General Electric Aircraft Engines

Cincinnati, Ohio

System Study

Technology Assessment and Prioritizing

NASA/CR—2005-213972

October 2005
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General Electric Aircraft Engines

Cincinnati, Ohio

NASA/CR—2005-213972

October 2005

National Aeronautics and

Space Administration

Glenn Research Center

Prepared under Contract NAS3–01135, Work element 4.1, Task order 23

System Study

Technology Assessment and Prioritizing
Acknowledgments

This document summarizes the effort of many participants, all of whom were instrumental to the successful completion of the P21

Systems Study. They are:

GE Aircraft Engines

Xiaorong Lu P21 system study technical lead

Greg Steinmetz Technical support and coordination

Darin DiTommaso Technical support and coordination

Jorge Seda Work Element Technical Manager

Bob Orlando Turbine cooling

Tom Moniz Mechanical design

John Henry Mechanical design

Paul Cooker Cycle design

Martin Manning Cycle design

Steve Martens Active noise reduction

Bob Bergholz Thermal management and advanced cooling

Steve Mitchell Smart containment system

Eric Ott Shape changing airfoils

Bill Myers Intelligent combustor

Bob Albers HPT clearance control

NASA

Mary Jo Long Davis

Clayton Meyers

Michael Tong

GA Tech

Dimitri Mavris

Jimmy Tai

Michelle Kirby

Available from

NASA Center for Aerospace Information

7121 Standard Drive

Hanover, MD 21076

National Technical Information Service

5285 Port Royal Road

Springfield, VA 22100

Trade names or manufacturers’ names are used in this report for

identification only. This usage does not constitute an official

endorsement, either expressed or implied, by the National

Aeronautics and Space Administration.

Available electronically at http://gltrs.grc.nasa.gov
NASA/CR—2005-213972 iii 

Contents 

1.0 Executive Summary ......................................................................................................................... 1 

1.1 Task Objectives................................................................................................................... 1 

1.2 Study Results ...................................................................................................................... 1 

1.3 Conclusions......................................................................................................................... 2 

2.0 Project Overview ............................................................................................................................. 2 

2.1 Program Work Scope.......................................................................................................... 2 

2.2 Baseline Selection............................................................................................................... 5 

3.0 Response Surface Equation Creation............................................................................................... 5 

3.1 Approach............................................................................................................................. 5 

3.1.1 Approach for Constructing Response Surface Equations...................................... 5 

3.1.2 Primary tool: PREDATER..................................................................................... 6 

3.2 Validation............................................................................................................................ 7 

4.0 Technology Impact Matrix and Technology Modeling ................................................................... 9 

4.1 GEAE and NASA Technology Impact Matrix (TIM) ........................................................ 9 

4.1.1 Acoustic benefits model....................................................................................... 10 

4.1.2 Emission benefit model ....................................................................................... 10 

4.1.3 Some comments on T15....................................................................................... 11 

4.2 GEAE TIM: Selected Technology Modeling ................................................................... 12 

4.2.1 Modulated cooling ............................................................................................... 12 

4.2.2 Cooled cooling..................................................................................................... 12 

4.2.3 HPT ACC for reduced EGT overshoot................................................................ 12 

4.3 NASA TIM: Construction Considerations and Results .................................................... 13 

4.3.1 Combustion related technologies......................................................................... 15 

4.3.2 Active tip clearance control using Hi Temp SMA (T1)....................................... 15 

4.3.3 Variable area core nozzle via Hi Temp SMA (T7).............................................. 15 

4.3.4 Variable area fan nozzle via Hi Temp SMA (T8)................................................ 15 

4.3.5 Active flow control via Hi Temp piezoelectric ceramics (T3) ............................ 15 

4.3.6 Magnetic bearing technology (T6) ...................................................................... 16 

4.3.7 Active blade damping (T4) .................................................................................. 16 

4.3.8 Compressor IGV control via Hi Temp SMA (T9)............................................... 16 

5.0 Response Surface Equation Construction Results ......................................................................... 16 
NASA/CR—2005-213972 iv 

6.0 Technology Ranking and System Benefits .................................................................................... 18 

6.1 Individual Technology Evaluation.................................................................................... 18 

6.1.1 SFC, fuel burn, and design range......................................................................... 18 

6.1.2 Acoustic assessment............................................................................................. 18 

6.1.3 Emissions............................................................................................................. 24 

6.1.4 Fan diameter and propulsion system weight........................................................ 24 

6.2 Engine System Level Impact: Combined Technologies ................................................... 26 

7.0 Conclusions.................................................................................................................................... 27 

7.1 Deliverable Met ................................................................................................................ 27 

7.2 Additional Deliverables .................................................................................................... 27 

7.3 Engine System Level Impact ............................................................................................ 27 

7.4 Engine System Level Impact ............................................................................................ 27 

8.0 Recommendations for Future Work............................................................................................... 28 

9.0 Work Element Schedule ................................................................................................................ 28 
1.0 Executive Summary

1.1 Task Objectives 

The objective of this NASA funded project is to assess and prioritize advanced technologies required 

to achieve the goals for an “Intelligent Propulsion System” through collaboration among GEAE, NASA, 

and Georgia Tech. Key GEAE deliverables are parametric response surface equations (RSE’s) relating 

technology features to system benefits (SFC, weight, fuel burn, design range, acoustics, emission, etc...) 

and listings of Technology Impact Matrix (TIM) with benefits, debits, and approximate readiness status. 

TIM has been completed for GEAE and NASA proposed technologies. The combined GEAE and NASA 

TIM input requirement is shown in table 1. In the course of building the RSE’s and TIM, significant 

parametric technology modeling and RSE accuracy improvements were accomplished. GEAE has also 

done preliminary ranking of the technologies using Georgia Tech/GEAE USA developed technology 

evaluation tools. System level impact was performed by combining beneficial technologies with 

minimum conflict among various system figures of merits to assess their overall benefits to the system. 

The shortfalls and issues with modeling the proposed technologies are identified, and recommendations 

for future work are also proposed. 

