airfoil separation control with plasma actuators - digital...

Airfoil Separation Control with Plasma Actuators

By

Shawn Fleming

Bachelor of Science in Mechanical EngineeringOklahoma State University

Stillwater, OK, USA2008

Submitted to the Faculty of theGraduate College of

Oklahoma State Universityin partial fulfillment ofthe requirements for

the Degree ofMASTER OF SCIENCE

May, 2010

Airfoil Separation Control with Plasma Actuators

Thesis Approved:

Dr. Jamey Jacob

Thesis Advisor

Dr. Andrew Arena

Dr. David Lilley

Dr. A. Gordon Emslie

Dean of the Graduate College

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TABLE OF CONTENTS

Chapter Page

1 INTRODUCTION 1

1.1 Importance of Problem . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.2 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.3 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.4 Thesis Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2 Previous Work 7

2.1 Low Speed Airfoils . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.2 Boundary layer Characterization . . . . . . . . . . . . . . . . . . . . . 12

2.3 Active Flow Control . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

2.4 Plasma Actuator Flow Control . . . . . . . . . . . . . . . . . . . . . . 16

3 Experimental Set-Up 29

3.1 Plasma Actuators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

3.2 PIV Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

3.3 Bench-Top Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

3.4 Wind Tunnel Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

4 Results 39

4.1 Actuator Development . . . . . . . . . . . . . . . . . . . . . . . . . . 39

4.2 X-Foil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

4.3 Wind Tunnel Flow Control Tests . . . . . . . . . . . . . . . . . . . . 57

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5 Discussion and Conclusions 102

5.1 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

5.2 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108

5.3 Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

A High Re Testing 114

A.1 Wind Tunnel Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114

A.2 Subsonic Wind Tunnel Results: La203a Performance . . . . . . . . . 121

B Input File and MATLAB Codes 125

B.1 WaLPT Algorithm Input File . . . . . . . . . . . . . . . . . . . . . . 125

B.2 MATLAB Codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126

B.2.1 Mask Generation Code . . . . . . . . . . . . . . . . . . . . . . 126

B.2.2 PIV Post-Processing . . . . . . . . . . . . . . . . . . . . . . . 128

BIBLIOGRAPHY 157

iv

LIST OF FIGURES

Figure Page

1.1 Progression of Stall Across an Airfoil [24] . . . . . . . . . . . . . . . . 2

2.1 Flight Reynolds-number Spectrum [21] . . . . . . . . . . . . . . . . . 8

2.2 Low-Reynolds-number airfoil performance [21] . . . . . . . . . . . . . 10

2.3 Laminar Separation Bubble Geometry [21] . . . . . . . . . . . . . . . 11

2.4 Overall Categorization of Flow Control Approaches [7] . . . . . . . . 14

2.5 Passive and Active Flow Control Devices . . . . . . . . . . . . . . . . 14

2.6 Schematic of the Typical Plasma Actuator . . . . . . . . . . . . . . . 16

3.1 Teflon Plasma Actuator with 1/2 inch Copper Electrodes . . . . . . . 30

3.2 Acrylic Plasma Actuator with 1/2 inch Copper Electrodes . . . . . . 30

3.3 Alumina Plate Plasma Actuator with 1/2 inch Copper Electrodes . . 31

3.4 LabView Block Diagram for 1 Channel Output . . . . . . . . . . . . . 32

3.5 LabView Block Diagram for 2 Channel Output . . . . . . . . . . . . . 32

3.6 Schematic of PIV Setup . . . . . . . . . . . . . . . . . . . . . . . . . 34

3.7 Schematic of bench-top Setup . . . . . . . . . . . . . . . . . . . . . . 35

3.8 Liebeck La203a CAD Model . . . . . . . . . . . . . . . . . . . . . . . 37

3.9 Liebeck La203a Airfoil . . . . . . . . . . . . . . . . . . . . . . . . . . 38

3.10 Wind Tunnel of Setup . . . . . . . . . . . . . . . . . . . . . . . . . . 38

4.1 Plasma Actuator Parameters . . . . . . . . . . . . . . . . . . . . . . . 40

4.2 Plasma Actuator Benchmarking: Varying Frequency (Teflon with 1/4

in. Copper Electrodes) . . . . . . . . . . . . . . . . . . . . . . . . . . 42

v

4.3 Plasma Actuator Benchmarking: Varying Modulation Frequency (Teflon

with 1/4 in. Copper Electrodes) . . . . . . . . . . . . . . . . . . . . . 42

4.4 Velocity Vectors for Teflon with 1/4 in. Copper Electrodes . . . . . . 43

4.5 Vorticity for Teflon with 1/4 in. Copper Electrodes . . . . . . . . . . 43

4.6 Velocity Profile for Teflon with 1/4 in. Copper Electrodes . . . . . . . 44

4.7 Plasma Actuator Benchmarking: Varying peak-to-peak Voltage (Acrylic

with 1/2 in. Copper Electrodes) . . . . . . . . . . . . . . . . . . . . . 46

4.8 Plasma Actuator Benchmarking: Varying Frequency (Acrylic with 1/2


4.9 Velocity Vectors for Acrylic with 1/2 in. Copper Electrodes . . . . . . 47

4.10 Vorticity for Acrylic with 1/2 in. Copper Electrodes . . . . . . . . . . 47

4.11 Velocity Profile for Acrylic with 1/2 in. Copper Electrodes . . . . . . 48

4.12 Plasma Actuator Benchmarking: Varying Frequency (Alumina with

1/2 in. Copper Electrodes) . . . . . . . . . . . . . . . . . . . . . . . . 50

4.13 Velocity Vectors for Alumina with 1/2 in. Copper Electrodes . . . . . 50

4.14 Vorticity for Alumina with 1/2 in. Copper Electrodes . . . . . . . . . 51

4.15 Velocity Profile for Alumina with 1/2 in. Copper Electrodes . . . . . 51

4.16 Plasma Actuator Benchmarking: Varying Frequency (Teflon with 1/2


4.17 Maximum Velocity Comparison for each Dielectric . . . . . . . . . . 53

4.18 XFoil Separation Point Tracking Reynold’s Number of 100,000 at an

Angle of Attack of 10 Degrees . . . . . . . . . . . . . . . . . . . . . . 55

4.19 XFoil Separation Point Tracking Reynold’s Number of 650,000 at an

Angle of Attack of 10 Degrees . . . . . . . . . . . . . . . . . . . . . . 55

4.20 XFoil Separation Point Tracking . . . . . . . . . . . . . . . . . . . . . 56

4.21 Wind Tunnel Plasma Actuator Test Matrix . . . . . . . . . . . . . . 58

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4.22 Actuators Off (a) Flow Field Velocity Vectors, (b) Flow Field Vorticity,

(c) Flow Field Urms, (d) Flow Field TKE . . . . . . . . . . . . . . . 61

4.23 Actuators Off Reverse Flow Probability within the Flow Field . . . . 61

4.24 Leading Edge Actuator, Constant Activation (a) Flow Field Velocity

Vectors, (b) Flow Field Vorticity . . . . . . . . . . . . . . . . . . . . 62

4.25 Leading Edge Actuator, Constant Activation Reverse Flow Probability

within the Flow Field . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

4.26 Leading edge Actuator, Pulsed Activation with an F+ = 1 (a) Flow

Field Velocity Vectors, (b) Flow Field Vorticity, (c) Flow Field Urms,

(d) Flow Field TKE . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

4.27 Leading edge Actuator, Pulsed Activation with an F+ = 1 Reverse

Flow Probability within the Flow Field . . . . . . . . . . . . . . . . . 64

4.28 Aft Actuator, Constant Activation (a) Flow Field Velocity Vectors, (b)

Flow Field Vorticity, (c) Flow Field Urms, (d) Flow Field TKE . . . 65

4.29 Aft Actuator, Constant Activation Reverse Flow Probability within

the Flow Field . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

4.30 Aft Actuator, Pulsed Activation with an F+ = 1 (a) Flow Field Ve-

locity Vectors, (b) Flow Field Vorticity . . . . . . . . . . . . . . . . . 66

4.31 Aft Actuator, Pulsed Activation with an F+ = 1 Reverse Flow Prob-

ability within the Flow Field . . . . . . . . . . . . . . . . . . . . . . . 67

4.32 Steady Activation on the LE and Aft Actuators (a) Flow Field Velocity

Vectors, (b) Flow Field Vorticity, (c) Flow Field Urms, (d) Flow Field

TKE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

4.33 Steady Activation on the LE and Aft Actuators Reverse Flow Proba-

bility within the Flow Field . . . . . . . . . . . . . . . . . . . . . . . 69

4.34 Pulsed Activation with an F+ = 1 on the LE and Aft Actuators (a)

Flow Field Velocity Vectors, (b) Flow Field Vorticity . . . . . . . . . 69

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4.35 Pulsed Activation with an F+ = 1 on the LE and Aft Actuators Re-

verse Flow Probability within the Flow Field . . . . . . . . . . . . . . 70

4.36 Out-of-Phase, Pulsed Activation with an F+ = 1 on the LE and Aft

Actuators (a) Flow Field Velocity Vectors, (b) Flow Field Vorticity . 70

4.37 Out-of-Phase, Pulsed Activation with an F+ = 1 on the LE and Aft

Actuators Reverse Flow Probability within the Flow Field . . . . . . 71

4.38 Velocity Profiles for 50,000 Reynolds Number Cases: Solid Black, No

Control; Solid red, LE Steady; Dashed Red, LE Pulsed F+ = 1; Solid

Blue, Aft Steady; Dashed Blue, Aft Pulsed F+ = 1; Solid Green, Both

Steady; Dashed Green, Both Pulsed F+ = 1 in-phase . . . . . . . . . 73

4.39 Velocity Profile Comparison of In-Phase and Out-of-Phase Actuator

Activation at 50,000 Reynolds Number: Solid Black, No Control; Solid

Red, Both Pulsed F+ = 1 in-phasae; Solid Blue, Both Pulsed F+ = 1

out-of-phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74




4.42 Leading edge Actuator, Constant Activation (a) Flow Field Velocity


TKE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

4.43 Leading edge Actuator, Constant Activation Reverse Flow Probability



Field Velocity Vectors, (b) Flow Field Vorticity . . . . . . . . . . . . 79



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4.46 Leading edge Actuator, Pulsed Activation with F+ = 0.198 (a) Flow


4.47 Leading edge Actuator, Pulsed Activation with F+ = 0.198 Reverse





Flow Probability within the Flow Field . . . . . . . . . . . . . . . . 82





4.52 Pulsed Activation on the LE and Aft Actuators with F+ = 0.198 (a)

Flow Field Velocity Vectors, (b) Flow Field Vorticity, (c) Flow Field

Urms, (d) Flow Field TKE . . . . . . . . . . . . . . . . . . . . . . . 84

4.53 Pulsed Activation on the LE and Aft Actuators with F+ = 0.198

Reverse Flow Probability within the Flow Field . . . . . . . . . . . . 85






Control; Solid Red, LE Steady; Dashed Red, LE Pulsed F+ = 1; Dash-

Dot Red, LE Pulsed F+ = 0.198; Dotted Red, LE Pulsed F+ = 0.297;

Solid Blue, Both Steady; Dashed Blue, Both Pulsed F+ = 0.198; Dash-

Dot Blue, Both Pulsed F+ = 0.297 . . . . . . . . . . . . . . . . . . . 88

ix




4.59 Leading edge Actuator, Constant Activation (a) Flow Field Velocity


TKE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

4.60 Leading edge Actuator, Constant Activation Reverse Flow Probability













Flow Probability within the Flow Field . . . . . . . . . . . . . . . . 95







x




Flow Field Velocity Vectors, (b) Flow Field Vorticity, (c) Flow Field

Urms, (d) Flow Field TKE . . . . . . . . . . . . . . . . . . . . . . . . 98




Control; Solid Red, LE Steady; Dashed Red, LE Pulsed F+ = 1; Dash-

Dot Red, LE Pulsed F+ = 0.148; Dotted Red, LE Pulsed F+ = 0.222;

Solid Blue, Both Steady; Dashed Blue, Both Pulsed F+ = 0.148; Dash-

Dot Blue, Both Pulsed F+ = 0.222 . . . . . . . . . . . . . . . . . . . 101

5.1 δ∗ and θ Vs. x/c for 50,000 Reynolds Number, Actuators Off . . . . . 104

5.2 δ∗ and θ Vs. x/c for 50,000 Reynolds Number, Aft Actuator, Constant

Activation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104

5.3 δ∗ and θ Vs. x/c for 50,000 Reynolds Number, Leading Edge Actuator,

Constant Activation . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

5.4 δ∗ and θ Vs. x/c for 75,000 Reynolds Number, Constant Activation on

the LE and Aft Actuators . . . . . . . . . . . . . . . . . . . . . . . . 106

5.5 δ∗ and θ Vs. x/c for 100,000 Reynolds Number, Pulsed Activation on

the LE and Aft Actuators with F+ = 0.222 . . . . . . . . . . . . . . . 107

5.6 F+ Vs. Reynold Number for Pulsed Activation Tests . . . . . . . . . 111

A.1 La203a Large Wind Tunnel Wing CAD Model . . . . . . . . . . . . . 115

A.2 La203a Large Wind Tunnel Wing . . . . . . . . . . . . . . . . . . . . 116

A.3 OSU Large Low-Speed Wind Tunnel . . . . . . . . . . . . . . . . . . 118

xi

A.4 OSU Wind Tunnel Test Section with Lift/Drag Balances and Pitot-

Static Tube for Wake Surveys . . . . . . . . . . . . . . . . . . . . . . 118

A.5 OSU Wind Tunnel Test Section with Lift/Drag Balances and Pitot-

Static Tube for Horizontal Sweeps . . . . . . . . . . . . . . . . . . . . 119

A.6 Manometer Bank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120

A.7 La203a Airfoil Performance Curves (taken from Liebeck [10]) . . . . . 122

A.8 La203a Experimental Coefficient of Pressure Data for Different Angles

of Attack Ranging from -6 degrees to 16 Degrees . . . . . . . . . . . . 122

A.9 Experimental, Computational, and Reference for the Lift Curve of a

La203a Airfoil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123

A.10 Comparison of the Multiple Lift Curves at Several Different Reynold’s

Number . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123

xii

CHAPTER 1

INTRODUCTION

1.1 Importance of Problem

The main purpose of wings on aircraft is to produce lift. Wings produce lift by

changing their angle of attack, but there is a point when that angle of attack becomes

too large for the wing to continue to produce lift. At that time the air flow over the

top of the wing starts to separate and become detached from the suction side of the

wing. This angle of attack that causes separation over the entire top surface of the

wing is called the stall angle or αstall. Generic stall pattern to general wing platforms

is a much easier thing to discuss. Certain stall patterns can make it easier for a pilot

to recover from a stall. Straight wings tend to stall from the centerline outward, while

highly tapered wings tend to stall from the tips inward. When the stall starts at the

inboard section of the straight wings, it generates less downwash on the tail, allowing

for an easier nose down behavior. Also when the stall starts at the inboard side of

the ailerons the pilot has better ability to maintain roll control. When the stall starts

at the outboard part of the wing during a turn, one wing is moving faster than the

other. The wing stalls in the direction of the slower wing and will “fall out” of the

turn in that direction. The plane then enters a spin and the pilot has to recover from

a stall and a spin.

So the real question is “What makes an airfoil stall?” At αstall the flow detaches

from the upper surface of the airfoil. The pressure in this separated region can no

longer maintain suction, which leads to a loss in lift. The lower surface of an airfoil

will not stall because the free stream flow is along the lower length of the airfoil

1

because it has a favorable pressure gradient. At the point of separation, there is a

loss in lift and an increase in drag. There is also a change in momentum due to the

loss in suction along the top surface. The progression of stall, as an airfoil is taken to

higher angles of attack, can be seen in Fig. 1.1[24]. A favorable pressure gradient is

where there is a decreased pressure in the direction of the flow, allowing the flow to

accelerate. An adverse pressure gradient is an increase in pressure against the flow

direction, making the flow decelerate.

Figure 1.1: Progression of Stall Across an Airfoil [24]

In general stall characteristics for an airfoil can be characterized in part by the

leading edge (LE) radius and the thickness of the airfoil. An airfoil is considered

“fat” if it has a rounded LE and a thick cross-section (t/c > 14%). “Fat” airfoils stall

gently from the trailing edge (TE) and stall progresses forward. The moment changes

slightly forward on a “fat” airfoil due to a loss in lift at the TE promoting a nose

down behavior. A “moderate” airfoil has a thinner thickness (6% < t/c < 14%) and

unlike a “fat” airfoil, a “moderate” airfoil stalls abruptly from the LE. Moderately

thick airfoils create a separation bubble at the LE. The bubble reattaches and then

collapses. This collapse is what marks the stall of a “moderate” airfoil. Stall happens

suddenly and over the entire upper surface of the airfoil. There is a large shift in

moment for a “moderate” airfoil leading to a large nose down behavior. A “thin”

airfoil has a thickness less than that of the other two types of airfoils (t/c < 6%)

and sharp LE. The “thin” airfoil generates a separation bubble near the LE then

reattaches and grows toward the TE. The moment shifts slightly for a “thin” airfoil

2

and causes a moderate nose down behavior.

Now if we consider a wing the same question still applies, “What makes a wing

stall?” The cause is still much the same. The wing stalls when a significant portion

of airfoil sections stalls, where each wing section is just an airfoil. CLMaxfor the wing

is not achieved until almost all of the wing is stalled. Once the wing has reached its

CLMaxmost of the sections are well past their cLMax

for sections, CLMax. At this point

the wing has started to lose lift.

Stall is inevitable when trying to max out lift. Part of the problem is that once

a wing stalls, there is a large decrease in lift, a large increase in drag. This decrease

in lift, and increase in drag lowers the L/D ratio of the wing and the aircraft as a

whole. The problem is how can we increase the operational range of airfoils so that

we can take wings to higher angles of attack before the flow separates from the upper

surface?

