-61804-360-3 95
obtained results confirmed the feasibility of the
morphing wing technology, and, having in mind that
our project used a real wing structure, create the
premises for a future application of this technology
on real aircrafts.
6 Acknowledgments The authors would like to thank to the Thales
Avionics team for their support - mainly to Mr.
Philippe Molaret, Mr. Bernard Bloiuin, and Mr.
Xavier Louis, and to the Bombardier Aerospace
team - Mr. Patrick Germain and Mr. Fassi Kafyeke
for their help. We would also like to thank the
CRIAQ and the NSERC for the funds received on
the CRIAQ MDO 505 project.
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