Wake Filling Techniques for Reducing

Rotor-Stator Interaction Noise

Christopher M. Minton

Thesis submitted to the faculty of Virginia Polytechnic Institute and State

University in partial fulfillment of the requirements for the degree of

Master of Science

In

Mechanical Engineering

Dr. Wing Fai Ng, Chair

Dr. Clinton L. Dancey

Dr. Ricardo A. Burdisso

April 2005

Blacksburg, VA

Copyright 2005, Christopher M. Minton

Wake Filling Techniques for Reducing

Rotor-Stator Interaction Noise

Christopher M. Minton

(Abstract)

Several flow control schemes were designed and tested to determine the most suitable

method for reducing the momentum deficit in a rotor wake and thus attenuate rotor-stator

interaction noise. A secondary concern of the project was to reduce the amount of

blowing required air for wake filling and thus limit the efficiency penalty in an aircraft

engine environment. Testing was performed in a linear blow down cascade wind tunnel,

which produced an inlet Mach number of 0.345. The cascade consisted of five blades

with the stagger angle, pitch, and airfoil cross-section representative of 90% span of the

rotor geometry for NASA’s Active Noise Control Fan (ANCF) test rig. The Reynolds

number for the tests was 51025.7 x based on inlet conditions and a chord length of 4

inches. Trailing edge jets, trailing edge slots, ejector pumps, and pressure/suction side

jets were among the configurations tested for wake filling. A range of mass flow

percentages were applied to each configuration and a pressure loss coefficient was

determined for each. Considerable reduction in wake losses took place for discrete jet

blowing techniques as well as pressure side and suction side jets. In the case of the

pressure and suction side jets, near full wake filling occurred at 0.75% of the total mass

flow. In terms of loss coefficients and calculated momentum coefficients, the

suction/pressure surface jets were the most successful. Jets located upstream of the

trailing edge helped to re-energize the momentum deficits in the wake region by using a

flow pattern capable of mixing the region while also adding momentum to the wake. The

slotted configuration was modeled after NASA’s current blowing scheme and served as a

baseline for comparison for all data. Digital particle image velocimetry was performed

for flow visualizations as well as velocity analysis in the wake region.

iii

Acknowledgements

I would like to thank Dr. Wing Fai Ng for providing me with the opportunity to work

on such an exciting and relevant research project and for the funding needed for my

Masters degree. Dr. Ng’s company Techsburg, Inc and all of those associated with it

have been a delight to be around and work with. I wish to also thank Dr. Clinton L.

Dancey and Dr. Ricardo A. Burdisso for their time serving on my committee.

For the past year I have worked with Matthew Langford at Techsburg, Inc. Mr.

Langford was the manager for phase two of the Fan program for which this research was

performed. I would like to sincerely thank him for his guidance and instruction, which

helped me to complete this thesis.

I would like to give a special thanks to Greg Dudding and the Techsburg, Inc.

machine shop crew who provided the fan program with quality hardware for our test

section. Their work was near flawless and they were always wiling to help.

All of the DPIV was performed by Jordi Estevadeordal at ISSI©. Jordi is one of the

best at conducting such experiments and I am grateful for the opportunity to work with

him on this project.

I would like to finally thank my family for all their support over the years. My

accomplishments would not be possible without them and I am forever grateful to have

them in my life.

iv

Table of Contents

Acknowledgements ________________________iii

Table of Contents _________________________iv

Index of Figures___________________________vi

Index of Equations _______________________ vii

Nomenclature____________________________viii

Chapter 1 Introduction ____________________ 1 1.1 Background and motivation _____________________________________ 1

1.2 Fan noise generation____________________________________________ 3

1.3 Previous related research________________________________________ 6

1.4 Thesis objectives _______________________________________________ 8

Chapter 2 Experimental Procedure __________ 9 2.1 Wind tunnel operation __________________________________________ 9

2.2 Test section properties _________________________________________ 10

2.3 Flow control arrangement ______________________________________ 13

2.4 Total pressure loss coefficient ___________________________________ 14

2.5 Digital particle image velocimetry________________________________ 15

2.6 Flow control configurations _____________________________________ 16 2.6.1 TEB, 12 Discrete Jets ______________________________________ 17

2.6.2 12 PS jets, 12 SS jets _______________________________________ 17

2.6.3 Slotted jets _______________________________________________ 19

2.6.4 Ejector Pump_____________________________________________ 20

Chapter 3 Cascade Test Results ____________ 21 3.1 Pressure loss coefficient data ____________________________________ 21

3.2 Blowing efficiency analysis______________________________________ 26

3.3 Momentum coefficient analysis __________________________________ 28

Chapter 4 DPIV Results __________________ 30 4.1 Jet mixing____________________________________________________ 30

v

4.2 SS and PS jets ________________________________________________ 32

4.3 Comparisons to SS and PS jets __________________________________ 38 4.3.1 SS and PS jets and discrete jet TEB __________________________ 38

4.3.2 SS and PS jets and the Slot Blade ____________________________ 39

4.4 DPIV results for Ejector Pump __________________________________ 41

Chapter 5 Conclusions and Future Work ____ 43 5.1 Optimization of SS and PS jets __________________________________ 43

5.2 Other forms of wake filling _____________________________________ 44

5.3 Final conclusions______________________________________________ 44

References:______________________________ 45

Appendix A: Techsburg Inc. Facility ________ 47

Appendix B: Uncertainty Analysis __________ 49

Appendix C: DPIV images and equipment ___ 51

Appendix D: Cascade Test Data ____________ 57

vi

Index of Figures

Figure 1-1: High bypass ratio turbofan engine flyover noise levels (Owens, 1979) ......... 2

Figure 1-2: Typical compressor frequency spectrum (Saunders, 1998) ............................ 4

Figure 1-3: Upwash velocity definition ............................................................................. 5

Figure 2-1: Cascade test section ...................................................................................... 11

Figure 2-2: Blade orientation for cascade test ................................................................. 12

Figure 2-3: SLA model, 12 jets with sharp TE................................................................ 16

Figure 2-4: 12 TE jets, (a) Sharp TE (b) Blunt TE ....................................................... 17

Figure 2-5: SS and PS jets SLA model............................................................................ 18

Figure 2-6: Cross section of SS and PS jet configuration................................................ 18

Figure 2-7: Trailing edge slot configuration.................................................................... 19

Figure 2-8: Ejector pump model ...................................................................................... 20

Figure 2-9: Cross section of ejector pump blade ............................................................. 20

Figure 3-1: Baseline comparison of all test cases ............................................................ 23

Figure 3-2: Wake profile, TE slot .................................................................................... 23

Figure 3-3: Wake profile, sharp TE with twelve jets....................................................... 24

Figure 3-4: Wake profile, blunt TE, 12 jets ..................................................................... 24

Figure 3-5: Wake profile, SS and PS jets ........................................................................ 25

Figure 3-6: Wake profile, ejector pump........................................................................... 25

Figure 3-7: Average loss coefficient vs. mass flow percentages ..................................... 27

Figure 3-8: Average loss coefficient vs. momentum coefficient ..................................... 29

Figure 3-9: Comparison of optimal mass flow rate and momentum coefficient ............. 29

Figure 4-1: Diagram of counter-rotating vortex pair, (Cortelezzi et al.,2001) ................ 31

Figure 4-2: Position of downstream stator in relation to test blade, Location A ............. 32

Figure 4-3: DPIV post-processed median velocity for SS and PS, Location A .............. 33

Figure 4-4: Wake view used for flow seeding, Location B ............................................. 34

Figure 4-5: Trailing edge view used for flow seeding, Location C ................................. 34

Figure 4-6: SS and PS flow seeding for trailing edge and wake regions......................... 35

Figure 4-7: SS and PS at 0.75% blowing at TE............................................................... 36

Figure 4-8: Image from Location C at 0.75% mass flow ................................................ 36

Figure 4-9: SS and PS at 0.75% blowing, velocity diagram showing mixing................. 37

Figure 4-10: SS and PS jets show diffusion in seeded flow experiment ......................... 37

Figure 4-11: Comparison of SS and PS jets with trailing edge discrete jets ................... 39

Figure 4-12: Wake view of slot blade and SS and PS jets, Location B........................... 40

Figure 4-13: TE view of slot blade and SS and PS jets, Location C ............................... 41

Figure 4-14: Free stream seeding for DPIV, Location C................................................. 42

vii

Index of Equations

Equation 1-1 BN

BPF *60

= ...................................................................................... 3

Equation 2-1

−

−=

−

11

2

1

_

_γγ

γ upStatic

upTotal

P

PM ............................................................ 9

Equation 2-2 µ

ρ lV∞=Re ......................................................................................... 12

Equation 2-3 ( ) 411****2**

βρ

−= gdPACm orificeDJet

& .............................. 13

Equation 2-4 100% xm

mm

CV

Jet

&

&& = ................................................................................ 13