In this thesis, we performed a series of experiments where we looked at using

plasma actuators to add energy into a fluid flow for the purpose of reattaching flow in

a separated region on a highly cambered wing. Several different dielectrics were tested

on a set of bench-top tests to show how different dielectric materials can produce

higher or lower velocity plasma jets. The materials used were Teflon, acrylic, and

alumina plate. Two different widths of copper tape were examined when testing the

Teflon dielectric to see if there was a difference in plasma jet velocities between the

two different size electrodes. The plasma actuators were configured in such a way

that two electrodes were placed on either side of a dielectric material with a small

gap between one edge of one electrode and another edge of the second electrode.

One electrode was exposed to air. The other was placed on the opposite side of the

dielectric so that it was not exposed to air.

3

1.2 Objective

In certain situations it is desirable to increase your coefficient of lift or alleviate drag

by controlling separation on an airfoil. In this work, plasma actuators were used to

control the separation of an airfoil at high angles of attack. The purpose of this thesis

was to examine the use of various configurations of single dielectric barrier discharge

(SDBD) or plasma actuators for control of stall on low speed airfoils. A plasma

actuator consists of two electrodes separated by a dielectric medium, one exposed

on the top surface of the dielectric material and one embedded on the underside of

the dielectric material, and a high voltage low current signal input to the electrodes.

The dielectric materials used in this investigation were: Teflon, acrylic and alumina.

The electrodes were a 1/2 inch and 1/4 inch copper tape. There were two objectives

examined in this investigation. The first objective was to examine how different

geometries effect each of the three different dielectrics in bench-top testing. These

results were implemented in further wind tunnel testing. The second objective was to

demonstrate separation control on an airfoil in a wind tunnel at a high angle of attack

using a plasma actuator near the LE of the airfoil and another actuator located near

the mid-chord to reattach a separated flow. Various configurations were tried during

this portion of the investigation: One with just the LE actuator on; one with the

downstream actuator on; and then with both actuators on, both synchronously and

asynchronously. These three configuration were looked at for an input signal giving

a steady plasma activation and a pulsed plasma activation. For the pulsed activation

a variety of frequencies were examined.

1.3 Methodology

Several parameters were used to determine how each of the dielectrics would behave,

parameters such as operating frequency, modulation frequency, and max peak-to-

4

peak voltage. An optimum frequency was found by stepping the frequency up from

3,000 Hz to 15,000 Hz and keeping the duty cycle at 100% to maintain a plasma jet

in steady operation. The modulation frequency and peak-to-peak voltage were held

constant. The measurements to determine velocity were performed using particle

image velocimetry (PIV). Once a maximum velocity was obtained by varying the

operating frequency, the modulation frequency was varied and the duty cycle was

then held constant at 50%. The modulation frequency was varied from 5 Hz to

1,000 Hz while holding the operating frequency at 15,000 Hz, and the peak-to-peak

voltage constant. The maximum velocity was again found using PIV to determine the

optimum modulating frequency. The last parameter investigated was the maximum

peak-to-peak voltage for a given material. Once the best parameters were found

using one material, the same procedure was used to determine the optimum operating

frequency and the maximum peak-to-peak voltages for the other two materials.

Using the results from the bench-top test, we ran a series of experiments in a

wind tunnel to see how the plasma actuators performed in a freestream flow. First

the stall angle of attack was determined. The test wing was positioned at an angle of

attack of 22 degrees, and a Reynolds number of 50,000, 75,000, 100,000 and 150,000.

Two plasma actuators were attached to the upper surface of the airfoil, one near the

leading edge and another at the 40% chord. These actuators were controlled much in

the same fashion as the bench-top tests. The wind tunnel experiments were run both

in a steady state, or with the duty cycle at 100%, and unsteady or pulsed state, with

the duty cycle at 50%. The plasma frequency was held constant at 10,000 Hz and

for the steady activation the duty cycle was held at 100%. During the steady state

activation, one run was performed with the rear actuator on but the front actuator off.

Then a second run was performed with the front actuator on and the rear actuator

off. A third run was performed in steady state with both actuators on at the same

time. Several runs were performed in an pulsed activation with both actuators on at

5

a phase angle of 0 degrees and 180 degrees. During the pulsed activation the duty

cycle was set to 50% and a variety of modulation frequencies.

1.4 Thesis Outline

This thesis is arranged as follows. In Chapter 2 an investigation was also done on

the previous work that has been done with plasma actuators for aerodynamic uses.

Chapter 3 goes into depth of how the apparatus and diagnostic experiments were

setup and performed throughout this investigation using plasma actuators to control

separation on an airfoil. Chapter 4 shows the results for all of the bench-top, com-

putational, and wind tunnel tests performed. Chapter 5 discusses the conclusions

reached and a short discussion on what other future work should be investigated.

6

CHAPTER 2

Previous Work

In Chapter 2 an investigation was also performed on previous work that has been done

with plasma actuators for aerodynamic uses. Research in Low speed airfoils was done

to provide knowledge on what to expect from the wind tunnel tests performed at lower

Reynolds numbers. Boundary layer characteristics were examined here to provide an

incite on how flow behaves along a given surface. Research was then preformed to

investigate the different methods of flow control and how these control methods are

used. Further literature review was done to examine the different approaches to the

method of flow control that is described within this thesis.

2.1 Low Speed Airfoils

There are a wide range of Reynolds numbers that todays airfoils operate in, this

range can be seen in Fig. 2.1[21]. A particularly interesting area of flight is the low

Reynolds number flight regime. Lissaman [21] discusses this particular flight region

extensively. The choice of the right airfoils for a particular mission has always seemed

to be a bit mystical, but there has always been prerequisites for choosing an airfoil,

that has satisfactory performance across the flight envelope. The shape of airfoils

is very important, and the teardrop or paisley motif-like shapes have a universal

aesthetic appeal. There is an ideal shape for an airfoil. It depends on the size and

speed of the wing. This dependence is called the “scale effect”.

The scale effect was first observed in the 30s. It was seen that the excellent

qualities of an insect or bird wing doesn’t scale up when you try to use the same

7

Figure 2.1: Flight Reynolds-number Spectrum [21]

shape for an airplane wing and vise versa. This all goes back to the fact that an

airfoil is designed dependent on the size and speed at which the wing is traveling,

so a different size leads to a different shape. Lissaman states, “This scale effect is

characterized by the chord Reynolds number, R, defined by R = V c/ν, where V

is the flight speed, c is the chord, and ν is the kinematic viscosity of the fluid in

which the airfoil is operating.” This Reynolds number is of importance because it

quantifies two important effects to airfoil behavior, internal (fluid momentum) and

viscous (fluid stickiness) effects. The viscous effect tends to have more effect on

airfoil behavior because it determines how much drag and the maximum lift an airfoil

is capable of producing. Lift and drag are usually described in a non-dimensional

coefficient form CL and CD respectively. Lift and drag coefficients are defined as

L/qc and D/qc, respectively, where L is lift per unit span and D is the drag per unit

span, q is the dynamic pressure of the fluid (with the dynamic pressure q = 1/2ρV 2,

ρ is the density of the fluid), and c is the chord. CL and CD are both dependent on

the Reynolds number and the angle of attack at which the airfoil is operating.

Lately the development of small flying vehicles has brought us into the low Reynolds

number flight regime. Being at Reynolds number of half a million and below leads

8

to the need for a new low Reynolds number airfoil that was previously not needed.

The operating range for such an airfoil is usually between sea level and 30 km. Usu-

ally the function of an airfoil is to produce lift that is perpendicular to the flight

direction. Drag is the bi-product connected to the force needed to propel the lifting

surface. A parameter is used to describe the effectiveness of an airfoil. This param-

eter is the lift-to-drag ratio CL/CD, where CL/CD|max is a measure of the airfoil’s

max performance. Designing airfoil to have a CL/CD|max that occurs at a high CL,

this minimizes the size of the lifting surface. While operating at the lower Reynolds

numbers, viscous effects are large and result in a high drag and limit the max lift that

can be produced. But at higher Reynolds numbers, CL/CD improves, and the viscous

effects have less of an impact on airfoil performance. There is a Reynolds number,

where the performance of the airfoil changes. The critical Reynolds number is about

70,000. Smooth airfoils have the greatest benefit from the critical Reynolds number

while rough turbulated airfoils do not gain the same performance increase.

At the low Reynolds numbers rough airfoils actually benefit from the surface

discontinuities. These surface discontinuities actually promote attachment. Smooth

airfoils do not have the same benefit that the rough ones do in this low Reynolds

numbers flows. As the Reynolds number increases, the smoothness of the airfoil

begins to become more important. This is apparent by examining Fig. 2.2[21].

While discussing the fundamental fluid mechanics, Lissaman states, “All airfoils

have region of lower-than-static pressure”. For most airfoils, this lower-than-static re-

gion is on the suction surface. For a symmetrical non-lifting airfoil that does not have

this types of suction surface the thickness alone induces a lower pressure and acceler-

ates the flow over the airfoil. Once the flow has moved past this low pressure region

it must slow down to about freestream velocity at the TE. This slow down region

is called an adverse pressure gradient or pressure recovery region. In low Reynolds

number flows the boundary layer maybe be laminar and attached, but might not be

9

Figure 2.2: Low-Reynolds-number airfoil performance [21]

able to handle an adverse pressure gradient, therefore laminar flow has a tendency to

have poor separation resistance. Often times when a laminar flow separates there is

a rapid transition to a turbulent flow. In a turbulent flow, the increased entrainment

leads to the reattachment of the separated flow as a turbulent boundary layer. This

detachment of the laminar boundary layer and reattachment as a turbulent boundary

layer is called a laminar separation bubble. The structure of a laminar separation

bubble can be see in Fig. 2.3[21]. When a laminar separation bubble forms, the flow

separates from the surface at a near constant separation angle. At this point the

transition occurs and the turbulence starts to develop. If the entrainment due to

the turbulent flow is strong enough the flow will reattach to the surface and a the

turbulent boundary layer rearranges itself to a normal turbulent profile.

At Reynolds numbers greater than Rec, reattachment can occur creating a lam-

inar separation bubble. During this occurrence, it is the airfoil characteristics that

determine the type of laminar bubble. The bubble that is formed can be either long

or short. At Reynolds numbers around 100,000, long bubbles can exist and tend

10

Figure 2.3: Laminar Separation Bubble Geometry [21]

to extend over about 20-30% of the airfoil’s lifting surface. With this much of the

lifting surface being covered with a laminar bubble, it greatly changes the pressure

distribution over the surface, basically changing the airfoil’s shape and performance.

At Reynolds numbers greater than 100,000, short laminar bubbles tend to form in-

stead of long laminar bubbles. A short bubble’s length is usually only a few percent

and therefore does not tend to change the pressure distribution. The short laminar

bubble usually represents the “transition-forcing mechanism”. As the angle of attack

is increased, the airfoil requires a much greater pressure recovery. Because of the

need for greater pressure recovery, a short bubble can “burst”, and at this point the

short bubble becomes a long one. A sudden stall results from the severe loss in airfoil

performance.

At Reynolds numbers of about 200,000, the laminar bubble can be avoided. Avoid-

ing the laminar bubble is possible because the transition point happens far enough

upstream from the adverse pressure gradient that the bubble is avoided. The tran-

sition actually occurs in a turbulent boundary layer that can withstand the adverse

11

pressure gradient. When Reynolds numbers approach the 500,000 range airfoil per-

formance improves even more. The laminar separation bubble is not solely linked to

the chord-wise Reynolds number, but is also influenced by the local boundary layer

Reynolds number. This local boundary layer Reynolds number is associated with the

region where the pressure recovery starts. However, if an adverse pressure gradient

is severe enough and close enough to the leading edge, a bubble like characteristic

can still be seen. These occurrences can even happen at Reynolds numbers of a few

million. This is usually the case with a thin, small nose radius airfoil.

2.2 Boundary layer Characterization

Boundary layers are characterized by several parameters, including boundary layer

thickness, δ, displacement thickness, δ∗, momentum thickness, θ, and shape factor H.

According to Munson [25], “δ∗ represents the outward displacement of the streamlines

caused by the viscous effects on the plate.” The momentum thickness is the height

of the freestream flow needed to compensate for lack of momentum flux inside the

boundary layer because of the shear force near the surface. The shape factor is used

to determine what type of flow you are in. These parameters are defined as such:

δ∗ =∫ h

0

(1− u

Ue

)dy (2.1)

θ =∫ h

0

u

Ue

(1− u

Ue

)dy (2.2)

H =δ∗

θ(2.3)

where u is the stream-wise velocity, Ue is the freestream velocity, y is the height

above the surface, and h is a large distance away from the surface. The thickness of

a laminar boundary layer is predicted by theory as:

12

δ

x=

5.0√Rex

(2.4)

where x is the distance from the leading edge and Rex = Uex/ν. So it is seen that δ

is proportional to√x.

2.3 Active Flow Control

Flow control can be considered anything that is done to alter the flow to a more

desirable behavior. The flow is often altered by the addition of mass, momentum,

energy, vorticity, or even actively changing the shape of the surface the flow is moving

over. Flow control can be broken up into two different types: active or passive, based

on weather the mechanism is actively adding energy to the flow or not. The difference

between these two classifications depends on several factors: whether energy is added,

whether the flow control is a steady control or unsteady, or if the system can be

modified after it is built. Active flow control can be either steady or unsteady but

some form of external energy source, whether it is electrical or mechanical, is needed

to operate the device. On the contrary, passive flow control requires no external

energy added. An overall view of flow control can be seen in Fig. 2.4[7]. Fig. 2.5 is

a further classification of flow control broken up into the types of devices that would

be found under each of the two flow control categories.

According to Gad-el-Hak [3], passive devices do not need the addition of external

energy to work but they often come with an associated penalty to the amount of drag

they produce. The drag increase is caused because passive devices often trip the flow

intentionally allowing for a transition between laminar flow (LF) to turbulent flow.

The aim of passive devices is to make this transition in flow upstream of the natural

laminar flow (NLF) separation point. Devices like boundary-layer fences are used to

help prevent the separation of flow at the tips of swept wings. Vortex generators are

used by placing them on a body in order to raise the energy and momentum of the

13

Figure 2.4: Overall Categorization of Flow Control Approaches [7]

Figure 2.5: Passive and Active Flow Control Devices

14

flow near the surface. Other means of achieving a passive flow control device is to

change the geometric shape of the body or fabricate features into the body to achieve

the desired flow characteristics.

Active devices use some form of energy or fluid to add energy or momentum to

the flow. Active flow control devices expend energy. For them to be truly useful, the

energy gained from the postponed separation needs to exceed the amount of energy

expended. Unlike passive flow control devices, active flow control does not suffer

from the same drag penalty. There are three types of active flow control devices:

Micro Electric Mechanical System (MEMS), Mass Flux (MF), and Zero Net Mass

Flux (ZNMF). Gad-el-Hak, MEMS are devices that require a moving device or wire to

induce a change in the boundary layer to cause a transition from laminar to turbulent

flow. Many investigations have been performed on MEMS devices using flaps. There

has been proof that you can manipulate a separated flow so that reattachment can

improve a flight region. MF devices are designed to remove or add mass to the flow

field. Suction and blowing are examples of MF devices. Both chord and span wise

laminar flow control (LFC) can greatly improve with the addition of suction and

blowing devices [1]. These improvements have been seen in both wind tunnel testing,

as well as flight tests. The last type of active flow control devices are ZNMF. ZNMF

devices, like synthetic jets, remove some fluid from the flow and then that same fluid is

injected back into the flow at a higher energy level and momentum. The synthetic jets

of Glezer et al. [2] are unique flow control devices because the jets are formed entirely

from the working fluid. Another ZNMF flow control device that is being investigated

include plasma actuators. Unlike synthetic jets, plasma actuators energize a region

of flow and with this added energy the momentum of the flow is increased.

15

2.4 Plasma Actuator Flow Control

Single Dielectric Barrier Discharge (SDBD) plasma actuators generate a body force

due to the plasma that is generated. The plasma is generated along the electrode

interface, when a low-current, high-voltage, and high-frequency AC signals are sent

to an exposed electrode, thereby ionizing the surrounding air. The ionized air then

creates a body force on its surroundings, inducing a near wall plasma jet. Investiga-

tions have shown that the usefulness of the plasma actuator depends on the type of

dielectric, the electrode width, the gap between the exposed and embedded electrode,

and the input signal. A schematic of a plasma actuator can be see in Fig. 2.6.

Figure 2.6: Schematic of the Typical Plasma Actuator

Bolitho [5] investigated what the effects of input power and actuator geometry

would have on the type of plasma jet or the vortex generation. bench-top and wind

tunnel testing was done to see what the different effects would have in a static test

case as well as with low Reynolds number flows. The purpose of the bench-top testing

was to see what types of plasma jets could be produced and at what angle. The bench-

top tests were run by changing the input power, operating frequencies, duty cycle,

spacing between the exposed electrodes, and the modulation frequency. The wind

tunnel tests focused on changing the duty cycle, modulation frequency, and sideslip

angle.

16

During bench-top testing Bolitho showed that the strength of the plasma jet is

proportional to the input power. By varying the input power to the exposed electrodes

asymmetrically, an angled plasma jet can be varied over a 180 degree range. Bolitho

also showed that the strength of the plasma actuator can be controlled by varying

the operating frequency, a similar level of plasma control to that of varying the input

power. An adverse reaction to lowering the operating frequency to one side of the

plasma actuator was that the momentum decreased linearly. When investigating the

effects of varying duty cycle, a degree of control over the plasma jet angle could be

achieved. Bolitho experimented with asymmetric duty cycle by leaving one of the

exposed electrodes at a duty cycle of 50% and varying the other electrode between

20% and 50%. The varying duty cycle allowed for the angle to vary between a span

of -90% to 90%. Varying the modulation frequency was investigated by varying the

frequency to each of the electrodes simultaneously to see what effects this would have

on the types of plasma jet produced. At the lower frequencies, two independent jets

were seen near the wall in either direction. As the frequency was increased, vortices

were formed by the exposed electrodes. As the frequency neared the critical frequency

the vortices that were produced impinged on each other and nearly canceled each

other out. Once past the critical frequency, the plasma jet created resembles that of

a plasma jet under steady operation. During construction of the plasma actuators

the spacing of the two exposed electrodes gave each of the actuators a unique critical

frequency. Bolitho showed that modulation frequency does not affect the amount

of momentum induced, the amount of momentum induced increases as the spacing

between the exposed electrodes is increased.

