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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
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AIAA 1977 0001-1452 vol. 15 no. 2, 243-249
International Air Transport Association, April, 2005
http://www.iata.org/whatwedo/environment/aircraft_noise.htm
John, D. St., & Samuelsen, G. S., 2000, “Effect of Jet Injection Angle and Number of Jets
on Mixing and Emissions From a Reacting Crossflow at Atmospheric Pressure”, NASA
CR-2000-209949
Kamontani , Y. & Greber, I., 1972, “Experiments on a Turbulent Jet in a cross flow”,
AIAA J. 10, 1425-1429
Karassik, I.J., Krutzsch, W.C., Fraser, W.H., Messina, J.P., Pump Handbook, 2nd ed.,
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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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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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