1.2 Study Results 

Figures 13 to 19 shows the impact of each proposed technology on new engines in terms of SFC, fuel 

burn, design range, noise, emission, fan diameter, and total propulsion weight relative to the QAT 

baseline using TIES One-on and One-off methods. The impact of HPT clearance control on deteriorated 

engines is also shown in the same figure. On the left side of the figures, the technology list is shown, 

consistent with table 1. The technology numbering (simplified as “T” followed by a number) listed in 

table 1 will be referred throughout the report unless otherwise indicated. Throughout this study, SFC 

refers to specific fuel consumption at mid cruise point, and fuel burn refers to the fuel burn at 

5600 nautical mile (NM) mission. 

Notice that the top ten technology rankings for SFC, fuel burn and design range are listed at the 

bottom of these figures for both One-on and One-off methods. The top ten remain the top ten for both 

methods, although the order changed slightly. T13 (Intelligent HPT rotor cooled cooling), T19 (Active tip 

clearance control using high temperature SMA), T20 (Variable area fan nozzle via high temperature 

SMA), T5 (HPT blade cooling flow modulation), T15 (Shape changing airfoil) have relatively significant 

impact on SFC, fuel burn and design range. T14 (Smart Containment System), which reduced engine 

weight, has minimum impact on SFC, however, it reduces fuel burn and significantly increases design 

range. 

Among the acoustic technologies T1 (Steady fluidic injection), T2 (Synthetic jet actuators), T3 

(Shape memory alloy), T4 (Active liners), T1 and T2 have the best acoustic benefits while T2 has 

minimum impact on fuel burn and design range. Among the emission technologies, T16 (GEAE 

Intelligent combustor) reduces NOx by 50 percent from the baseline QAT level, equivalent to 15 percent 

additional reduction from 1996 ICAO limit. In other words, the QAT baseline goal is 70 percent below 

1996 ICAO limit while the P21 goal is 85 percent below 1996 ICAO limit. NASA’s active combustion 

control (T21) retains the same NOx level as the QAT baseline. 

The engine system level impact was estimated by selecting the best technologies among the 

incompatible technologies and including all the beneficial technologies. The final system contains all the 

proposed technologies except for T1, T3, T15, T21, and T22. The engine system level impacts from 

combining all the technologies are shown in table 3. With respect to the QAT Baseline, SFC was 

improved by delta 1.7 percent, fuel burn improved by delta 2.0 percent, design range improved by delta 

1.9 percent, Noise (cumulative margin) improved by 3.3 EPNdB, NOx reduced by 50 percent, and 

propulsion system weight reduced by 73 lbs. 

NASA/CR—2005-213972 1
All the above technology evaluation results, except for T23 and T24, are based on new engine 

designs. In modeling the benefits of the proposed technologies, the new engine was resized to obtain the 

maximum benefit while retaining the same cycle parameters as the QAT baseline. The QAT baseline 

engine was designed with an optimized cycle that minimizes fuel burn with balanced noise and Engine 

Related Operating Cost (EROC). 

For deteriorated engine cases, T23 and T24 and their system impacts are shown in yellow in 

figures 13 to 19. T23 and T24 are two different methods to achieve HPT clearance control. T23 is based 

on elastic stretch, smart materials or advanced thermal systems. T24 uses more traditional mechanical 

actuators. Both T23 and T24 target to recover deteriorated HPT adiabatic efficiency. The difference is 

that T24 requires more HPT chargeable cooling flow (G31W42) than T23 from having more leakage 

passages from its segmented hardware. As shown in figures 13 to 15, T23 achieves better SFC, fuel burn 

and design range than T24. 

1.3 Conclusions 

For the Intelligent Engine System (Propulsion 21) system study, each technology was evaluated to 

determine the impact to SFC, fuel burn, design range, acoustics, emissions, fan diameter, and propulsion 

system weight. The optimum combination of technologies and their overall benefits to the system were 

also performed, resulting in improvement potential of 3.3 EPNdB Cumulative margin, 2 percent fuel burn 

and 50 percent NOX reductions from the QAT baseline. All the technology evaluations, except T23 and 

T24, were based on new engines where the engine was resized to obtain the maximum system benefit 

while maintaining the same cycle parameters as the QAT baseline. The impact of HPT clearance control 

on deteriorated engines, T23 and T24, were also evaluated. 

Recommendations for future system study work include, but not limited to, adding manufacturing 

cost, maintenance cost, and customer value analysis as figures of merits beside SFC, fuel burn, design 

range, emission and acoustics. Long-term system study goals include improving and enhancing the life 

prediction model and adding thermal dynamic/transition analysis modeling capabilities. 

2.0 Project Overview 

2.1 Program Work Scope 

Propulsion 21 overall is a NASA funded task with the objective to develop technologies that will 

enable commercial gas turbine engines to produce reduced fuel burn, fewer emissions and less noise 

while increasing reliability. The engine entry into service (EIS) date is in the timeframe of 2008 to 2012. 

The System Study is a work element of the overall Propulsion 21 task. The focus of this system study is 

to assess and prioritize advanced technologies so that these technologies can be carefully integrated to 

achieve the best balance of system benefits between dissimilar and contradictory figures of merits. 

The work scope defined in the original contract for system study includes the following tasks for both 

GEAE and GT: 

(1) Define engine and aircraft technology baselines; 

(2) Define Technology Impact Matrix (TIM) and Technology Audit Datasheets (TAD) of Proposed 

Technologies; 

(3) Perform One-Off Technology Ranking; 

(4) Perform Engine System Level Impact; 

(5) Identify Modeling Shortfalls and Make Recommendations for Future Efforts. 

To facilitate the collaboration, GEAE proposed the work scope definition shown in figure 1, 

leveraging each partner’s strength, and agreed to by NASA and GT. The plan was for GEAE to build the 

latest QAT/UEET engine and aircraft models using GEAE internal tool PREDATER to construct the 

NASA/CR—2005-213972 2
response surface equations. The response surface equation is to be used in TIES for technology 

evaluation. 

Key GEAE deliverables are parametric response surface equations (RSE’s) relating technology 

features to system benefits (SFC, weight, fuel burn, design range, acoustics, emission, etc...) and listings 

of Technologies Impact Matrix (TIM) with benefits, debits, and approximate readiness status. 