Bolitho varied the duty cycle, the effects of sideslip angle, and the wind tunnel

speed. During the varying duty cycle investigation, the focus was to see how much

vorticity can be created. One side of the actuator was kept at a duty cycle of 50%

while the other side was allowed to vary between 10% and 50%. The vorticity did

17

not significantly change with duty cycle, but there were changes in the location and

size of the vortices. When investigating the effects of sideslip, the maximum vorticity

increased for all cases when the duty cycle was between 10% and 50% and the sideslip

angle was nonzero. The effectiveness of the vectoring actuators was investigated as

speed was increased. During both of the two cases that were being investigated, that

the effectiveness of the jet actuators diminished.

Ozturk [6] investigated the use of plasma actuators as micro-thrusters. These

thrusters were investigated by doing both bench-top and wind tunnel testing. bench-

top testing was done by varying several parameters: inner diameter, forcing frequency,

and duty cycle. Wind tunnel testing was done by varying the wind tunnel speed.

During the bench-top testing, different velocities were achieved by varying the

inner diameter of the thruster. There were three different size inner diameters used:

0.635 cm, 1.016 cm, and 1.27 cm. That the 1.27 cm had the largest velocity and

produced the maximum amount of thrust. The maximum thrust decreased as the

diameter of the thruster decreases. The thruster with an inner diameter of 0.635

cm had a larger velocity than the one with the thruster with an inner diameter of

1.016 cm. Further investigation was done varying the duty cycle for each of the

three plasma thrusters at different forcing frequency. The velocities were affected

by the change in duty cycle and forcing frequency. As the duty cycle increased, the

velocity also increased, but the opposite was true with forcing frequency. The peak

thrust, maximum velocity and average velocity for each of the three plasma thrusters

was found to be at all different values. The velocity profiles of each of the smaller

diameter plasma thrusters were seen to be practically parabolic with a maximum

velocity occurring near the centerline. As the inner diameter of the plasma thruster

was increased, the centerline velocity decreased and the velocity near the wall was

seen to increase.

Ozturk then conducted wind tunnel tests on the plasma thrusters by varying the

18

wind tunnel speeds. Three different wind tunnel speeds were used to test the plasma

thrusters: 0.62 m/s, 1.28 m/s and 2.32 m/s. The 1.016 cm diameter thruster showed

the best results as the tunnel speed was increased from 0.62 m/s to 2.32 m/s. The

effects started to decrease as the speed got higher and the velocity profiles became

harder and harder to distinguish. The larger thrusters were seen to have a smaller

effect especially as the tunnel speed increased to 2.32 m/s.

Ozturk also looked at jet vectoring plasma actuators. The jet vectoring plasma

actuators were investigated by doing wind tunnel testing. These tests were done by

varying duty cycle and wind tunnel speed. Many of these tests used and expanded

on the work done by Bolitho. No quiescent measurements and the only part of the

input signal that was being varied was the duty cycle throughout all the tests. Duty

cycle was the only parameter investigated at because it has the greatest sensitivity

and has the greatest effect on the plasma jet vectoring angle. During these tests a

maximum vorticity was seen when one exposed electrode had a duty cycle of 50%

and the other electrode had a duty cycle of 0%. These jets formed along the wall

and were considered to be linear cases. For vectoring cases a duty cycle of 50% was

placed on one electrode and a varying duty cycle between 20% and 40% was placed on

the other. Lower vorticity was observed from these tests because of the asymmetric

plasma strength on each of the electrodes.

Jet vectoring plasma actuators were placed on a NACA 0012 in the chord-wise

direction and placed at an angle of attack of 10 degrees. Plasma jet vectoring ac-

tuators proved to be effective in the controlling of separation at low tunnel speeds

around 0.62 m/s. Three cases were run using three different duty cycle configurations:

0%/50%, 30%/50% and 50%/50% for the left and right electrodes respectively. For

all three cases, appreciable separation control was achieved. Ozturk also investigated

the effect of pulsing the actuator at a duty cycle of 50% on both electrodes. For the

three cases stated above, the strongest vortex was generated when the electrodes are

19

pulsed at a 50%/50%, followed by 30%/50% then 0%/50%. The effectiveness of a

jet vectoring actuator decreases with an increase in tunnel speed. At higher tunnel

speeds a simple linear actuator is a better choice for flow control.

He et al. [8] did experiments using weakly ionized plasma actuators to help with

flow control separation on a wing to try and replace the leading edge slats and trailing

edge flaps. A SDBD plasma actuator was set up to make an array of actuators at

the leading edge and trailing edge. Setting up the plasma actuators this way would

effectively eliminate hinge gaps that are created by the moving control surfaces. Hinge

gaps directly affect the drag component in viscous drag calculation on a given wing.

Hinge gaps are also a large source of radar signal reflection. Removing the hinge gap

would reduce the radar signature of a given wing, making a hinge-less wing more

desirable in many military applications. The benefit of plasma actuators would come

from being able to tile a generic wing to focus on regions of separation, to be able

to control aerodynamic forces produced within these regions, and by the wing itself.

Being able to control these forces would allow us to be able to change the wing’s

aerodynamic performance to suit various flight conditions.

The SDBD plasma actuators used were made up of two electrodes separated by a

dielectric material, one electrode exposed to air and the other being fully embedded in

the dielectric material. A high voltage AC input was supplied to the electrodes, and

when the input amplitude was large enough, the air ionized. The ionization begins

at the edge of the exposed electrode and extends over the region that is covered by

the embedded electrode. The ionized air creates a body force which is given by

f ∗b = −(ε0λ2D

)ϕE (2.5)

where ϕ is the electric potential, E is the electric field, λD is the Debye field, and

ε0 is the permittivity of air. The body force can be manipulated by changing the

arrangement of the electrode and dielectric. This way a wide verity of arrangements

20

can be made to handle different situations.

These SDBD plasma actuators were investigated in both a quasi-steady or un-

steady activation. During steady activation the frequency used was well above the

fluid response frequency. With the activation frequency above the fluid frequency

there was a constant body force that was sensed by the fluid. During unsteady acti-

vation a driving frequency was switched on and off to excite the region of instabilities

in the fluid flow. By activating the plasma actuators in an unsteady fashion, the

power consumed by the actuator was reduced. This investigation looked at using a

10% duty cycle that showed a 90% reduction in power consumption over the steady

operation. The unsteady case also showed a better overall flow control.

These experiments showed that a SDBD plasma actuator, located on the leading

edge of a NACA 0015 wing, was able to suppress stall well past the stall angle of

attack. There was also an increase in the lift-to-drag ratio at higher post-stall angles

of attack. The plasma actuator used for this experiment was arranged and oriented

so the plasma jet was toward the suction side of the airfoil when the airfoil was

at positive angles of attack. The actuator was operated at both quasi-steady and

unsteady states. During both cases there was an increase in the operational angle

of attack. When the plasma actuator was operated in the quasi-steady state, the

actuator drew more power than the unsteady case but was less effective than the

unsteady actuator. For the unsteady case, an optimum frequency, was found to be:

St =fc

U∞= 1 (2.6)

or could also be written as:

F+ =fcxU∞

= 1 (2.7)

where c is the chord length. The Strouhal number (St) equal to one is seen to be an

optimum for various operations involving plasma actuators in unsteady operations.

21

F+ is the non-dimensional frequency, where xc is the distance from the actuator to the

trailing edge. During unsteady operation plasma actuators produce periodic vortices

that flow into the fluid in the direction of the flow. The unsteady frequency f has a

correlation with the wavelength of the vortices. This wavelength, λ = crf

where cr is

the convection speed. The Strouhal number then becomes:

St =fc

U∞=(crL

λU∞

)= 1 (2.8)

With a Strouhal number of one this seems to be optimum for separation control

because this would maintain a pair of vortices in the separated region. The unsteady

plasma actuators worked the best when oriented to have a wall jet in the direction of

the fluid flow.

Plasma actuators placed near the trailing edge for roll control were also inves-

tigated. When placing plasma actuators near the trailing edge, the lift coefficient

shifted in a way that would increase the wings chamber. Simulations were run, and

plasma actuators placed near the trailing edge generated ∆CL larger than that gen-

erated with actuators located near the leading edge. When several actuators were

placed and operated in conjunction, their effect on ∆CL was additive. This investiga-

tion also looked into replacing moving aileron surfaces with plasma actuators for roll

control. One actuator was placed on the upper surface of the wing while another ac-

tuator of the same length La, was placed on the bottom. The wing had dimensions of

wing span b and the chord length c, on a standard NACA 0015 rectangular wing. This

configuration was designed so that the actuator on the upper surface would produce

an increase in lift while the actuator on the lower surface would produce a decrease

in lift. This change in lift would affect the entire wing area Sw. This arrangement

resulted in a positive roll moment LR. The lift force is uniform in span over the area

of the plasma actuator Sa. The magnitude of the roll moment is LR = 2 (∆CL) qSara

where ra is the moment arm from the center of the span to the lift center. The roll

22

moment coefficient becomes

CLR=

LR

qSwb=

2 (∆CL)SaraSwb

(2.9)

With a leading edge plasma actuator, the flow could be reattached on a NACA 0015

airfoil up to 18 degrees angle of attack, which is 4 deg past the normal stall when

operated in a quasi-steady state. During unsteady operation stall was postponed by

8 deg. The leading edge plasma actuator resulted in an increase in both CLmax and

αstall, and also improved L/D by as much as 340%. When placing a plasma actuator

at the trailing edge and operating it in a quasi-steady state, the actuator influenced

the flow like a plain trailing edge flap.

Mabe et al. [9] investigated the use of SDBD plasma actuators to improve airfoil

performance. A NACA 0021 was used during the testing with a plasma actuator

located near the leading edge, where it could affect the transition point, the leading

edge separation bubble, and at the flap shoulder, where it could affect the flow over a

detached flap and possibly reattach the flow on the flap. The plasma actuators used

during the experiments were operated at ± 5 kV at a frequency of 5 kHz a 10% cycle,

and an F+ = 1.

A control experiment was done on an airfoil with no plasma actuators at two

Reynolds numbers (100,000 and 200,000). The slope of the life curve (dCL/dα) was

2π. This slope is only viable over a small range of angles between 6 to 8 degrees for

a Reynolds number of 200,000 and between 2 to 6 degrees for a Reynolds number

of 100,000. A plasma actuator was placed at the leading edge but not activated

to see what effect the presence of the actuator itself would have on the flow. The

presence of the actuator caused a decrease in the maximum lift (CLmax) even though

the maximum stall angle (αstall) was increased by 2 to 4 degrees. The non-active

actuator actually created a discontinuity on the surface of the airfoil that in effect

shortened the leading edge separation bubble and reduced the lift generated by the

23

airfoil. When the plasma actuator was activated in an unsteady state with F+ = 1,

the surface disturbance was increased and further reduced the initial dCL/dα and

in doing so increased αstall. Increasing αstall generated some lift that helped recover

some of the lift lost by the presence of the plasma actuator. With the addition of

the passive actuator at x/c = 0.05, there was a decrease in drag by 20% on the clean

airfoil at a Reynolds number of 100,000. Was also noticed that there was no noticeable

effect at a Reynolds number of 200,000. When the plasma actuator was activated, it

eliminated the separation bubble over most of the suction side of the airfoil, but the

vortices that were created by having an F+ = 1 increased the skin friction. It was

observed that the active plasma actuator actually accelerated the transition earlier

from laminar flow to turbulent flow and decreased the amount of lift generated at

given angle of attack.

A plasma actuator was also placed near the flap shoulder (x/c = 0.65) to see if

flow could be reattached if the flow is detached over the flap. Leaving the actuator

passive did not have any effect on the leading edge separation bubble. The passive

actuator actually caused earlier separation over the flap and therefore increased the

drag. Even when the plasma actuator was activated and the flap was never deflected

there was no observable benefit from the active actuator. Even in the presence of

the active plasma actuator, the momentum generated was so insignificant that the

suction upstream was not noticeable. The wing actually stalled earlier than it would

have if there was no actuator present.

Yurchenko et al. [12] did an investigation on boundary layer control through the

use of localized plasma generation. During the generation of plasma, the thermal pat-

terns that were generated in the boundary layer proved to be an innovative method

for controlling the boundary layer. The boundary layer control was realized using

“span-wise-regular microwave-initiated discharges.” The behavior and characteristics

of an airfoil was shown to improve during the plasma actuation. During a numerical

24

simulation of the flow control system using span-wise arrays of plasma actuators, a

boundary layer that has transitioned to a turbulent boundary layer is less susceptible

to the thermal patterns generated during plasma activation. Further experiments

were done using a wind tunnel to test the span-wise array of plasma actuators and

take aerodynamic measurements such as: lift, drag, pitch moment, and pressure co-

efficients. Wind tunnel tests showed that the plasma actuators adjusted the pressure

around the airfoil in a favorable manner, was able to delay separation when the angle

of attack was increased, as well as increasing CL without increasing drag when the

angle of attack was increased past the stall angle.

Yurchenko et al. [13] also did an investigation on localized plasma generation

using wind tunnel tests. These tests were done to investigate the ability to control

a boundary layer using plasma actuation generated by using microwave radiation.

These tests were preformed in the Aerodynamic Facility for Interdisciplinary Research

(AFIR). The test results showed that there was a delay in separation by 15% at pre-

stall angles of attack, and during activation there was a decrease in drag by about

5%. These improvements can be considered as a method of “flow stabilization”. This

allows for the delay of separation at post-stall angles of attack as well as an increased

probability of flow reattachment once separation occurs.

Little et al. [11] investigated the use of plasma actuators to help control separation

on the flap of a high-lift airfoil. The test was designed to evaluate the efficacy of a

single dielectric barrier discharge (DBD) plasma actuator. The actuator was placed on

the shoulder of the detached flap in a position that would allow for flap reattachment

in flow velocities between the Reynolds numbers of 240,000 (15 m/s) and 750,000

(45 m/s). During these experiments the moment coefficients that were calculated

were of an order of magnitude lower than those seen in previous tests. The control

authority for these tests is still maintained due to the amplification of the natural

shedding frequency of vorticites from the flap shoulder. This behavior has a tendency

25

to transfer momentum between the freestream and separated regions of flow around

the airfoil. This change in momentum changes the circulation around the airfoil and

can enhance the lift of the airfoil. The activation of the DBD demonstrated how it

could control the flow over a detached TE flap of a high-lift airfoil.

Another set of experiments in active flow control using plasma actuators was

done by Vey et al. [15]. This set of experiments was focused on the low Reynolds

number speeds of less then 100,000. The reason for this region of flight speeds was to

concentrate on the use of plasma actuators for the development of micro air vehicle

(MAV) applications. During the testing, force measurements and frequency response

of lift was investigated for different wing-actuator combinations at different angles of

attack. Many of these measurements and flow field visualization was done using a PIV

system. Active flow control using plasma actuators is very productive while operating

in low Reynolds numbers flow. Testing showed CL increased up to ∆CL = 0.45

through the use of periodic actuation. These results were found for actuator placement

at the leading edge or at wing tips. The forcing frequency, for use during the periodic

activation, was dependent on the wing’s angle of attack. When this frequency was

optimized for a certain angle of attack, there was a greater increase in lift. Vey also

demonstrated that leading edge flow control was more effective when the aspect ratio

was increased. Control authority was seen to decrease as the Reynolds number is

increased.

Burman et al. [16] examined separation control over Low Pressure Turbines (LPT)

using plasma actuators. DBD plasma actuators were evaluated in quiescent air as

well as in air flow with a Reynolds number of 50,000. The plasma actuators were

tests in both a steady actuation as well as pulsed. During both tests cases, velocity

and total pressures were measured and then studied to examine the effects of excita-

tion frequency and amplitude on the flow, and to see how pulsed operation effected

the separation. The same measurements were made for actuators orientated oppo-

26

site and aligned, as well as, downstream and span-wise plasma discharges. When

the actuators were tested in quiescent flow, the momentum generated scaled with

the increase to excitation frequency and amplitude. For the cases where the plasma

actuator operation was pulsed, separation control increased monotonically with in-

creased modulation frequency and duty cycle. When examination of the orientation

of the plasma actuators was done, even though the reversed orientation successfully

demonstrated separation control, the aligned orientation was a much better means of

flow control.

Guo et al. [18] investigated the effect of a new plasma actuator configuration

on thrust. This new design was introduced to try and take advantage of discharge

asymmetry. This new design focused on controlling the surface charge by the addition

of a third electrode. The new configuration was seen to produce about 70% more

thrust than that of the conventional plasma actuator design.

Thomas et al. [20] investigated the use of SDBD plasma actuators for use in active

aerodynamic flow control. Experiments were run to try and optimize the body force

that was produced by these types of actuators. This study was focused on being able

to improve control authority of plasma actuators while at higher Reynolds numbers.

Actuator parameters such as dielectric material, dielectric thickness, applied voltage,

applied frequency, voltage waveform, exposed electrode geometry, covered electrode

widths, and multiple actuator arrays were tested. The limiting factor to the amount

of body force you get is in the formation of plasma streamers. Investigations were

preformed to figure out a way to gain a higher control authority by delaying the

formation of streamers. By using a dielectric with a higher dielectric strength, lower

dielectric constant, and using a thicker material, that plasma streamer development

was delayed. Another method that was discovered to reduce streamer formation

was to lower the AC frequency that was applied to a given actuator. Thomas et

al. discovered that a plasma actuator with a serrated TE, rather than a conventional

27

straight TE, actually produced a higher body force. When examining the construction

of not only single actuators but multiple actuator arrays, Thomas found that if your

embedded electrode is not wide enough, it actually constrains the body force, therefore

limiting the actuator and not allowing for optimum body for production. When

multiple actuators were arranged in an array there was an increase to the total body

force but the body force does not sum linearly. At with multiple actuators the wall jet

thickened with the addition of the other actuators due to the increase of momentum

flux close to the wall. Overall lift enhancement and drag reduction could be achieved

by using plasma actuators in the fuselage and wing Reynolds number of 6.8X106 and

1.2X106 respectively.

