Sanjay Garg

Glenn Research Center, Cleveland, Ohio

Klaus Schadow

Schadow Technology, San Clemente, California 

Wolfgang Horn and Hugo Pfoertner

MTU Aero Engines, München, Germany

Ion Stiharu

Concordia University, Montreal, Quebec, Canada

Sensor and Actuator Needs for 

More Intelligent Gas Turbine Engines

NASA/TM—2010-216746

July 2010

GT2010–22685
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Sanjay Garg

Glenn Research Center, Cleveland, Ohio

Klaus Schadow

Schadow Technology, San Clemente, California 

Wolfgang Horn and Hugo Pfoertner

MTU Aero Engines, München, Germany

Ion Stiharu

Concordia University, Montreal, Quebec, Canada

Sensor and Actuator Needs for 

More Intelligent Gas Turbine Engines

NASA/TM—2010-216746

July 2010

GT2010–22685

National Aeronautics and

Space Administration

Glenn Research Center

Cleveland, Ohio 44135

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Level of Review: This material has been technically reviewed by technical management. 
Sensor and Actuator Needs for More Intelligent Gas Turbine Engines 

Sanjay Garg 

National Aeronautics and Space Administration 

Glenn Research Center 

Cleveland, Ohio 44135 

Klaus Schadow 

Schadow Technology 

San Clemente, California 92673 

Wolfgang Horn and Hugo Pfoertner 

MTU Aero Engines 

80995 München, Germany 

Ion Stiharu 

Concordia University 

Montreal, Quebec, Canada H3G 1M8 

Abstract 

This paper provides an overview of the controls and 

diagnostics technologies, that are seen as critical for more 

intelligent gas turbine engines (GTE), with an emphasis on the 

sensor and actuator technologies that need to be developed for 

the controls and diagnostics implementation. The objective of 

the paper is to help the “Customers” of advanced technologies, 

defense acquisition and aerospace research agencies, 

understand the state-of-the-art of intelligent GTE technologies, 

and help the “Researchers” and “Technology Developers” for 

GTE sensors and actuators identify what technologies need to 

be developed to enable the “Intelligent GTE” concepts and 

focus their research efforts on closing the technology gap. To 

keep the effort manageable, the focus of the paper is on “OnBoard Intelligence” to enable safe and efficient operation of 

the engine over its life time, with an emphasis on gas path 

performance. 

Introduction 

With the increased emphasis on aircraft safety, enhanced 

performance and affordability, and the need to reduce the 

environmental impact of aircraft, there are many new 

challenges being faced by the designers of aircraft propulsion 

systems. There is significant investment being made by 

various NATO (North Atlantic Treaty Organization) countries 

in development of advanced controls and health management 

technologies that will help meet these challenges through the 

concept of Intelligent Propulsion Systems. The key enabling 

technologies for an Intelligent Propulsion System are: the 

increased efficiencies of components through active control; 

advanced diagnostics and prognostics integrated with 

intelligent engine control to enhance operational reliability and 

component life; and distributed control with smart sensors and 

actuators in an adaptive fault tolerant architecture. 

Development of appropriate sensor and actuation systems is 

critical to affordable and reliable implementation of the 

technologies for a more intelligent gas turbine engine. 

In 2004, NATO RTO (Research and Technology 

Organization) established an Applied Vehicle Technology 

(AVT) Task Group to review the status of technologies that 

contribute to a “More Intelligent Gas Turbine Engine” and 

recommend technology development needs with an emphasis 

on the type of sensors and actuators needed to enable these 

technologies. The Task Group completed its work in 2008 and 

published a NATO RTO report documenting the findings in 

April 2009 (Ref. 1). The objective of the report was twofold: 

i) Help the “Customers” (NATO defense acquisition and 

aerospace research agencies) understand the state-of-the-art of 

intelligent engine technologies, how these technologies can 

help them meet challenging performance and operational 

reliability requirements for aircraft engines, and what 

investments need to be made in sensor and actuator 

technologies to enable the various capabilities of “Intelligent 

Engines” so that limited resources are used in a most efficient 

manner; and ii) Help the “Researchers” and “Technology 

Developers” identify what sensor and actuator technologies 

need to be developed to enable the “Intelligent Engine” 

concepts so that their research efforts can be focused on 

closing the gap from current capability to that needed to meet 

identified requirements, and also increase their awareness of 

“requirements” that need to be met other than performance 

(such as cost, durability, etc.) to enable the transition of 

technology to a product. 

The overall technology areas that fall under the umbrella of 

“intelligent engines” are too broad to be covered by one report. 

To keep the effort manageable, the focus of the report was on 

“On-Board Intelligence” to enable safe and efficient operation 

of the engine over the life time, and adapt to changing internal 

and external environments to provide “optimum” achievable 

performance based on operation mode and current conditions. 

NASA/TM—2010-216746 1 
The discussion in the report was limited to: i) description of 

technologies for active control of components in the gas path to 

enhance performance and reduce emission and noise; 

ii) intelligent control and condition monitoring from the overall 

engine gas path performance perspective; and iii) advanced 

control architecture concepts such as distributed engine control. 

This paper provides an overview of the significant findings of 

the report in terms of identifying the sensor and actuator needs 

to realize these intelligent engine concepts with the ultimate 

objective being to identify sensor and actuator technology 

development roadmaps. 

The paper is organized as follows. The first section discusses 

various concepts for active control of engine gas path 

components such as inlet, compressor, combustor, turbine and 

nozzle, with an emphasis on performance and operating 

environment specifications for sensors and actuators to enable 

the active component control capability. The next section 

describes the various aspects of intelligent engine control and 

condition monitoring from an overall gas path system 

perspective and discusses the sensor needs for implementation 

of model based control and diagnostics. The technologies 

required to move from the current highly centralized engine 

control architecture to more distributed control architecture are 

then discussed. This section discusses challenges due to the 

harsh environment of the engine, as summarized in Figure 1, 

and weight and volume limitations that imply the need for 

developing high temperature electronics and data 

communication hardware to enable smart, self diagnostic 

sensors and actuators to fully utilize the benefits of distributed 

control architecture. The requirements, other than performance, 

that a sensor or actuator technology needs to meet in order to be 

considered for implementation on an engine are then briefly 

discussed in the next section. The paper concludes by 

summarizing a roadmap to intelligent engine technology 

development. 

Actively Controlled Components 

Modern aircraft engines face challenging performance 

requirements driven by customers’ and public needs. To achieve 

these requirements, the engine has to operate at the physical 

limits which are given by material and gas properties. Gas 

turbines also face a variety of challenges during operation such 

as: Inlet flow distortion and separation; Compressor surge and 

stall; Combustion instabilities; Flow separations on airfoils; 

Flutter and high cycle fatigue; and Engine noise (Ref. 2). The 

traditional engine control design problem has been to transition 

the operating point of the engine from one point to another in 

the most expedient manner without compromising any 

predefined limits. The presence of full authority digital engine 

controllers (FADECs) on most modern aircraft offers the 

possibility to take advantage of more sophisticated control 

techniques. The rapid progress of micro processing capability 

combined with advances in sensor technology, becoming 

cheaper, faster, and smaller, offer new possibilities of effective 

engine control. 

Figure 1.—Environment within an aircraft gas turbine engine.