Upon completion of the system study, GEAE met the deliverables of constructing response surface 

equations and transmitting them to GT. In addition, GE delivered results beyond the original work scope. 

GE completed the TIM for GEAE proposed technologies and coordinated GE expert evaluation of NASA 

TIM. The combined GEAE and NASA TIM input requirements are shown in table 1. In the course of 

building the RSE’s and TIM’s, significant parametric technology modeling capability enhancement and 

RSE accuracy improvements were accomplished and substantial effort spent on validating the NASA 

TIM. GEAE completed preliminary ranking of the technologies using Georgia Tech/GEAE USA 

developed technology evaluation tools. System level impact was also performed by combining 

technologies with minimum conflict in order to assess the overall system benefits. The shortfalls and 

issues with modeling the proposed technologies were identified, and recommendations for future work are 

proposed. 

Engine Update

UEET Cycle

UEET Flowpath

Aircraft Model

Sensitivities

Aircraft Performance

Sensitivities

• Range

• Fuel Burn

• Payload

• Mission Mix

Engine Design •

Cycle / Flowpath

• Sfc

• Weight

• Fan diameter

Technology Impact

Matrix Formulation

CTQ Response

Surface Eqns

TIES Analysis/

Technology Rankings

GEAE, NASA, GT. 

GEAE

PREDATER

Strategize

Engine Config

Engine Technology

Technology/Design 

Variables

Aircraft

Engine Update

UEET Cycle

UEET Flowpath

Aircraft Model

Sensitivities

Aircraft Performance

Sensitivities

• Range

• Fuel Burn

• Payload

• Mission Mix

•

• Range

• Fuel Burn

• Payload

• Mission Mix

Engine Design •

Cycle / Flowpath

• Sfc

• Weight

• Fan diameter

Technology Impact

Matrix Formulation

CTQ Response

Surface Eqns

TIES Analysis/

Technology Rankings

GEAE, NASA, GT. 

GEAE

PREDATER

Strategize

Engine Config

Engine Technology

Technology/Design 

Variables

Aircraft

Figure 1.—Roles and responsibilities. 

NASA/CR—2005-213972 3
TABLE 1.—COMBINED GEAE AND NASA TIM INPUT REQUIREMENTS 

NASA/CR—2005-2139724
2.2 Baseline Selection 

Baseline engine and aircraft selection for the system study was discussed among GEAE, NASA, and 

GT. It was agreed by NASA, GEAE, and GT to use the QAT type aircraft and the balanced Noise-EROC 

QAT engine as the baseline for the Propulsion 21 system study. The QAT Balanced Noise-EROC engine 

was developed as a “derivative” of the UEET medium size engine. 

The QAT/UEET represents an advanced aircraft and engine system with the best fit for the 

Propulsion 21 system study. The QAT/UEET engine was flown on the QAT/UEET aircraft in a typical 

aircraft mission to determine the fuel burn, design range, acoustics, and emissions. 

GEAE's UEET engine concept was designed to revolutionize the state of the art in propulsion 

technology with the biggest reduction in aircraft fuel burn (CO2), emissions (NOx), noise and Engine 

Related Operating Cost (EROC) relative to a baseline engine. Multi functional revolutionary engine 

technologies were carefully integrated to achieve the best balance between challenging and contradictory 

program goals with an EIS of 2015. The UEET engine features technology advancements that will 

revolutionize the commercial propulsion engine state of the art for the next 15 to 20 years in the area of 

emissions, performance, noise, and cost of ownership. 

These features include: 

• Ultra low noise, low speed counter rotating swept fan blades 

• Counter rotating vaneless booster 

• 6 stage HPC, all blisk rotors with advanced materials 

• Ultra low emissions TAPS combustor with CMC liners 

• Non deteriorating, low leakage seals 

• Two stage HPT with advanced materials 

• Robust, high DN HP rotor bearings 

• Simplified main engine frames and architecture 

• Counter rotating, vaneless LPT 

• Intelligent Propulsion Controls 

3.0 Response Surface Equation Creation 

3.1 Approach 

3.1.1 Approach for constructing response surface equations

The approach for constructing response surface equations involves three steps. The first is to build 

parametric engine design model using GEAE parametric engine design tool PREDATER. The second is 

to run design of experiment using PREDATER by varying key control parameters such as fan pressure 

ratio (FPR), component efficiencies, cooling flows and obtaining the response of the system metrics, such 

as SFC, fuel burn, range, noise, emission, and propulsion system weight. This process is shown in figure 

2. The third step is to post process the responses to obtain the response surface equation using a 

commercial statistic tool. 

Since GEAE parametric engine design tool PREDATER plays an important role in this system study, 

below is a more detailed introduction of this tool. 

NASA/CR—2005-213972 5
Figure 2.—Approach for constructing response surface equations. 

Aircraft Performance

Customer Value

Airline Financial Model

• LLP

• EGT Margin

• Engine Temperatures

• Maint Cost per hr

• Avg Mission length

• Range

• Fuel Burn

• Payload

• Mission Mix

• Acoustics

• Mature Engine

Cost

• Engine Weight,

Size, Thrust

• Fuel Flow

• Engine Size, 

Architecture

• Module Costs

Manufacturing Cost

Maintenance Cost

Engine Design

Cycle / Flowpath

•

•

•

•

•

• Engine Size, 

Architecture

• •

•

•

Aircraft Performance

Customer Value

Airline Financial Model

• LLP

• EGT Margin

• Engine Temperatures

• Maint Cost per hr

• Avg Mission length

• Range

• Fuel Burn

• Payload

• Mission Mix

• Acoustics

• Mature Engine

Cost

• Engine Weight,

Size, Thrust

• Fuel Flow

• Engine Size, 

Architecture

• Module Costs

Manufacturing Cost

Maintenance Cost

Engine Design

Cycle / Flowpath

•

•

•

•

•

• Engine Size, 

Architecture

• •

•

•

Figure 3.—PREDATER engine design evaluation process. 