28

CHAPTER 3

Experimental Set-Up

Chapter 3 goes into depth of how the apparatus and diagnostic experiments were

setup and performed throughout this investigation using plasma actuators to control

separation on an airfoil. The construction method and guidelines for constructing a

plasma actuator is outlined in this section. The program used to generate plasma

along the actuator is also discussed here. A discussion on how PIV measurements

were taken is also provided to give a background on how the results were achieved.

The experimental setup for both the bench-top and wind tunnel tests is provided to

help with experimental reproduction for future experiments.

3.1 Plasma Actuators

Plasma actuators are constructed using a dielectric material and copper electrodes.

The dielectric materials that were investigated are Teflon, acrylic, and alumina. The

Teflon used was a 1/32 inch thick, generally about 1 inch wide and ran the span

of the wings being tested Fig. 3.1. The acrylic was 1/8 inch thick, 2 inches wide

and about 12 inches long Fig. 3.3. The alumina plates were 0.025 inches thick and

about a 4 inch by 4 inch squares Fig. 3.2. Two different widths of copper electrodes

were looked at and compared when the Teflon was tested, 1/4 inch and 1/2 inch

wide copper tape. One set of Teflon actuators, the acrylic actuators and the alumina

actuators all used the 1/2 inch copper tape. The 1/4 inch copper tape was compared

with the 1/2 copper tape on the Teflon. Two strips of copper tape were used on each

plasma actuator. The exposed electrode was connected to the high voltage lead and

29

the embedded electrode was connected to ground. The high voltage lead was supplied

with an alternating current (AC) with an average peak-to-peak voltage of 50 kV for

Teflon. The AC signal was generated by a computer using a LabView program to

produce the square wave input signal and plasma frequencies between 3 kHz and 15

kHz (a block diagram of the LabView program can be seen in Fig. 3.4). For situations

when two transformers were used, a different LabView program was used (the block

diagram of the Labview program can be seen in Fig. 3.5). The signal was then sent

to a QSC RMX 1450 amplifier and out to a CMI 5012 transformer. The output from

the transformer was monitored for voltage with a North Star PVM-11 1000:1 high

voltage probe. The voltage probe was then connected to an oscilloscope to monitor

and maintain the voltage necessary.

Figure 3.1: Teflon Plasma Actuator with 1/2 inch Copper Electrodes

Figure 3.2: Acrylic Plasma Actuator with 1/2 inch Copper Electrodes

30

Figure 3.3: Alumina Plate Plasma Actuator with 1/2 inch Copper Electrodes

31

Figure 3.4: LabView Block Diagram for 1 Channel Output

Figure 3.5: LabView Block Diagram for 2 Channel Output

32

3.2 PIV Measurements

Particle image velocimetry (PIV) was used to measure flow field that was produced

while an active plasma actuator was being used. The flow field was a 2-D cross section

of the plasma actuator. The field was saturated with particles of about 1 micron in

size from a Turbofog fog generator. A thin laser sheet produced by a dual-head

Nd: YAG laser from Big Sky Lasers, was projected over the 2-D cross section of the

plasma actuator and the plasma jet being produced. Three lenses were used to alter

the original laser projection into a thin sheet spanning the cross section. The first

lens was a converging lens that focuses the beam coming from the laser heads into a

fine horizontal sheet. A second diverging lens, at the focal length, was used to turn

the sheet 90 degrees and gives a thinner more concentrated laser beam. The final lens

used was a cylindrical lens to spread the beam into the fine thin sheet that is needed

to be projected across the 2-D cross section. The lasers were pulsed in sync with a

Kodak Megaplus ES 1.0 CCD, high speed, and high resolution camera in combination

with a Quantum Composer timing box. Every time a PIV run was completed, the

Epix frame grabbing software captured 63 pairs of images, each measuring 1008 x

1018 pixels. Fig. 3.6 shows a schematic of this setup.

The PIV program we used to analyze each of the runs was a Wall adaptive La-

grangian Parcel Tracking algorithm (WaLPT). This algorithm was developed by Sholl

and Savas [4], it takes all the particles that were saturated in the region by the fogger

and treats them as fluid parcels. WaLPT then analyzed the movement and deforma-

tion of the fluid field and then compared it to the previous snap shot to determine

the individual velocities, vorticity, and acceleration of each particle. The WaLPT al-

gorithm was used to get very accurate measurements for the velocities near surfaces.

33

Figure 3.6: Schematic of PIV Setup

3.3 Bench-Top Testing

The bench-top testing phase of these experiments were done in quiescent flow. The

Plasma actuator was placed in a 20 in x 10 in x 12 in clear glass aquarium. Fog was

then injected into the aquarium from the Turbofog fog generator to allow for PIV

measurements to be taken by the process described above. The laser was positioned

so that the laser sheet passed over the midsection of the plasma actuator at a perpen-

dicular angle to the plasma jet. The three lenses were positioned to produce a thin

laser sheet to allow for better definition when PIV measurements were being taken.

The high speed Kodak Megaplus camera was placed perpendicular to the laser sheet

so that it was pointed down the long direction of the plasma actuator. The placement

of the camera in this fashion allowed the capturing of the wall jet that was produced

by the plasma actuator as well as the flow structure downstream of the actuator. A

block schematic of the bench-top setup is pictured in Fig. 3.7.

34

Figure 3.7: Schematic of bench-top Setup

35

3.4 Wind Tunnel Testing

For the wind tunnel tests a Liebeck La203a airfoil was used to create a test wing. A

profile of this airfoil is illustrated in Fig. 3.9. Using SolidWorks 3D CAD program, a

wing with a span of 6 inches and a chord of 6 inches was modeled. The CAD model

is illustrated in Fig. 3.8. The test wing was also designed to have two one-inch wide,

3/64 inch deep cuts located near the leading edge and at the 40% chord. These cuts

were designed so that the plasma actuators could be embedded into the surface of the

wing, to avoid artificially tripping the air flow over the actuator, causing separation.

The CAD drawing was then sent to a rapid prototyping machine to create two wing

sections made of an SLA plastic material, so that the final test wing had a span of 12

inches and a chord of 6 inches. The wing sections were then glued together with epoxy

and a piece of 1/4 x 20 all thread was fed through the 1/4 chord to allow a pivot and

mounting location. Plasma actuators were then secured into the grooves on the wing

surface by tape and the wing was mounted into the wind tunnel. The wind tunnel

used for these plasma actuator tests is a GDJ FLOTEK 1440 wind tunnel, with a test

section that is 12 in. x 12 in. x 36 in.. This wind tunnel is an Eiffel or Open-Loop

style wind tunnel. The air flow is pulled through a large inlet and through the test

section by the motor and fan in the exhaust section. This tunnel has a top speed of

about 16m/s at 1200 rpm. The laser was positioned on the outside of the wind tunnel

much like that used in the bench-top tests. The camera was positioned above the

tunnel in such a way that a large portion of the upper surface of the wing could be

seen. The Turbofog fog generator was placed at the inlet of the wind tunnel so that

when the tunnel was turned on the fog could be ingested into the inlet, pass through

the test section over the wing, and be exhausted out the back end of the tunnel.

While the tunnel was running PIV measurements were done as described above. The

36

test runs done in the wind tunnel will take many of the best parameters from the

bench-top tests and examine them in a free stream environment. A schematic of the

wind tunnel test setup is illustrated in Fig. 3.10.

Figure 3.8: Liebeck La203a CAD Model

37

Figure 3.9: Liebeck La203a Airfoil

Figure 3.10: Wind Tunnel of Setup

38

CHAPTER 4

Results

Chapter 4 shows the results for all of the bench-top, computational, and wind tunnel

tests performed. Between the bench-top testing and the wind tunnel testing there

were approximately 200 runs recorded. During the bench-top investigation roughly

100 tests were done to illustrate which dielectric material produces the strongest

plasma jet and which dielectric material would be best to use in further wind tunnel

testing. An investigation was performed using XFoil to help determine the optimum

location to place plasma actuators to provide separation control on a La203a air-

foil. With the results from the previous two investigations, wind tunnel testing was

performed at different Reynolds numbers to test for active separation control using

plasma actuators. Reattachment was achieved for three of the four Reynolds numbers

tested.

4.1 Actuator Development

As discussed earlier, the basic actuator consists of two electrodes separated by a di-

electric medium. During bench-top testing three different dielectric materials were

investigated while varying several parameters during their operation. The three dif-

ferent materials were Teflon, acrylic, and alumina. The parameters that were varied

included operating frequency, modulation frequency, and peak-to-peak voltage. The

duty cycle was set to 100% while the operating frequency was varied to have a steady

output of plasma. Once the optimum operating frequency was found the duty cycle

was reduced to 50%; this gave the plasma actuator a pulsing unsteady behavior. The

39

physical parameters that were varied can be seen in Fig. 4.1.

Figure 4.1: Plasma Actuator Parameters

The first set of experiments was performed using Teflon, which has a dielectric

constant of about 2.1, as the dielectric material, with 1/4 inch wide copper electrodes.

To establish an optimum operating frequency 14 runs were performed. The first set of

runs varied the frequency between 3,000 Hz and 15,000 Hz by steps of 1,000 Hz. The

peak-to-peak voltage was held constant at 50 kV and the duty cycle was set at 100%.

It was observed that there seemed to be two optimum frequencies for these cases; one

at about 8,000 Hz and another at 15,000 Hz. 15,000 Hz was a much higher frequency

than had been previously investigated, so 15 more runs were performed to investigate

the behavior of the plasma actuator at and near 15,000 Hz. As can be seen in Fig. 4.2

the optimum operating frequency was 15,000 Hz and had a maximum velocity of

110 cm/s, and this occurred about 28 mm downstream of the actuator according to

Fig. 4.6. The PIV measurements for the optimum run are seen in the next several

figures. Fig. 4.4 illustrates the velocity vectors generated by the plasma actuator and

it can be seen that a strong wall jet was produced. Figs. 4.4 and 4.5 show that a

standing vortex was generated above the plasma actuator, and this illustrates that

the actuator was pulling the surrounding air inward and projected the air outward in

the form of a wall jet. Fig. 4.6 shows the velocity profiles in relation to the position

of the plasma actuator. Fig. 4.6 shows how the velocity varied both a little upstream

and downstream of the actuator. The standing vortex that was generated by the

actuator can account for the variation in velocities. The swirling motion that was

40

generated by the actuator could be the reason for the slight rearward flow that is seen

in Fig. 4.6. The jet that was produced stretched forward of the actuator about 30

mm. Figs. 4.2 and 4.3 were plotted with a maximum velocity of 180 cm/s to allow

for comparison with other cases that were run later.

The next parameter that was examined was how varying the modulation frequency

changes the effect of the plasma actuator. To see what modulation frequency had the

biggest effect on the plasma jet, the frequency was varied between 5 Hz and 1,000 Hz

by semi-logarithmic steps. The voltage was once again held constant at 50 kV and the

duty cycle was reduced to 50% throughout the 23 runs, to generate a pulsed plasma

jet. The first 13 runs swept the whole range between 5 Hz and 1,000 Hz and it was

found that a modulation frequency of 50 Hz produced the greatest plasma jet velocity

as seen in Fig. 4.3. During this phase of experiments an interesting phenomenon was

observed in the PIV measurements, there was a standing vortex formed when the

modulation frequency reached 200 Hz. Another 10 runs were performed to try and see

how this vortex changed when the modulation frequency was changed around 200 Hz.

It was observed that the vortex would grow or shrink in size depending on how close

the frequency was to 200 Hz. The generation of the vortex was somewhat inconsistent,

and the velocities varied a little due to the inconsistency. Once the frequency was

beyond the 200 Hz range, the velocity produced by the plasma actuator decreased

well below that of the lower frequency range. The last thing performed during this

part of the investigation was to test and see what the highest peak-to-peak voltage the

Teflon could handle before it burned out. Several runs were performed by increasing

the peak-to-peak voltage by steps of 10 kV from 50 kV to determine the burn out

limit of 70 kV. Once this power setting was reached there was a saturation of plasma

streamers that led to the dielectric material breaking down and burning out. Once

the actuator burned out in any spot all plasma generation stopped. From this set of

experiments we were able to say that the Teflon produced the strongest plasma jet

41

when the following parameters were met: the plasma frequency was set to 15,000 Hz,

the peak-to-peak voltage was set to about 50 kV, and when operating the actuator

in a pulsed fashion the modulation frequency was set to 50 Hz.

Figure 4.2: Plasma Actuator Benchmarking: Varying Frequency (Teflon with 1/4 in.

Copper Electrodes)

Figure 4.3: Plasma Actuator Benchmarking: Varying Modulation Frequency (Teflon

with 1/4 in. Copper Electrodes)

42

Figure 4.4: Velocity Vectors for Teflon with 1/4 in. Copper Electrodes

Figure 4.5: Vorticity for Teflon with 1/4 in. Copper Electrodes

43

Figure 4.6: Velocity Profile for Teflon with 1/4 in. Copper Electrodes

44

The second set of experiments were performed using acrylic, with a dielectric

constant ranging for about 2.7-4.5, as the dielectric material, with 1/2 inch wide

copper electrodes. Acrylic was tested to see how it compared to the Teflon. The

main tests that were run on the acrylic were with a varying operating frequency

between 3,000 Hz and 15,000 Hz. 13 runs were performed at a peak-to-peak of 50

kV. No favorable results were seen while the actuator was operated at this voltage

level. Several runs were then performed to see the highest peak-to-peak voltage the

acrylic could withstand before it burned out. Acrylic’s highest peak-to-peak voltage

was observed to be 90 kV when the acrylic started to flex and burn out. Fig. 4.7

shows how the plasma jet velocity increased as the peak-to-peak voltage increased.

Having found a good operating voltage, the 13 runs that were performed at the lower

voltage, were re-performed, with the peak-to-peak voltage set at 80 kV, to see if

a more favorable set of results could be found while varying the plasma frequency.

Fig. 4.8 shows the results of these last 13 runs, and an optimum frequency of 7,000 Hz

was found with a corresponding maximum velocity of 146 cm/s. Throughout the runs

the acrylic mostly had a constant velocity over the frequency range. The maximum

velocity of the acrylic was observed to be higher than that of the Teflon. Fig. 4.9 shows

the velocity vectors for the acrylic plasma actuator. As with the Teflon a strong wall

jet is observed, but when examining Fig. 4.10 there was no standing vortex like was

observed in Fig. 4.5 for the Teflon dielectric material. Fig. 4.11 illustrates the velocity

profile of the plasma jet produced by the acrylic plasma actuator downstream of the

actuator. There was no upstream flow produced by the acrylic actuator, because of

the possible lack of a standing vortex. The maximum jet velocity for the acrylic is

found somewhere between 13 mm and 19 mm downstream of the actuator. Figs. 4.7

and 4.8 were plotted with a maximum velocity of 180 cm/s to allow for comparison

to other cases.

45

Figure 4.7: Plasma Actuator Benchmarking: Varying peak-to-peak Voltage (Acrylic

with 1/2 in. Copper Electrodes)

Figure 4.8: Plasma Actuator Benchmarking: Varying Frequency (Acrylic with 1/2

in. Copper Electrodes)

46

Figure 4.9: Velocity Vectors for Acrylic with 1/2 in. Copper Electrodes

Figure 4.10: Vorticity for Acrylic with 1/2 in. Copper Electrodes

47

Figure 4.11: Velocity Profile for Acrylic with 1/2 in. Copper Electrodes

48

The next set of experiments were performed with alumina, with a dielectric con-

stant of 4.5, as the dielectric material, with 1/2 inch wide copper electrodes. Alumina

is a common material used when dealing with plasma actuators because it can pro-

duce a strong plasma jet and has a high dielectric constant. For our purpose it was

used to compare with the Teflon dielectric material tested above. Like the other di-

electric materials, the alumina was tested with a varying operating frequency. The

alumina was first tested with a peak-to-peak voltage of 50 kV but burned out before

any tests were finished running. The peak-to-peak voltage was then reduced to 40

kV and the material fared much better. The alumina was then tested with a varying

operating frequency between 3,000 Hz to 15,000 Hz which was performed before on

the other dielectric materials. 13 runs were performed over this operating frequency

range and the results can be seen in Fig. 4.12. A maximum velocity of 162 cm/s was

found for an operating frequency of 8,000 Hz. Unlike the characteristics of the acrylic,

the alumina had a very non-constant velocity range. It was observed that once past

the peak operating frequency the velocity dropped off sharply. Fig. 4.13 shows the

velocity vectors for the alumina at its optimum frequency and it is seen that it too

produces a strong wall jet forward of the actuator. Fig. 4.14 shows a strong vorticity

in the direction of the wall jet, but there was no standing vortex present like there was

in the Teflon. The velocity profile is seen in Fig. 4.15 where the jet velocity produced

upstream and downstream is illustrated. The maximum velocity is located beyond 15

mm of the actuator, so peak velocity may not have been determined. The upstream

component of velocity that was produced is believed to come from the plasma jet

produced from the electrode on the bottom surface of the actuator. Fig. 4.12 was

plotted with a maximum velocity of 180 cm/s to compare to Teflon and acrylic.

49

Figure 4.12: Plasma Actuator Benchmarking: Varying Frequency (Alumina with 1/2


Figure 4.13: Velocity Vectors for Alumina with 1/2 in. Copper Electrodes

50

Figure 4.14: Vorticity for Alumina with 1/2 in. Copper Electrodes

Figure 4.15: Velocity Profile for Alumina with 1/2 in. Copper Electrodes

51

The last set of tests was performed with Teflon as the dielectric material again, but

with 1/2 inch wide copper electrodes instead of the 1/4 inch wide copper electrodes.