Equation 2-5 ρ∞= VAm bladeCV& ................................................................................. 13

Equation 2-6 )90sin())(( leStaggerAngPitchSpanAblade −= .................................... 13

Equation 2-7 RT

P=ρ ............................................................................................ 14

Equation 2-8 γRTMMaV ==∞ ......................................................................... 14

Equation 2-9 upStaticupTotal

HPupTotal

PP

PP

__

3_0_

−

−=ω ....................................................................... 14

Equation 3-1

=

∞•

•

V

V

m

mC Jet

Tot

Jet *µ ......................................................................... 28

Equation 3-2 Jet

JetJet

A

mV

ρ

*

= ................................................................................... 28

viii

Nomenclature

M Inlet Mach number

γ Specific heat ratio

UPTOTALP _ Total upstream pressure

UPSTATICP _ Static upstream pressure

HPP 3_0 Local total pressure from 3-hole probe

ω Local total pressure loss coefficient

OrificeA Area of orifice meter

g Gravity

dP Pressure difference across orifice meter

β Ratio of orifice/pipe diameters for flow meter

ρ Density

µ Dynamic Viscosity

Re Reynolds Number

DC Constant provided for orifice meter

%•

m Percent mass flow for flow control •

Jetm Mass flow through jets

•

Totalm Total mass flow for test blade

JetM Jet Mach number

JetV Jet Velocity

a Acoustic speed of sound

µC Momentum coefficient

∞V Free Stream Velocity

BladeA Area of one blade passage

DPIV Digital particle image velocimetry

TEB Trailing edge blowing

BLS Boundary layer suction

SS Suction side of test blade

PS Pressure side of test blade

BPF Blade passing frequency (Hz)

N Rotational speed of motor (RPM)

B Number of blades in BPF calculation

1

Chapter 1 Introduction

Chapter 1 is an introduction to the reasoning behind the research performed in this

thesis. Facts about noise pollution from today’s aircraft are given as well as some

strategies that are being explored to reduce the levels of noise produced. It includes an

explanation of the mechanisms that contribute to engine noise as well as a description of

fan noise generation. Previous wake-filling research and the goals for this research

project are also discussed.

1.1 Background and motivation

Aircraft noise is an escalating problem for those in communities near airports. Air

traffic is constantly increasing and will continue to do so. At the same time, more people

will be living within the noise footprint of today’s growing airports. The demand for

producing quieter aircraft is becoming quite large given the impact on those affected.

Noise pollution associated with take-off and approach of modern aircraft may cause

physical or psychological harm and studies have associated excessive noise with sleep

deprivation, high blood pressure, and poor learning habits of children. In some cases,

airports are paying millions of dollars to soundproof school classrooms to avoid being

sued. Residential real estate and other properties local to airports are seeing declines in

value as a result of aircraft noise. A detailed summary of airport noise related studies can

be found at the El Toro Information website (2005).

To assist with the problems, airports are cooperating to change flight procedures for

take-off and landing. For example, pilots can only use certain amounts of thrust at take

off and they must be at certain altitudes to make certain maneuvers. Research is being

funded to discover efficient means of reducing noise associated with all aspects of

modern aircraft, including the engine and the airframe. The focus of the current work is

to reduce excessive fan noise, which takes place as a result of rotor-stator interaction

within a turbofan engine.

2

All commercial aircraft must meet the International Civil Aviation Organization

(ICAO) noise certification standards, which apply to aircraft designs and types when they

are first approved for operational use. These restrictions have been progressively

tightened since the initial Chapter 2 standard was adopted in 1971. Since 1977, any new

aircraft designs have been required to meet the Chapter 3 standards. In January 2006, a

more stringent Chapter 4 will be applied for new aircraft designs, which will be one third

quieter than those for the current Chapter 3 (International Air Transport Association

website, 2005).

Owens (1979) compared components of flyover noise levels for a high bypass

turbofan engine. The results, shown in Figure 1-1, indicate that fan noise far exceeds that

of any other source during approach and take-off. The chart shows the ability of acoustic

liners to reduce sound levels; however, even with liners, the fan noise from the inlet and

exhaust still dominates the overall noise produced. Fan noise will become a greater

problem in the future as engine manufacturers continue to use higher bypass ratios and

noise regulations become increasingly stringent. The current NASA goals are to reduce

engine noise by 10dB by the year 2007 and 20 dB by the year 2022. Fan noise reduction

will likely remain in the forefront of engine noise research (Envia, 2001).

Reference: Owens, R.E.: Energy Efficient Engine Performance System - Aircraft

Integration Evaluation, NASA CR-159488, 1979.

Typical Engine Component Flyover Noise Levels

Figure 1-1: High bypass ratio turbofan engine flyover noise levels (Owens, 1979)

3

1.2 Fan noise generation

Some basic knowledge of fan noise generation is necessary to understand the research

that is underway for solving these issues. There are three spectral components that

contribute to fan noise. Figure 1-2 shows a typical frequency spectrum for a compressor.

The first is called broadband noise, which is a result of random aerodynamic behavior

and is distributed equally over a wide range of frequencies. The characteristics that cause

this type of noise are typically not periodic. For example, vortex shedding, boundary

layer turbulence, ingested atmospheric turbulence, and blade pressure field interaction all

contribute to the broadband or “white” noise (Saunders, 1998). Another component of

noise is multiple pure tones. These only occur in conditions where shocks are present at

the blade tips. This research will be applied to a subsonic, low speed fan (1800RPM) and

so these tones do not apply to this application.

Tonal noise, referred to as blade passing tones (BPT), occurs at the blade passing

frequencies (BPF) and is largely a result of rotor-stator interaction (Tyler and Sofrin,

1962). Air is drawn into a typical engine by the fan rotors, producing swirl in the flow,

which must be turned axially by exit guide vanes. Wakes from the rotors interact with

these exit guide vanes and as a result, noise is radiated in the far field. To determine the

BPF in Hertz, one must use Equation 1-1, where B is the number of blades and N is the

rotational speed of the rotor in RPM. The main objective of this research is to reduce

noise at the blade passing frequencies (1BPF, 2BPF, 3BPF, etc.) and thus decrease the

overall noise levels produced by fan rotor-stator interaction.

Equation 1-1 BN

BPF *60

=

4

Frequency (Hz)

Figure 1-2: Typical compressor frequency spectrum (Saunders, 1998)

SPL (dB)

5

Rotor-stator interaction noise occurs because of momentum deficits due to the

viscous wakes from the rotor blades. Sutliff et al. (2002) states that periodic wake

disturbances interact with the stator causing unsteady surface pressures on the stator vane

that in turn couple to the duct acoustic modes. Figure 1-3 shows how the component of

upwash velocity results in unsteadiness on a stator vane. The free stream refers to the

location between two blades and WheelU is constant. It can be seen that deficits in the

wake result in differences between absolute velocities in the wake with respect to the free

stream. The perpendicular component of the difference between the two results in the

upwash velocity shown.

Figure 1-3: Upwash velocity definition

Rotation

6

1.3 Previous related research

Trailing edge blowing (TEB) may be defined as the process of using some means of

flow control on a blade’s trailing edge to re-energize a low velocity, high loss region in

the wake of an airfoil. Many tests have shown that TEB can significantly reduce

mass/momentum deficits. Trailing edge blowing has been used in many turbo machinery

applications and this section will discuss a few of them.

Guillot and Stitzel (2002) performed preliminary cascade tests on 2-dimensional rotor

geometry incorporating TEB. They tested four different flow control designs consisting

of trailing edge jets, trailing edge slots, vortex generating jets and suction side jets. They

proved that the wake could be significantly decreased with trailing edge jets and suction

side jets. The slot configuration and the vortex generating jets did not perform as well.

They found that suction side jets would reduce losses in the wake at smaller percentages

of air than NASA’s current blowing configuration. Their best design, which incorporated

suction side jets, reduced losses by 62.5% and had a predicted sound power level

reduction of 7dB.

Carter (2001) tested a high-turning compressor stator, which incorporated boundary

layer suction from an ejector pump as well suction side jets developed by use of a single

supply pressure source. His experiments were conducted to prove that this method would

reduce the loss coefficients inherent with stator design. He tested a range of inlet cascade

angles as well as varying percentages of supply air to determine the efficiency of the

design. He discovered that significant loss coefficient reductions took place at low

cascade angles. Using 1.6% of the total mass flow, the loss coefficient was reduced by

65%. At higher angles, the wake became larger and flow control effects were limited.

Naumann and Corcoran (1992) produced tests that showed discrete jet blowing from

the trailing edge was the most successful way to attenuate wake on a simulated blade (flat

plate). Their apparatus involved a large-scale water channel in which the airfoil was

tested. The configurations observed were continuous slots, double continuous slots, and

discrete jets all from the trailing edge. Their work also included configurations with

vortex generating jets to assist in mixing. They found it possible to achieve full wake

attenuation with discrete jets at the trailing edge and proved TEB would reduce

7

turbulence shear stresses, vorticity, and fluctuation in velocities. They also concluded

that characteristics of a re-energized wake by TEB would greatly depend on the blowing

configuration.

