1. Aeroelastic Behavior of a Typical Airfoil Section
with Shape Memory Alloy Springs
Vagner Candido de Sousa*
Department of Aeronautical Engineering
Engineering School of Sao Carlos
University of Sao Paulo, Brazil
* Visiting Scholar at the Dynamic and Smart Systems Lab
The University of Toledo (Summer/Fall, 2015)

2. Where we are
2
São Carlos
Campus
Research center
São Paulo
(Capital)
State of São Paulo
São Carlos - SP
Brazil

3. University of São Paulo
• A state university founded in 1934
• Campi: São Paulo (4), Bauru,
Piracicaba, Pirassununga, Lorena,
Ribeirão Preto, São Carlos (2)
• Undergrads: 58.204
• MSc: 14.149, PhD: 15.398
• Other: 5.041
• Professors: 6.008
• Articles: 16.013 (WoS/ISI)
3
* 2013
Campus 1

4. University of São Paulo, Campus of São Carlos
• Institute of Physics
• Institute of Mathematic and
Computer Sciences
• Institute of Architecture
• Institute of Chemistry
• Engineering School of São Carlos
– Dep. of Aeronautical Eng.
– Dep. Electrical Eng.
– Dep. Geotechnical Eng.
– Dep. Hydraulics
– Dep. Materials Eng.
– Dep. Mechanical Eng.
– Dep. Production Eng.
– Dep. Structural Eng.
– Dep. Transportation Eng.
4

5. Department of Aeronautical Engineering
• Research
– Aerodynamics
– Aeroservoelasticity
– Flight Dynamics
– Aeronautical Structures
5

6. Our lab – Laboratory of Aeroelasticity
6
• Students (Summer, 2015)
– MSc: 1
– PhD: 6
– Post doc: 1
• Collaborations in
– USA
– Canada
– UK
• Facilities
– Blower wind tunnel
– Whirl Tower
– Smart table
– Sensors (accelerometers, laser
vibrometer)
– Acquisition system (dSPACE, LMS Scadas,
LDS Photon)
– Shakers (Modal Shop, APS Long-Stroke
Vibration Exciter)

7. Current topics of interest
• Fixed-wing and rotary-wing
aeroelasticity
• Smart materials for energy
harvesting and/or vibration control
• Wind energy harvesting (fixed and
rotary wing )
• Shape memory alloys
• Helicopters vibration damping
(piezoelectric based pitch link
device)
• Self-powered circuits for
piezoelectric active/semi-
active/semi-passive control
• Bio-inspired aircraft (morphing) and
aquatic robots
• In short,
Aeroelasticity
+
smart materials
7

8. Aeroelasticity
• Interaction between
aerodynamic forces and
structural motions
• Airfoil and non-airfoil structures
• Transmission lines
• Suspension bridges
• Tall chimneys and
buildings
• Static phenomena
– Divergence
– Control reversal
• Dynamic phenomena
– Buffeting
– Flutter (many kinds)
8
flowsol.co.uk
Wings

9. Very brief history (incidents related to aeroelasticity)
• 1903 (Prof. Samuel P.) Langley
Monoplane
– Low torsional stiffness wings
• 1916 Handley Page 0/400
Bomber
– Horizontal tail problems
9

10. Very brief history
• 1918 Fokker D-VIII
– Wing failures in high-speed
dives
• 1925 Albatros D.III
– Lower wing failures
10

11. Very brief history
• 1930 Junker F-13
– Horizontal tail problems
• Region of strong rising gust in
England
• 1938 Junkers 90-V1
– Crashed during a “non-
conservative” flight test
11

12. Very brief history
• 1940 Tacoma Narrows Bridge
• Structural failure
• 1959/1960 Lockheed Electra
• In-flight wing break-up
12

13. Very brief history
• 1960-1970 Rockets
– Problems observed during wind
tunnel tests and corrected
• 1970-1980 Space shuttle
13

14. An important observation
• Most of those structures had
sufficient strength in static tests
• Problems appeared under
aerodynamic loads
– Related to aeroelastic
phenomena
14

15. Static aeroelasticity phenomena (elastic + aerodynamic forces)
• Divergence
– Static aerodynamic forces
become too large for the wing
torsional stiffness to resist
– Aerodynamic loads increase the
incidence; increasing incidence
the aerodynamic loads increase
• Wing twists until it breaks
15
Langley’s Aerodrome, 1903
First report of static divergence

16. Static aeroelasticity (elastic + aerodynamic forces)
• Control reversal
– Wings deform in such a way the
control surfaces do not respond
as expected to the pilot’s
commands
– MiG-25’s (formerly Ye-155R/P)
first flight revealed insufficient
wing rigidity
• The resulting control reversal
was dangerous, and
maneuverability limitations
were imposed
16
– On October 30, 1967
• Aileron reversal caused by
exceeding the instrument
speed limit crashed an Ye-
155P1