The 1/2 inch wide tape was examined to see if it had a large impact on the plasma

jet produced by the actuator. This actuator was tested by varying the operating

frequency between 3,000 Hz and 15,000 Hz. The results are seen in Fig. 4.16 and it

was clear that the Teflon with the 1/2 inch wide copper electrodes behaved similar

to that of the Teflon with the 1/4 inch wide copper electrodes. The 1/4 inch copper

electrodes seem to have a better mid-range velocity. The two different sized electrodes

had roughly the same velocity at the upper end of the plasma frequency range.

Figure 4.16: Plasma Actuator Benchmarking: Varying Frequency (Teflon with 1/2


52

When comparing the three types of dielectrics and their maximum velocity, it

was seen that alumina was the dielectric that produced the highest plasma jet. This

comparison is illustrated in Fig. 4.17. Even though the alumina produced the highest

plasma jet velocity, it was a very stiff and brittle material and cannot be flexed without

cracking. The acrylic produced the second highest velocity, and even though it was

not brittle like the alumina, it was not flexible. Both the Teflon with the 1/4 inch

wide copper electrodes and the Teflon with the 1/2 wide copper electrodes preformed

about the same. Both sets of Teflon produced a plasma jet with a velocity a little

over 100 cm/s. The Teflon may not produce the highest plasma jet velocity, but it

was flexible enough to be conformed to an airfoil for further testing.

Figure 4.17: Maximum Velocity Comparison for each Dielectric

4.2 X-Foil

To determine the best location to place the plasma actuators on the surface of the

La203a wing an extensive separation point investigation was performed. This in-

vestigation was performed using XFoil. Several different Reynolds numbers were

examined to see how different Reynolds numbers would affect the point of separa-

tion. The La203a airfoil was run through a wide range of angles of attack to see

53

how the separation progressed along the airfoil. Each run varied the angle of at-

tack from -6 to 16 degrees, for each of the following Reynold’s numbers: 50,000,

100,000, 175,000, 250,000,375,000, 500,000 and 650,000. For each Reynolds number

there were 12 graphs made examining the coefficient of skin friction in comparison

to the percent chord location. Figs. 4.18 and 4.19 illustrate how the separation point

changed as Reynolds number changed. By tracking the point where the coefficient of

skin friction goes to zero, we could track the progression of separation over an airfoil

as the angle of attack was increased. Examining Fig. 4.18 it can be observed that

a leading edge separation bubble was formed, but the flow then reattached further

downstream. By examining Fig. 4.19 there was a similar trend to the previous run at

the lower Reynolds number but the flow does not actually detach until close to the

trailing edge. The results of the separation tracking is pictured in Fig. 4.20. From

these investigations it was seen that the La203a airfoil stalls at the trailing edge and

progressed forward as the angle of attack increased to the point where almost the

entire airfoil was separated. It was decided to place two actuators on the surface of

the airfoil. The first actuator was placed close to the leading edge to help prevent the

development of any separation bubbles, and the second was located about the 40%

chord, where throughout this investigation it was seen that this was the next most

likely location where separation would occur. Fig. 3.8 illustrates the plasma actuator

placement.

54

Figure 4.18: XFoil Separation Point Tracking Reynold’s Number of 100,000 at an

Angle of Attack of 10 Degrees

Figure 4.19: XFoil Separation Point Tracking Reynold’s Number of 650,000 at an

Angle of Attack of 10 Degrees

55

Figure 4.20: XFoil Separation Point Tracking

56

4.3 Wind Tunnel Flow Control Tests

Wind tunnel tests were performed using a La203a wing model. Two grooves cut into

the suction surface to enable the embedding of plasma actuators flush to the rest of

the surface. The wind tunnel tests were designed to test the plasma actuators under

different Reynolds numbers and different plasma activation states. The plasma actu-

ators were tested for flow control at 50,000, 75,000, 100,000, and 150,000 Reynolds

numbers. The different plasma activation cases consisted of testing the LE actuator

solo, aft actuator solo (placed at the 40% chord as stated above), and both actua-

tors being used together. For the different activation scenarios, two different things

were performed: one was to test steady activation of the plasma actuator, then the

actuators were pulsed at different frequencies to test unsteady activation. For all the

wind tunnel tests the wing was placed at an angle of attack of approximately 20 to 22

degrees to achieve full separation from the airfoil. This αstall was varied to provide a

deep stall condition. Fig. 4.21 illustrates the different plasma actuator configurations

tested during the wind tunnel investigation.

For a Reynolds number of 50,000, eight runs were performed. For all eight runs

the angle of attack was held constant at 20 degrees to achieve the deep stall condition

we were looking for. The first run for any case performed in this investigation was

a baseline test to compare between actuator off and actuator on conditions. For the

first run Fig. 4.22 shows a set of four graphs showing various measurements taken.

Fig. 4.22 (a) shows the velocity flow field with lines coming from the airfoil surface

to indicate where measurements were taken, and also shows clear flow separation and

deep stall. Fig. 4.22 (b) show the vorticity in the flow field. Fig. 4.22 (c) measures

Urms and (d) is a measurement of the Turbulent Kinetic Energy (TKE) within the

flow. By examining these for graphs you can also visually see the shear layer formed

57

Figure 4.21: Wind Tunnel Plasma Actuator Test Matrix

58

when the flow separated. Another measurement taken during testing was the reverse

flow probability. Reverse Flow Probability (RFP) is measured when a velocity vector

is divided by the mean velocity vector within the flow field. Fig. 4.23 shows the

RFP within the flow, and as can be seen, there was a high RFP along the airfoil,

illustrating a separated region. Since the angle of attack was placed so that a deep

stall condition was achieved, the flow separated close to the leading edge. The next

test that was preformed was to activate the LE actuator with a steady activation.

During this test the duty cycle was placed at 100% to achieve a constant plasma

activation. Fig. 4.24 shows that the flow was reattached by looking at Fig. 4.24 (a).

It can also be observed that there was a standing vortex that was generated by the

plasma actuator, Fig. 4.24 (b). The presence of the standing vortex demonstrated

that energy was injected into the flow to promote reattachment. To further show that

the flow was reattached Fig. 4.25 shows that the high probability of reverse flow along

the airfoil surface was gone. The third test performed was to pulse the LE actuator

at modulation frequency of F+ = 1. To achieve the pulsed activation the duty cycle

was reduced to 50%, actively lowering the power sent to the actuator. Both Fig. 4.26

and Fig. 4.27 showed when pulsing the plasma, attachment can still be achieved.

Examination of Fig. 4.26 (c) and (d) clearly shows where the plasma actuator was

injecting energy into the flow. The next two tests were performed using only the

aft plasma actuator placed at the 40% chord. These two tests were performed in the

same fashion as the tests performed on LE actuator. When this actuator was tested it

was seen that it had no effect on separation and results in Fig. 4.28 through Fig. 4.31

confirm this. Fig. 4.28 shows that the actuator was generating energy but because the

flow was so far separated, it had no effect, and this is confirmed further by Fig. 4.31.

The last three tests were all preformed with both the LE and aft actuators on. The

first two tests were performed the same way as the tests were performed on the LE or

aft actuators. The first test was performed with a steady activation and the second

59

test being the pulsed case where F+ = 1. The results for the steady activation can

be seen in Fig. 4.32 and Fig. 4.33. Fig. 4.32 (a) illustrates that the flow is reattached

to the surface. Fig. 4.32 (c) and (d) demonstrates where the two actuators were

injecting energy into the flow. Fig. 4.33 demonstrates that when the actuators were

activated in this configuration the RFP was decreased. It was observed that at the

40% chord location, there was a high RFP in this region, which would indicate that

the aft plasma actuator was active. The pulsed activation results are seen in Fig 4.34

and Fig. 4.35. Fig 4.34 (a) shows that the flow was reattached to the surface of the

airfoil just as it was in the previous cases. Fig. 4.35 further confirms that reattach

had been achieved when the actuators were activated in this manner. The final test

performed with both actuators on was to see if activating the plasma actuators out-

of-phase from each other had more of an effect than the regular pulsed case. The

initial results are pictured in Fig. 4.36 and Fig. 4.37. The initial findings presented

in Fig. 4.36 demonstrated that the flow had been reattached and Fig. 4.37 confirmed

it. When comparing Fig. 4.35 and Fig. 4.37 it was observed that there was a lower

RFP in the out-of-phase case than there was in the in-phase case.

60

Figure 4.22: Actuators Off (a) Flow Field Velocity Vectors, (b) Flow Field Vorticity,

(c) Flow Field Urms, (d) Flow Field TKE

Figure 4.23: Actuators Off Reverse Flow Probability within the Flow Field

61

Figure 4.24: Leading Edge Actuator, Constant Activation (a) Flow Field Velocity

Vectors, (b) Flow Field Vorticity

Figure 4.25: Leading Edge Actuator, Constant Activation Reverse Flow Probability

within the Flow Field

62

Figure 4.26: Leading edge Actuator, Pulsed Activation with an F+ = 1 (a) Flow

Field Velocity Vectors, (b) Flow Field Vorticity, (c) Flow Field Urms, (d) Flow Field

TKE

63

Figure 4.27: Leading edge Actuator, Pulsed Activation with an F+ = 1 Reverse Flow

Probability within the Flow Field

64

Figure 4.28: Aft Actuator, Constant Activation (a) Flow Field Velocity Vectors, (b)

Flow Field Vorticity, (c) Flow Field Urms, (d) Flow Field TKE

65

Figure 4.29: Aft Actuator, Constant Activation Reverse Flow Probability within the

Flow Field

Figure 4.30: Aft Actuator, Pulsed Activation with an F+ = 1 (a) Flow Field Velocity


66

Figure 4.31: Aft Actuator, Pulsed Activation with an F+ = 1 Reverse Flow Proba-

bility within the Flow Field

67

Figure 4.32: Steady Activation on the LE and Aft Actuators (a) Flow Field Velocity

Vectors, (b) Flow Field Vorticity, (c) Flow Field Urms, (d) Flow Field TKE

68

Figure 4.33: Steady Activation on the LE and Aft Actuators Reverse Flow Probability


Figure 4.34: Pulsed Activation with an F+ = 1 on the LE and Aft Actuators (a)

Flow Field Velocity Vectors, (b) Flow Field Vorticity

69

Figure 4.35: Pulsed Activation with an F+ = 1 on the LE and Aft Actuators Reverse

Flow Probability within the Flow Field

Figure 4.36: Out-of-Phase, Pulsed Activation with an F+ = 1 on the LE and Aft

Actuators (a) Flow Field Velocity Vectors, (b) Flow Field Vorticity

70

Figure 4.37: Out-of-Phase, Pulsed Activation with an F+ = 1 on the LE and Aft

Actuators Reverse Flow Probability within the Flow Field

71

A set of velocity profiles was generated for each run performed at seven locations

across the field of view. These seven locations are the red lines pictured in Fig. 4.22

(a) for each run. The x/c locations of the seven lines that are used for measurements

are as follows: 0.089, 0.155, 0.245, 0.340, 0.434, 0.538, 0.637. These profiles were then

plotted on top of each other to show how different activation cases affected the flow

differently. This comparison can be seen in Fig. 4.38. The black line in this figure

represents the separated case or the baseline. The red solid line represents steady

activation of the LE actuator and the dashed red line is the same actuator but with

pulsed activation with F+ = 1. The blue lines are the aft actuator cases represented

in the same fashion as the LE actuator cases. The green lines represent the cases

where both actuators were activated, with the solid line being the steady activation

and the dashed line being the pulsed, F+ = 1, in-phase case. It can be observed that

in four of the six activation cases presented in Fig. 4.38 reattachment was achieved.

In the two cases where the aft actuator was active, reattachment was not achieved

and the flow remained separated. The lower part of Fig. 4.38 also illustrates the

effect of the actuator activation on the vertical flow within the flow field. Along

the first measurement line it can be seen that the LE actuator was actually pulling

the flow inward toward the surface of the airfoil. Examining the third measurement

location it is seen that with the activation of the aft actuator, even in the cases where

reattachment was not achieved, the actuator was actively drawing in the air flow.

A further comparison was performed with the cases of in-phase and out-of-phase

activation of the actuators. This comparison can be seen in Fig. 4.39. The black

line here is the separated case, as it was before, the red line is the in-phase case,

and the blue line is the out-of-phase case. As can be observed in this figure, both

the in-phase and out-of-phase cases reattached the flow. Further observation reveals

that the out-of-phase case had a more favorable effect on the separated flow than the

72

in-phase case did at almost every location.

Figure 4.38: Velocity Profiles for 50,000 Reynolds Number Cases: Solid Black, No

Control; Solid red, LE Steady; Dashed Red, LE Pulsed F+ = 1; Solid Blue, Aft

Steady; Dashed Blue, Aft Pulsed F+ = 1; Solid Green, Both Steady; Dashed Green,

Both Pulsed F+ = 1 in-phase

73

Figure 4.39: Velocity Profile Comparison of In-Phase and Out-of-Phase Actuator

Activation at 50,000 Reynolds Number: Solid Black, No Control; Solid Red, Both

Pulsed F+ = 1 in-phasae; Solid Blue, Both Pulsed F+ = 1 out-of-phase

74

A similar set of eight runs were performed for a Reynolds number of 75,000.

Several things changed when than Reynolds number increased to 75,000. First, the

angle of attack had to be increased to 21-22 degrees to achieve the same type of deep

stall condition that was present when the Reynolds number was 50,000. In this set

of experiments, the aft actuator was not run alone, because when the aft actuator

was activated without the LE actuator in the previous runs, it had no effect on the

separated flow. Also a couple of different forcing frequencies had to be tested because

through some trial and error an F+ = 1 no longer reattached the flow as it did with a

Reynolds number of 50,000. The first run performed at 75,000 Reynolds number was

the separated case for all comparisons. Figs. 4.40 and 4.41 illustrate the separated

flow. Further trials with the standard actuator configuration demonstrated that these

plasma actuators had no effect on the separated flow, so a small alteration was made

to the setup. We connected a second transformer to the actuator so we had two

power leads connected to the same actuator, one hot lead to the exposed electrode

and another hot lead to the embedded electrode to effectively double the power input

to the actuator to 100 kV. The signal was then altered so that the two power leads

were 180 degrees out of phase from each other. This change allowed us to have a

better control authority over the actuator.

The next set of runs completed were with just the LE actuator active. The LE

actuator was tested with a steady activation and with a pulsed activation. The

constant activation of the LE actuator reattached the separated flow and this can be

seen in Figs. 4.42 and 4.43. Fig. 4.42 (a) demonstrates that the flow was reattached

during this activation and is confirmed by examining the RFP seen in Fig. 4.43.

Further examination of Fig. 4.42 (c) and (d) illustrates where the actuator is injecting

energy into the flow. During the pulsed activation cases, the actuator was pulsed at

three different forcing frequencies. The first frequency tested corresponded to F+ = 1.

75

Results for this test case are seen in Figs. 4.44 and 4.45. The flow separated again

under this condition, so it was decided to test some lower forcing frequencies to see if

pulsing the plasma had any effect at this Reynolds number. It was also observed that

the flow separated from the same location when the actuator was pulsed at F+ = 1

and when no actuator was on at all. Varying the forcing frequencies by 5-10 Hz

starting at 10 Hz, it was seen that a forcing frequency of 10 Hz and 15 Hz reattached

the flow, which correspond to F+ = 0.198 and 0.297 respectively. Forcing frequencies

above 15 Hz showed no effect on the flow which remained separated. The results with

F+ = 0.198 can be seen in Figs. 4.46 and 4.47. Fig. 4.46 (a) shows that the flow

was reattached and was confirmed in Fig. 4.47. F+ = 0.297 also showed favorable

results and was tested to compare to the case with F+ = 0.198. The results from the

F+ = 0.297 tests are illustrated in Fig. 4.48 and Fig. 4.49. Very similar results were

seen when comparing the two different F+ cases. Three runs were performed using

both the LE and aft actuator. One run was performed using a constant activation of

both actuators and the other two runs were pulsed activation. The two pulsed cases

had synchronous activation at F+ of 0.198 and 0.297. F+ = 1 was not tested in this

case because it proved ineffective when tested with the LE. The results from these

three runs can be seen in Figs. 4.50 through 4.55. The steady activation showed

similar results to when the two actuators were activated at a Reynolds number of

50,000. The largest difference was seen in Fig. 4.51, since the actuator had more

control authority there was a lower RFP for the Reynolds number flow of 75,000. For

the case where both actuators were active with F+ = 0.198, the flow was reattached

and is demonstrated in Figs. 4.52 and 4.53. Fig. 4.52 (a) illustrates that reattachment

was achieved, and the RFP in Fig. 4.53 supports this. The results for F+ = 0.297

when both actuators were on is pictured in Figs. 4.54 and 4.55. F+ = 0.297 with

both actuators on had similar results to that of F+ = 0.198 with both actuators on.

76




77

Figure 4.42: Leading edge Actuator, Constant Activation (a) Flow Field Velocity


78

Figure 4.43: Leading edge Actuator, Constant Activation Reverse Flow Probability



Field Velocity Vectors, (b) Flow Field Vorticity

79



Figure 4.46: Leading edge Actuator, Pulsed Activation with F+ = 0.198 (a) Flow


80

Figure 4.47: Leading edge Actuator, Pulsed Activation with F+ = 0.198 Reverse




81





82



83

Figure 4.52: Pulsed Activation on the LE and Aft Actuators with F+ = 0.198 (a)

Flow Field Velocity Vectors, (b) Flow Field Vorticity, (c) Flow Field Urms, (d) Flow

Field TKE

84

Figure 4.53: Pulsed Activation on the LE and Aft Actuators with F+ = 0.198 Reverse




85



86

Profiles for each of the runs performed for Reynolds number 75,000 are shown

in Fig 4.56. Each one of the profiles were plotted together to show comparisons

between all the runs. The black line represents the baseline separated case. The four

runs performed on the LE actuator are shown by the red line. The solid red line is

the constant activation case, the dashed line is the pulsed case at an F+ = 1, the

dash-dot line is the pulsed case with F+ = 0.198 and the dotted line is the case with

F+ = 0.297. The case when both the LE and aft actuators were activated together are

shown by the blue lines. The case with constant activation is the solid line, the dashed

line is F+ = 0.198, and the dash-dot line is the case with F+ = 0.297. Fig 4.56 shows

that every case except one reattached the flow. The only case that did not reattach

the flow was the case where the LE actuator was activated with F+ = 1. The case

that provided the best results seemed to be when both actuators were activated with

constant activation. The bottom part of Fig 4.56 shows that when the LE actuator

was active that it pulled flow inward towards the actuator from the flow above the

actuator.