Current engine components are designed with large safety 

margins to ensure safe operation in worst case deterioration 

and operating conditions. The potentially available 

performance of engine components often is not exploitable 

due to the fact that different limits and margins have to be 

taken into account during the design (Ref. 3). One way to 

overcome this situation is the use of active elements in gas 

turbine engines. The idea behind active control is the ability to 

sense the current condition and to react with an adequate 

control action. Unstable operating conditions can be avoided 

by changing the component behavior. Extreme or deteriorated 

conditions can be covered by adapting the component to the 

current situation. Thus, the components can be optimized at 

the design stage without compromising performance by 

operational limits or singular events. Furthermore, an actively 

controlled engine will offer the best possible performance at 

any flight condition and point of time. 

An important aspect of active control is its system nature. 

Although a control system consists of many separate 

components, it is essential to keep an overall systems 

perspective in mind when designing these subcomponents. 

The physical process is determined by the interaction of 

different phenomena and the interaction of individual 

elements. Adding feedback control can change the system 

dynamics and a controlled component can have different 

properties. An interdisciplinary (fluids, control, structures, 

instrumentation,...) approach is needed for success because the 

systems aspects are critical (Refs. 4 and 5). 

In the following, the benefits of active control technologies 

to further increase the operational flexibility and efficiency of 

each engine component is briefly reviewed, including 

highlighting the physical control processes and characterizing 

the sensor and actuator technology needs. The sensors and 

actuators have to operate reliably in the gas path pressure and 

temperature conditions summarized in Figure 1. 

Active Inlet Flow and Noise Control

The main purpose of an engine intake is to provide the first 

compressor stage with nearly clean and undistorted air. For 

50 000g centrifugal

 acceleration

>100g casing vibration

 to beyond 20kHz

2000+oC 

Flame temperature

- 40oC ambient

Cooling air

at 650+oC

1100+oC

Metal temperatures

10 000rpm

0.75m diameter

40+ Bar

Gas pressures

8mm+

Shaft movement

2.8m

Diameter

Foreign objects

Birds, Ice, stones

Air mass flow 

~2 tonne/sec

Aerodynamic 

Buffeting

120 dB/Hz to 10kHz

20000+ hours

Between service

NASA/TM—2010-216746 2 
NASA/TM—2010-216746 3 

commercial aircraft the engine intake is integrated into the 

nacelle. The challenge for these configurations is the increased 

tolerance against cross wind which usually requires thicker 

intake lips. But thicker intake lips generate significantly higher 

aerodynamic losses and, consequently, higher SFC (Specific 

Fuel Consumption) during cruise. The application of active or 

deployable-on-command passive flow control mechanisms 

enable the avoidance of the design antagonism. For military 

aircraft, the engine is completely embedded into the aircraft 

frame in order to reduce the aerodynamic losses and radar 

pattern of the airframe. The intake duct for these applications 

is formed as an S-shape duct connecting the intake opening in 

the airframe with the front stage of the installed engine in 

order to improve the stealth characteristic of the aircraft. The 

purpose of the S-shape intake duct is the reorganization of the 

air in order to provide the compressor an undisturbed 

axisymmetric flow. The challenge for this type of 

configuration is the prevention of flow separation during the 

flow reorganization and turning during all flight conditions 

(take-off, cruise and climb). 

In general, the active control of inlet flow distortions at the 

engine intake face (fan or low pressure compressor) can 

improve both the efficiency of the intake itself (by intake loss 

reduction) and the level of flow conformity upstream of the 

compressor. The reduced flow distortion reduces the jeopardy 

of a stalled compressor and can be traded against higher 

compressor efficiency. Possible active flow control devices 

are deployable vortex generators, pulsed micro jets or an 

active intake shape change. Reference 6 provides an example 

study of active flow control for inlets. 

Active noise suppression is also a research area for inlet 

control. A number of concepts have been proposed to improve 

the effectiveness of acoustic treatment found in the inlet of 

commercial aircraft engines. Some of these techniques include 

actively modifying the porosity of the face sheet covering the 

inlet honeycomb structure and therefore actively changing the 

acoustic characteristics of the cavities in the honeycomb. 

Active noise cancellation that generates noise in the aircraft 

engine inlet to cancel the noise generated by the fan is another 

concept being studied. This technology works to reduce tones 

—that are characteristic of the noise generated by the rotorstator interaction. The technology works to reduce noise, but 

the accompanying system (measurement devices, acoustics 

sources, and controllers) makes it difficult to package the 

device in a real system (Ref. 7). 

Based on the above discussion, the sensor and actuator 

requirements for active inlet control are listed in Table 1. 

TABLE 1.—SENSOR AND ACTUATOR REQUIREMENTS FOR ACTIVE INLET CONTROL 

Technology Sensed 

variable 

Sensor requirements Controlled variable Actuator requirements 

Active inlet 

flow control 

Static 

pressure 

• 0 to 500 Hz bandwidth 

• ±0.1% accuracy 

• Case-mounted installation 

• Inlet geometry, vortex 

generator geometry, flaps, 

jet, suction 

• Flow control bandwidth 0 to 2 kHz 

• 0 to 2% core mass flow 

• Geometry control bandwidth 0 to 100 Hz 

• Supersonic inlet control 1 to 3 Hz 

Active noise 

control 

Dynamic 

pressure 

• 100 kPa differential, 

• 10 kHz, resolution—0.5% of full 

scale output 

• Honeycomb geometry, 

acoustic waves 

• Piezoelectric actuator, 2.5 to 5 mm 

deflection 

Active Fan and Compressor Control

The compression system is one of the key elements of the 

aircraft engine. An efficient thermodynamic cycle requires 

high overall pressure ratios at a minimum amount of loss. 

Turbomachinery losses occur due to friction losses, secondary 

flows, separations and shock losses. The leakage of air 

between rotating and stationary parts forms another significant 

source of losses. The stable operation of the jet engine has to 

be assured throughout the operational envelope of the aircraft. 

For the compression system, this results in the requirement of 

stall free operation at any possible flow condition. Today’s 

compressors are designed with an adequate stall margin to 

meet this requirement. At the engineering stage, stall margin 

stack-ups are used where different effects such as transient 

operating line excursion, inlet distortion and tip clearances are 

taken into account. The stall margin requirement limits the 

exploitable performance of a compressor in terms of pressure 

ratio, efficiency, and engine dynamics. Various active control 

concepts to allow safe operation of the engine with reduced 

stall margins, and to increase efficiency by reducing clearance 

and avoiding flow separation are currently being researched. 

These are briefly discussed in the following. 

Active Stall Control 

Active stall control offers two major advantages for a gas 

turbine. A direct benefit is given by the enhanced stability of 

the compressor. This additional margin may be used to close 

existing lack of stability or to tighten operability requirements 

through quicker engine acceleration and deceleration or 

additional allowances for inlet distortion. An additional 

benefit can be gained by addressing the compressor design. If 

parts of the stall margin stack up could be provided by active 

systems only if required, the basic stack up would allow for 

lower incremental stall margin. This would release new design 
Figure 2.—Enhanced compressor operating point by 

active stall control. 

space which can be used to optimize overall performance, 

component efficiency and parts count (airfoils or stages) and 

thus production and maintenance costs. The active stall control 

concept is shown in Figure 2. 