17. Dynamic aeroelasticity (inertial + elastic + aerodynamic forces)
• Buffeting • Flutter (many kinds)
– Coupled bending/torsion
modes
• Airfoil
• Non-airfoil (eg, bridges)
– Galloping
– Stall flutter
– “Whirl mode”
– Potentially catastrophic
17

18. Dynamic aeroelasticity: buffeting
• Airfoil and non-airfoil structures
• Random vibration
• Usually just inconvenient
18
Laminar flow
Turbulent flow
(vortex shedding)
Flow separation
(transition region)
Surface subject
to turbulent flow

19. Dynamic aeroelasticity: “galloping” flutter
• Large amplitude, low frequency
oscillation
• Bluff bodies (usually non-airfoil)
– Transmission lines (mostly with
ice accretion)
– Cable affected by vortex
shedding of another cable
19

20. Dynamic aeroelasticity: stall flutter
• Airfoil and non-airfoil
structures
• Periodic (partial or complete)
flow separation from the
airfoil during the oscillation
• Nonlinear aerodynamic
reaction to the motion of the
structure
– Suspension bridges
– Helicopter rotors (rotorcraft
blades)
– Turbomachinery blades
• Free vortices are generated in the
vicinity of the separation points
• The periodic vortex shedding
creates regions of reduced and
even reversed velocity in the
vicinity of the airfoil
20

21. Dynamic aeroelasticity: “whirl mode” flutter
• Two Lockheed L-188 “Electra”,
– Braniff Flight 542
• September 29, 1959
• near Buffalo, TX
• 34 fatalities
– NW Orient Airlines Flight 710
• March 17, 1960
• near Cannelton, IN
• 63 fatalities
• disintegrated during flight
– wing brake-up
21
Actual aircraft before crash (stinsonflyer.com)
• In both cases,
– No survivors
– Inconclusive investigations

22. “Whirl mode” flutter (a new investigation at NASA Langley)
• Wind tunnel tests of an Electra 1/8-
scale model showed:
– Overly stiff wing
– Outboard nacelles responding
differently than intended
– Flutter “passes on” from nacelle to
(even a “flutter-free”) wing
• Growing flutter magnitude
decreased the oscillation
frequency from 5 to 3 Hz
• Wing frequency was also 3 Hz
– Harmonic coupling
22
YouTube channel: NASA Langley CRGIS
Flutter Tests of the Full Span Lockheed Electra

23. Dynamic aeroelasticity: “whirl mode” flutter (a new investigation)
23
• According to the crash report,

24. Dynamic aeroelasticity: (aeroelastic) flutter
• Bending/torsion coupled motion
• Self-sustained unstable motion
• Antonov An-148
– March 5, 2011 (test flight)
– near Garbuzovo (350 mi south
of Moscow), Russia
• Airspeed indicator failed
(showing lower airspeed)
• Pilots accelerated 70 mi/h
above the design limit speed
• Low-frequency vibrations
created
• In-flight wing break-up
24

25. Dynamic aeroelasticity: non-airfoil flutter
• Bending/torsion coupled motion
• Self-sustained unstable motion
• Tacoma Narrows Bridge
– Opened to traffic on July 1, 1940
– Collapsed on November 7, 1940
– Stationary wind design limit: 160 km/h
– Wind speed before failure: 60 km/h
25

26. Aeroelastic flutter
• Under airflow excitation, structures
may exhibit aeroelastic oscillations
– due to interactions of
aerodynamic, elastic and inertial
forces
• At a critical airflow speed, lifting
surfaces undergo self-sustained
oscillations (linear flutter speed)
– Flutter: bending/torsion coupled
motion with growing amplitudes
• Potentially catastrophic
26

27. Aeroelastic and vibration control
• Allows flight vehicles to operate
beyond the traditional flutter
boundaries
• Improves ride qualities
• Minimizes vibration fatigue
damage
27
(Giurgiutiu 2000, JIMSS v. 11; Nitzsche et al 2015, JIMSS)
Controlled
Uncontrolled
Grows until the
structure fails

28. Conventional passive aeroelastic control / flutter prevention
• There is no universal solution
• Frequent strategies
– add mass or redistribute mass
(‘mass balance’)
– increase torsional stiffness, i.e.,
increase ωα
– increase (or decrease) ωh/ωα if it
is near one (for fixed ωα)
– add damping to the structure
(hydraulic dampers)
– require the aircraft to be flown
below its critical Mach number
• Penalties
– Extra weight
– Non-optimized operation
28
(Dowell et al. 2015, A Modern Course in Aeroelasticity, p. 118)