87


Control; Solid Red, LE Steady; Dashed Red, LE Pulsed F+ = 1; Dash-Dot Red, LE

Pulsed F+ = 0.198; Dotted Red, LE Pulsed F+ = 0.297; Solid Blue, Both Steady;

Dashed Blue, Both Pulsed F+ = 0.198; Dash-Dot Blue, Both Pulsed F+ = 0.297

88

Eight more runs were performed at a Reynolds number of 100,000. The angle

of attack that was needed to maintain the deep stall condition that was desirable

was about 22 degrees. The runs that were performed here were the same runs that

were performed when the Reynolds number was 75,000. The first run was with no

actuators active. This was the separated flow case that was used for comparison.

The separated flow can be seen in Figs. 4.57 and 4.58. These figures demonstrate

that the flow is separated from the airfoil, as is seen with the share layer in Fig. 4.57

(a) through (d), and with the high RFP seen in Fig. 4.58. The next four tests were

performed using the LE actuator. The first test was to activate the LE actuator

with a steady activation. The results are seen in Figs. 4.59 and 4.60. Reattachment

was achieved in this configuration and these two graph illustrate this. Fig. 4.59 (a)

shows that the flow had been reattached to the surface of the airfoil while (c) and

(d) both show where the LE actuator injected energy into the flow. Further proof of

reattachment in this configuration is seen in Fig. 4.60 because the high RFP seen in

the previous case is gone. The next configuration run was to pulse the LE actuator

with F+ = 1 to see if the flow would reattach. Figs. 4.61 and 4.62 show that the flow

was not reattached when the LE actuator was pulsed with F+ = 1. The last two

runs that were performed on the LE actuator was to pulse the actuator with a forcing

frequency of 10 Hz and 15 Hz or F+ = 0.148 and F+ = 0.222 respectively. The results

for F+ = 0.148 are seen in Figs. 4.63 and 4.64. For this case it was observed that the

flow was reattached along the surface of the airfoil. For the last test performed on

the LE actuator with F+ = 0.222, the results are presented in Figs. 4.65 and 4.66. It

can be seen that when the LE actuator was pulsed with F+ = 0.222, that the results

were very similar to the case when the LE actuator was pulsed with F+ = 0.148.

The last set of runs performed at this Reynolds number were to have both actuators

active. Three runs were completed for this configuration. The first run was to have

89

the actuators active with a steady activation. The results from this run are pictured

in Figs. 4.67 and 4.68. Just as was observed for the LE case, this configuration also

reattached the flow to the surface of the airfoil. It can be observed that the RFP

in Fig. 4.68 along the surface of this case was lower than that of the case when just

the LE actuator was used as pictured in Fig. 4.60. The next test was to run both

actuators pulsed with F+ = 0.148. Results are seen in Figs. 4.69 and 4.70. These

figures illustrate that the flow was reattached for this configuration as was recorded

before with just the LE actuator active. It can be observed that the aft actuator is

active by examining the RFP in Fig. 4.70. The last test run at this Reynolds number

was to pulse both actuators at F+ = 0.222. The results from this test are presented

in Figs. 4.71 and 4.72. The flow reattached for this case as can be observed in these

two figures.



90


Figure 4.59: Leading edge Actuator, Constant Activation (a) Flow Field Velocity


91

Figure 4.60: Leading edge Actuator, Constant Activation Reverse Flow Probability




92





93





94





95





96



97


Flow Field Velocity Vectors, (b) Flow Field Vorticity, (c) Flow Field Urms, (d) Flow

Field TKE

98



99

Profiles for each of the runs performed for Reynolds number 100,000 are shown in

Fig 4.73. Each one of the profiles was plotted together to show comparisons between

all the runs. The black line represents the baseline separated case. The four runs

performed on the LE actuator are shown by the red line. The solid red line is the

constant activation case, the dashed line is the pulsed case at F+ = 1, the dash-

dot line is the pulsed case with F+ = 0.148 and the dotted line is the case with

F+ = 0.222. The cases when both the LE and aft actuators were activated together

are represented by the blue lines. The case with constant activation is the solid line,

the dashed line is F+ = 0.148, and the dash-dot line is the case with F+ = 0.222.

Fig 4.73 shows that every case except one reattached the flow. The only case that

did not reattach the flow was the case where the LE actuator was activated with

F+ = 1. The bottom part of Fig 4.73 shows that when the LE actuator was active

that it pulled flow inward towards the actuator from the flow above the actuator. The

vertical fluctuation for this Reynolds number was less evident due to the increase in

freestream velocity.

100


Control; Solid Red, LE Steady; Dashed Red, LE Pulsed F+ = 1; Dash-Dot Red, LE

Pulsed F+ = 0.148; Dotted Red, LE Pulsed F+ = 0.222; Solid Blue, Both Steady;

Dashed Blue, Both Pulsed F+ = 0.148; Dash-Dot Blue, Both Pulsed F+ = 0.222

101

CHAPTER 5

Discussion and Conclusions

5.1 Discussion

We have investigated the use of plasma actuators for airfoil separation flow con-

trol. We first examined the impact of actuator configuration on the jet velocity and

momentum, namely actuator material or dielectric constant, for a variety of input pa-

rameters including plasma frequency, modulation frequency, and voltage difference.

Once an optimum configuration for maximum jet velocity was determined, this was

applied to controlling separation over a La203a airfoil at low Reynolds numbers.

From the bench-top tests, it was observed that depending on what task is being

performed, that different dielectric materials are better for particular situations. In

the case that a material’s physical properties do not matter as much as achieving

the strongest plasma jet possible, the alumina dielectric material was the best choice

for the job. If a material is needed to perform at a wider range of input voltages

without the material failing, then acrylic is the best material for a mid-range plasma

jet generation. As was required for this investigation, the material’s ability to be

formed to a surface was the most desirable parameter. It would have been desirable

if the alumina or acrylic could have been used for this task, but both materials lacked

the flexibility or manufacturability that the Teflon could provide. So for the task of

affixing a plasma actuator to the surface of an airfoil, Teflon provided the needed

flexibility, so to write.

While investigating the La203a airfoil, it was seen that it has a tendency to stall

at the trailing edge and with the separation point moving forward as the angle of

102

attack is increased, which is the typical trend for a “fat” airfoil. Two strategies

were investigated for separation flow control. By placing a plasma actuator near

the leading edge the plasma jet can affect the leading edge separation bubble. By

placing an actuator at the 40% chord the plasma jet is adding momentum close to the

separation point at higher angles of attack and impacting the incipient separation.

The added momentum being added to the flow in these key locations provides the

best chance to maintain flow attachment.

From the wind tunnel test data, boundary layer profiles were graphed for each

of the runs. The boundary layer profiles provides critical information about the flow

characteristics over a surface, such as if the flow is laminar, turbulent or even if the flow

is separated. Two additional boundary layer parameters that were calculated from

the profile data for all the tests include δ∗ and θ, the displacement and momentum

thicknesses respectively. δ∗ and θ measures the mass and momentum flux within the

flow. These equations are very useful all the way until separation occurs, once the

flow is separated these two parameters become ill defined. Thus, these should be

used in conjunction with the profile or skin friction data. As an example of this,

Fig. 5.1 illustrates the case where no flow control was active for a Reynolds number

of 50,000 at an angle of attack of approximately 20 degrees. If the boundary layer

was just showing typical growth behavior the slope should not be negative anywhere.

Similar observations were seen for many of the cases where the flow was separated

or unaffected by the plasma actuators, such as seen in Fig. 5.2. For a case where

the plasma actuators were used to control separation, it was observed that the two

parameters had a negative slope. This negative slope demonstrates that the boundary

layer growth is being reversed and that the boundary layer is shrinking. The test case

where the LE actuator was run under constant activation at a Reynolds number of

50,000 is pictured in Fig. 5.3. Cases where both actuators were used had results very

similar to those pictured in Figs. 5.4 and 5.5.

103

Figure 5.1: δ∗ and θ Vs. x/c for 50,000 Reynolds Number, Actuators Off

Figure 5.2: δ∗ and θ Vs. x/c for 50,000 Reynolds Number, Aft Actuator, Constant

Activation

104

Figure 5.3: δ∗ and θ Vs. x/c for 50,000 Reynolds Number, Leading Edge Actuator,

Constant Activation

105

Figure 5.4: δ∗ and θ Vs. x/c for 75,000 Reynolds Number, Constant Activation on

the LE and Aft Actuators

106

Figure 5.5: δ∗ and θ Vs. x/c for 100,000 Reynolds Number, Pulsed Activation on the

LE and Aft Actuators with F+ = 0.222

107

Specific configurations of SDBD plasma actuators for separation control depend on

the particular application. For a situation where the only goal is to control separation

at the LE and power consumption is not a factor, then using just a LE actuator is a

good solution, since separation was controlled across the range of Reynolds numbers

investigated. Another option would be to use an array of actuators starting at the LE

and moving aft to control separation over a much wider range of the airfoil, as was seen

when both the LE and aft actuators were used together. When power consumption

is a concern, using an actuator in a pulsed fashion as was done in this investigation,

the actuator uses 50% less power because it is only on for half the time. Using two

pulsed actuators at a duty cycle of 50% consumes the same amount of power as one

actuator alone, so in cases where separation is an issue in multiple locations, multiple

pulsed actuators would be a better choice.

5.2 Conclusions

This thesis had several objectives. The first objective was to examine how different

geometries in a SDBD plasma actuator affect each of the three dielectrics in bench-top

testing. The three dielectrics tested were Teflon, acrylic, and alumina. The results

from the bench-top testing were then implemented in wind tunnel tests. The second

objective was to attempt to control separation on an airfoil at different Reynolds

numbers using different plasma actuator configurations at post-stall angles of attack.

Bench-top testing demonstrated that the alumina produced the strongest plasma

jet of the three dielectric materials, with a maximum jet velocity of 161 cm/s at a

plasma frequency of 8,000 Hz. The alumina also proved to be a very brittle material

and would not be the ideal material for any surface with curvature, unless it was

machined that way from the start. The alumina was relatively unaffected by changes

in plasma frequency. The acrylic demonstrated that it could withstand a much wider

108

range of input voltages than that of the other two dielectrics, but when at some of

the lower voltages, the plasma jet was very weak and unusable. The acrylic had a

maximum input voltage of 80 kV and produced a jet velocity of 146 cm/s at a plasma

frequency of 7,000 Hz. The acrylic was more sensitive to plasma frequency than the

alumina. The acrylic proved to be less brittle than the alumina but was still not

malleable enough to conform to a surface unless designed to do so. The Teflon was

shown to produce a plasma jet velocity of 110 cm/s at a plasma frequency of 15,000

Hz, and was affected greatly by varying the plasma frequency. This jet velocity was

achieved with an input voltage of 50 kV. Teflon is a very flexible material, therefore

making it an ideal material for a highly curved surface like an airfoil. Even though

the Teflon did not produce the strongest jet velocity it was chosen as the dielectric

material to be used on the wing test model in the wind tunnel for several reasons:

One it produced a moderately strong plasma jet velocity, also Teflon actuators were

easy and very cheap to make, and finally, Teflon provided the flexibility that was

needed to attach an actuator to the LE of an airfoil.

Wind tunnel testing demonstrated that plasma actuators were effective for Reynolds

numbers up to 150,000 at the power levels used herein. For tests completed at 50,000

Reynolds number, all cases tested were able to reattach a separated flow over the

La203a wing model except when the aft actuator was run alone. This was the case

because when the wing was placed at a 20 degree angle of attack, it was in a deep

stall configuration and the actuator was just not able to draw the air flow back to the

surface. The wind tunnel test matrix was adjusted upon observation of these tests

and can be seen in Fig. 4.21. As it is seen in the test matrix a reduced frequency

of F+ = 1 was used for the pulsed cases at this Reynolds number, and separation

control was achieved as pictured in Fig. 5.6. No other reduced frequencies were inves-

tigated at a Reynolds number of 50,000 because separation control was achieved with

F+ = 1. For Reynolds number of 75,000 similar results were recorded for many of the

109

test cases. Separation control was achieved for all test cases except when the LE ac-

tuator was pulsed at F+ = 1. An array of reduced frequencies was tested to examine

if reattachment could be achieved for a pulsed configuration. F+ was examined from

0.099 < F+ < 9.885. It was observed that F+ = O (1) and F+ > 1 separation con-

trol did not work. While testing the lower frequencies, a modulation frequency of 10

and 15 Hz was observed to reattach the flow, corresponding to reduced frequencies of

F+ = 0.198 and F+ = 0.297, respectively. Frequencies higher than this had no effect

on the separated flow and were also not considered for further testing as is seen in the

test matrix. The same set of tests were run at 100,000 Reynolds number. Separation

control was achieved for test runs in this Reynolds number. For pulsed cases F+ = 1

was tested again and still had no effect, so the lower frequencies found for 75,000 were

examined. Both modulation frequencies of 10 and 15 Hz, corresponding to reduced

frequencies of F+ = 0.148 and F+ = 0.222, reattached the separated flow. During

the initial testing of 150,000 Reynolds number, no separation control was achieved

for any cases including both steady and pulsed activation case with F+ correspond-

ing to F+ = 1, 0.099 and 0.148. This is due to the limited control authority of the

plasma actuator. Fig. 5.6 summarizes the separation control demonstrated during

the pulsed activation cases. According to the literature F+ > 1 should be a more

effective control strategy, but on the contrary it was observed that F+ < 1 improved

flow control performance that F+ = O (1) did not demonstrate. In conclusion, it was

demonstrated that separation control can be achieved using plasma actuators while

at lower Reynolds numbers.

110

Figure 5.6: F+ Vs. Reynold Number for Pulsed Activation Tests

111

5.3 Recommendations

In this thesis bench-top testing of three common dielectric materials was performed.

The state of the art of plasma actuators and their materials has been constantly

evolving and will continue to evolve. There are several tests that need to be performed.

First, this research should return to the bench-top to evolve the science along with

the new technology. A list of all materials needs to be created, then systematically

tested for a variety of parameters. Test all materials in the same configuration to

examine their performance. Then test other parameters such as; material thickness,

electrode configuration, and power to examine their effects. Develop some trends

that illustrate how increasing material thickness effects the velocity produced by the

plasma jet. Then examine how the electrode configuration affects the jet velocity by

testing several configurations such as; have the two electrodes with different widths,

have a gap (or overlap) between the trailing edge of the exposed electrode and the

leading edge of the embedded electrode, test how different shapes of the electrode

effect like a chevron or serpentine configurations. Finally test each material for an

operational voltage range, so to develop an upper limit for a particular material. With

that upper limit documented, that actuator can then be operated for a longer period

of time without burning out.

A second set of tests that would need to be run on this new technology would be

to take the best configuration from the bench-top and apply it to a series of wind

tunnel tests. The testing should start on a flat plate to expand the science of these

actuators to incorporate the effect of a fluid flow over the actuator. By developing

this freestream test model, a change in velocity, (∆V ), can be demonstrated. With a

known ∆V for a particular actuator an actuator can be chosen for a specific situation.

Once the specifics for a particular actuator is known, test parameters like duty cycle,

112

how multiple actuators in an array, and phasing multiple actuators effect that change

in velocity. Now with the ∆V is known for a vast amount of actuator designs, create

a test case that has a constant pressure gradient or known pressure gradient. With

these test cases develop a method for comparing the ∆V for a known actuator to a

dimensionless pressure gradient coefficient, such as Pohlhausen or Thwaites’ param-

eter [26]. With this relationship it will be known if a particular plasma actuator can

control a specific pressure gradient.

Separation control has been demonstrated in this paper, but not other aerody-

namic performance effects. Activation of the plasma actuators created a vortex and

body force that effected the flow. It was not examined in this thesis whether these

entities improved or reduced the aerodynamic performance of an airfoil. According

to the literature, both an increase and decrease to lift has been seen. Lift, drag and

moment need to be measured to examine the aerodynamic effects of these actuators.

The setup illustrated above needs to be placed on a lift balance and run with the

same settings as were used in this investigation to get the lift and drag data. A test

wing with static pressure ports needs to be created and tested to gather the pressure

distribution and moment calculations.

This investigation concentrated on orienting the plasma actuators such that the

plasma jet was generated in the direction of the flow. With the jet positioned in this

manner the momentum is injected into boundary layer in the flow direction, thereby

energizing the downstream flow. A further investigation needs to be performed into

what effect a plasma actuator positioned to generate a counter-flow plasma jet.

113

APPENDIX A

High Re Testing

The appendix contains results from testing a larger La203a airfoil in the OSU subsonic

wind tunnel at high Reynolds numbers. Due to time constraints and limited control

authority found in the small scale testing, plasma actuator flow control tests were not

performed. However, the baseline results are included here for completeness and to

serve as a reference for future experiments.

A.1 Wind Tunnel Setup

In a joint effort between the University of Kentucky (UK) and Oklahoma State Uni-

versity (OSU) a larger Liebeck La203a wing was made using a SLA rapid prototyper.

This larger wing had a span of 36 inches and a chord length of 8 inches. This wing

fit snugly into the OSU large wind tunnel. This wing was designed with a series

of pressure ports designed to measure the coefficient of pressure along the top and

bottom side of the wing. A total of 25 pressure ports were designed into the wing, 12

on the top, 12 on the bottom and one at the leading edge. A 3D CAD model for this

wing is shown in Fig. A.1 and a finalized SLA wing is illustrated in Fig. A.2.