The general feasibility of stall control has been proven in 

different compressor and engine demonstrators. The basic 

principle goes back to the possibility of detecting the flow 

conditions close to the compressor stall point and 

counteracting by blowing, guide vane movement or dethrottling. When approaching the stall point, a compressor 

develops stall precursors: high frequency pressure and velocity 

fluctuations which can be measured by pressure probes or hot 

wire sensors. The fluctuations occur as modal waves or 

pressure spikes. The time between the measured precursor and 

the stall or surge event depends on the aerodynamic nature of 

the phenomenon. The time delay between the first occurrence 

of a stall precursor and the stall event is in the order of a few 

milliseconds. Therefore, it is very challenging to measure and 

react on a characteristic unsteady disturbance which leads to a 

compressor stall. Additionally, the kind of unsteady event is 

very dependent on the actual compressor design and not 

directly transferable for different compressor designs. 

Based on the detected stall condition, different possibilities 

of counteracting and extending the stable operating range have 

been proposed. One of the promising technologies consists of 

injecting high velocity air through discrete holes in the casing 

into the tip gap of the compressor blade. The feasibility of 

extending the operating range by tip injection has been 

demonstrated in several compressor rigs as well as in complete 

engines (Refs. 8 and 9 for example). Other approaches to stall 

control consist of high frequency control of variable guide 

vanes and use of fast actuating bleed valves to stabilize the 

compression system. 

Active Flow Control 

Passive flow control has been used in the compression 

systems to improve the aerodynamics during off-design 

operation of a subcomponent. However, these devices 

decrease aerodynamic performance during operation at design 

condition. A better approach consists in a fully controlled 

application of flow control which is only deployed when 

needed. Example applications of active flow control for 

compressors are described in References 10 and 11. Some of 

the active flow control techniques currently under 

investigation include: transpirated and aspirated compressor 

airfoil and annulus; pulsed jets including zero-mass-flow 

devices (aka Synthetic Jets); micro-sized flow actuation 

devices; airfoil morphing and vortex generators. 

The typical sensed variable for active flow control is static 

pressure. However, the measurement of other physical 

properties like velocity gradients or shear stresses is 

sometimes more appropriate to describe internal conditions of 

a fluid flow. The introduction of optical measurement 

techniques (laser or infrared diodes) is advisable due to their 

non-destructive measurement principle. The development of 

advanced sensors can improve the prediction capability 

significantly, e.g. a shear stress sensor can identify a flow 

separation more reliable then a pressure sensor. 

Active Clearance Control 

Clearances represent one of the basic problems in 

turbomachinery as they have a negative impact on efficiency. 

In the compressor especially, radial blade tip clearances have a 

detrimental effect on component performance and stability. 

Active clearance control (ACC) helps to maintain stability and 

efficiency by maintaining optimized radial clearances 

throughout the whole operating range of the compressor. In 

conventional design, the thermal behavior of the compressor 

often is adapted by adding weight to the casing. Presently 

available systems are based on the thermal expansion of the 

casing, which can be controlled by modulating cooling air. 

The amount of cooling air is scheduled over an operating 

parameter, such as corrected speed or pressure ratio. Current 

ACC systems are not able to compensate transient clearance 

changes because of the thermal inertia of the casing and the 

missing link between actual clearances and amount of cooling 

air.

Innovative ACC systems are designed as closed-loop 

systems. By measuring the actual blade tip clearance a signal 

can be generated which is fed into an actuator. The actuator 

adjusts the position of the casing, modifying clearance to an 

optimum value. The actuator may be designed as a thermal, 

mechanical or pneumatic acting system (Ref. 12). The main 

advantages of advanced clearance control systems are given 

by the capability to react on any clearance change and thus 

counteracting deterioration and transient effects. This improves 

NASA/TM—2010-216746 4 
NASA/TM—2010-216746 5 

the component efficiency, not only for a new engine with 

lower incremental margins but also for a deteriorated engine 

by keeping optimum clearances over the engine life. 

Based on the above discussion, the sensor and actuator 

requirements for active control of compression system are 

summarized in Table 2. 

TABLE 2.—SENSOR AND ACTUATOR REQUIREMENTS FOR ACTIVE FAN AND COMPRESSOR CONTROL 

Technology Sensed 

variable 

Sensor requirements Controlled 

variable 

Actuator requirements 

Active stall 

Control 

Static 

pressure 

• 35 kPa dynamic range 

• ±0.2% accuracy 

• 5 to 100 kHz bandwidth

• Case-mounted 

installation 

• Jet, guide vane 

movement, bleed 

air 

• Strong dependence on stall/surge dynamics 

• Bandwidth 

• 80 to 150 Hz full amplitude 

• 500 to 600 Hz small signal 

• 1 to 4% core mass flow 

Active flow 

control 

Static 

pressure 

• 35 kPa dynamic range 

• ±0.5% resolution 

• 20 Hz to 100 kHz 

bandwidth for sensors 

(depending of the flow 

phenomena measured) 

• Jet (pulsed, zeronet-mass-flow) , 

suction, blowing, 

airfoil geometry 

change 

• Fluidic actuation devices installed in airfoil at different 

frequency ranges: 

• 200 to 300 Hz, 

• 500 Hz to 5 kHz 

• 50 to 100 kHz 

• Steady blowing of < 2% core flow at 1 to 2 Hz 

• Shape memory alloys installed in airfoil for shape variation

• Deployable within few seconds 

Active 

clearance 

control 

Clearance • 2.5 mm range 

• Accuracy 25 μm 

• 50 kHz bandwidth 

• Case-mounted 

installation 

• Casing geometry • Thermal, mechanical, pneumatic devices 

• Actuation rate > 0.1 mm/s bandwidth 1 to 5 Hz 

• Force 10 kN 

• Stroke 3 mm 

• Resolution 0.02 mm 

Active Combustion Control 

The three main areas of interest in the active control of 

aircraft engine combustion systems are: pattern factor control, 

emission minimizing control and combustion instability 

control. Of these, combustion instability control is the most 

challenging and is discussed in a little more detail below, 

followed by a brief discussion of the other two approaches. 

Combustion Instability Control 

As the requirements for reducing emissions become more 

stringent, the combustor designs move toward a “lean” burning 

solution where the fuel/air mixture is richer in air to allow for 

complete combustion of the fuel. The lowest level of NOx 

(nitrogen oxides) emissions for gas turbines can be achieved by 

employing lean combustion strategy at low flame temperature. 

However, as the fuel-air ratio approaches the lean blow-out 

(LBO) limit, the flame temperature will not support sufficiently 

fast CO (carbon monoxide) oxidation rates and its concentration 

in the combustor exhaust increases. There is a "window" of 

fuel/air ratio, and of corresponding flame temperature, that will 

simultaneously result in low NOx and CO. However thermoacoustic instabilities in these regimes are commonly observed and 

pose a development challenge. Active control of such oscillations 

will allow for more efficient combustor designs. 

