School of Aerospace Engineering MITE RECENT PROGRESS IN COMPRESSOR STALL AND SURGE CONTROL L. N....

School of Aerospace Engineering

MITE

RECENT PROGRESS IN RECENT PROGRESS IN COMPRESSOR COMPRESSOR

STALL AND SURGE CONTROLSTALL AND SURGE CONTROL

L. N. Sankar, J. V. R. Prasad, Y. Neumeier, W. M. HaddadN. Markopoulos, A. Stein, S. Niazi, A. Leonessa

School of Aerospace EngineeringGeorgia Institute of Technology

Supported by the U.S. Army Research Office Under the Multidisciplinary University Research Initiative (MURI) on Intelligent Turbine Engines


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Background

• Modern turbine engines are highly developed, complex systems.

• There is a continuing trend towards fewer stages, and high pressure ratios per compression stage.

• Compressor instabilities (rotating stall and surge) develop, that must be controlled at high pressure ratios, especially at low mass flow rates.


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Compressor Performance Map

Cho

ke L

imi t

Sur

ge L

imit

Volumetric Flow Rate

Tot

al P

ress

ure

Ris

e

Desired Extension of Operating Range

Lines of Constant Efficiency

Lines of Constant Rotational Speed


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SurgePressure Rise

Flow Rate

PeakPerformance

Mild Surge Deep Surge

An “axisymmetric” phenomenon that causes periodic variations in mass flow rate and pressure rise. Deep surge can create a reversed flow in the entire compression system.

Pressure Rise

Flow Rate

MeanOperating Point

Limit CycleOscillations


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ROTATING STALL

Loca

l Sep

arat

ion

Loca

l Sep

arat

ion

1

Rotating Stall is a local separation patternthat rotates at a fraction of the spool RPM


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Different Strategies for Compressor Control

Controller UnitBleed Air

PressureSensors

AirInjection

Bleed Valves

Movable Plenum Walls

Guide Vanes

Steady Blowing


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Prior Work• An excellent survey by Bram de Jager summarizes

worldwide activities on rotating stall and surge control.

• A number of researchers in U. S. are exploring compressor stall and surge control, using theoretical, computational, and experimental techniques.

– MIT, Purdue, Penn State, Cal Tech, Wright Labs, and all major U. S. Industries

• This presentation will focus on Georgia Tech Activities.


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Georgia Tech Center for IntelligentTurbine Engines

– Start Date: November 1, 1995

– Research Team: Eleven faculty members with expertise in controls, compressors, combustion,

propulsion, fluid mechanics, diagnostics, MEMS and neural net.

– Facilities: Combustion, compressor, micro- electronics and fluid mechanics laboratories

– Research Areas: Control of combustor processes, Nonlinear control theory, Control of compressor stall and surge,

MEMS


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MITE Program Objectives Develop general

• Control approaches

• Sensors/actuators

• Computational approaches

that will permit engine manufacturers to improve the design process,performance, operability and safety of future gas turbines.

Demonstrate developed technologies on small-scale experiments

Transfer developed technologies to industry and government


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MITE Research TeamName School Research Area

Dr. Mark Allen ECE MEMS

Dr. Martin Brooke ECE Hardware Neural Networks

Dr. Ari Glezer ME Flow control/actuators

Dr. Wassim Haddad AE Nonlinear control theory

Dr. Jeff Jagoda AE Combustion and spray diagnostics

Dr. Suresh Menon AE LES of reacting flows

Dr. Y. Neumeier AE Control of combustor and compressor processes

Dr. J.V. R. Prasad AE Control of compressor instabilities

Dr. L.N. Sankar AE CFD of compressor flow

Dr. Jerry Seitzman AE Combustion mixing control and sensors

Dr. Ben Zinn AE/ME Control of instabilities and combustion processes

Supporting Staff: Research engineers, post doctoral fellows, graduate students, machineand electronic shops personnel, computer group, library and administrative supportpersonnel.