3.1.2 Primary tool: PREDATER 

PREDATER is a GEAE linked computer analysis tool that combines parametric engine design with 

aircraft performance analysis, system cost assessment, airline economic analysis and ultimately customer 

economic value per figure 3. An engine design model, aircraft performance model, and manufacturing 

cost model were built and integrated into the PREDATER system. Maintenance cost modeling and airline 

economic modeling were also incorporated. PREDATER has the capability to call modules assessing 

PREDATER Parametric Model

Aircraft

Performance

• Range

• Fuel Burn

• Payload

• Mission Mix

• Acoustics

• Engine Weight,

Size, Thrust

• Fuel Flow

Engine Design

Cycle / Flowpath 

Baseline

QAT Aircraft

QAT Engine

+Technology

FPR Fan η CoolingFlows

T41 HPT η ∆Engine Weight

OPR PWXH

Key Control Parameters

Figures of 

Merits(FOM) 

Prop Sys 

Weight

SFC, Noise, 

Emissions

Fuel Burn

Design Range

PREDATER Parametric Model

Aircraft

Performance

• Range

• Fuel Burn

• Payload

• Mission Mix

• Acoustics

• Engine Weight,

Size, Thrust

• Fuel Flow

Engine Design

Cycle / Flowpath 

Baseline

QAT Aircraft

QAT Engine

+Technology

FPR Fan η CoolingFlows

T41 HPT η ∆Engine Weight

OPR PWXH

Key Control Parameters

Figures of 

Merits(FOM) 

Prop Sys 

Weight

SFC, Noise, 

Emissions

Fuel Burn

Design Range

NASA/CR—2005-213972 6
engine manufacturing cost; maintenance cost and customer value analysis, although for this study, they 

were not used. The full system was run and checked out to ensure proper communication between the 

modules. 

PREDATER has Design of Experiments (DOE) capability, which allows the rapid investigation of 

wide design space. The factors that varied in the DOE study are key control parameters, and they are 

component performance and architecture characteristics. In general, key component characteristics 

assessed include, but not limited to, compressor pressure ratio, overall pressure ratio, fan pressure ratio, 

T41, T3, all HPT and LPT chargeable and non chargeable flows, all components (fan, HPC, LPC, HPT 

LPT) efficiencies, customer bleed, power extraction, weight and more. In summary, PREDATER covers 

the spectrum required for technology evaluation focused on system benefits. 

3.2 Validation 

Before doing the full-scale design of experiment (DOE) and constructing the response surface 

equations, the system and methodology were validated. The purpose of the validation was two folds: 

Validate the tool and validated the accuracy of the RSE. 

(1) Validation of commercial tool JMP. For this purpose, JMP was compared to PEZ, an internally 

developed GEAE tool with vigorous statistics algorithm which is widely used and thoroughly tested 

inside GEAE. JMP is a commercial software developed by SAS Institute Inc. It has good plotting and 

visualization capability and the response surface equations generated from JMP can be easily read by 

TIES, which is the technology evaluation tool using the response surface equations as input. 

For validation purpose, 3 factor DOE was conducted. The 3 factors are: Fan Pressure Ratio (FPR), 

Design Overall Pressure Ratio (OPR), nd Maximum turbine inlet temperature (T41). It turns out JMP and 

PEZ give exactly the same response surface equations and regression accuracy. The response surface 

equations shown in figure 4 exhibits reasonable physical trend. 

FPR OPR T41

Noise

Cum

Margin HC NOxr CO NOx

FPR OPR T41

Weight

Prop.

System

FB

5600 NM

Design

Range

FB

2500 NM

Fan

Dia. SFC

FPR OPR T41

Noise

Cum

Margin HC NOxr CO NOx

FPR OPR T41

Noise

Cum

Margin HC NOxr CO NOx

FPR OPR T41

Weight

Prop.

System

FB

5600 NM

Design

Range

FB

2500 NM

Fan

Dia. SFC

FPR OPR T41

Weight

Prop.

System

FB

5600 NM

Design

Range

FB

2500 NM

Fan

Dia. SFC

Figure 4.—Response surface equations from 3 factors design of experiments. 

NASA/CR—2005-213972 7
(2) Validating the accuracy of response surface equations (RSE) by comparing actual data with 

predicted value based on response surface equations. Figure 5 shows the comparison for SFC at midcruise point and fan diameter. These two parameters have very smooth trend and RSE fits into the actual 

runs very well. Figure 6 shows the comparison for propulsion system weight and design range. The RSE, 

which always has smooth trend, leave space for further improvement. 

Design FPR Design FPR

SFC

∆ Fan Diameter, inch

Figure 5.—Comparison between response surface equation and actual runs. Design Range, NM

Design FPR Design FPR

Total Propulsion System Weight, lbs

Figure 6.—Comparison between response surface equation and actual runs. 

NASA/CR—2005-213972 8
Design FPR

Total Propulsion System Weight, lbs

Design FPR

Design Range, NM

Design FPR

Design Range, NM

Figure 7.—Comparison between RSE and actual runs: original versus improved. 

By changing FPR range, the RSE error can be reduced by half as shown in figure 7. The difference 

between RSE and actual runs are indicated by square root of mean percent error (SRME) as shown in the 

formula below (“Act” stands for actual values, “RSE” stands for predicted values based on response 

surface equations, “n” stands for the number of points. In figure 7, “RSE, SRME” and “Opt RSE, SRME” 

are original and improved SRME numbers respectively): 

= ∑ −

n

SRME Act RSE Act n

1

2 ( [( )/ ] )/

4.0 Technology Impact Matrix and Technology Modeling 

4.1 GEAE and NASA Technology Impact Matrix (TIM) 

To assess the impact of proposed technologies, the first step is to compile the Technology Impact 

Matrix (TIM). TIM serves as a listing of the benefits/detriments/enabling relationships each technology is 

expected to produce. The TIM provides the inputs to modify the engine design for each technology 

alternative. 

The combined GEAE and NASA TIM were completed for technologies shown in table 1. Listed in 

the first row are the key control parameters. Shown in the first column are the technology reference 

number simplified as “T” followed by a number. The second column list 17 GEAE and 5 NASA 

technologies/suite for new engines. In addition, 2 technologies for deteriorated engines are tabulated. 