Active combustion instability control (AIC) manipulates 

combustion behavior using a dynamic hardware component 

(actuator) that rapidly modifies an input into the combustion 

process. In closed-loop control, a sensor is monitoring the 

combustor output in real time to determine actuator action via 

control algorithms. Initial AIC combustor experiments were 

motivated to control combustion instabilities in aero engine 

augmenters. More recently the instability control has been 

focused on very-low emissions stationary gas turbines and will 

become critical for future aero engines with operation near 

lean blow-out limits. AIC generally focuses on combustion 

dynamics with high bandwidth actuation, typical in the 100 to 

1000 Hz frequency range. 

Despite the success of AIC implementation in surface 

power gas turbines, challenges remain for AIC 

implementation in aero-engines. These challenges include 

development of light and reliable actuators, efficient and safe 

control authority of the actuators on the combustion process, 

and robust control algorithms. A practical AIC system for 

mitigation of combustion instabilities in a lean, premixed 

single-nozzle combustor was demonstrated by United 

Technologies Research Center (UTRC) at realistic operating 

conditions (Ref. 13). A single-nozzle combustor, which 

replicated longitudinal combustion instabilities in an aero 

engine, was also used by NASA (Ref. 14). Two adaptive 

control algorithms were successfully evaluated against a 

simplified simulation of combustion instability, a physicsbased model, and in the combustor rig. 
Conventional sensors for AIC typically include 

piezoresistive-type or piezoelectric-type transducers for 

pressure measurements, and photodiodes and photomultipliers 

to provide information on chemiluminescence and heat 

release. Current sensors provide global and line-of-sight 

information. Future sensors, which would determine localized 

conditions, will benefit active control (for example local flame 

blow-out sensors and local fuel/air ration sensors). 

Challenges remain for scale-up with liquid fuel modulation, 

where time delays increase with liquid fuel atomization, 

droplet heating, vaporization, and combustion. The current 

actuator limits in amplitude, rate, and bandwidth will become 

even more severe in future applications as AIC requirements 

move to higher frequencies. For the NASA single-nozzle 

combustion rig, Georgia Tech developed a magnetostrictive 

actuator that is connected to a pintle-type injector. Other AIC 

actuators that have been developed include: (1) compression 

drivers that add acoustic energy at particular frequencies; 

(2) flow injectors that add secondary mass flux at a particular 

timing; (3) mechanical devices, piezoelectric actuators, and 

pulsed air jets that either trip the transient boundary layers or 

change the shear layer mixing; (4) pulsed-combustion 

actuators that generate periodic heat release and sound waves; 

and (5) moving surfaces that create local disturbances. 

Emission Control 

For a given combustor design, it is possible to reduce the 

NOx emission through active control of the fuel/air mixture. 

The challenges for this technology are development of 

emission sensors for the harsh engine environment, 

development of simplified NOx production models that can be 

used for control design, and determining the most suitable 

approach to actively control the fuel/air mixture ratio. 

Pattern Factor Control 

The Burner Pattern Factor is defined as the ratio of the 

difference between the maximum and average temperature at 

the turbine inlet to the average temperature at the turbine inlet. 

Reducing the burner pattern factor through active control will 

allow for more efficient fuel burning, decreased emissions and 

increased life of turbine blades. The biggest challenge here is 

getting reliable long life sensors to measure temperature in a 

high temperature environment. The actuation challenge is to 

provide independent fuel modulation for each fuel injector. 

Based on the above discussion, the sensor and actuator 

requirements for Active Combustion Control are summarized 

in Table 3. 

TABLE 3.—SENSOR AND ACTUATOR REQUIREMENTS FOR ACTIVE COMBUSTION CONTROL 

Technology Sensed 

variable 

Sensor requirements Controlled 

variable 

Actuator requirements 

Combustion 

instability 

control 

Static 

pressure 

• 10 kPa dynamic range 

• ±5% accuracy 

• 1 kHz bandwidth 

• Fuel modulation, 

acoustic energy, 

jets, moving 

surface 

• High bandwidth actuation, typically 500 Hz to 

1 kHz frequency range. 

• Fuel flow modulation goal at 1 to 5% of mean 

flow 

Emission 

control 

emissions 

(CO, NOx) 

• ±5% accuracy 

• < 5 Hz bandwidth 

• Installation in HPT 

• Fuel flow 

actuation 

• Schedule on emission sensing 

• 5 to 10% of total fuel flow modulated at 0.1 to 

1 Hz 

Pattern factor 

control 

Temperature • ± 5 °C accuracy 

• < 1 Hz bandwidth 

• Installation on HPT stator vanes 

• Fuel flow 

actuation 

• Fuel flow modulation on each nozzle 

• 5 to 10% of total fuel flow modulated at 0.1 to 

1 Hz 

 

Active Turbine Control 

Modern aero engine turbines are designed and optimized 

with respect to several main targets. As turbine efficiency has a 

strong impact on the thermodynamic cycle, the component 

efficiency plays an important role for the optimization of fuel 

burn and emissions. Increased turbine efficiency is 

characterized by large flow turning angles and high pressure 

gradients. Separation bubbles occur on the airfoil surfaces 

causing losses and limiting the design space. Another important 

source of losses are the tip clearances. Overtip leakage does not 

contribute to turbine work and causes strong vortices at the 

blade tips. As the cycle efficiency increases with temperature, 

the trend in modern gas turbines goes towards very high turbine 

inlet temperatures. Current inlet temperatures are beyond 

tolerable material temperatures, so strong cooling is required. If 

the cooling flow is injected behind the first stator vane throat, it 

will reduce the cycle efficiency to a large extent. Turbine 

capacity is another important parameter for engine operation, as 

it limits the flow through the gas turbine and controls the 

compressor working line. 

Active Turbine Tip Clearance Control 

The radial gap between the casing and the rotating parts of 

a turbine (i.e. blade tips or shroud) causes aerodynamic losses 

which negatively affect gas turbine performance. Opening this 

gap yields a decrease in turbine efficiency leading to an 

increase in thrust specific fuel consumption (TSFC). Tip 

clearance varies with rotor speed due to centrifugal forces and 

gas conditions such as temperature and pressure. Tip clearance 

changes during transient maneuvers due to the thermal 

behavior of the turbine components rotor, blades and casing. 

During an acceleration, for example, the rotor speed increases 

NASA/TM—2010-216746 6 
leading to a closure of tip clearance. The gas temperature 

increases and heats up the turbine components, wherein the 

blades heat up quickly due to their low mass and full contact 

to the gas while the casing heats up much slower. This results 

in the condition of least tip clearance within a flight mission, 

which is called “pinch point”. The difference in thermal 

behavior of the components leads to tip clearance variations 

with time even after the demanded rotor speed has been 

reached. With respect to a safe engine operation, the cold 

build clearance is designed for minimized tip clearances on 

one hand, but also for rub avoidance between blades and the 

casing in all situations within a mission. However, every 

operating point besides the pinch point features a larger 

clearance and therefore lower efficiency. Passive clearance 

control systems modify thermal behavior with different 

materials, insulation techniques, etc, but these devices are not 

capable of compensating clearance variations due to speed 

changes. In order to minimize tip clearance during different 

operating conditions, active clearance control (ACC) should 

be incorporated.

Most modern engines feature a thermal turbine ACC-system, 

which is state of the art technology. By applying cooling air 

onto the supporting structure of the turbine, the radial position 

of the casing can be modified in order to minimize tip clearance 

by thermal expansion. This technology’s benefit is mostly 

exploited during cruise operation for commercial aircraft. 

However, thermal ACC-systems are relatively slow, so they 

cannot react to quick speed changes, which must be considered 

in the amount of cooling air supplied onto the casing. Provision 

of additional clearance is necessary to allow engine acceleration 

without rub-in. 

A possibility to overcome the delay of the casing 

adjustment is to position it mechanically rather than thermally. 