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Research Activities Control of combustor mixing processes (e.g., fuel-air, combustor

pattern factor) via synthetic jets

Control of axial and centrifugal compressor stall by passive andactive (e.g., flow throttling, fuel flow rate control) means

Wireless MEMS pressure sensor for high temperature applications

Neural net control of combustion processes

Nonlinear control framework for engine compression systems

CFD of compression systems

LES of two-phase reacting flows

“Smart” fuel injection systems


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Compressor Control- Modeling Efforts

• Two and three-dimensional compressible flow solvers for modeling compressor stall and surge control

• Multi-mode models for rotating stall and surgein axial flow compressors

• Centrifugal compressor model for surge control involving pressure, mass flow rate, and impeller RPM dynamics

• Model extensions for compressor stall control via fuel modulations


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Compressor Control- Theory

• Reduced order models based on CFD for modelingcompression system transients

• Optimal nonlinear control framework to address disturbance rejection, control saturation and robustness

• Adaptive control framework for elimination of rotating stall and surge

• Nonlinear stabilization framework for interactionbetween higher order system modes

• Combined model and fuzzy rule based methodologyto address actuator rate and amplitude limits

• Corrections to rotating stall control theories.


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A Simplified Compressor Model with Heat Addition

pN

oddnn

nAnrn

ncK

ddA

1!

)()(

1

pN

evennn

nAnsn

ncK

dd

0!

)()(

2

outTΔΨ

TK5KΦ4K7KdτGd

~~

)ct1(toutT1ΔΨ9KG1

8KdτoutTd

~

~

~

Q6KoutT

~TK5K4K3K

d)(d ΔΨ


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Experimental Studies

• Experimental Demonstrations– Rotating stall control through

• Throttling

• Recirculation of air from plenum to inlet

• Combustion process modulations

• Passive means

• New facility development– A centrifugal compressor facility for the study of

flow dynamics, and for the development of active and passive control methods


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Sample Results

• Experimental Studies

• Control Theory

• CFD Modeling


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Schematic of the Axial Compressor Facility (Bleed Control)

Controller

Rotatingstallamplitude

Servo motor and throttle

Computer Main Throttle

Bleed/recirculation loop


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Schematic of the Axial Compressor Facility (Fuel Control)

Fuel Supply

Main Throttle

Controller

Rotatingstallamplitude

Needle Valve

Servo motor

Computer

Fuel modulation loop

Diffusion flame simulates heat release in a real engine combustorOperating point around 300 0F


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Fuzzy Logic Control of Rotating Stall

• Fuzzy Rules were developed using numerical simulations.

• The numerical simulations utilized the Moore-Greitzer Model, a system of ODEs.

• Control variable was the amount of opening of a bleed valve placed in the plenum chamber.

• Following simulations, these rules were implemented in hardware, at our axial compressor facility.


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Fuzzy Logic Controller

Compression System

Defuzzifier Inference Engine Fuzzifier

Measured/ComputedPressure Fluctuationsat compressor casing

Throttle OpeningOutput


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Fuzzy Logic Control of Rotating Stall

0

100000

200000

300000

400000

500000

600000

700000

800000

0 10 20 30 40 50 60 70 80 90 100

Main Throttle(%)

Ro

tati

ng

Sta

ll A

mp

litu

de Closed-Loop Fuzzy Logic

Control 50% Bleed

bleed

bleed


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Rotating Stall Control by Flow Separators

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

0.02

35.0 40.0 45.0 50.0 55.0 60.0

Main Throttle Openning (%)

Rot

. Sta

ll A

mpl

itude

(%

of

Pam

b)

No Separator

8 Separators

8 Separators with active feedback control

No Separator with active feedback control


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CFD ModelingCFD Modeling

Perspective View of the NASA Low Speed Centrifugal Compressor

• Detailed study and simulation of NASA Low Speed Centrifugal Compressor

• Simulation and Validation of Air Bleeding & Blowing/Injection as a Means to Control and Stabilize Compressors Near Surge Line