These technologies are two different approaches to attain HPT active clearance control. One uses smart 

materials/elastic stretch/advanced thermal systems, and the other uses mechanical actuators. It is worth 

mentioning that the impact of HPT clearance control are three folds: (1) Improve cruise SFC, fuel burn 

and design range for new engines, however, this benefit is already included in the QAT baseline and will 

NASA/CR—2005-213972 9
not be considered in this study; (2) Reduce EGT overshoot for new engines, and this impact is evaluated 

and listed as T17; (3) Improve cruise SFC, fuel burn and design range for deteriorated engines and this is 

evaluated through T23 and T24. 

Tabulated in the body of the TIM table are key control parameter deltas representing the change 

relative to the QAT baseline for each technology item. As supplement to the TIM table, the acoustic 

benefits model and emission benefits model, which are not listed in the TIM table due to limited space, 

are shown. 

4.1.1 Acoustic benefits model 

Acoustic assessment was carried out utilizing a preliminary-design method based on correlation of 

propulsion system component noise levels. The component noise metric output of this method is Effective 

Perceived Noise Level or EPNL, in decibels. Each of the component contributions to the total propulsion 

system EPNL have their own separate correlation methodology, based on cycle parameters and certain 

basic geometric definitions. The following components were considered in the assessments: 

1. Combustor/Core Noise 

2. Fan Exhaust Noise 

3. Fan Inlet Noise 

4. Jet Mixing Exhaust Noise 

5. Airframe Noise 

The correlation used in estimating the component EPNL values were developed under GE internal 

programs over a period of several years, and are based on an accumulated data base from engine test 

decompositions from CF6, CFM56, CF34, E3

, and GE90 engine families. Use was also made of published 

Advanced Ducted Propulsion (ADP) data and QCSEE engine test data. 

As part of the UEET study, a counter-rotating fan was evaluated, and it showed significant potential 

for reducing fuel consumption, propulsion system weight, and direct operating cost. It was estimated that 

the counter-rotating fan (CRF) concept could also provide a noise benefit as well. Therefore, a 

preliminary-design level estimation procedure was developed to evaluate this concept in the context of 

previous baseline UEET/QAT study. The same methodology was adopted in this study. It should be noted 

that the conceptual reason for a CRF being quieter than a single rotating fan (SRF) is based on the notion 

that fan noise varies as some high power of fan tip speed, and that each stage of a CRF runs at a 

significantly lower tip speed that the SRF equivalent. Each stage of a CRF produces roughly a pressure 

ratio that is the square root of the total fan pressure ratio, and hence can run at significantly lower tip 

speed to produce the required pressure ratio. When the noise levels from each of the two stages are 

summed (anti-logarithmically), the sum is still less than that of the equivalent single-stage fan. 

This noise benefit model is build into PREDATER to calculate the overall engine cumulative noise 

margin. Shown in figure 8 are cumulative noise margin for the four acoustic technologies. 

4.1.2 Emission benefits model

There are two emission related technologies, T16, GEAE Intelligent Combustor and T21, the NASA 

Active Combustion Control. The NASA combustion technology emission level will remain the same as 

QAT baseline while the Propulsion 21 combustion technology targets to reduce the emission by 

50 percent from QAT baseline. Shown in figure 9 are GEAE emission benefits model for QAT and P21 

(indicated as “Intel Comb). This model is built into PREDATER to calculate the LTO NOx level. 

NASA/CR—2005-213972 10
Active Noise Reduction

FPR

Cumulative Margin, EPNDB

Baseline CR

Only

Synthetic Jet

Actuators or

Steady Fluidic

Injection

Smart Memory

Alloy

Active Liners

Total Impact

Active Noise Reduction

FPR

Cumulative Margin, EPNDB

Baseline CR

Only

Synthetic Jet

Actuators or

Steady Fluidic

Injection

Smart Memory

Alloy

Active Liners

Total Impact

Figure 8.—Cumulative noise margin for acoustic related technologies. 

TAPS LTO Emissions

UEET/QAT Goal

Intelligent Engine Goal

0

20

40

60

80

100

120

140

OPR

LTO NOx

CAEP/2

TAPS LTO Emissions

UEET/QAT Goal

Intelligent Engine Goal

0

20

40

60

80

100

120

140

OPR

LTO NOx

CAEP/2

Figure 9.—GEAE PREDATER emission model. 

4.1.3 Some comments on T15 

The Shape Changing Airfoil Technology T15 was assessed using inputs from the Shape Changing 

Airfoil project technical effort to assess the system level impact of implementation. Due to the early stage 

of development of this technology and several unknowns that had not yet been explored, several 

assumptions were made to enable an overall assessment. Only preliminary assessment of this 

configuration could be performed under the scope of the Shape Changing Airfoil concept assessment 

effort and this configuration is not considered to be optimum. 

A fan efficiency improvement was determined based on the ability to modify the baseline QAT blade 

camber into the optimum mission cruise stage blade configuration while keeping the standard baseline 

blade shape under take-off and climb conditions. 

Assessment of the risks associated with the Shape Change Airfoil technology for QAT fan blade 

applications suggest that there are significant design, performance, safety, and material constraints which 

would have to be addressed in order to move forward with this technology as it applies to QAT fan blades 

and the overall QAT mission cycle. It is critical that these issues be assessed to determine the feasibility 

of implementing such a system. 

NASA/CR—2005-213972 11
4.2 GEAE TIM: Selected Technology Modeling 

One critical step for constructing Response Surface Equations (RSE) is to build the modeling 

capabilities for each technology to accurately model the impact of each technology. The GE special 

technologies here refer to these technologies that are seldom or never modeled in past studies. Examples 

are modulated cooling (T5 and T6) and cooled cooling (T13) under the technology suite of Thermal 

management and advanced cooling; the HPT clearance control benefit from reduced EGT overshoot 

(T17) and the benefit for deteriorated engines (T23 and T24). By enhancing the modeling capabilities for 

these technologies, significant parametric technology modeling and RSE accuracy improvements were 

accomplished 

4.2.1 Modulated cooling 

T5 (HPT blade cooling flow modulation) and T6 (HPT vane cooling flow modulation) are two 

technologies employing the modulated cooling concept. The benefits are reduced fuel burn and increased 

design range. An example is shown in figure 10. In this example, the same cooling level reduction is 

applied to HPT cooling flows at cruise off-design. The X-axis, labeled as “Cooling Scale at Cruise,” is the 

ratio of reduced cooling level at cruise off-design versus the design cooling level. The model has the 

capability to apply different modulation level to the HPT and LPT chargeable and non-chargeable cooling 

flows. 