NASA has investigated different mechanical actuation 

systems for the high pressure turbine (Ref. 15). Most 

sophisticated concepts for a mechanical ACC system use 

electrical or hydraulic actuation mechanisms with mechanical 

transmission. Other actuation concepts based on piezo-electric 

movement or shape memory alloys are promising but need 

further development. Closed-loop control laws incorporate a 

tip clearance sensor, giving a signal to the control unit, based 

on which the ACC actuator adapts its position. In principle, 

such closed-loop controls can detect any kind of clearance 

variation (symmetric, asymmetric, deterioration) and react 

quickly (if in use with a mechanical actuation system) 

(Ref. 16). However, turbine tip clearance sensors have to meet 

high demands on accuracy and must operate successfully in a 

high temperature, high vibration environment with 

contaminated air. 

Film Cooling Flow Control 

Structures in the hot section of a gas turbine need to be 

cooled by air flows to provide sufficient durability. As cooling 

air flows represent a loss for the thermodynamic cycle, their 

amount needs to be optimized. Film-cooling of gas turbine 

vanes is the current approach to maintaining turbine durability 

in the hot engine environment. The effectiveness of this 

approach depends on the extent to which the cool jet-fluid 

adheres to the cooled component surface. Lift-off of the 

cooling jet flow, or other mechanisms promoting mixing, 

cause loss of cooling effectiveness as they allow the hot "freestream" fluid to come in contact with the component surface. 

The cooling effectiveness can be improved by actively 

controlling the jet flow in a manner such as to prevent/delay 

lift-off and suppress mixing. Furthermore, an actively 

controlled film-cooling system coupled with appropriate 

sensory input (e.g. temperature or heat flux) can adapt to 

spatial and temporal variations of the hot gas path. Thus, it is 

conceivable that the efficiency of film-cooling systems can be 

further improved by intelligently directing the flow where it is 

most needed. Because of the small passages for the flow, it is 

envisioned that MEMS (Micro Electro-Mechanical Systems) 

technology will be critical to develop the enabling actuation 

system for active control of turbine film-cooling (Ref. 17). 

Cooling Air Control 

For state of the art core engines, about 20 to 30 percent of 

the air delivered by the HPC (High Pressure Compressor) is 

used for cooling the HPT (High Pressure Turbine), thus 

“bypassing” the cycle and having further detrimental effects 

on the core. For engines currently in service, the cooling air 

flow path is fixed and the cooling air is “hot” compressor 

discharge air. If the supplied air flow is cooled by a heat 

exchanger, colder turbine metal temperatures can be achieved. 

As a result, the amount of cooling air can be reduced or the 

turbine inlet temperature increased. Both directions lead to an 

improved gas turbine cycle.

Based on the above discussion, the actuator and sensor 

requirements for active turbine control are summarized in 

Table 4.

Active Nozzle Control

The areas to be considered for active nozzle control include 

actively reducing the exhaust noise, thrust vectoring control 

using mechanical or fluidic actuation, and afterburner stability 

control. 

Active Noise Control 

The reduction of aircraft noise continues to be the subject of 

considerable effort. Much of the effort has been on advancing 

noise reduction technologies where they can be turned on and 

off or even change geometry of the various components. The 

reason for this is that the noise reduction technologies almost 

always result in some loss of performance to the aircraft 

engine. If technologies can be developed that can be turned off 

when noise reduction is not needed, then there could be a 

system benefit to the aircraft. Two of the specific technologies 

that have been under investigation are variable geometry 

chevron nozzles and fluidic injection. Flight testing has 

demonstrated the effectiveness of serrations (chevron nozzles) 

for noise reduction, but also confirmed the expected 

NASA/TM—2010-216746 7 
NASA/TM—2010-216746 8 

TABLE 4.—SENSOR AND ACTUATOR REQUIREMENTS FOR ACTIVE TURBINE CONTROL

Technology Sensed variable Sensor requirements Controlled variable Actuator requirements 

Active clearance 

control 

Clearance • 2.5 mm range, 

• Accuracy ±25 μm 

• 50 kHz bandwidth 

• Case-mounted installation 

• Casing geometry • Thermal, mechanical, pneumatic devices 

• Actuation rate > 0.1 mm/s bandwidth 1 to 

5 Hz 

• Force 10 kN 

• Stroke 3 mm 

• Resolution 0.02 mm 

Film cooling flow 

control 

Static pressure • Equivalent to compressor flow 

control 

• Steady flow control may be 

based on operating point. 

• Jets, boundary layer 

suction, plasma 

actuator 

• Plasma actuator bandwidth 10 to 200 Hz 

at 5 kHz, voltage 5 to 25 kV 

• Steady blowing <0.1% of core flow 

Cooling air 

control 

Surface 

temperature 

turbine stator 

blade 

• Min resolution ± 5° 

• Steady state, 1 Hz 

• Total flow 

modulation or 

• Individual blade flow 

modulation 

• 1 Hz bandwidth 

• 20% modulation of baseline cooling flow

performance penalty (Ref. 18). Since noise reduction is only 

needed at very low altitude, work has been ongoing to 

implement shape memory alloy materials (SMA) in chevron 

nozzles for the outer nacelle of an aircraft engine, which will 

withdraw the serrations at altitude.

Shape memory alloys have the unique characteristic that 

they can be trained to change shape at a specific temperature. 

Thus, for take-off, the chevron nozzle can be one shape and 

then once out of noise sensitive regions, they can be another 

for aerodynamically efficient shape. The primary challenge is 

to produce an SMA based system that would be capable of 

providing sufficient operational stiffness and high movement 

whilst still being cost effective and safe (Ref. 19). 

Fluidic injection started as a way to avoid mechanical 

chevrons and get the same fluid dynamic effect with injected 

flow. Again, this has the advantage that it can be turned off 

when not needed (Ref. 20). 

Thrust Vectoring 

Mechanical thrust vectoring is already available in currently 

operational fighters. The replacement of the current mechanical 

systems with a fluidic approach has various potential benefits, 

such as weight reduction and reliability advantages. 

Computational and reduced scale experimental studies jointly 

performed by airframe and engine manufacturers have 

demonstrated the potential of fluidic actuation in throat area 

control of the nozzles of afterburning engines and also for 

thrust vector control, either for enhanced agility of combat 

aircraft or in future unmanned vehicles, to potentially reduce 

the need for moving aerodynamic control surfaces. By fluidic 

skewing of the nozzle throat, effective thrust vectoring can be 

accomplished. However the amount of air flow to control flow 

direction is around 1 percent of injected flow for every 1.5° of 

vector angle (Ref. 21), which would have to be considered in 

the overall performance cycle of the engine. 

Afterburner Stability Control 

It is well known that current augmented military jet engines 

have the potential problem of instabilities of the exhaust jet 

during afterburner operation. Basically, there are two forms of 

instability: Axial, low frequency (buzz, rumble); and Radial, 

high frequency (screech). The existing stability control systems 

monitor certain frequency bands of the dynamic pressure 

(<100 Hz for longitudinal instability, > 500 Hz for radial 

instability). When any of these stabilities is detected, current 

practice is to cut afterburner fuel flow and to actuate (open) the 

nozzle. The existing identification methods have to be improved 

in order to avoid false alarms. More intelligent sensors could 

improve the effectiveness of incident detection. Alternatives to 

piezo-electric sensors have to be investigated. Suppression of 

instabilities by active control using pulsed fuel injection is being 

investigated and is somewhat analogous to the application for 

combustor instability control discussed earlier.

Based on the above discussion, the sensor and actuator 

requirements for active nozzle control are summarized in Table 5.