Sell, Brookfield, and Waitz (1998) performed TEB tests on a 1/6th scale model of a

high-bypass ratio fan stage. Their tests focused on using TEB to reduce the

mass/momentum deficit in the rotor wake, which results in radiated fan noise. They

found that they could reduce wake by up to 85% at 1.5 chord length downstream while

using less than 2% mass flow. Sell (1997) performed cascade tests using an airfoil

modeled after a fan rotor. His tests used boundary layer suction and trailing edge

blowing and found TEB to be the most effective means of reducing the wake. For flow

percentages of 1.08%, he achieved significant wake filling and reduced BPF sound levels

from 8 to 24 dB. An estimated 7 dB reduction in broadband noise would take place with

his flow configuration.

Leitch (1997) and Saunders (1998) used TEB on inlet support struts in a turbofan

propulsion simulator (TPS). By eliminating wakes from these supports the fan face

would experience a more uniform flow field, thus resulting in a lesser amount of noise at

the blade passing frequencies. To monitor changes in BPF, testing was done in an

anechoic chamber at a range of fan speeds with and without the inlet guide vanes. Rao

(1999) conducted similar experiments on a 1/14th scale TPS, which used MEMS based

micro-valves to control the flow rate on every trailing edge blowing hole. A PID

controller used free stream and wake axial flow velocities in determining the blowing

rates necessary for the best possible wake attenuation.

8

1.4 Thesis objectives

As stated, the goals for this research were to design a flow control scheme capable of

reducing the momentum deficit in a rotor wake. Eliminating this wake would

significantly reduce fan noise levels, which occur mostly from rotor-stator interaction.

Since flow control air would be supplied from an engine compressor, another concern

was to reduce the amount of required blowing air to fill the wake. In all, five different

trailing edge blowing configurations were tested. The best configuration was employed

on an actual rig rotor design and tested at NASA’s Aero-Acoustic Propulsion Laboratory.

9

Chapter 2 Experimental Procedure

The focus of Chapter 2 is to discuss the experimental procedure. The operation of the

wind tunnel facility, the pressure measurement scheme, and all test section properties are

given in this chapter. The flow control arrangement and the equations associated with

conducting the experiments are given as well. Specifications for all flow configurations

are summarized in the final section of the chapter.

2.1 Wind tunnel operation

A linear blow down wind tunnel was used for testing, which included an upstream

pressure source and a control valve followed by a diffuser, screens, and a nozzle for flow

conditioning. Air into the compressor was first passed through a cycling refrigerated

dryer, which lowered the dew point of the air to roughly 40°F. The air storage tanks were

pressurized to approximately 135 psig by a screw type compressor. See Appendix A for

equipment specifications and pictures of the compressor, dryer and control valve.

The control valve downstream of the tanks was used to maintain a steady test section

Mach number of 0.345. Static pressure taps and a Kiel total pressure probe were located

approximately one chord upstream of the center blade in the cascade. These pressure

measurements were acquired by the controller, which calculated a Mach number from

Equation 2-1

Equation 2-1

−

−=

−

11

2

1

_

_γγ

γ upStatic

upTotal

P

PM

10

The settings of the controller used to operate the control valve were established

through a series of iterative tests. A proportional gain of 0.7 proved to be optimal, as did

an integral gain of 0.03. No differential gain was needed, thus producing a PI controller.

Once initiated, the controller opened the valve and the Mach number climbed to a set

valve position previously entered into the controller. After the set point was reached, the

automatic controls were initiated and the controller maintained the Mach number for

approximately 15 seconds. As the pressure in the tank decreased, the controller opened

the valve gradually to keep the Mach number constant.

2.2 Test section properties

Various types of data were obtained within the confines of the test section shown in

Figure 2-1. Downstream of the test (center) blade, a traversing device translated a 3-hole

probe at mid-span location. Data acquired from the probe were used to calculate a loss

coefficient. During operation of the wind tunnel, the traverse would travel one pitch (six

inches) over a time span of twelve seconds.

The blades are oriented for this experiment with the test blade having TEB applied

from a regulated pressure source. Equal lengths of tubing were inserted into manifold

blocks on both sides of the test blade. These aluminum manifolds were mounted to the

windows and an o-ring gasket was positioned around the inlet geometry of the blade to

prevent any air leakage.

Windows enclosing the cascade test section were made from Lexan®. Underneath

the blades, a window was installed and above them an adjustable tailboard was placed to

help maintain periodicity within the test section. All of the above mentioned parts were

machined from Lexan® for the visual purposes of DPIV (digital particle image

velocimetry) testing.

11

Figure 2-1: Cascade test section

Linear traverse

mechanism

Flow control

supply air

(both sides)

Lexan

tailboard

3-hole wedge

probe

Upstream

static pressure

taps

Test Blade

Flow

12

The diagram shown in Figure 2-2 displays the arrangement of the blades and outlines

the control volume for the test (center) blade. This control volume represents the total

volume of mass flow of the free stream over the test blade. Measurements pertaining to it

were used in calculating percentages of blowing air for all tests.

Flow control tests were performed on blade models that had sharp and blunt trailing

edges. Therefore, the airfoil shape of the blades above and below the flow-controlled

blade was identical to maintain periodicity. The solidity for the sharp blades was 0.66 as

compared to that of the blunt configuration, which was 0.59. The sharp blade’s chord

was 4.00”, slightly more than that of the blunt design’s, which was 3.56”. The pitch and

span were both 6” and the stagger angle was approximately 68.7°. A Reynolds number

of 51025.7 x was calculated from Equation 2-2 based on inlet conditions and a chord

length of 4 inches. Free stream turbulence was measured to be approximately 1.00%.

Equation 2-2 µ

ρ lV∞=Re

Figure 2-2: Blade orientation for cascade test

Bottom blade

Pressure Surface

Traverse

Slot Location

Adjustable

Tailboard

Flow Flow Control

Test Blade

Top Blade

Suction Surface

13

2.3 Flow control arrangement

A flow control arrangement (See Appendix A) was produced so that a specified range

of mass flow rates could be delivered to the test blade. The assembly used an upstream

pressure source, a pressure regulator, and an orifice plate. After passing through the

orifice plate, air would travel through two equal lengths of tubing and through the test

blade. To calculate the mass flow rate traveling through the blade, Equation 2-3 was

used.

Equation 2-3 ( ) 411****2**

βρ

−= gdPACm orificeDJet

&

To determine the correct percentage of mass flow for each case it was necessary to

determine the total mass flow rate over one blade. Once that value was found the

percentage of mass flow for each blade could be calculated for each case by using

Equation 2-4 along with Equation 2-5 and Equation 2-6.

Equation 2-4 100% xm

mm

CV

Jet

&

&& =

Equation 2-5 ρ∞= VAm bladeCV&

Equation 2-6 )90sin())(( leStaggerAngPitchSpanAblade −=

14

Assuming ideal gas law, a density was found from the pressure and temperature

within the test section using Equation 2-7. The area used for this calculation pertained to

the control volume of airflow over only the test blade. The velocity of the free stream

was determined from the inlet Mach number and the acoustic speed of sound shown in

Equation 2-8.

Equation 2-7 RT

P=ρ

Equation 2-8 γRTMMaV ==∞

2.4 Total pressure loss coefficient

The total pressure loss coefficient has been used in similar experiments to define

wake losses. Equation 2-9 defines the total pressure loss coefficient for the experiments

performed in the cascade tunnel. The upstream stagnation and static pressures were

acquired from Yokogawa (EJA510A) pressure transmitters. Measurements from the 3-

hole probe were used to calculate a flow angle to calibrate the position of the tailboard to

ensure periodicity in the test section. The cascade blades produced a turning angle of

roughly 5° and so the 3-hole probe was turned 5° into the flow to produce an accurate

total pressure reading for HPP 3_0 . Validyne® (DP15) pressure transducers were used for

all pressure measurements pertaining to the 3-hole probe. An uncertainty analysis for all

pressure measurement devices can be found in Appendix B.

Equation 2-9 upStaticupTotal

HPupTotal

PP

PP

__

3_0_

−

−=ω

15

2.5 Digital particle image velocimetry

DPIV is one of the most useful diagnostic tools for measuring complex flows since it

is capable of providing instantaneous velocity data. This DPIV technique has been

successfully applied to a variety of flows, and the results have demonstrated the

resolution necessary for exploring flow features in complex flow fields. DPIV

experiments can readily capture unsteady phenomena, such as vortices and jet mixing at

the trailing edge. Hundreds and thousands of images can be readily acquired for

averaging and statistical analysis.

The process of DPIV uses a seeding device upstream of the test section, which evenly

disperses small tracer particles during wind tunnel operation. The seeder used is a

cyclone type fluidized bed with tangential high-pressure air to inject solid aluminum

oxide submicron particles into flow. The location of the seeder must be far upstream to

prohibit influence of the flow with the rod or the jets.