29. Conventional active aeroelastic control
• Aerodynamic control surfaces
operated by servo-hydraulic
actuators
• Penalties/limitations
– Multiple energy conversions
(mechanical, hydraulic, electrical)
– Large number of parts
• Potential failure sites
• Extra weight
– High vulnerability of the hydraulic
pipes network
– Limited frequency bandwidth
29
(Giurgiutiu 2000, JIMSS v. 11)

30. Smart materials as an alternative (e.g., piezo actuators)
• Direct conversion of electrical
energy to high-frequency linear
motion (mechanical energy)
• Electrical energy is easier to
transmit throughout the aircraft
(electric lines are much less
vulnerable than hydraulic pipes)
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(Giurgiutiu 2000, JIMSS v. 11)
(reverse piezoelectric effect)

31. An example
31
• Active control flap for noise and
vibration reduction
• Piezo-stack actuators
(Straub and King 1996)

32. Smart materials (piezos)
• Advantages
– Can be embedded in the
structure (e.g. on-blade
actuation)
– High energy/mass ratio
– Direct piezoelectric effect can
also be exploited
• Passive and active strategies
• Sensing and actuation
• Energy harvesting
• Disadvantages
– Piezos (reverse effect)
• Very small strokes (e.g. 0.1%)
• Requires displacement
amplification mechanisms
32

33. Fixed wing aircraft studies
• Heeg 1993 (NASA Langley)
– Piezoelectric actuators
– Flutter suppression of a rigid
wing supported by springs
– +20% flutter speed
• McGowan et al. 1998
– 12% decrease flutter dynamic
pressure
– 75% decrease gust bending
moment
33

34. A rotating-wing application of smart materials
• Feszty and Nitzsche 2011
– Carleton University, Canada
• Stiffness modulation using
piezoelectric actuators for vibration
control in helicopters
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(flight tested)
Nitzsche et al
2015, JIMSS

35. Flutter can be exploited for wind energy harvesting
• Vibrations in a general sense
can be exploited for energy
harvesting
– Direct piezoelectric effect
• Flutter oscillations can provide a
useful additional source of small
amounts of electrical power
– e.g., for embedded Structural
Health Monitoring systems
– Airfoil-based generators
35

36. An example
• The RC glider was modified to
include:
– two piezoelectric patches
placed at the roots of the wings
• to harvest energy from wing
vibrations
– a cantilevered piezoelectric
beam installed in the fuselage
• to harvest energy from rigid
body motions of the aircraft
36
(SR Anton and DJ Inman, 2008)

37. An airfoil model for flutter investigations
37
(Mozaffari-Jovin et al 2015, JVC)
2D problem

38. How we investigate flutter in our lab
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• 2-DOF (or 3-DOF)
– Plunge (h)
– Pitch (α)
– (Control surface position, β)
• U∞ is the airflow speed

39. Experimental 2-DOF airfoil model
39
Pitch DOF
wire springPlunge DOF
springs (2/4)

40. Numerical results and experimental tests
• Linear case, U = 12 m/s • Nonlinear case (freeplay in the
pitch DOF), U = 10 m/s
40
Continuous lines: experimental, dashed lines: simulation
Linear: Erturk et al. (2010), Appl. Phys. Lett. 96(18)
Nonlinear: Sousa et al. (2011), Smart Mater. Struct. 20(9)

41. Possibilities of study for an smart airfoil/flutter model
• Aeroelastic control
– Classical aeroelasticity
• Structural reinforcement
• Mass tuning
– “Smart” materials
• Sensing and actuation
– Piezoelectric materials
– Shape memory materials
• Energy Harvesting
• Aeroelastic control + Energy
Harvesting
• Smart materials
• Piezoceramics
(electromechanical coupling)
– Active control (actuation)
– Passive (shunt damping)
– Hybrid
– Energy Harvesting
• SMAs
– Passive control (high loss factor,
hysteretic damping)
– Active control (stiffness and
frequency variation)
41

42. SMA elements can be included in the airfoil model
(my current work)
42
k
• Motivation:
– Modify the aeroelastic
behavior of the airfoil by
exploiting the pseudoelastic
hysteresis of SMAs
SMA
behavior

43. Preliminary results: aeroelastic behavior with SMA springs
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44. An intermediate case is presented,
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 1
0 3 N e 11.6 m·sf U 
 

45. Thank you!
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Special thanks to:
The University of Toledo and MIME Department, Toledo – OH/USA
Dynamic and Smart Systems Lab (smartsys.eng.utoledo.edu)