Intelligent Control and Health Monitoring 

Reference 22 provides an overall summary of the state-ofthe-art of engine control and health monitoring. Typical aircraft 

engine control systems maintain fan speed or engine pressure 

ratio to regulate thrust which is not directly measurable. The 

control logic is generally based on a variant of a ProportionalIntegral scheme combined with limit logic which selects a fuel 

flow rate command based on various physical limits, 

acceleration/deceleration schedules (maximum rotor speed 

rate-of-change as a function of rotor speed), and the current 

operating state (speed governor loops). The various on-wing 

health monitoring systems of today, which are a collection of 

separate, unrelated technologies, provide a basic level of 

monitoring. Their capabilities are relatively limited and the 
TABLE 5.—SENSOR AND ACTUATOR REQUIREMENTS FOR ACTIVE NOZZLE CONTROL

Technology Sensed variable Sensor requirements Controlled variable Actuator requirements 

Active noise 

control 

No sensor • N/A • Variable nozzle 

geometry, jets 

• Shape memory alloys 30 mm actuation, 

stiffness <1 mm deflection 

• Pulsed jets ~1 to 4 kHz, 0.6*exhaust 

velocity, 1% engine flow 

Thrust 

vectoring 

Jet direction • Reaction force, optical position 

detection? 

• Nozzle geometry, jets • 1.5% of core flow / 1.5° of vector angle. 

Afterburner 

stability 

control 

Dynamic 

pressure 

• 40 to 800 kPa static, ±35 kPa 

dynamic range, 20 Hz to 10 kHz, 

220 to 650 °K 

• Nozzle geometry / area 

fuel flow actuation 

• Existing afterburner actuators 

• Reaction time < 0.1 s 

information they provide is used mostly to initiate 

maintenance actions, not for real-time decision-making. While 

these traditional control and diagnostic techniques are timetested and reliable, advanced techniques provide the promise 

to meet the challenging requirements of improved fuel 

efficiency, increased durability and life, decreased life cycle 

costs, and improved operations. Using an on-board engine 

model to meet the challenging control and diagnostics 

requirements has emerged as the most viable approach. 

The concept of model-based control and diagnostics is 

shown in Figure 3. The engine model is driven with the 

measured engine inputs (shown here as control signals, u, but 

usually also includes environmental conditions) to obtain the 

predicted engine sensor outputs y

 . The predicted outputs are 

differenced with the measured engine sensor outputs, y, to 

form residuals, which can be used to diagnose engine health 

and adapt the model. 

One of the major challenges in implementation of modelbased control and diagnostics is to have the model reflect the 

actual condition of the engine. Historically a single, fleet 

average model is used based on known or expected fleet 

average performance of a particular engine type. Use of this 

average model to predict individual engine performance 

within a fleet results in varying model errors, corresponding to 

how each engine deviates from the average. The resulting 

model error couples with normal flight variations in the input 

conditions to cause systematic error in the residuals, which 

limits the capability of the model to accurately predict the 

Figure 3.—Model-based control and diagnostics concept. 

unmeasured variables. Also, when a fault occurs in the engine, 

if this fault is not appropriately reflected in the model, it can 

cause significant errors in estimation of the unmeasured 

variables. Thus, it is important to ensure that the model being 

used for control reflects the true condition of the engine. 

Typically a “tracking filter” is used to estimate model 

parameters related to deterioration causing the model to 

“track” the individual engine over time. Since the accuracy of 

the estimates based on the tracking filter is a function of the 

available sensors, the effectiveness of model based control can 

be improved if appropriate additional sensors are available. 

In this model-based structure, the model can provide 

outputs for which there is no sensor, i.e. virtual sensors. These 

virtual sensors provide the capability to directly control 

unmeasured variables such as thrust and stall margin. 

Additionally, the model outputs can be used for sensor fault 

accommodation, where model output (predicted sensor 

reading) temporarily replaces a failed sensor, and virtual 

duplex redundancy, where the model output permanently 

replaces one sensor in a duplex pair. Also, the tracked 

parameters can be monitored to provide an indication of the 

health of the components of the engine, e.g. the level of 

deterioration in health parameters such as component 

efficiency. Typically, abrupt faults are detected with the 

diagnostics algorithm and slowly changing health assessed by 

monitoring these tracked parameters. References 23 to 27 

discuss various approaches for model based control, and fault 

detection and isolation of aircraft engines. If the effect of the 

fault on engine operability and/or safety is small, no 

accommodation is required and the diagnostics information 

can be used to schedule maintenance. However, if the fault has 

an appreciable effect, then accommodation can potentially 

avoid in-flight shut downs, stalls, excessive life consumption, 

etc. (Refs. 28 and 29). 

Challenges and Sensor Needs

Challenges exist in several areas in implementing the 

technologies described above. The models must be 

computationally efficient in order to run in real time without 

sacrificing accuracy. However, model error is difficult to 

quantify because it must be evaluated in closed loop (i.e. with 

the tracking filter) which couples it with the choice of tracked 

parameters and their observability with the given sensor suite. 

u 

y 

w v 

environment

&

control

signals

Random 

variation

Sensor 

errors

Sensor

output

Predicted

sensor

output

Engine Model

ν residuals

FADEC

Real Engine

+

PLA 

- Σ

Closed Loop

Control

^y Fault 

Diagnostics

Tracking

Filter

Virtual Sensors

states &

parameters

Accomodation

u 

y 

w v 

Engine Model

environment

&

control

signals

Random 

variation

Sensor 

errors

Sensor

output

Predicted

sensor

output

ν residuals

FADEC

Real Engine

+

PLA 

-

Closed Loop

Control

^y Σ Fault 

Diagnostics

Tracking

Filter

Virtual Sensors

states &

parameters

Accomodation

NASA/TM—2010-216746 9 
This creates a sensor paradigm shift where sensors are chosen 

not only for direct control purposes but also for model 

accuracy (Ref. 30). Equally important is the fault model or 

signature as it limits the sensitivity of fault detection. Finally, 

the increased complexity brings certification and maintenance 

challenges. Any engine models used inside the control loops 

will need to be certified. The complexity of the models and 

adaptive nature of the tracking filter adds to the challenge. 

Typical gas path sensors consist of temperature, pressure and 

rotor speed measurements. Any improvements in the accuracy, 

uniformity and reliability of these gas path sensors will result in 

a direct improvement in the accuracy of performance 

diagnostics and model-based control technologies. Also, there 

are currently stations within the engine gas path that are not 

instrumented due in part to the harsh operating temperatures 

that exist at these locations. Measurements at these additional 

locations will further enhance the accuracy of gas path analysis 

techniques. In addition to conventional gas path pressure and 

temperature measurements, the ability to sense additional 

parameters would be beneficial in diagnosing engine 

performance faults and providing improved estimate of 

unmeasured variables such as thrust. For example, gas path 

debris monitoring sensors for monitoring and quantifying 

engine debris ingestion and discharge are desirable. Mass flow 

sensors to estimate the flow through the fan duct and the nozzle 

will help generate better estimates of the thrust being produced 

by the engine—especially if there is any damage which results 

in degraded engine performance. Additional need is in 

improved fuel flow sensors. These sensor requirements are 

summarized in Table 6. 