A thin, laser sheet creates a plane within the flow field which is formed by an

arrangement of spherical and cylindrical lenses. This was done from underneath the test

section through a Lexan® window. Two lasers provide two separate pulses separated by

a given time and light scattered by the tracer particles in the illuminated plane is recorded

using digital photography. Local fluid velocity is then obtained from the ratio of the

measured displacement between two images to the time between exposures, which is a

known parameter. Cross-correlation cameras readily resolve the directional ambiguity

and were used to image two views of the flow field simultaneously. See Appendix B for

a description of all equipment used in DPIV testing and an uncertainty analysis. All

DPIV references in this section are from Estevadeordal et al. (2002)

16

2.6 Flow control configurations

Solid Concepts, Inc. fabricated all test blades from a high-definition stereo

lithography apparatus (SLA) material (SOMOS 11120). The two-dimensional rotor

geometry was based on 90% span of NASA’s ANCF rig rotor blades. Each blade was

designed to use some form of blowing to re-energize the wake at the trailing edge and

thus reduce the mean wake deficit. Among the blades that were tested were trailing edge

jets, trailing edge slots, ejector pumps, and pressure/suction side jets. This section

describes the specifications for each.

A diagram of a sharp trailing edge blade is shown in Figure 2-3. It shows how the

internal passages of every blade were designed so that the flow would be evenly

distributed along the span. The flow control inlets on every blade extended through the

windows where the flow control air was connected and an o-ring was placed around the

hub to prevent any leakage. Heli-coil thread inserts were placed into previously

developed holes in the SLA to support the blade and help prevent any unwarranted

vibrations.

Figure 2-3: SLA model, 12 jets with sharp TE

Heli-coil threads

Internal passage profile

Flow

Control

Air

Flow

Control

Air

Flow Control Inlet

17

2.6.1 TEB, 12 Discrete Jets

Two configurations used twelve discrete trailing edge jets with the difference

between them being either a sharp or blunt trailing edge. The jet exit dimensions were

0.07” by 0.06” and tangent to the trailing edge camber line for both designs. It was

necessary to have the tabs in between the jets for the sharp trailing edge design to

maintain the airfoil shape of the sharp trailing edge. Figure 2-4 shows a photograph of

the two configurations.

Figure 2-4: 12 TE jets, (a) Sharp TE (b) Blunt TE

2.6.2 12 PS jets, 12 SS jets

A picture of the SS and PS blade can be seen in Figure 2-5. A cross section shown in

Figure 2-6 illustrates the internal geometry. The objective for the SS and PS model was

to enhance mixing by injecting a minimal percentage of mass flow from inclined jets into

the cross flow of both pressure and suction surfaces. The exit dimensions for these jets

were 0.03” by 0.065” and located at 0.875 inches upstream of the trailing edge, which

corresponds to approximately 78% of the blade’s chord. The incline of the jets was 15°

from the blade surfaces. The SS and PS jets used the same exit area of the 12 TEB jets

configurations.

(a) (b)

18

Figure 2-5: SS and PS jets SLA model

Figure 2-6: Cross section of SS and PS jet configuration

Flow control air

PS Jet

SS Jet

19

2.6.3 Slotted jets

The slotted jet design incorporates a blowing configuration modeled after a rig rotor

used for TEB experiments in the NASA ANCF test rig. It was constructed and tested to

serve as a baseline model to which all other configurations could be compared. In the

actual rig blade, optimal blowing rates were between 1.6% and 1.8% including self-

pumping caused by centrifugal forces acting on rotor.

The internal structure of the slot blade is similar to the other blades until it reaches a

point approximately 1.25” from the trailing edge. At this juncture the jets begin to

transform and each pair of jets forms into one slot with exit dimensions 0.83 inches by

0.040 inches. Figure 2-7 shows the slot blade.

Figure 2-7: Trailing edge slot configuration

20

2.6.4 Ejector Pump

This configuration was designed to create suction on both surfaces of the blade. The

design used a blunt trailing edge (3.56” chord) with slots at the trailing edge measuring

0.70 inches by 0.050 inches. The ejector pumps were located 3.00 inches from the

leading edge or at 84% of the chord. The dimensions of the motive jet were 0.032” by

0.157” and two were placed in every ejector pump channel as shown in Figure 2-8. A

cross section in Figure 2-9 displays the design that was tested. Injecting high-momentum

air through the model creates a low-pressure region capable of entraining flow from the

surrounding environment (Karassik et al., 1986). Increased blowing enhances suction

and more mass/momentum injection occurs at the trailing edge.

Figure 2-8: Ejector pump model

Figure 2-9: Cross section of ejector pump blade

PS Suction Slots

SS Suction Slots

MotiveFlow Control Air

TEB

21

Chapter 3 Cascade Test Results

The purpose of Chapter 3 is to provide and explain the processed wake data from

cascade testing and to summarize the results. The chapter begins by presenting total

pressure loss coefficients versus percent pitch. Wake filling effectiveness is discussed for

each blowing configuration and comparisons are made between them. The blowing

configurations are analyzed further by determining the optimal momentum coefficients

and mass flow percentages. From the results presented in this chapter, the primary

conclusion is that the suction and pressure side jets design is superior to all other test

cases.

3.1 Pressure loss coefficient data

Figure 3-1 shows a baseline (no blowing) case for each test configuration and it can

be seen that small discrepancies in losses occurred. This was due to the differences in

blunt and sharp trailing edges as well as the influence of the jet holes on the wake with no

blowing. For example, the ejector pump model used entrainment slots on the suction and

pressure sides. When no flow control was applied, minimal suction took place and the

structure of the suction ports decreased the turning angle slightly, resulting in the wake

shift seen in Figure 3-1. The slot and 12 TEB jets blades had roughly the same baseline

wake profile and the SS and PS jets design had slightly lower losses in the wake. This

was likely due to the little effect the flush mounted SS and PS jets had on the boundary

layer. For the SS and PS jets, it is also conceivable that air re-circulated from the

pressure side to the suction side, reducing losses with no blowing. The sharp trailing

edge with 12 jets used trailing edge tabs between jets, which may have slightly increased

the losses, making it comparable to the two blunt trailing edge blades.

Figure 3-2 through Figure 3-6 show the wake profiles for all the test blades as

different blowing percentages were applied to reduce the wake. The total pressure loss

coefficient was plotted against pitch-wise location. Negative percent pitch refers to the

suction side and positive pitch represents the region downstream of the pressure side.

The figures use the same color scheme for identical blowing rates for comparison.

22

For the slot blade, shown in Figure 3-2, significant wake reduction did not take place

for mass flow percentages as high as 1.45%. In some cases of low percentage blowing,

higher losses occurred due to the low velocity flow being injected from the trailing edge.

It would later be determined in DPIV that percentages around 2.00% would result in

wake filling.

A plot of the local loss coefficient versus the percent pitch-wise location is shown in

Figure 3-3 for the sharp trailing edge blade with 12 jets. It can be seen that in the

baseline case (no blowing), there is a clearly defined wake represented by higher losses.

As the percentage of air injected into the blade increases, those losses begin to decrease.

A mass flow percentage of 1.00% almost completely diminished the total pressure losses

for this case. In the case of 1.25% blowing, over-filling occurred in the wake. Over-

filling refers to a negative loss coefficient as a result of excessive blowing.

The wake data for the blade with 12 jets and a blunt trailing edge is shown in Figure

3-4. When compared to the slot configuration, which also had a blunt trailing edge, the

discrete jet configuration outperforms the slot configuration by a wide margin. By using

a smaller exit area for the jets, it was possible to increase velocities at identical mass flow

percentages, which increased the momentum ratio of the jet to free stream conditions.

The exit area was the same for the 12 discrete jet configurations (sharp/blunt) as well as

the suction and pressure side jets.

The best configuration in terms of blowing flow rate required for complete wake

filling was the suction and pressure side jets shown in Figure 3-5. Though the baseline

case for this blade was slightly lower than the others (producing smaller wake to be

filled) it still performs the best. Percentages as low as 0.75% show greatly diminished

losses and over-blowing occurred at 1.00%.

Figure 3-6 shows the wake profile for the ejector pump model. Cases of small

blowing percentages displayed no change in total pressure losses. Wake reduction did

not occur until approximately 0.75% and at 1.25% the wake has been filled. It cannot be

confirmed from the available data whether or not the suction ports entrained the

surrounding flow. However, DPIV allowed a visual examination of the region and gave

insight into the performance of this blade.

