Experimental wind tunnel testing of a new

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




CANADA


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




CANADA


OLIVIU SUGAR GABOR




CANADA


TEODOR LUCIAN GRIGORIE




CANADA


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])


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.


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


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).


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


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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ISBN: 978-1-61804-360-3 97

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Experimental wind tunnel testing of a new