114

Figure A.1: La203a Large Wind Tunnel Wing CAD Model

115

Figure A.2: La203a Large Wind Tunnel Wing

116

The OSU low-speed subsonic wind tunnel will serve as the main test facility for

the laboratory tests. A schematic of the OSU wind tunnel is illustrated in Fig. A.3.

The low turbulence wind tunnel is an open loop wind tunnel with 1:16 contraction

and has a clear test section with a cross-section of 1x1m and 2 m long with swappable

test sections. A 125 hp centrifugal fan powers the tunnel and has a top speed of 70

m/s. Tunnel speed is controlled with a feedback control mechanism and monitored

by multiple Pitot-static probes. The tunnel is instrumented with wall mounted lift

and drag balance and a traversing Pitot-static probe. The layout of the lift and drag

balance and Pitot-static probe can be seen in Fig. A.4 and Fig. A.5.

Two wall mounted balances are placed on both sides of the test section, mounted

on an external bracket. Each balance consists of two Transducer Technologies strain

gages that be can tailored to the specific tests load expectations. The strain gages

are conditioned using a model 2120B Vishay Strain Gage Conditioner. Each load

cell is calibrated separately using calibration weights prior to each wind tunnel test.

Labview and a NI USB-6158 DAQ unit is used to monitor and record the data at

typically 1 kHz. The pyramidal balance is a 6 component Aerolab model with load

limits for lift, drag, and side forces of 275, 85 and 95 lbs, respectively, and 720 in-lbs

for pitching, yawing, and rolling moments.

High fidelity velocity data are obtained using either a hot-wire or PIV system

(discussed above). Multiple Dantec MiniCTA hot-wire systems are available to mea-

sure velocity and velocity fluctuations at multiple points in the tunnel simultaneously.

Both single and two component hot-wires are available.

Pressure measurements were taken using a bank of water manometers. This bank

of manometers consists of 50 individual water filled manometers, which are all linked

to an adjustable reservoir. The manometer has a 44 inch range, with 22 inches for

positive pressures and 22 inches for negative pressures. Each one of the manometer

117

tubes can then be hooked to individual ports to allow for a pressure profiles. The

manometer bank is illustrated in Fig. A.6.

Figure A.3: OSU Large Low-Speed Wind Tunnel

Figure A.4: OSU Wind Tunnel Test Section with Lift/Drag Balances and Pitot-Static

Tube for Wake Surveys

118

Figure A.5: OSU Wind Tunnel Test Section with Lift/Drag Balances and Pitot-Static

Tube for Horizontal Sweeps

119

Figure A.6: Manometer Bank

120

A.2 Subsonic Wind Tunnel Results: La203a Performance

Tests on the La203a airfoil were performed in the OSU wind tunnel to determine

baseline performance parameters and to compare with the reported data, as given

by Camacho and Liebeck [10]. The reported data is shown in Fig. A.8, Fig. A.9 and

Fig. A.10.

Based on the data taken during these wind tunnel tests on the large La203a wing,

it was seen that we were able to obtain a fairly good comparison to the actual data

taken for that airfoil. The original data taken for this airfoil can be seen in Fig. A.7.

These test were done using a bank of water manometers to collect the coefficient of

pressure measurements over the wings surface through pressure ports designed into

the wing. The raw data form these tests are seen in Fig. A.8. Looking at Fig. A.9

you can see how well our lift curve fit to both the reported lift curve and the lift

curve that is predicted using XFoil. Through further experimentation at different

Reynold’s numbers our lift curves remained close to the same throughout the runs.

At a Reynold’s number of 250,000 we had a slight shift in the lift curve as can be

seen in Fig. A.10.

From the tests done in the large wind tunnel on the large La203a wing model

sereval things were discovered. First off the construction method used to create the

pressure ports allowed for acquisition of pressure measurements over a large angle of

attack sweep and a wide range of reynold’s numbers. These ports were easy to hook

up to a bank of water manometers to observe the distribution of pressure across the

surface of the airfoil. I feel that if there were several more ports near the leading

edge it would allow for a better resolution at the higher angles of attack. With this

wing we were able to repeat the actual data that was done by Camacho and Liebeck

[10] seen in Fig. A.7. This comparison illustrated in Fig. A.9 and Fig. A.10 is how

121

Figure A.7: La203a Airfoil Performance Curves (taken from Liebeck [10])

Figure A.8: La203a Experimental Coefficient of Pressure Data for Different Angles

of Attack Ranging from -6 degrees to 16 Degrees

122

Figure A.9: Experimental, Computational, and Reference for the Lift Curve of a

La203a Airfoil

Figure A.10: Comparison of the Multiple Lift Curves at Several Different Reynold’s

Number

123

accuratly we were able to repeat the actual data in our wind tunnel. The biggest

difference was about 1% near stall.

124

APPENDIX B

Input File and MATLAB Codes

B.1 WaLPT Algorithm Input File

lptmode, 0=singlepass, 1=small to large, 2=large to small, 3= LPT

2 2 0 1

input file names ( one line per file )

run1.lst

processed\run1

image size nxc, nyc, pixr

1008 1018 10 1.00

flow size, nxf, nyf

1008 1018

flow offset, xf, yf

0 0

window size, nxw, nyw, 2**n

32 32

amod, min, max windows dimensions 2**n, correlaltion level corlvl

0 8 32 0.50

step size, nxs, nys

12 12

window type, wtype 1-7, see source listing

1

125

peak type, ptype 0=grid,1=parabolic,2=gaussian

2

laundary type, ltype 0=no laundering,1=rejection

0

extension parameter, 0= none, zero padding, 1= smooth (nth order)

1

filter widths (1/) fltrwx,fltrwy; 0= no filtering, 1,2,.. higher

10 10 1

wall parameters: nwalls, parex, motion, intflag, outmask

1 0 0 0 1

wall geometry file

mask8bit.bin

motion parameters: dxcg, dycg ,rot

0.0 0.00 0.00

0.00 0.00 0.00

0.00 0.00 0.00

B.2 MATLAB Codes

B.2.1 Mask Generation Code

%FIRST MASK

%path=’C:\XCAP\images\shunt\masks\’;

%path=’/Volumes/Big Daddy/karthik/’

path2=’K:\10.01.09\’

126

%path2=’C:\XCAP\data\06.19.09\’

maskfile=strcat(path2,’mask10bit.bin’)

maskfile2=strcat(path2,’mask8bit.bin’);

nxc=1008;

nyc=1018;

colormap(gray);

% load 10 bit xcap image as 16 bit image

fid=fopen(maskfile,’r’);

maskimage=fread(fid,[nxc,nyc],’int16’);

st=fclose(fid);

figure(1);

imagesc(maskimage.’),axis off,title(’original mask’);

% set values in array to floor and ceiling of the raw xcap image

for i=1:nxc;

for j=1:nyc;

if maskimage(i,j)>240;

%maskimage(i,j)=0;

maskimage(i,j)=0;

else

%maskimage(i,j)=255;

maskimage(i,j)=255;

end

127

end

end

% figure(1);

% imagesc(maskimage.’),colormap(gray),axis off,title(’rough mask’);

%save the mask file(s)

fid=fopen(maskfile2,’w’);

fwrite(fid,maskimage,’int8’);

st=fclose(fid);

% display mask

figure(2);

colormap(gray);

imagesc(maskimage.’),axis off,title(’final mask’);

%end

B.2.2 PIV Post-Processing

function simp_piv

% program to average turbine data sets

base=’run’;

%base=’runpvgj’

re=75;

run=1

128

ntot=63; %number of tensor files

uinf=0.15*re*1000/(6*2.54)

%set base path of files

%basepath=’E:\jacob\processed\’;

%basepath=’E:\mark\piv\30may03\processed\’

%basepath=’C:\Documents and Settings\FML\My Documents\Mark\PIV\19May03\’

%basepath=’D:\11.20.02 processed’

basepath=’K:\shawn\03.06.10\processed\’;

wallpath=’K:\shawn\03.06.10\’;

%conversion info - spatial and temporal scales to give units in cm/s

scale=89.01; %pixels/cm

pulse=20; %in micro-seconds

%conversion factors to cm/s

convel=(scale*pulse/1000000);

convor=(pulse/1000000);

%check image

%check array size

k=1; [ny,nx]=tensfunc2(base,run,k,basepath)

%set size of arrays

%nx=83;ny=82;

129

%create empty arrays

uav=zeros(ntot,nx,ny);

vav=zeros(ntot,nx,ny);

vortav=zeros(ntot,nx,ny);

contav=zeros(ntot,nx,ny);

un=zeros(nx,ny);

vn=zeros(nx,ny);

vorn=zeros(nx,ny);

conn=zeros(nx,ny);

corn=zeros(nx,ny);

rfp=zeros(nx,ny);

sep=zeros(nx,ny);

urms=zeros(nx,ny);

dudxn=zeros(nx,ny);

dvdxn=zeros(nx,ny);

dudyn=zeros(nx,ny);

dvdyn=zeros(nx,ny);

%characteristic velocity based on 5400 fpm (~30 m/s)

uf=30;

%chord length

chord=6*2.54;

%read in data files

for i=1:ntot,

% i=38;

130

[u,v,vort,cont,corr,dudx,dvdx,dudy,dvdy]=tensfunc(base,run,i,basepath);

un=u+un;

vn=v+vn;

vorn=vort+vorn;

conn=cont+conn;

corn=corr+corn;

uav(i,:,:)=u;

vav(i,:,:)=v;

vortav(i,:,:)=vort;

contav(i,:,:)=cont;

dvdxn=dvdxn+dvdx;

dudyn=dudyn+dudy;

dudxn=dudxn+dudx;

dvdyn=dvdyn+dvdy;

neg_pixels=0;

for j=1:nx

for k=1:ny

if u(j,k) < 0,

neg_pixels=neg_pixels+1;

rfp(j,k)=rfp(j,k)+1;

end

end

end

% calculate the area of the region of separation in camera view

(grid)

total_size=size(u);

long=total_size(1);

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wide=total_size(2);

total_area=long*wide;

fract_neg_area(i)=neg_pixels/total_area;

% determine the point of separation

% eliminate values nearest blade surface

for kk=1:ny

flag=0;

for k=nx:-1:1

if u(k,kk)~=0

if flag==0

u(k,kk)=0;

end

flag=1;

end

end

end

exit=0;

sep_point_d(i)=0;

sep_point_o(i)=0;

for over=47:ny,

for down=40:nx,

if u(down,over)<0 & exit==0,

sep(down,over)=0;

sep_point_d(i)=down;

sep_point_o(i)=over;

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exit=1;

else

sep(down,over)=255;

end

end

end

end

%%%%%%%%%%%%%%% PROCESSING %%%%%%%%%%%%%%%%%%%%%

%set edge regions to zero if need be

un(:,1)=0; vn(:,1)=0; vorn(:,1)=0; rfp(:,1)=0;

un(:,2)=0; vn(:,2)=0; vorn(:,2)=0;

un(1,:)=0; vn(1,:)=0; vorn(1,:)=0;

un(:,ny-1)=0; vn(:,ny-1)=0; vorn(:,ny-1)=0;

un(:,ny)=0; vn(:,ny)=0; vorn(:,ny)=0;

%set edges for individual arrays

uav(:,:,1)=0; uav(:,:,2)=0;

uav(:,:,3)=0; uav(:,:,4)=0;uav(:,1,:)=0;

uav(:,:,ny)=0; uav(:,:,ny-1)=0;

vav(:,:,1)=0; vav(:,:,2)=0;

vav(:,:,3)=0; vav(:,:,4)=0;vav(:,1,:)=0;

vav(:,:,ny)=0; vav(:,:,ny-1)=0;

vortav(:,:,1)=0; vortav(:,:,2)=0;

vortav(:,:,3)=0; vortav(:,:,4)=0;vortav(:,1,:)=0;

vortav(:,:,ny)=0; vortav(:,:,ny-1)=0;

133

% eliminate values nearest blade surface

for kk=1:ny

flag=0;

for k=nx:-1:1

if un(k,kk)~=0

%k,kk

if flag==0

un(k,kk)=0;

vn(k,kk)=0;

rfp(k,kk)=0;

end

flag=1;

end

end

end

%calculate averages

un=un/ntot; vn=vn/ntot; vorn=vorn/ntot; conn=conn/ntot; corn=corn/ntot;

dudyn=dudyn/ntot; dvdxn=dvdxn/ntot; dudxn=dudxn/ntot; dvdyn=dvdyn/ntot; rfp=rfp/ntot;

%scale data

un=un/convel;

vn=vn/convel;

vorn=vorn/convor;

vortav=vortav/convor;

134

%calculate Re based on average velocity

%REDO FOR TURBINE BLADE, BASE ON VELOCITY MAG and SSL TO COMPARE WITH RE ABOVE

umean=mean(mean(un(:,:)));

re=umean*chord/0.151;

fprintf(’\n Approximated average u velocity is %6.2f cm/s\n Re based on this is %5.0f\n’,umean,re);

% play with FFT

% ctf=fft2(un);

% size(ctf);

% nfft=length(ctf);

% power=abs(ctf(1:nfft/2)).^2;

% freq=(1:nfft/2)/(nfft/2)*0.5;

%plot(ctf,’ro’)

%plot(1./freq,power)

fprintf(’\nThinking....’)

%calculate tke turbulence

for j=1:nx

fprintf(’.’)

for k=1:ny

dum1=0; dum2=0; dum3=0;

for i=1:ntot

%dum1=sqrt(un(j,k)^2+vn(j,k)^2);

dum2=sqrt(uav(i,j,k)^2+vav(i,j,k)^2)+dum2;

%dum3=(dum1-dum2)^2+dum3;

135

end

tke(j,k)=dum2/ntot;

%urms(j,k)=sqrt(dum3)/ntot;

end

end

mag=sqrt(un.^2+vn.^2);

urms=std(uav,0,1);

urms=squeeze(urms);

vrms=std(vav,0,1);

vrms=squeeze(vrms);

velrms=sqrt(urms.^2+vrms.^2);

%skin friction coef.

% mu=0.0000185;

% shear=mu*dvdxn;

% cf=shear/(0.5*1.23*uf^2);

%cf=cf(1,12:82);

%size(cf)

%% PLOTTING

fprintf(’\nPlotting\n’)

offset=5;

xllim=offset;

136

yllim=offset;

xulim=nx-offset;

yulim=ny-(offset);

%yllim=20;

%yulim=50;

%vertices for patch command for slab (if needed)

xc=9; yc=27;

x=[1 81 81 xc xc 1];

y=[45 45 40 40 yc yc];

mean(mean(vortav));

%non-averaged plots (for movies)

%for i=1:ntot,

%figure(i)

%colormap jet;

%plot

%contourf(squeeze(vortav(i,:,:)),50),axis off, axis equal,axis([xllim xulim yllim yulim]),title(’Vorticity’),axis ij,shading flat;

%quivernodot(squeeze(uav(i,:,:)),squeeze(vav(i,:,:)),5,’b’),axis equal,axis([xllim xulim yllim yulim]),axis ij,axis off

%dump

%dumpfile=strcat(’g:\output\Tecplot\run’,int2str(run),’r’,int2str(ren),’a’,int2str(alf),’-’,int2str(i),’.dat’)

%fid=fopen(dumpfile,’w’)

%fprintf(fid,’variables = "x", "y", "phi"\n’);

%fprintf(fid,’zone i=%i j=%i f=point\n’,nx,ny);

%for k=ny:-1:1

137

% for j=1:nx

% fprintf(fid,’%f %f %f\n’,(k-1)*0.4/82+0.3,(j-1)*0.2/81,vortav(i,j,k)/mean(mean(vortav(i,:,:))));

% end

% end

%fclose(fid);

%end

%rotate the data

%un=rot90(un,-1);vn=rot90(vn,-1);mag=rot90(mag,-1);

%vorn=rot90(vorn,-1);conn=rot90(conn,-1);rfp=rot90(rfp,-1);

%urms=rot90(urms,-1); corn=rot90(corn,-1);

%dvdxn=rot90(dvdxn,-1); dudyn=rot90(dudyn,-1);

%dudxn=rot90(dudxn,-1); dvdyn=rot90(dvdyn,-1);

% % wallpath determination

% if (re == 30)

% if (run <= 14)

% wallpath=’E:\mark\piv\30may03\processed\walls1\’;

% else wallpath=’E:\mark\piv\30may03\processed\walls2\’;

% end

% end

% if (re == 50)

% if (run <= 9)

% wallpath=’E:\mark\piv\30may03\processed\walls1\’;

% else wallpath=’E:\mark\piv\30may03\processed\walls2\’;

% end

138

% end

%wallpath=’E:\jacob\processed\’;

%wallpath=’E:\mark\piv\30may03\processed\walls1\’;

%wallpath=’E:\mark\piv\30may03\processed\walls2\’;

%wallpath=’E:\mark\piv\30may03\processed\’;

%wallpath=’C:\Documents and Settings\FML\My Documents\Mark\PIV\19May03\’;

% read in wall info for wall.*** files

avefile=strcat(wallpath,’wall.ave’)

[avex,avey]=textread(avefile,’%n %n’);

%avex=flipud(avex);

linfile=strcat(wallpath,’wall.lin’);

[linx,liny]=textread(linfile,’%n %n’);

linx=flipud(linx);

extfile=strcat(wallpath,’wall.ext’);

[extx,exty]=textread(extfile,’%n %n’);

extx=flipud(extx);

% This make corrections to the surface

avexoffset = 40;

aveyoffset = -10;

avex=avex+avexoffset;

avey=avey+aveyoffset;

% Convert lin,ave data from pixel size (nyc=1018) to vector size (ny=83 or 80)

139

p2v=1018/ny;

avex=avex/p2v;

avey=avey/p2v;

%linx=linx/p2v;

%liny=liny/p2v;

extx=extx/p2v;

exty=exty/p2v;

scale2=p2v/scale;

%spline fit new boundary file

boundx=1:nx;

boundy=spline(avex,avey,boundx);

bdydx=diff(boundy)./diff(boundx);

m=-1./bdydx;