4.2.2 Cooled cooling 

The concept of cooled cooling is to reduce the cooling air temperature so that the amount of cooling 

required will be reduced, hence reduced fuel burn and increased design range. The use of fan air as a heat 

sink to reduce the temperature of the turbine cooling air was evaluated here. Shown in figure 11 is an 

example of cooling flow versus reduced cooling air temperature. It indicated that significant cooling flow 

level could be reduced as cooling air temperature is reduced. 

4.2.3 HPT ACC for reduced EGT overshoot 

Two different approaches are used to model the benefit of EGT overshoot for HPT clearance control. 

The first approach increases T41 while fixing cooling flow. The second reduces exhaust gas temperature 

(EGT) stack adders. 

Both approaches give similar benefits. However, the first approach requires fixing cooling flow while 

the rest of the technologies do not. The second approach is much easier to implement in the Design of 

Experiment environment. Due to these reasons, the second approach was used in constructing the 

response surface equations to evaluate the benefits for T17. 

To model the impact of HPT ACC on deteriorated engines, it is assumed that the HPT ACC can 

improve the deteriorated HPT adiabatic efficiency. The approach was to apply HPT adiabatic efficiency 

improvement to a deteriorated engine model so that the HPT efficiency could be recovered to the original 

baseline level up to a maximum deteriorated level. 

The deterioration model was built based on CFM56-7B engine deterioration model. The CFM56-7B 

deterioration model was constructed based on field experience of the CFM56-7B engine with 20000 flight 

hours. The QAT deterioration model is a scaled version of the CFM56-7B model. SFC, fuel burn and 

design range are all improved due to enhanced HPT adiabatic efficiency from T23, while additional 

cooling flow required minimizes T24 benefit. 

NASA/CR—2005-213972 12
FB vs Modulated Cooling

Cooling Scale at Cruise

FB, LB

0.6 0.7 0.8 0.9 1.0

Figure 10.—Impact of modulated cooling on fuel burn. 

Cooling Flow vs ∆ Cooled Air Temperature

∆ (Base - Cooled) Air Temperature

Cooling Flow

Cooling Flow vs ∆ Cooled Air Temperature

∆ (Base - Cooled) Air Temperature

Cooling Flow

Figure 11.—Impact of cooling air temperature reduction on cooling flow.

4.3 NASA TIM: Construction Considerations and Results 

GEAE received a draft version NASA’s TIM from GA Tech and spent substantial work effort 

evaluating and validating the technology estimated effects. A series of meetings were held with NASA 

technologies owners to better understand the technology and its readiness level. Table 2 shows NASA 

TIM after the first screening. Some numbers were deleted and others added to the original NASA TIM 

based on GEAE technologist’s expert advice on best-projected system impact for these technologies. 

Furthermore, GEAE design tools were employed to estimate the system impact as an input to the TIM. 

The final version of NASA’s TIM is jointly listed with GEAE’s in table 1. There were significant delta 

changes from the original to the final TIM versions. Some technologies were grouped together and others 

not included in the final TIM. The following explains the rationale behind the assessment of each 

technology listed in table 2. Within this section, for the convenience of discussion, the technology 

numbering refers to the number in table 2 instead of the final combined GEAE/NASA TIM in table 1. 

NASA/CR—2005-213972 13
Deleted

Added

NASA IPSFT Technology Applications ∆FPR ∆OPR ∆TIT ∆ηfan tip ∆ηfan hub+LPC ∆ηHPC ∆ηHPT ∆ηLPT

Tech No. % % °F pt pt pt pt pt

T1 Active Tip Clearance Control Using Hi Temp SMAT2 Noise Control via Synthetic Jets and Piezoelectric CeramicsT3 Active Flow Control via Hi Temp Piezoelectric CeramicsT4 Active Blade Damping (e.g. Hi Temp Piezoelectric Ceramics)T5 Active Blade Damping via Magnetic Bearing TechnologyT6 Magnetic Bearing TechnologyT7 Variable Area Core Nozzle via Hi Temp SMAT8 Variable Area Fan Nozzle via Hi Temp SMAT9 Compressor Inlet Guide Vane Control via Hi Temp SMA

T10 Combustor Fuel Nozzle Control via Hi Temp SMAT11 LDI Combustor TechnologyT12 Active Combustion Control (includes Ceramic Thermocouple

& Passive Acoustic Tomography)

∆HPT NC (CDP) ∆HPT C (CDP) ∆HPT C ∆LPT NC ∆LPT C ∆Cffan ∆Cfcore ∆Cdfan ∆Cdcore Weight

% Corr. Flow % Corr. Flow % Corr. Flow % Corr. Flow % Corr. Flow pt pt pt pt %

∆Leng ∆Wbare ∆Wmech ∆Wnozz ∆SMfan ∆FanLoad ∆HPCLoad

%% %% ND % %

DeletedAdded

NASA IPSFT Technology Applications ∆FPR ∆OPR ∆TIT ∆ηfan tip ∆ηfan hub+LPC ∆ηHPC ∆ηHPT ∆ηLPT

Tech No. % % °F pt pt pt pt pt

T1 Active Tip Clearance Control Using Hi Temp SMAT2 Noise Control via Synthetic Jets and Piezoelectric CeramicsT3 Active Flow Control via Hi Temp Piezoelectric CeramicsT4 Active Blade Damping (e.g. Hi Temp Piezoelectric Ceramics)T5 Active Blade Damping via Magnetic Bearing TechnologyT6 Magnetic Bearing TechnologyT7 Variable Area Core Nozzle via Hi Temp SMAT8 Variable Area Fan Nozzle via Hi Temp SMAT9 Compressor Inlet Guide Vane Control via Hi Temp SMA