23

Figure 3-1: Baseline comparison of all test cases

Figure 3-2: Wake profile, TE slot

24

Figure 3-3: Wake profile, sharp TE with 12 jets

Figure 3-4: Wake profile, blunt TE, 12 jets

25

Figure 3-5: Wake profile, SS and PS jets

Figure 3-6: Wake profile, ejector pump

26

3.2 Blowing efficiency analysis

For every blowing case presented in Section 3.1, an average loss coefficient was

determined across an entire pitch. Figure 3-7 shows these values plotted against the

corresponding mass flow rate percentages. As was found in section 3.1, the slot blade’s

performance was inferior to the other test cases. Not until mass flow percentages of

1.75% do the average losses begin to decrease. Due to limitations on the pressure source

used for testing, this was the highest percentage attainable for cascade testing.

The two blades (blunt and sharp), which incorporated 12 TEB jets, filled the wake at

approximately the same rate. Interpolating from the graph, the optimal values

corresponding to zero losses for these two cases was 1.15% for the sharp TE and 1.20%

for the blunt TE. When comparing these two blades’ average losses for no blowing, it

can be seen that the blunt trailing edge is slightly higher. This is most likely due to the

differences in their trailing edge geometries.

The best configuration was determined to be the SS and PS jets blade, which reduced

average total pressure loss coefficients significantly more than any other design at lower

flow rate percentages. Interpolating from Figure 3-7 where an average loss coefficient

would be zero for full wake filling, the corresponding optimal flow rate percentage is

0.8%.

The ejector pump performed worse than the TEB jets and SS and PS jets

configurations. However, wake filling was achievable and if higher mass flow

percentages had been applied, there would have been an optimal value obtained like the

other blades. For comparison, an optimal value of 1.35% was found from extrapolating

the data in Figure 3-7.

27

-0.02

-0.01

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 2.00

Mass Flow %

Avera

ge L

oss C

oeff

icie

nt, ωω ωω

12 Jets Sharp 12 Jets Blunt

SS and PS Jets Ejector Pump

Slot Blade

Figure 3-7: Average loss coefficient vs. mass flow percentages

28

3.3 Momentum coefficient analysis

A parameter commonly associated with jet blowing experiments is the momentum

coefficient, which is defined by Equation 3-1. This equation represents a momentum

ratio between the jets and the free stream conditions and is a relevant parameter for any

momentum deficit application. It incorporates the mass flow percentage as well as the

velocities corresponding to them and has been used in many jet-blowing experiments.

Kozak and Ng (2000) defined a momentum coefficient to classify their blowing for wake

reduction of inlet guide vanes in a F109 turbofan engine. Free stream velocity is

determined from inlet Mach number and jet velocity is found from Equation 3-2. Figure

3-8 shows a plot of average loss coefficient versus the calculated momentum coefficient.

In terms of this momentum ratio, the SS and PS jets blade is clearly superior to all other

forms of blowing. When compared to the 12 jets trailing edge blowing cases, which used

the same jet exit area, it can be seen that this blowing pattern encourages more reduction

in the wake with much less momentum in the jets. Figure 3-9 shows a comparison of the

optimal flow rate and momentum coefficient conditions.

Equation 3-1

=

∞•

•

V

V

m

mC Jet

Tot

Jet *µ

Equation 3-2

Jet

JetJet

A

mV

ρ

*

=

29

-0.02

-0.01

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.000 0.005 0.010 0.015 0.020 0.025 0.030 0.035 0.040

Momentum Coefficient, Cµµµµ

Avera

ge L

oss C

oeff

icie

nt, ωω ωω

Slot Blade

12 Jets, Sharp TE

12 Jets, Blunt TE

SS and PS

Ejector Pump

Figure 3-8: Average loss coefficient vs. momentum coefficient

0.018

0.0330.035

0.040

0.800

1.150 1.2001.350

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

0.040

0.045

0.050

SS and PS 12 Sharp 12 Blunt Ejector Pump

Mom

entu

m C

oeffic

ient Cµ

µ µ µ

0.000

0.500

1.000

1.500

2.000

2.500

3.000

3.500

Mass F

low

%

Momentum Coefficient

Mass Flow %

Figure 3-9: Comparison of optimal mass flow rate and momentum coefficient

30

Chapter 4 DPIV Results

The results presented in Chapter 3 showed which blades performed the best in terms

of mass flow percentages and momentum coefficients. It was determined that the model

incorporating the SS and PS jets was more efficient at wake filling than the other blowing

configurations. To better understand the wake behavior, DPIV tests were performed on

all test configurations. DPIV was performed by Innovative Scientific Solutions, Inc.

(ISSI©) from Dayton, Ohio.

Chapter 4 begins by discussing previous studies on jet mixing to understand the

behavior of a mixing jet in cross flow conditions. Chapter 4 uses results from the DPIV

to explain the behavior of each blade. In particular, the SS and PS jet model is

thoroughly discussed along with comparisons of its behavior with that of the other

configurations.

4.1 Jet mixing

To understand the success of the SS and PS jets model, some background information

must be given on the general behavior of a mixing jet in cross flow applications. These

jets have been applied to a variety of applications, including gas turbine blade cooling, jet

dilution, exhaust gas cooling, and fuel injection. Cross flow mixing is typically used to

generate a homogeneous mixture of injected air with mainstream flow. The SS and PS

jets configuration attempts to fill the wake region by creating a uniform flow field from

inclined cross flow jets as opposed to trailing edge blowing of the other blades.

Holdeman and Walker (1977) performed mixing studies on rows of jets in a confined

cross flow. The experiments monitored the penetration and mixing levels of jets

containing cool air into a heated free stream. The study was performed for dilution zone

mixing for gas turbine combustion chambers where rapid mixing must take place. Round

holes were tested with variations in size and spacing. They discovered that the

momentum flux ratio was the most important variable to influence mixing and jet

penetration.

31

The mixing capabilities of jets in cross flow are a direct result of the vortex structures

they form when injected into the free stream. There are four types of vortical structures

that result from this type of jet. Shear layer vortices, horse shoe vortices, counter-rotating

vortex pair (CVP), and wake vortices. All of them enhance molecular mixing

downstream of a transverse jet, although the stream-wise entraining structures of the CVP

dominate the mixing behavior (CISM website, 2005). Though the jets for the SS and PS

configuration exit at an angle of 15 degrees, it is hypothesized that variations of the

described vortices are still present and responsible for the success of the design. The

reason for the incline is to also ensure that momentum is being added to the wake region.

Cortelezzi and Karagozian (2001) performed a study of the formation of the counter-

rotating vortex pair (CVP) and Figure 4-1 shows a diagram. They observed vortex ring

rollup, interactions, tilting, and folding, which led to the initiation of the CVP. Early

studies performed by Kamotani and Greber, 1972 and Fearn and Weston 1974 identified

the structure and observed it to dominate the cross section of the jet in the far field (far

field described to be 5 to 10 diameters downstream) and Broadwell and Breidenthal

(1984) suggested the overall mixing efficiency was associated with the strength of the

CVP.

Figure 4-1: Diagram of counter-rotating vortex pair, (Cortelezzi et al.,2001)

John and Samuelsen (2000) performed mixing experiments on a RQL (Rich-

burn/Quick-mix/Lean-burn) combustor region, which studied the effect of varying the jet

exit angle and number of jets while holding the mass flow and jet momentum conditions

constant. The jet angle was varied from 0 degrees to 45 degrees (from normal) and it was

discovered that mixing efficiency was optimal at 0 degrees (transverse jet). They also

discovered a trade-off between the number of jets used and the jet exit angle, whereby

larger angle required fewer jets.

32

4.2 SS and PS jets

With some basic knowledge of the mixing capabilities of jets in cross flow, the

behavior of the SS and PS jets tested for this thesis can be described. The following

section presents velocity data determined from DPIV for the SS and PS jets, which

confirms what was learned from the pressure data. Velocity measurements allow an

inspection of the shape and thickness of the wake region and show the decreases in wake

as a result of blowing. To further enhance knowledge of the wake’s behavior, the flow

control air was seeded and flow visualization images were captured using the same

camera equipment responsible for the velocity measurement.

Cameras were positioned in three locations. Figure 4-2 shows Location A, which

represents the position of the exit guide vanes where rotor-stator interaction would occur.

It is positioned on the centerline of the traverse and tilted at the stagger angle. Images

were acquired from this region and a DPIV algorithm was used to calculate the median

velocity distribution. Median velocities were used as opposed to mean velocities to reject

the influence of outliers.

Figure 4-2: Position of downstream stator in relation to test blade, Location A

33

Figure 4-3 shows velocity behavior in the wake region for SS and PS jets. A velocity

scale is shown to the right of the figure, with lower velocities represented by the blue

areas and higher velocities by those in red. A dotted line is shown to represent the

location of the center of the traverse slot (See Figure 4-2). The pressure surface side and

the suction surface side are located above and below the wake, respectively.

In the baseline case there is a distinct region of dark blue defining the wake, which

was re-energized by the blowing. In cases of 0.50% and 0.75% it can be seen that the

blue region is injected with enough air to raise the velocity. This validates the total

pressure loss coefficient data. As even more air is injected, a high-speed region begins to

form within the wake, which can be seen by the red region in 1.00% and 1.25% blowing.