%find the normal lines

q=[7 15 25 35 45 55 65]; %x-locations of normal lines, user selectable

xo=boundx(q);

yo=boundy(q)+3;

b=yo-xo.*(-1./bdydx(q));

yfo=[5 5 5 5 5 35 60]; %y end points, user selectable

yf=yfo.*ones(1,size(q,2));

xf=(yf-b)./(-1./bdydx(q));

%sin/cos transformations

theta=atan(bdydx(q));

140

slpcos=cos(theta);

slpsin=sin(theta);

%create lines for each of the normals from [xo,yo] to [xf,yf]

%and find the interpolated variables along these lines

spacing=100;

for i=1:size(q,2)

xint(i,:)=linspace(xo(i), xf(i), spacing);

yint(i,:)=linspace(yo(i), yf(i), spacing);

uint(i,:)=interp2(un,xint(i,:),yint(i,:));

vint(i,:)=interp2(vn,xint(i,:),yint(i,:));

urmsint(i,:)=interp2(urms,xint(i,:),yint(i,:));

vrmsint(i,:)=interp2(vrms,xint(i,:),yint(i,:));

dstar(i)=trapz(yint(i,:),(1-uint(i,:)./umean));

dtheta(i)=trapz(yint(i,:),uint(i,:)./umean.*(1-uint(i,:)./umean));

if (theta(i)==0)

uloc(i,:)=uint(i,:);

vloc(i,:)=vint(i,:);

else

uloc(i,:)=uint(i,:).*slpcos(i) + vint(i,:).*slpsin(i);

vloc(i,:)=vint(i,:).*slpcos(i) + uint(i,:).*slpsin(i);

end

end

xint(1,:);

yint(1,:);

uint(7,:);

141

vint(7,:);

%start edits here

%% PLOTS

% figure(1);

% colormap jet;

% quiver(un,vn,5),axis equal,axis([xllim xulim yllim yulim]),title(’Velocity’),axis ij

% hold on;

% plot(boundx,boundy+3,’r-’),axis equal,axis ij;

% hold off;

% figure(2);

% subplot(2,1,1),plot(boundx,boundy,’bo-’),axis ij

% subplot(2,1,2),plot(bdydx,’gs-’); axis([0 90 -1 1]),hold on

% subplot(2,1,2),plot(m/100,’bo-’); hold off

% figure(3);

% plot(boundx,boundy+3,’b-’),axis equal,axis ij;

% hold on;

% for i=1:size(q,2)

% plot([xo(i) xf(i)],[yo(i) yf(i)],’r’);

% %quiver(-vloc,uloc,5),axis equal,axis([xllim xulim yllim yulim]),title(’Tangential Velocity’),axis ij;

142

% end

% hold off;

wall=linspace(1,nx,spacing);

% figure(4)

% for i=1:size(q,2)

% plot(uint(i,:),wall,’b--’),axis ij

% plot(vint(i,:),wall,’rd--’)

% hold on

% end

% hold off

% figure(5);

% colormap jet;

% contourf(vorn,50),axis off, axis equal,axis([xllim xulim yllim yulim]),title(’Vorticity’),axis ij,shading flat;

% colorbar; %gtext(’s^{-1}’);

% hold on


figure(6);

colormap jet;

contourf(rfp,50),axis off,axis equal,axis([xllim xulim yllim yulim]),title(’Reverse Flow Probability (Flow Direction \rightarrow)’),axis ij;,shading flat;

colorbar;

%patch(x,y,’k’);

hold on

plot(boundx,boundy+3,’r-’),axis equal,axis ij;

143

hold off

figure(7);

colormap jet;

subplot(2,2,1),quiver(un,vn,5),axis equal,axis([xllim xulim yllim yulim]),axis ij,axis off%,axis tight

title(’a’)

hold on;


for i=1:size(q,2)

plot([xo(i) xf(i)],[yo(i) yf(i)],’r’);

%quiver(-vloc,uloc,5),axis equal,axis([xllim xulim yllim yulim]),title(’Tangential Velocity’),axis ij;

end

hold off

subplot(2,2,2),contourf(vorn,50),axis off,axis equal,axis([xllim xulim yllim yulim]),axis ij;shading flat;

title(’b’)

%colorbar;


hold on


hold off

subplot(2,2,3),contourf(velrms,50),axis off,axis equal,axis([xllim xulim yllim yulim]),axis ij;shading flat;

title(’c’)

%colorbar;


hold on


hold off

144

subplot(2,2,4),contourf(tke,50),axis off,axis equal,axis([xllim xulim yllim yulim]),axis ij;shading flat;

title(’d’)

%colorbar;


hold on


hold off

% figure(7);

% colormap jet;

% contourf(urms,50),axis off, axis equal,axis([xllim+2 xulim-2 yllim yulim]),title(’RMS Velocity Variation’),axis ij;,shading flat;

% colorbar;


% figure(8);

% colormap jet;

% contourf(conn,50),axis off, axis equal,axis([xllim xulim yllim yulim]),title(’Continuity (as a check of 3-D effects): Run 4’),axis ij,shading flat;

% colorbar;

% figure(9);

% colormap jet;

% contourf(corn,[0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1.0]),axis off, axis equal,axis([xllim xulim yllim yulim]),title(’Average PIV Correlation: Run 4’),axis ij;

% colorbar;

offset=0;

xllim=offset;

yllim=offset;

145

xulim=nx-offset;

yulim=ny-(offset);

figure(10);

colormap jet;

quiver(un,vn,5),axis equal,axis([xllim xulim yllim yulim]),axis ij,axis off%,axis tight

%title(’Velocity Profile Locations’)

hold on;


for i=1:size(q,2)

plot([xo(i) xf(i)],[yo(i) yf(i)],’r’);

%quiver(-vloc,uloc,5),axis equal,axis([xllim xulim yllim yulim]),title(’Tangential Velocity’),axis ij;

end

hold off;

sp=500;

sp2=50;

% figure(11);

% walldist=linspace(1,ny);

% for i=1:7

% %pause

% subplot(2,1,1),plot(uloc(i,:)+(i-1)*sp,walldist,’b-’),axis([0 3500 0 50])

% hold on;

% title(’Velocity Profiles’);

% xlabel(’u’);

% ylabel(’\eta’);

146

% subplot(2,1,1),plot([(i-1)*sp (i-1)*sp],[0 100],’k--’);

% subplot(2,1,2),plot(urmsint(i,:)+(i-1)*sp2,walldist,’b-’),axis([0 7*sp2 0 50])

% hold on

% subplot(2,1,2),plot([(i-1)*sp2 (i-1)*sp2],[0 100],’k--’);

% xlabel(’u\prime’);

% % subplot(3,1,3),plot(vrmsint(i,:)+(i-1)*sp2,walldist,’r-’),axis([0 7*sp2 0 50])

% % hold on

% % subplot(3,1,3),plot([(i-1)*sp2 (i-1)*sp2],[0 100],’k--’);

% % xlabel(’v\prime’);

% end

%hold off;

sp=1;

figure(13)

walldist=linspace(1,ny)*scale2/(6*2.54);

for i=1:7

%pause

subplot(2,1,1),plot(uloc(i,:)/uinf+(i-1)*sp,walldist,’b-’),axis([0 7 0 0.5])

hold on

title(’Velocity Profiles’);

xlabel(’u/U_o’);

ylabel(’y/c’);

subplot(2,1,1),plot([(i-1)*sp (i-1)*sp],[0 100],’k--’);

subplot(2,1,2),plot(vloc(i,:)/uinf+(i-1)*sp,walldist,’b-’),axis([0 7 0 0.5])

hold on

xlabel(’v/U_o’);

147

ylabel(’y/c’);

subplot(2,1,2),plot([(i-1)*sp (i-1)*sp],[0 100],’k--’);

end

%hold off;

%?????????????????????????velocity profiles?????????????????

uso=0;

walldist=linspace(1,-.2,nx);

% figure(12);

% plot(un(:,20),walldist,’ko-’);axis([-25 450 0.05 0.6]);%,axis ij;

% hold on;

% plot(un(:,20)+uso,walldist,’bo-’)

% plot(un(:,30)+2*uso,walldist,’ko-’);

% plot(un(:,40)+3*uso,walldist,’bo-’);

% plot(un(:,50)+4*uso,walldist,’ko-’);

% plot(un(:,60)+5*uso,walldist,’bo-’);

% %plot(un(:,70)+6*uso,walldist,’ko-’);

% grid on;

% hold off;

colormap(bone);

airfpoints=[0.1 .2 .3 .4 .5 .6 .7];

figure(14)

%for i=1:7

plot(airfpoints,dstar,’b-’)

xlabel(’x/c’),ylabel(’\delta^*, \theta’)

148

hold on

plot(airfpoints,dtheta,’b--’)

%end

legend(’\delta^*’,’\theta’)

size(dstar)

dstar

% figure(15);

% colormap jet;

% contourf(mag,50),axis off, axis equal,axis([xllim xulim yllim yulim]),title(’Mag’),axis ij,shading flat;

% colorbar; %gtext(’s^{-1}’);

% hold on


%

% hold off

% figure(5)

% contourf(un,50),axis equal,axis ij

%

% figure(6)

% contourf(vn,50),axis equal,axis ij

fprintf(’\nDone\n\n’);

return

%end of main routine

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

149

%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%%%

function [e1,e2,vorticity,continuity,corr,dudx,dvdx,dudy,dvdy]=tensfunc(base,run,batch,basepath)

% MATLAB Script to read WALPT data and image files.

% Jamey Jacob, Jan. 18 2000

% Version 1.1, last modified Feb. 15, 2000

% Miner version May 30, 2001 - only data read

%

% For use with MATLAB release 11 (5.3)

% Ticker will not work with older versions (see "movie")

% [email protected]

run=int2str(run);

bat=int2str(batch);

% file and path names

%set extension

if batch < 10

bat=strcat(’.00’,bat);

else

if batch < 100


else

150

bat=strcat(’.’,bat);

end

end

%set tensor file name

lptfile=strcat(base,run,bat);

%lptfile=strcat(base,run,bat);

%SET PATHS AND FILE NAMES

path=strcat(basepath);

rdfile=strcat(path,lptfile);

% read data file into header and tensor arrays

fprintf(’ Reading single tensor file %s in %s\n’,lptfile,path)

fid=fopen(rdfile,’r’);

%fid=fopen(rdfile,’r’,’ieee-le’);

%[FILENAME,PERMISSION,MACHINEFORMAT] = fopen(fid)

header=fread(fid,64,’int16’);

version=header(1); % walpt version number (starting with 300)

nxc =header( 2) ; nyc =header( 3); % camera size

nxuv=header( 4) ; nyuv=header( 5); % velocity array size

nxw =header( 6) ; nyw =header( 7); % window sizes in pixels

nxs =header( 8) ; nys =header( 9); % step sizes in pixels

nxf =header(10) ; nyf =header(11); % flow region size in pixels

xf =header(12) ; yf =header(13); % flow region offset in pixels

nbits=header(14); % pixel depth of original flow images

151

% utensor=[nxuv,nyuv,7]

% read tensor components from file in succession

e1=fread(fid,[nxuv,nyuv],’float’); % u

e2=fread(fid,[nxuv,nyuv],’float’); % v

e3=fread(fid,[nxuv,nyuv],’float’); % du/dx

e4=fread(fid,[nxuv,nyuv],’float’); % dv/dx

e5=fread(fid,[nxuv,nyuv],’float’); % du/dy

e6=fread(fid,[nxuv,nyuv],’float’); % dv/dy

e7=fread(fid,[nxuv,nyuv],’float’); % correlation

st=fclose(fid);

%rotate fields

e1=e1.’;

e2=e2.’;

e3=e3.’;

e4=e4.’;

e5=e5.’;

e6=e6.’;

e7=e7.’;

% Check and replace the "missing" 1000 in velocity

% fields with zeros (option XXXX in walpt).

% (This option is for use with IDL or similar programs.)

for i=1:nyuv

for j=1:nxuv

if e1(i,j) > 999

152

e1(i,j) = 0;

end

if e2(i,j) > 999

e2(i,j) = 0;

end

end

end

%Items to return

corr=e7;

% Calculate vorticity,continuity

vorticity=e5-e4; %du/dy-dv/dx

continuity=e3+e6; %du/dx+dv/dy

dudx=e3;

dvdx=e4;

dudy=e5;

dvdy=e6;

return

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%

function [nx,ny]=tensfunc2(base,run,batch,basepath)

153

%reads tensor file and returns array size

run=int2str(run);

bat=int2str(batch);

% file and path names

%set extension

if batch < 10


else

if batch < 100


else

bat=strcat(’.’,bat);

end

end

%set tensor file name

lptfile=strcat(base,run,bat);

%lptfile=strcat(base,run,bat);

%SET PATHS AND FILE NAMES

path=strcat(basepath);

rdfile=strcat(path,lptfile);

lptima1=strcat(’image1.lpt’);lptima2=strcat(’image2.lpt’);

%imfile1=strcat(path,’image’,’1-’,reg,’-’,cdnstr,’.lpt’)

%imfile2=strcat(path,’image’,’2-’,reg,’-’,cdnstr,’.lpt’);

154

%imfile2=strcat(path,lptima2);

% read data file into header and tensor arrays

fprintf(’ Reading tensor file %s in %s to determine array size\n’,lptfile,path)

fid=fopen(rdfile,’r’);

%fid=fopen(rdfile,’r’,’ieee-le’);

%[FILENAME,PERMISSION,MACHINEFORMAT] = fopen(fid)

header=fread(fid,64,’int16’);

version=header(1); % walpt version number (starting with 300)

nxc =header( 2) ; nyc =header( 3); % camera size

nxuv=header( 4) ; nyuv=header( 5); % velocity array size

nxw =header( 6) ; nyw =header( 7); % window sizes in pixels

nxs =header( 8) ; nys =header( 9); % step sizes in pixels

nxf =header(10) ; nyf =header(11); % flow region size in pixels

xf =header(12) ; yf =header(13); % flow region offset in pixels

nbits=header(14); % pixel depth of original flow images

% utensor=[nxuv,nyuv,7]

% read tensor components from file in succession

e1=fread(fid,[nxuv,nyuv],’float’); % u

e2=fread(fid,[nxuv,nyuv],’float’); % v

e3=fread(fid,[nxuv,nyuv],’float’); % du/dx

e4=fread(fid,[nxuv,nyuv],’float’); % dv/dx

e5=fread(fid,[nxuv,nyuv],’float’); % du/dy

e6=fread(fid,[nxuv,nyuv],’float’); % dv/dy

e7=fread(fid,[nxuv,nyuv],’float’); % correlation

155

st=fclose(fid);

nx=nxuv;

ny=nyuv;

return

156

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160

VITA

Shawn Fleming

Candidate for the Degree of

Master of Science

Thesis: Airfoil Separation Control with Plasma Actuators

Major Field: Mechanical & Aerospace Engineering

Biographical:

Personal Data: Born in Aurora, Colorado, USA on June 3rd, 1983.

Education:Received the B.S. degree Oklahoma State University, Stillwater, Okla-homa, USA, 2008, Mechanical and Aerospace EngineeringCompleted the requirements for the degree of Master of Arts/Science witha major in Mechanical and Aerospace Engineering Oklahoma State Uni-versity in May, 2010.

Experience:Graduate Research Assistant, Oklahoma State University School of Me-chanical and Aerospace Engineering, 2008-2010; Teaching Assistant, Ok-lahoma State University School of Mechanical and Aerospace Engineer-ing, 2008-2010; Intern, L-3 Communications Aeromet, 2008; Intern, Pratt& Whitney, tinker Air Force Base, 2007; Intern, The NORDAM Group,Thrust Reverses and Nacelles, 2006.

Name: Shawn Fleming Date of Degree: May, 2010

Institution: Oklahoma State University Location: Stillwater, Oklahoma

Title of Study: Airfoil Separation Control with Plasma Actuators

Pages in Study: 160 Candidate for the Degree of Master of Science

Major Field: Mechanical and Aerospace Engineering

Separation flow control using single dielectric barrier discharge, or plasma actuators,was investigated at low Reynolds numbers on a La203a airfoil. A combination of twoactuators placed on the airfoil was used to investigated the impact of placement forsingle actuators and aggregate flow control impact using both actuators simultane-ously. One actuator was placed near the airfoil’s leading edge while the other wasplaced near x/c = 0.4.

Prior to the wind tunnel study, bench-top testing was performed on three dielectricmaterials to determine the impact of dielectric on control authority; these materialswere Teflon, acrylic, and alumina. The following parameters were tested to determineeffect on jet velocity: plasma frequency, modulation frequency, and voltage input. Theplasma frequency was varied from 3,000 to 15,000 Hz, under constant activation witha duty cycle of 100%. The modulation frequency was then tested over a range from5 to 1,000 Hz with a semi-logarithmic step while operating at a duty cycle of 50%.Alumina produced the highest plasma jet velocity and momentum input but wastoo brittle and inflexible to be applied to the surface of the airfoil. Teflon provided areasonable trade off between the flexibility required and a relatively high peak plasmajet velocity and momentum coefficient.

Wind tunnel testing was performed to demonstrate the ability of plasma actuatorsto control separation over an airfoil in deep stall. The actuators were tested in avariety of configurations including activating the leading edge actuator alone, the aftactuator alone, and both actuators simultaneously. Each configuration was testedacross a range of Reynolds numbers from 50,000 to 150,000 with both steady andpulsed activation. The steady activation was performed while holding duty cycle at100% while the pulsed cases had a duty cycle of 50%. For the pulsed configurationsa range of reduced frequencies was examined from 0.1 to 10. It was observed thatthe lower reduced frequencies exhibited a stronger control. Control authority wasdemonstrated with Reynolds numbers up to a Reynolds number of 150,000. Theleading edge actuator performed best in both constant and pulsed activation, whilethe aft actuator performed best when operated in conjunction with the leading edgeactuator to maintain control authority across the entire suction surface.

ADVISOR’S APPROVAL: Dr. Jamey Jacob