T10 Combustor Fuel Nozzle Control via Hi Temp SMAT11 LDI Combustor TechnologyT12 Active Combustion Control (includes Ceramic Thermocouple

& Passive Acoustic Tomography)

∆HPT NC (CDP) ∆HPT C (CDP) ∆HPT C ∆LPT NC ∆LPT C ∆Cffan ∆Cfcore ∆Cdfan ∆Cdcore Weight

% Corr. Flow % Corr. Flow % Corr. Flow % Corr. Flow % Corr. Flow pt pt pt pt %

∆Leng ∆Wbare ∆Wmech ∆Wnozz ∆SMfan ∆FanLoad ∆HPCLoad

%% %% ND % %

TABLE 2.—ORIGINAL NASA TIM AFTER FIRST ITERATION

NASA/CR—2005-213972 14
4.3.1 Combustion related technologies: 

In the original NASA TIM, there were four technologies related to combustion: Combustor fuel 

nozzle control via Hi Temp SMA (T10); LDI combustor technology (T11), active combustion control 

(T12), ceramic thermocouples and passive acoustic tomography (T12). Based on the information provided 

by NASA technology owners, T10 and T11 were considered actuation methodology, T12 control 

methodology and T12 sensing methodology. Since system performance is the evaluation target, it was 

natural to group all the four technologies into one and call this suite the Active Combustion Control, 

which is listed in the final NASA TIM in table 1. 

The potential benefits include: 

(1) Reduced HPT non-chargeable cooling flow 

(2) Reduced NOx emission 

(3) Reduction in combustor weight. 

(4) Increased combustor/turbine life from reduced hot spot temperature. Life related benefit was not 

modeled or addressed in this study. 

The potential negative impacts include: 

(1) Need a fail/safe design criteria; 

(2) Increased wiring, plumbing, cost, maintenance and control requirements. 

4.3.2 Active tip clearance control using Hi Temp SMA (T1) 

Based on GEAE technologist input, this technology was considered more applicable to fan blade tips 

because of its feasibility, more space, environment, and easier access to the fan area. Based on fan aero 

database and technologist input, an aggressive benefit for SMA fan clearance reduction is an increase in 

fan efficiency. This is based on the aggressive assumption of reducing fan clearances by 50 percent. 

The potential negative impact on weight is minimum. Power requirement is minimum assuming this 

technology can be realized using thin wire SMA structure which does not require too much power. 

4.3.3 Variable area core nozzle via Hi Temp SMA (T7) 

Based on design tool study, varying core nozzle area (A8) for the QAT cycle, could find no 

significant benefit. 

4.3.4 Variable area fan nozzle via Hi Temp SMA (T8) 

Based on design tool study, varying fan nozzle area (A18) for the QAT cycle could result in a 

potential increase in fan efficiency (ED12) and engine weight increase. 

Note that variable A18 technology is not additive with the SMA fan airfoil. All the results of varying 

A8 or A18 are very cycle dependent. In other words, existing engines might benefit more or less from 

these technologies. 

4.3.5 Active flow control via Hi Temp piezoelectric ceramics (T3)

The potential benefit for this technology includes weight reduction from a short transition duct. 

However, the QAT baseline already assumes a short transition duct, and the weight reduction benefit does 

not apply. Another benefit could be stall margin improvement. Based on HPC rig result, for the HPC stall 

margin technology (piezoelectric), assumed an improvement in stall line and corresponding increase in 

operating line, which translates into improvement in HPC efficiency based on new engine design 

experience. 

NASA/CR—2005-213972 15
4.3.6 Magnetic bearing technology (T6) 

The potential benefits for this technology is two folds: First, lower overall vibration level, which 

could improve reliability and life. However, as previously stated for this study, life related benefit was not 

modeled. Second benefit is the higher DN capability. However, the QAT new engine design is not limited 

by DN; hence there is no immediate impact from higher DN capability. 

The shortcomings for aircraft engine applications are listed: 

(1) Weight penalty is huge plus magnetic bearings need auxiliary bearings to handle blade-out load 

and as safety backup. 

(2) Offset bottom case clearance grind to allow rotor drop during shut down; 

(3) Cooling flow requirement under hot section; 

(4) Extra power requirements. 

GEAE conducted an ideal case assessment for magnetic bearing technologies attempting to minimize 

the above mentioned disadvantages. This ideal case assessment is based on the following assumptions: 

• An innovative magnetic bearing concept will be designed to support counter rotating rotors; 

• Magnetic field will be transmitted through the counter rotating rotors; 

• These advanced magnetic bearings will not require back up bearing and lube systems; 

• A concept will support the rotors during engine off and fan blade out conditions. 

All the mentioned technologies were taken into consideration for evaluation. However, the following 

two technologies were not included because GEAE technologists could not estimate a benefit over 

existing systems or a practical method to implement: 

4.3.7 Active blade damping (T4) 

The concerns on this technology are two folds: First, the target TRL 9 date is 2017 while the 

Propulsion 21 EIS is 2008 to 2012 or 2015 at the latest. Secondly and most important, is the 

implementation of this technology in a rotating structure and its effect on LCF life. 

4.3.8 Compressor IGV control via Hi Temp SMA (T9) 

The concerns on this technology are two folds: First using SMA will not provide additional benefit to 

the current rotor actuator. Secondly and most important, SMA is an on-off switch while IGVs need 

continuous and instant actuation control. 

5.0 Response Surface Equation Construction Results 

For this study, a 12-factor Design of Experiment (DOE) table, with central composite design of 

281 runs, was generated as input to the PREDATER analysis and results from the DOE were post 

processed using the commercial statistical tool JMP to obtain the response surface equations. The RSE are 

shown in figure 12. The 12 factor key control parameters and the 12 responses representing the system 

figures of merits are listed. 