This is an indication of over-blowing and results in the negative pressure loss coefficients

found for this configuration in Chapter 3.

Figure 4-3: DPIV post-processed median velocity for SS and PS, Location A

Center of traverse slot

SS

Jet from

Over-

blowing

PS

SS SS

SS SS

PS

PS PS

PS

Baseline 0.50% Blowing 0.75% Blowing

1.00% Blowing 1.25% Blowing

Wake Region 110

109

108

107

106

105

104

103

102

101

100

99

98

97

96

95

94

93

92

91

90

Velocity (m/s)

34

DPIV images were taken while the flow control air was seeded to further investigate

the performance of the SS and PS model. To perform these experiments, the seeding

device was placed downstream of the orifice meter in the flow control plumbing (See

Appendix A). Figure 4-4 and Figure 4-5 show the dimensions of the pictures presented

and the camera positions used for the wake and trailing edge views. The laser sheet,

which illuminates the PIV particles, enters the test section from beneath, resulting in the

shadow region shown in the figures.

Figure 4-4: Wake view used for flow seeding, Location B

Figure 4-5: Trailing edge view used for flow seeding, Location C

35

Figure 4-6 shows three different flow rate percentages for the SS and PS jets design.

The pressure difference as a result of the seeder limited the amount of blowing air for

these experiments and so percentages of 1.00% were not exceeded. On the right are

views of the wake region (location B) and on the left are corresponding views of the

trailing edge (Location C). With each increase in blowing, the wake region is mixed

progressively better. 0.75% blowing shows a larger area being filled when compared to

the 0.25% case in this plane. It should be noted that the laser sheet illuminating the DPIV

particles is centered on a jet.

Figure 4-6: SS and PS flow seeding for trailing edge and wake regions

Another observation is of the small vortex structures, which protrude from the suction

side jets (no visual is available for the pressure side, but the same effect likely occurs).

This is what distinguishes this blade’s design from the others. Where all other cases use

trailing edge blowing, this model injects mass/momentum in a way, which uses these

vortices to mix the wake region with the surrounding flow. The high frequency, short-

length scale vortices are clearly shown to mix the region downstream of the jets. Figure

4-7 shows a closer view of the suction side jet for the most efficient test case (0.75%

blowing). The jet exits from the suction side and begins to interact with the free stream

flow, which changes the trajectory of the jet. During this initial stage of injection,

stream-wise vortex generation is hypothesized to be taking place.

SSPS 0.25%

TE View

SSPS 0.50%

TE View

SSPS 0.75%

TE View

SSPS 0.25%

Wake View

SSPS 0.75%

Wake View

SSPS 0.50%

Wake View

36

Figure 4-7: SS and PS at 0.75% blowing at TE

The ability of the SS and PS jets design to continue mixing downstream of the trailing

edge is shown in Figure 4-8. The jets on both sides re-energize the low momentum

region immediately following the trailing edge. The two jets can be visualized in the

figure. Figure 4-9 displays a velocity diagram for this particular case as additional

support for this flow pattern. This diagram clearly shows the higher velocity jets

downstream of the injection point and the velocity behavior downstream as the jets begin

to entrain the surrounding flow and mix the region.

Figure 4-8: Image from Location C at 0.75% mass flow

Jet Exit

From SS

Trailing Edge SSPS 0.75%

TE View SS Blade Surface

Vortex

Formation

SSPS 0.75%

Wake View PS Jet

SS Jet

Continued mixing

downstream

37

Figure 4-9: SS and PS at 0.75% blowing, velocity diagram showing mixing

A picture of the SS and PS jets blade was taken after DPIV testing had been

completed. This photograph in Figure 4-10 shows how the jets diffused in the span-wise

direction and gives indication to the diffusion attributes of the SS and PS jets. Complete

mixing needed to be achieved at a half chord location from the trailing edge and this

photograph is evidence that this was achieved for cascade testing.

Figure 4-10: SS and PS jets show diffusion in seeded flow experiment

38

4.3 Comparisons to SS and PS jets

The following section explains the differences between the most successful case and

the other blowing configurations with the support of DPIV images obtained from flow

control seeding experiments. What has been determined is the ability of inclined cross

flow jets to achieve wake filling more efficiently than any other test case presented in this

thesis. In many previous studies, trailing edge blowing has been used in attempts to

reduce wake deficits. However, there is evidence that it seems there may be other, more

efficient ways to achieve uniformity in the region and reduce momentum deficits. The

images presented in this section give some insight into the reasons that the SS and PS jets

performed better than others.

4.3.1 SS and PS jets and discrete jet TEB

When comparing the images of the SS and PS jet model with that of the two blades,

which used trailing edge jets, distinct differences in the mixing capabilities can be

noticed. Figure 4-11 shows the flow control seeding results for these blades for blowing

mass flow percentages up to 1.00% (0.75% for SS and PS Jets). All momentum

coefficients were identical for each blowing percentage. As previously discussed,

increases in mass flow and momentum coefficient for the SS and PS jets widen the

mixing region downstream of the blade. When compared to the other two blades of equal

flow rate, the same behavior was not realized. Increased blowing for the blunt TE 12 Jets

blade produced a thinner mixing region. This explains the loss coefficient data for this

blade, whereby losses were reduced through the middle of the region, but outside the

blowing jet there were still losses. For the sharp TE 12 Jets blade, more mixing occurred

compared to the blunt 12 Jets design, most likely as a result of the trailing edge tabs

between the jets, which encouraged the mixing. However, both trailing edge blowing

blades maintain unsteadiness at low percentages of mass flow, which can be noticed by

the waviness of the jet downstream.

39

SS and PS Blunt 12 Jets Sharp 12 Jets

Figure 4-11: Comparison of SS and PS jets with trailing edge discrete jets

4.3.2 SS and PS jets and the Slot Blade

This section displays the seeding images that contrast the best-case scenario of the SS

and PS jets with the slot blade, which was based on NASA’s baseline model. The

differences in blowing and blade structure are also reiterated. The two designs use very

different forms of blowing and the images displayed illustrate their differences.

Structurally, the exterior of the two blades are similar with the only difference

between them being the sharp TE for the SS and PS jets and the blunt TE for the slot.

The exit area of the jets for the SS and PS jets configuration is considerably less than that

of the slot configuration. (See Chapter 2 for blade specifications) This allowed for

higher momentum jets, which increased the jet penetration into the free stream as defined

by the momentum coefficient. The major difference between these two cases is the style

of blowing. The slot blade uses mass flow injection directly into the trailing edge region

to re-energize the low velocities in the wake. In contrast, the SS and PS model injects

mass upstream of the trailing edge with an inclined cross flow jet, which possibly

provided stream-wise vortex generation to mix the wake with the surrounding free

stream.

40

Figure 4-12 and Figure 4-13 show the comparison of wake views and trailing edge

views for the slot blade and SS and PS models. The cases for the slot blade show vortex

shedding at the lowest blowing percentages. These structures propagate downstream and

are speculated to be the reason for the total pressure losses found from probe traverse

data. When compared to the mixing region associated with the SS and PS jet, the vortex

structures that formed are vastly different.

The reasons the SS and PS jets worked so well in comparison can be explained as

follows. First, there was nearly 4 times the amount of jet penetration as defined by the

momentum coefficient. It is known from previously mentioned studies that this

parameter is important when quantifying the mixing abilities of a blowing jet. Second,

there is no indication of any stream-wise vortex generation for the slot case. The vortices

created by the slot were span-wise and do not operate with the same mixing efficiency as

the set of vortex structures associated with inclined jets in a cross flow.

Figure 4-12: Wake view of slot blade and SS and PS jets, Location B

41

Figure 4-13: TE view of slot blade and SS and PS jets, Location C

4.4 DPIV results for Ejector Pump

The model constructed with an ejector pump on both blade surfaces did not perform

as well as the SS and PS or the trailing edge blowing cases as determined from the

pressure data. This section uses DPIV to examine the possible reasons for the poor

performance of this design.

For the ejector pump to work properly, it must produce a motive mass flow with

enough velocity to reduce the pressure substantially below the local pressures on both

blade surfaces. This pressure differential induces suction and adds to the mass injection

from the trailing edge. Therefore, the success or failure of this design depends on its

ability to entrain air from the suction ports on both suction and pressure sides.

42

Figure 4-14 shows all blowing percentages for the ejector pump configuration with

the free stream seeded. The images do not show that any substantial suction took place

for any blowing case. In fact, the exact opposite occurred as the flow control air was

escaping from the entrainment slots on the suction side. There is no visualization for the

pressure side so the behavior on that surface could not be determined. The higher

pressures on the pressure side may have allowed for entrainment, though it is possible

that air from the pressure side traveled all the way through the blade and out of the

suction side ports. The exact behavior is unknown but it can be said definitively that

minimal suction occurred for all blowing percentages. Even so, this blade reduced losses

as shown in Chapter 3 by using trailing edge blowing. It is possible that the air, which

exited the entrainment slot actually assisted in mixing downstream.