TABLE 6.—SENSOR REQUIREMENTS FOR INTELLIGENT CONTROL AND HEALTH MONITORING 

Component Technology Sensed Variable Sensor Requirements 

Inlet Stall margin estimation Pressure 0 to 2.5 psi range, 0.25% accuracy, 500 Hz bandwidth 

Fan/compressor Thrust estimation Mass Flow 1.75% accuracy 

Fan/compressor Vibration monitoring Accelerometer 1000 g range, 3% accuracy, 40 kHz 

Combustor Thrust estimation Fuel mass flow ±0.1% accuracy 

Turbine Clearance management Clearance 2.5 mm range, 25 μm accuracy, 50 kHz bandwidth 

Turbine Life management/ 

temperature margin 

Temperature T41, T48, 5° accuracy, 2 to 10 Hz, flow and blade 

temperature 

Nozzle Exhaust debris monitoring Exhaust gas composition 1% accuracy 

 

Distributed Engine Control 

Presently, engine control system architecture is based on a 

centralized design in which discrete sensors and effectors are 

directly wired to an engine-mounted electronics package. This 

avionics unit, often known as the FADEC (Full Authority 

Digital Engine Control), contains all the necessary circuitry to 

properly interface with engine control devices as well as 

cockpit command and data communications. The design of a 

centralized engine control system is primarily based on the 

single overriding concern of minimal control system weight 

because of its effect on overall vehicle performance. Much of 

the design is based on legacy, the result of incremental 

improvement over many years. This constraint severely limits 

the design choices for avionics engineers. The centralized 

engine control architecture is shown in Figure 4. 

The FADEC houses specific electronics to interface with 

engine-mounted control elements (sensors and actuators). 

Dual redundancy is often used which drives up harness weight 

while connector size drives enclosure dimensions. The large 

FADEC housing is environmentally hardened, cooled, and colocated on the engine structure. The engine structure is quite a 

severe environment for an avionics package. Vibration and 

temperature extremes force the electronics to be custom 

designed for a specific engine. Circuit components are 

specifically designed for maximum density to achieve small 

physical size thereby increasing stiffness and raising the 

natural frequency of resonant mechanical vibration modes. 

This adversely affects heat dissipation in the assembly. The 

large number of conductors and the physical size of the 

connector shells mounted on the FADEC enclosure often drive 

the package dimensions. The entire package must be mounted 

on low frequency isolators to reduce the shock loads 

experienced over a mission profile. Temperature extremes at 

the engine structure require cooling to reduce the operating 

temperature of semiconductor junctions to an acceptable level. 

This is maintained by conduction cooling the entire assembly 

with a cold plate using the aircraft fuel supply as the heat 

removal media.

Under a centralized engine control system architecture, the 

need to reduce overall weight drives a chain of design 

constraints which result in an optimized engine control 

system, but one which is costly to both procure and maintain. 

Furthermore, because it is so highly optimized, it is inflexible 

to use in multiple platforms or even to accommodate upgrades 

in an existing application. Changing the engine control 

architecture to a distributed system can radically alter the 

interrelated chain of constraints which ultimately drive overall 

cost of ownership.

NASA/TM—2010-216746 10 
CPU /

Memory

Actuation

electronics

Sensor electronics

Sensor electronics

Actuation

electronics

Sensor electronics

Actuation

electronics

Actuator_1

Sensor_1

Sensor_ j

Actuator_n

Sensor_2

Actuator_2

Communication

Power

BUS

FADEC

Figure 4.—Centralized engine control architecture. 

Figure 5.—Distributed engine control architecture. 

In a distributed engine control system architecture, as 

shown in Figure 5, any number of control elements are tied 

together through a common, standardized, communication 

interface. Sensors and actuator electronics are removed from 

the FADEC and are replaced by control nodes which may 

provide sensor data, operate actuators, or perform 

combinations of both. The massive wiring harness which 

previously tied together the control element to interface 

circuitry in the engine-mounted avionics package is replaced 

by a simple but robust communication structure. Weight 

reduction is the primary motivation but the standardized 

interface is also an enabling feature which is necessary to 

effectively implement future active and adaptive control 

applications (Ref. 31).

In a distributed engine control architecture, weight 

optimization no longer drives the design and packaging of the 

FADEC. This leads to broad cross platform standardization 

and significant cost reductions in both acquisition and 

maintenance. The issue of system upgrade becomes one 

largely focused on software re-qualification instead of 

complete system re-qualification. 

NASA Glenn Research Center in conjunction with 

members of the U.S. Department of Defense and the U.S. 

Aerospace industry has established a Distributed Engine 

Control Working Group (DECWG) to examine the current and 

future technology requirements to enable distributed control 

for aircraft engines. The work of this group to date in terms of 

assessing the paradigm shift from centralized engine control 

architecture to an architecture based on distributed control 

using open system standards is summarized in Reference 32. 

It is important to note that no new sensors or actuators are 

needed to enable distributed engine control. What is needed is 

to have on-board electronics located on or close to the sensing 

element or the actuator effector such that network 

communications can be enabled and the wiring harness 

required for communications between sensors and actuators 

and the engine controller can be substantially reduced. 

Another challenge for enabling distributed engine control is to 

supply the power needed for the on-board electronics—

innovative power supply architectures and technologies will 

need to be developed to exploit the full potential benefits of 

distributed engine control. 

Universal Sensor and Actuator 

Requirements 

The previous sections have focused on the requirements for 

sensors and actuators for “More Intelligent Gas Turbine 

Engines” from the perspective of performance and operating 

environment. Even if a technology is available, which meets 

these performance requirements, there are still various hurdles 

to be overcome for the technology to transition into a real 

engine. Such requirements relate to TRL (Technology 

Readiness Level), durability, reliability, volume, weight, cost 

etc. This section provides an overview of such universal 

requirements which any sensor or actuator technology will 

have to meet before it can be implemented on a product. The 

objective here is to help educate the researchers or technology 

developers on the extensive process that the technology has to 

go through beyond just meeting performance requirements. 

The hope is that such knowledge will help the technology 

developers as well as decision makers to prevent wasteful 

investment in developing solutions to performance 

requirements, which have no potential to meet the “universal” 

requirements. These “universal” requirements can be divided 

into 2 broad areas: (1) technology maturation and (2) value 

proposition of the technology. The technology maturation 

requirements are generally well understood by technology 

developers. The process of moving a product, process or 

component towards maturity typically follows the 

development route as described in the Technology Readiness 

NASA/TM—2010-216746 11 
Level (TRL) definitions (Ref. 33). The process typically 

follows a gated process involving formal reviews at specific 

stages, generally related to specific TRLs. Business, 

manufacturing, legislative etc. issues must be covered at an 

appropriate level at all stages. The technology value 

proposition is briefly described in the following, since it is not 

that well understood by technology developers. 

Technology Value Proposition 

A fundamental premise (beyond basic safety) for 

considering the incorporation of any component onto/into the 

engine is that it adds value. Some components will be 

considered intrinsic to the engine design and functionality 

(e.g. engine control, fuel system components, cycle 

temperature sensors), and as a result, their value is tied 

directly to the overall product’s attributes (fuel burn, range, 

direct maintenance cost). All other non-intrinsic components 

added to the engine are required to provide some level of 

value that, at a minimum, mitigates the negative effects of its 

installation (weight, volume, energy consumption, installed 

losses). In the best case, the value added will provide direct 

positive impact to the customer in terms of increased revenue 

opportunities, or via easily measured life-cycle cost 

reductions. 