• Useful Operating Range of Compressor was Extended to 60% Below Design Conditions


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Simulation Setup

• 20 Full Blades with 55° Backsweep

• Inlet Diameter 0.87 m

• Exit Diameter 1.52 m

• Tip Clearance 2.54 mm (1.8% of Blade Height )

• Design Conditions:

– Mass Flow Rate 30 kg/sec

– Rotational Speed 1862 RPM

– Total Pressure Ratio 1.14

– Adiabatic Efficiency 0.992

NASA Low Speed Centrifugal CompressorNASA Low Speed Centrifugal Compressor


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Uncontrolled Operation

1.05

1.07

1.09

1.11

1.13

1.15

1.17

1.19

1.21

1.23

1.25

15 20 25 30 35 40 45

Corrected Mass Flow (kg/s)

Tot

al P

ress

ure

Rat

io

Experiment

CFD

Stall, Unstable

Design Point

Stable OperationC

Uncontrolled, Stall OperationLarge, Unbounded Fluctuations

-2

-1

0

1

2

-25 -15 -5 5

% of Mass Flow Rate Fluctuations

% o

f Tot

al P

ress

ure

Fluc

tuat

ions C


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Off-Design Results (Uncontrolled)

Unstable Condition Blades Stall After 3 Cycles (t*)

At Beginning

After 1 Cycle

After 3 Cycles (t*)

Velocity Vectorsat Midpassage

GrowingReversed Flow

LE

TE


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Compressor Control Setup

0.04RInlet

Impeller

Casing

°

RInlet

Rotation Axis

Injection Angle, =5ºYaw Angle, =0º5% or 10%Injected Mass Flow Rate


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Controlled Operation

Controlled Operation with 10% Air Injection (Fluctuations are Decreased to 2~3%Extension of Useful Operating Range (60% Below Design)

-2

-1

0

1

2

-25 -5

% of Mass Flow Rate Fluctuations

% o

f Tot

al p

ress

ure

Fluc

tuat

ions

D

1.05

1.07

1.09

1.11

1.13

1.15

1.17

1.19

1.21

1.23

1.25

5 15 25 35 45

Corrected Mass Flow (kg/s)

Tot

al P

ress

ure

Rat

io

Experiment

CFD

10% Injection

5% Injection

Stall, Unstable

Design PointControlledAir Injection

D

.m=17.5 kg/sec )


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Air Injection

0

25

50

75

100

-0.3 -0.1 0.1 0.3 0.5Normalized Axial Velocity, Vn/Ut

Per

cent

Im

mer

sion

No Injection (t*)

5% Injection

10% Injection

Controlled, Stable Operation

Injected Air (10%)

Injection SuppressesStalled Reverse FlowRegions Near LE


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DLR Centrifugal Compressor

0

0.5

1

1.5

2

2.5

3

0 0.2 0.4 0.6 0.8 1

Meridional Chord, S/Smax

Loc

al S

tatic

Pre

ssu

re,

p/pt

o Experiment (time mean)

CFD

Control simulationsare currently inprogress


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NASA ROTOR-67Axial Compressor

0.6

0.8

1

1.2

1.4

1.6

-125 -50 25 100 175 250

% Chord

M

CFD

EXP.l

Relative Mach No. at 30% Pitch

Results for Rotating Stall Simulation considering six flow passages are in progress

51.4 cm


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Concluding Remarks

• A concerted effort involving control theory, simulations and experimental studies is underway at Georgia Tech to understand and control compressor instabilities.

• Encouraging results have been obtained in all these areas.

• A combined CFD-Feedback Control simulation is currently in progress.

School of Aerospace Engineering MITE RECENT PROGRESS IN COMPRESSOR STALL AND SURGE CONTROL L. N....

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