Figure 4-14: Free stream seeding for DPIV, Location C

43

Chapter 5 Conclusions and Future Work

Many conclusions can be made from the research presented in this thesis, the most

important of which is that the SS and PS jets configuration proved to be the most efficient

way to reduce fan rotor wake for this application. Other configurations, though

successful at reducing the mean wake deficit, did so with larger blowing percentages and

momentum coefficients. As a result of this research and its findings, the ANCF rig rotor

blades were re-designed using this method of wake filling and tested at NASA’s Aero-

Acoustic Propulsion Laboratory. This chapter discusses other means for wake filling for

future experiments and provides a final argument in favor of the SS and PS jets

configuration.

5.1 Optimization of SS and PS jets

Future work may be done to optimize a blowing pattern using SS and PS jets.

Variations could be made in the percent chord location of the jet or every other jet could

be staggered at a different distance from the trailing edge. The angle at which the jets

exit could be an important parameter to optimize. The loss coefficient plots for the SS

and PS jets showed averages near zero. However, the pattern still exhibited losses from

the jets and over-blowing occurred with only 1.00%. By increasing the angle from the

current position (15° from blade surface) it may be possible to reduce the momentum

coefficient and increase mixing. A cross flow jet normal to the flow may be another

solution for certain applications. Other sizes and shapes of the jet will most certainly

affect the behavior downstream and should also be explored.

44

5.2 Other forms of wake filling

In future testing, wake attenuation strategies using the other forms of blowing may be

perfected. The design that entrained flow from the suction side as well as pressure side

was not as successful as expected. There were no DPIV flow visualizations that

exhibited any substantial suction on either surface. Total pressure loss coefficient data

suggests the same for both blade surfaces and it appears that using an ejector pump on

both sides was a hindrance.

Trailing edge blowing with slot configurations has proven to be inferior to other

methods discussed in this thesis and other publications. Guillot, Stitzel, Naumann,

Corcoran, and others all found that this style of TEB was less efficient than discrete jet

blowing. Though the mass flow percentages applied to every blade were the same, the

mixing did not occur and large vortex shedding took place at percentages where other

designs were filling the wake.

5.3 Final conclusions

In conclusion, wake behavior downstream of the trailing edge is highly dependent on

the method used to fill that region. While using some form of mass/momentum injection,

equal consideration should be given to mixing that region with stream-wise vortices if

possible. For the SS and PS jets design, very small amounts of blowing mass flow

achieved wake filling for the following reasons. Extensive jet penetration was achieved

by using smaller exit areas, allowing for higher momentum blowing jets when compared

to the slot blade. Also, blowing into a cross flow with an inclined jet results in vortex

formation capable of entraining the surrounding free stream and enhances mixing. Jet

blowing into a cross flow has been used for many other turbo machinery applications and

this thesis exhibits yet another aspect for which it is useful. The design of the suction and

pressure side jets has the potential to significantly reduce the wake with minimal impact

on engine efficiency.

45

References:

Broadwell, J. E., & Breidenthal, R. E., 1984, “Structure and Mixing of a transverse jet in

incompressible flow”, Journal of Fluid Mechanics vol. 148, 405-412

Corcoran, T.E. “Control of the Wake from a Simulated Blade by Trailing Edge

Blowing”, Masters Thesis, Lehigh University, Bethlehem, PA, 1992

Cortelezzi, L., & Karagozian, A.R., 2001, “On the Formation of the Counter-Rotating

Vortex Pair in Transverse Jets”, Journal of Fluid Mechanics vol. 446, 347-373

CISM website, International Centre for Mechanical Sciences, April, 2005

http://www.cism.it/cism/p2001/scopeC0100.htm

El Toro Information Site, April, 2005

http://www.eltoroairport.org/issues.html#noise

Envia, E., “Fan Noise Reduction: An Overview,” AIAA-2001-0661, 2001.

Estevadeordal, J., Gogineni, S., Goss, L., Copenhaver, W., and Gorrell, S., “Study of

Wake-Blade Interactions in a Transonic Compressor Using Flow Visualization and

DPIV,” ASME Journal of Fluids Engineering, 2002, Vol. 124, pp. 166-175.

Fearn, R. & Weston, R., 1974, “Vorticity Associated with a jet in cross flow”, AIAA J.

12, 1666-1671

Guillot S., Stitzel S., Burdisso R., 2002, “Fan Flow Control for Improved Efficiency and

Noise Reduction”, Fan Phase II proposal

Holdeman, J.D., & Walker, R.E., “Mixing of a Row of Jets with a Confined Crossflow”,

AIAA 1977 0001-1452 vol. 15 no. 2, 243-249

International Air Transport Association, April, 2005

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on Mixing and Emissions From a Reacting Crossflow at Atmospheric Pressure”, NASA

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AIAA J. 10, 1425-1429

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Mcgraw-Hill, 1986

46

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Turbofan Engine” AIAA-2000-0224, 2000

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Blowing,” Masters Thesis, Mechanical Engineering Department, Virginia Polytechnic

Institute and State University, Blacksburg, Virginia, 1997.

Naumann, R.G., “Control of the Wake from a Simulated Blade by Trailing Edge

Blowing”, Masters Thesis, Lehigh University, Bethlehem, PA, 1992

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Evaluation,” NASA/CR 159488, 1979.

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Trailing Edge Blowing.” Masters thesis, Virginia Polytechnic Institute and State

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Management Strategies for reduction of Rotor-Stator Interaction Noise”, Masters Thesis,

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Cambridge, MA, February 1997

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47

Appendix A: Techsburg Inc. Facility

The compressor used was a Kaeser CSD-100S screw type (1:1 drive), rated to 217

psig with a capacity of 288 CFM. Air into the compressor had to first be passed though

an Airtek CTHP330, which lowered the dew point of the air to roughly 40 degrees

Fahrenheit. The storage tanks are rated to 250 psig but for these tests a pressure of 135

psig was sufficient. Once the tanks were fully pressurized, a solenoid valve could then be

opened by means of a Siemens Moore 353 PID controller. The solenoid valve is an 8”

Leslie DBOY, balanced cage guided type, which incorporates an electro-pneumatic

controller. Figure A-1 shows the solenoid valve, the compressor, and the dryer. Figure

A-2 shows a view of the wind tunnel. Figure A-3 shows the flow control arrangement for

the cascade tests. It includes an upstream pressure regulator, thermocouple, and an

orifice meter. For flow seeding experiments the seeding device was added downstream

of the orifice meter as shown.

Figure A-1: (a) Kaeser compressor (b) Airtek dryer (c) Leslie DBOY valve

48

Figure A-2: Blow down wind tunnel operated at Techsburg, Inc.

Figure A-3: Flow control arrangement

49

Appendix B: Uncertainty Analysis

The following is an uncertainty analysis for the pressure measurement equipment as

well as the DPIV. Uncertainty for DPIV was provided by Estevadeordal et al. (2002)

Instrument uncertainties for pressure measurements include linearity, hysteresis, and

repeatability. Experimentally, the pressure measurement equipment performed much

better than the specifications provided by the manufacturer. Equation B-1 and Equation

B-2 show the maximum propagation uncertainty for the Mach number and pressure loss

coefficient.

Measurement Instrument Instrument Uncertainty

P1 0-5 psi Validyne Pressure transducer ±0.0125 psi

P2 0-5 psi Validyne Pressure transducer ±0.0125 psi

P3 0-5 psi Validyne Pressure transducer ±0.0125 psi

Pup_total 10-30 psi pressure transmitter ±0.04 psi

Pup_static 10-20 psi pressure transmitter ±0.02 psi

Table B-1: Instrument Uncertainties

Calculated Parameters Maximum Propagated Uncertainty

Pressure loss Coefficient ±0.01

Inlet Mach Number ±0.0066

Mass flow, jets ±0.00069 lbm/s

Momentum Coefficient ±0.005

Free Stream Velocity ±2m/s

Flow Angle ±0.50°

Table B-2: Maximum Propagated Uncertainty

Equation B-1

2

3

3

2

_

_

2

_

_

∂

∂+

∂

∂+

∂

∂= HP

HP

upStat

upStat

upTot

upTot

PP

PP

PP

δω

δω

δω

δω

Equation B-2

2

_

_

2

_

_

∂

∂+

∂

∂= upStat

upStat

upTot

upTot

PP

MP

P

MM δδδ

50

Uncertainty on velocity calculation from PIV

The velocity U (m/s) is computed using the formula U = ∆x / ∆t / M, where ∆x is the

displacement (pixels) of each interrogation region during ∆t (sec), the time interval

between the two exposures, and M is the magnification of the digital image relative to the

object (pixels/m). The displacement in pixels is obtained by using peak locator

algorithms (centroid) that finds the location of the peak on the correlation map obtained

from cross-correlating the two images and corrects for various biases [Westerweel, 1997]

and yields to sub-pixel accuracy (< 0.1 pixels). The ∆t is adjusted to yield typical

displacements of > 10 pixels to yield an uncertainty of <1%. Values in the lower velocity

regions however have higher uncertainties due to the lower ∆x; for example, a ∆x of 1

pixel could yield to uncertainty of ~ 10%. The maximum uncertainty in the ∆t is

calculated from the time interval between the two laser pulses. It was found that this

uncertainty increases with lower laser power and with lower ∆t. A conservative number

for the typical PIV experiments using a ∆t of 2 µs and powers around 20 mJ was found to

be 1%. The magnification is measured using images of targets located in the laser sheet

plane and it is read to better than 1%. Combining these three conservative measurements

of uncertainties yields to a maximum error of < 2% for 2D PIV with a camera at 90o

viewing. ISSI has recently developed and implemented high-resolution PIV algorithms

that include multipasses, multigrids and correlation corrections schemes that yield to

improved SNR.