One common way that value analysis is performed is via a 

calculation of customer net present value (NPV). This 

common metric allows for capture of the life cycle costs and 

benefits of the proposed component or feature. Typical 

evaluation elements include (but are not limited to) the 

following: 

Impact on Revenue 

Does the technology provide enhanced utilization rates, 

increased dispatch reliability, increased ETOPS (Extendedrange Twin-engine Operational Performance Standards) 

availability, or performance improvement? Is the technology a 

performance enabler? 

Impact on Cost 

How much will the cost of the engine go up if the 

technology were to be incorporated into the engine? What will 

be the overall impact of the technology on the life cycle cost 

of the engine in terms of labor and time cost associated with 

part removal, line maintenance, shop maintenance, repair, 

troubleshooting, etc. 

Other 

Other than revenue and cost, some other factors to be 

considered for sensors and actuators are impact on overall 

engine weight, the capability of the technology to fit into the 

specified volume (since real estate on an engine is at a 

premium), accessibility once installed onto/into the engine, 

cooling requirements, power and wiring requirements etc. 

Designing for ease of integration into the engine has to be an 

important element of developing any technology solutions to 

challenging sensor/actuator performance requirements. 

Summary and Recommendations 

Intelligent Gas Turbine Engines (GTE) can potentially meet 

future challenges related to capability, affordability, safety, 

and environmental compatibility. The key enabling 

technologies for an intelligent GTE are (1) increased 

efficiencies of components through active control, (2) 

increased overall engine gas-path performance and extended 

“on wing” life of the engine through model-based control and 

health monitoring, and (3) reduced weight ratio of control 

system to engine through distributed control with smart 

sensors and actuators. An overview of these technologies was 

provided, and sensor and actuator requirements were 

identified to achieve these future capabilities. Reference 1 

further documents the various sensor and actuator 

technologies that have the potential to meet these 

requirements. The concept of more intelligent gas turbine 

engines should be approached by incremental changes, both 

by improving existing technology and components and 

implementing new technologies. Although numerous newly 

built propulsion systems are already using intelligent 

components, it is expected that a sustained effort in the 

implementation of distributed and active control will be 

attempted, once the technologies identified in this report are 

developed and demonstrated. A close interaction between the 

“Customers” and “Researchers and Technology Developers” 

is needed to optimize investment for meeting challenging 

performance and implementation-related requirements. 

Recommendations for sensor and actuator development 

activities are summarized in Reference 1 to achieve a goal of 

Technology Readiness Level (TRL) 6 (fully demonstrate 

engineering feasibility) in the near-term (3 to 5 yr), mid-term 

(7 to 10 yr), and long-term (12 to 15 yr). 

References 

1. Dennis Culley, Sanjay Garg, S.J. Hiller, Wolfgang Horn, Aditya 

Kumar, H. Kirk Mathews, Hany Moustapha, Hugo Pfoertner, 

Taylor Rosenfeld, Pavol Rybarik, Klaus Schadow, Ion Stiharu, 

Daniel E. Viassolo, and John Webster, “More Intelligent Gas 

Turbine Engines,” RTO–TR–AVT–128, April 2009. Available at: 

http://www.rta.nato.int/Pubs/RDP.asp?RDP=RTO-TR-AVT-128. 

2. Simon et al., “Sensor needs for control and health management of 

intelligent aircraft engines,” NASA/TM—2004-212915. 

3. Tagashira et al., “A performance optimization control of variable 

cycle engines,” AIAA–2003–4984. 

4. Calhoun et al., “Feasibility and Benefit Assessment of Some 

Advanced Controls Technologies within the NASA UEET IPC 

Project,” ISABE–2003–1057. 

5. Greitzer, E.M., 2007, “Some Aerodynamic Problems of Aircraft 

Engines – Fifty Years After,” ASME Paper GT2007–28364 

6. Gorton, S.A., Owens, L.R., Jenkins, L.N., Allan, B.G., “Active 

Flow Control On A Boundary Layer Ingesting Inlet,” AIAA 2nd

Flow Control Conference, AIAA–2004–1203 

NASA/TM—2010-216746 12 
NASA/TM—2010-216746 13 

7. Remington, P.J., Sutliff, D.L. and Sommerfeldt, S., “Active 

Control of Low Speed Fan Tonal Noise Using Actuators Mounted 

in Stator Vanes: Part I Control System Design and 

Implementation,” AIAA–2003–3191, May 2003 

8. Weigl et al., “Active stabilization of rotating stall and surge in a 

transonic single stage axial compressor,” ASME 97–GT–411 

9. Leinhos, D.C., et al., “Experiments in Active Stall Control of a 

Twin-spool Turbofan Engine,” ASME GT–2002–30002, 

Amsterdam, Netherlands, 2002 

10. Hiller, S.J., Hirst, M., Webster, J., Ducloux, O., Pernod, P., 

Touyeras, A., Garnier, E., Pruvost, M., Wakelam, Ch., Evans, S., 

“ADVACT – An European Program for Actuation Technology In 

Future Aero-Engine Control Systems,” AIAA 3rd Flow Control 

Conference, 2006, AIAA–2006–3511 

11. Culley, D.E., Braunscheidel, E.P., Bright M.M., 2005, “Impulsive 

Injection for Compressor Stator Separation Control,” AIAA–

2005–3633, 41st Joint Propulsion Conference, Tucson, USA 

12. Jaw et al., “Experimental results of an active clearance control 

system for a centrifugal compressor,” ASME 97–GT–32. 

13. Cohen, J. M., Hibshman, J.R., Proscia, W., Rosfjord, T.J., Wake, 

B.E., McVey, J.B., Lovett, J., Ondas, M., DeLaat, J., and 

Breisacher, K., “Longitudinal Mode Aeroengine Combustion 

Instability: Model and Experiment,” NATO/RTO Spring 2000 

Symposium on Active Control Technology for Enhanced 

Performance Operation Capabilities of Military Aircraft, Land 

Vehicles and Sea Vehicles, Braunschweig, Germany, (2000). 

14. Kopasakis, G., "High Frequency Adaptive Instability Suppression 

Controls in a Liquid-Fueled Combustor,” AIAA 39th Joint 

Propulsion Conference and Exhibit, Huntsville, AL, July 2003, 

NASA/TM—2003-212535, AIAA–2003–9581. 

15. Steinetz, B.M.; Lattime, S.B.; Taylor, S.; DeCastro, J.A.; Oswald, 

J.; Melcher, K.J., “Evaluation of an Active Clearance Control 

System Concept,” NASA/TM—2005-213856, AIAA–2005–

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Sensor and Actuator Needs for More Intelligent Gas Turbine Engines 

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Garg, Sanjay; Schadow, Klaus; Horn, Wolfgang; Pfoertner, Hugo; Stiharu, Ion 

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14. ABSTRACT

This paper provides an overview of the controls and diagnostics technologies, that are seen as critical for more intelligent gas turbine 

engines (GTE), with an emphasis on the sensor and actuator technologies that need to be developed for the controls and diagnostics 

implementation. The objective of the paper is to help the “Customers” of advanced technologies, defense acquisition and aerospace research 

agencies, understand the state-of-the-art of intelligent GTE technologies, and help the “Researchers” and “Technology Developers” for GTE 

sensors and actuators identify what technologies need to be developed to enable the “Intelligent GTE” concepts and focus their research 

efforts on closing the technology gap. To keep the effort manageable, the focus of the paper is on “On-Board Intelligence” to enable safe 

and efficient operation of the engine over its life time, with an emphasis on gas path performance.

15. SUBJECT TERMS

Turbofan engines; Sensors; Actuators; Fault detection; Engine control 

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