51

Appendix C: DPIV images and equipment

LaserSheet

OpticalProbe

Nd:YAG

Nd:YAG

Sync

Computer

PIV Camera

Seed

Figure C-1: Schematic of DPIV setup for typical cascade measurements

Camera: Kodak/Redlake Model ES1, cross-correlation PIV, 1008 x 1012 pixels or 1k x 1k, 8 bit

greyscale. Used two for two simultaneous synchronized views.

Lasers: NewWave Solo 120-PIV, Dual Head (2 lasers in same head, one single power

supply)120 mJ/pulse max power, pulses are 5 nanosec duration, lasing media is solid rod

Nd:YAG at 15 Hz max. rep rate each laser or 30 Hz both lasers.

Electronic box: Delay generator Stanford 535 for synchronize lasers camera computer

Frame grabber: Transfers images from cameras to computer: EPIX FG model; driven by XCAP

software.

PIV software: ISSI post processing algorithms etc for velocity calculations.

Seeder: Cyclon type fluidized bed with tangential high pressure air to inject solid particles into

flow (AlOx submicron particles); location far upstream to non influence the flow with the rod or

the jets.

Optics: Prisms to direct beam, spherical to focus at test area, cylindrical lenses or rod to spread

into a sheet; access to tunnel is thru Lexon window at bottom and/or probe inserted above

tailboards.

Table C-1: Equipment specifications for DPIV

52

Figure C-2: Kodak/Redlake Model ES1, cross-correlation PIV.

Free Stream Seeding Images

Figure C-3: Free Stream Seeding Images, SS and PS

Baseline 0.50% 0.75%

1.25% 1.00%

53

Figure C-4: Free Stream Seeding Images, Blunt TE 12 Jets

Figure C-5: Free Stream Seeding Images, Sharp TE 12 Jets

54

Figure C-6: Free Stream Seeding Images, Slot Blade

In Figure C-7, a median velocity obtained from the particles passing through location

2 was graphed with respect to the percentage of pitch. The percent pitch axis is focused

on the wake region and does not include an entire pitch as with the pressure loss

coefficient data. For this reason, velocities on the pressure side of the blade were slightly

lower than that of the suction side. The baseline case has a velocity deficit in the wake

region associated with the higher losses determined from the local total pressure loss

coefficient. As blowing was increased, the velocities in the wake region began to rise

and would eventually equal those in the rest of the region. This figure agrees with the

findings in chapter 3 and shows steady velocities for 0.75%. Increases in blowing show

velocity profiles becoming higher in this region. Similar trends are noticed in the other

test cases shown in Figure C-8 through Figure C-11.

55

Figure C-7: Mean velocity vs. % pitch for SS and PS, Location A

Figure C-8: Mean velocity vs. % pitch for 12 jets, blunt TE, Location A

Figure C-9: Mean velocity vs. % pitch for 12 jets, sharp TE, Location A

SS+PS Jets

Suction

Side

Pressure

Side

12 Jets Blunt TE

Suction

Side Pressure

Side

12 Jets Sharp TE

Suction

Side Pressure

Side

Suction

Side Pressure

Side

56

Figure C-10: Mean velocity vs. % pitch for ejector pump, Location A

Figure C-11: Mean velocity vs. % pitch for slot blade, Location A

Ejector Pump

TE Slot

Suction

Side

Suction

Side

Pressure

Side

Pressure

Side

57

Appendix D: Cascade Test Data

The isentropic supply total pressure was found from Equation D-1, where P is the

static pressure in the test section and the mach number of the jet is found from Equation

D-2. Knowing this supply pressure gives some indication as to what pressure would be

needed from an engine compressor. Configurations which use lower supply pressures

would be more efficient in terms of the bleed air required to produce certain mass flow

rates. Figure D-1 shows a plot of average loss coefficient versus this isentropic supply

total pressure. This figure clearly shows the ability of the SS and PS jets to reduce

average losses at considerably lower supply pressures

Equation D-1 120

2

11

−

−+=

γγ

γJetM

P

P

Equation D-2 a

VM Jet

Jet =

-0.02

-0.01

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0 2 4 6 8 10 12 14 16 18 20 22 24

Isentropic Supply Total Pressure (psig)

Avera

ge L

oss C

oeff

icie

nt, ωω ωω

12 Jets, Sharp TE

12 Jets, Blunt TE

SS and PS

Ejector Pump

Figure D-1: Average loss coefficient vs. isentropic supply total pressure

58

Jet mass flow data

* refers to motive mass flow for ejector pump

Mass Flow % 12 Jets Sharp 12 Jets Blunt SS and PS Ejector Pump Slot Blade

0.25% 84 84 84 *63 20

0.50% 169 169 169 *131 40

0.75% 253 253 253 *196 59

1.00% 338 338 338 *262 79

1.25% 341 341 341 *327 99

1.45% - - - - 115

1.75% - - - - 139

2.00% - - - - 159

Table D-1: Jet Velocities for all test cases

Mass Flow % 12 Jets Sharp 12 Jets Blunt SS and PS Ejector Pump Slot Blade

0.25% 0.0018 0.0018 0.0018 *0.0013 0.0004

0.50% 0.0072 0.0072 0.0072 *0.0056 0.0017

0.75% 0.0161 0.0161 0.0161 *0.0125 0.0038

1.00% 0.0286 0.0286 0.0286 *0.0222 0.0067

1.25% 0.0361 0.0361 0.0361 *0.0346 0.0105

1.45% - - - - 0.0141

1.75% - - - - 0.0206

2.00% - - - - 0.0269

Table D-2: Momentum Coefficients for all test cases

Mass Flow % 12 Jets Sharp 12 Jets Blunt SS and PS Ejector Pump Slot Blade

0.25% - - - - -

0.50% 2.4754505 2.4754505 2.4754505 *1.45129317 0.12891233

0.75% 6.00372514 6.00372514 6.00372514 *3.41740719 0.2913

1.00% 11.82625427 11.82625427 11.82625427 *6.46807277 0.520886

1.25% 21.00822873 21.00822873 - *10.94123071 0.82

1.45% - - - - 1.1115

1.75% - - - - 2.16

2.00% - - - - -

Table D-3: Isentropic Supply Total Pressures for all test cases

Mass Flow % 12 Jets Sharp 12 Jets Blunt SS and PS Ejector Pump Slot Blade

0.25% - - - - -

0.50% 0.0279 0.0345 0.0183 *0.0378 0.0399

0.75% 0.0252 0.0262 0.0029 *0.0340 0.0372

1.00% 0.0080 0.0132 -0.0107 *0.0206 0.0364

1.25% -0.0054 -0.0031 - *0.0060 0.0410

1.45% - - - - 0.0383

1.75% - - - - 0.0253

2.00% - - - - -

Table D-4: Average Loss Coefficient for all test cases

59

Mass Flow % 12 Jets Sharp 12 Jets Blunt SS and PS Ejector Pump Slot Blade

0.25% 0.712 0.712 0.712 *0.534 0.169

0.50% 1.432 1.432 1.432 *1.110 0.339

0.75% 2.144 2.144 2.144 *1.661 0.500

1.00% 2.864 2.864 2.864 *2.220 0.669

1.25% 2.890 2.890 2.890 *2.771 0.839

1.45% - - - - 0.975

1.75% - - - - 1.178

2.00% - - - - 1.347

Table D-5: Velocity Ratio for all test cases

Mass Flow % 12 Jets Sharp 12 Jets Blunt SS and PS Ejector Pump Slot Blade

0.25% 0.246 0.246 0.246 *0.185 0.059

0.50% 0.496 0.496 0.496 *0.384 0.117

0.75% 0.742 0.742 0.742 *0.575 0.173

1.00% 0.991 0.991 0.991 *0.768 0.232

1.25% 1.000 1.000 1.000 *0.959 0.290

1.45% - - - - 0.337

1.75% - - - - 0.408

2.00% - - - - 0.466

Table D-6: Jet Mach Number for all test cases