12 Factors:

(1) ZFPRD: Fan Pressure Ratio 

(2) EGTadder: EGT stack adder reduction 

(3) DTE1C2: Cooled delta air temperature from baseline 

(4) ED12: Fan efficiency 

NASA/CR—2005-213972 16
(5) ED25: HPC efficiency 

(6) ZSWC42: Cooling flow scalar 

(7) ZSWC43: Cooling flow scalar 

(8) SG31W42: Modulated cooling scalar 

(9) SG27W42: Modulated cooling scalar 

(10) DELWT: Delta weight to propulsion system weight 

(11) ZPWXH: Power extraction 

(12) ZWB: Customer bleed 

12 Responses: 

(1) SFC_MP: SFC Mid Cruise 

(2) DIT2A: Fan diameter 

(3) WTTWAV: Propulsion system weight 

(4) FUEL7: Fuel burn at 5600 NM 

(5) RANGE10: Design range 

(6) CR_CUM_MARG: Baseline cumulative acoustic margin 

(7) CR_SFI: Baseline + SFI (T1) or SJA (T2) cumulative acoustic margin 

(8) CR_SMA: Baseline + SMA (T3) cumulative acoustic margin 

(9) CR_AL: Baseline + Active Liners (T4) cumulative acoustic margin 

(10) P21_CUM_MARG: P21 cumulative acoustic margin 

(11) NOXQAT: Baseline NOx, same for NASA Active Combustor (T21) NOx

(12) NOXP21: GEAE Intelligent Combustor (T16) NOx NOXP21 NOXQAT P21 CUM MARGIN CR AL CR SMA CR SFI CR CUM MARGIN RANGE 10 FUEL7 WTTWAV DIT2A SFC MP

ZFPRD EGTadderC DTE1C2 ED12 ED25 ZSWC42 ZSWC43 SG31W42 SG27W42 DELWT Z2PWXH ZWB

NOXP21 NOXQAT

P21 CUM

MARGIN CR AL CR SMA CR SFI

CR CUMMARGIN

RANGE

10 FUEL7 WTTWAV DIT2A SFC MP NOXP21 NOXQAT

P21 CUM

MARGIN CR AL CR SMA CR SFI

CR CUMMARGIN

RANGE

10 FUEL7 WTTWAV DIT2A SFC MP

ZFPRD EGTadderC DTE1C2 ED12 ED25 ZSWC42 ZSWC43 SG31W42 SG27W42 DELWT Z2PWXH ZWB

Figure 12.—Response surface equations. 

NASA/CR—2005-213972 17
6.0 Technology Ranking and System Benefits 

6.1 Individual Technology Evaluation 

The purpose of the technology benefits assessment was to determine the individual or technology 

groups that provide the greatest benefit to the engine platform. In this study, GEAE evaluated the 

internally suggested technologies as well as NASA suggested technologies. GEAE PREDATER was used 

to construct the response surface equations, and the Georgia Tech Technology Impact Evaluation System, 

TIES was used to conduct the technology assessment for all the new engine technologies. The 

deteriorated engine technologies T23 and T24 were not included in the TIES One-on and One-off study 

because they were not applied to new engines while the rest of the technologies were. Instead, the results 

from PREDATER for T23 and T24 were directly used and they are plotted with the rest of new engine 

technologies, indicated as yellow bars in figures 13 to 19. 

TIES is a disciplined methodology that combines expert technology impact assessment with a physics 

based description of the engine design space. The TIES method was developed by Georgia Tech and was 

used in cooperation as part of a larger Industry-University Partnership that GEAE has with Georgia Tech. 

In this study, the two methods in TIES, One-on and One-off were used. For one-on, the baseline is the 

QAT engine with no additional technology on, and then added only one technology at a time. For Oneoff, the baseline is the QAT engine plus all technologies on, and then technology removed one at a time. 

Figures 13 to 19 show the impact of each proposed technology on new engines, except T23 and T24, in 

terms of SFC, fuel burn, design range, noise, emission, fan diameter, and total propulsion weight relative 

to the QAT baseline using TIES One-on and One-off methods. Shown on the same charts is the impact of 

HPT clearance control on deteriorated engines. Throughout this study, SFC refers to specific fuel 

consumption at mid cruise point, and fuel burn refers to fuel burn at 5600 Nautical Mile (NM) mission. 

Note that all the technology evaluation charts are shown as deltas or delta percent values from their own 

baseline. 

6.1.1 SFC, fuel burn, and design range 

The top ten technology rankings for SFC, fuel burn and design range are listed at the bottom of these 

figures for both One-on and One-off methods. The top ten remain the top ten for both methods, although 

their order changed slightly. T13 (Intelligent HPT rotor cooled cooling), T19 (Active tip clearance control 

using high temperature SMA), T20 (Variable area fan nozzle via high temperature SMA), T5 (HPT blade 

cooling flow modulation), T15 (Shape changing airfoil) have significant impact on SFC, fuel burn and 

design range. T14 (Smart Containment System), which reduces engine weight, has minimum impact on 

SFC; however, it reduces fuel burn and significantly increase design range. 

6.1.2 Acoustic Assessment 

Among the acoustic technologies, T1 (Steady fluidic injection), T2 (Synthetic jet actuators), T3 

(Shape memory alloy), and T4 (Active liners), T2 has most acoustic benefits with minimum impact on 

fuel burn and design range. 

NASA/CR—2005-213972 18
Tech # 13 19 20 5 15 11 18 9 10 6

One_on 1 2 3 4 5 6 7 8 9 10

One_off 1 2 3 5 4 7 6 9 10 8

Top Ten SFC

Figure 13.—Technology evaluation: SFC. 

NASA/CR—2005-213972 19
Top Ten FB

Tech # 13 19 15 20 5 11 18 9 10 14

One_on 1 2 3 4 5 6 7 8 9 10

One_off 2 1 4 3 6 7 5 9 10 8

Figure 14.—Technology evaluation: Fuel burn at 5600 NM. 

NASA/CR—2005-213972 20
Top Ten Range

Tech # 13 19 15 14 5 11 20 18 9 10

One_on 1 2 3 4 5 6 7 8 9 10

One_off 5 1 2 3 8 7 4 6 9 10

Figure 15.—Technology evaluation: Design range. 

NASA/CR—2005-213972 21
Figure 16.—Technology evaluation: Noise. 

NASA/CR—2005-213972 22
Figure 17.—Technology evaluation: LTO NOx. 

NASA/CR—2005-213972 23
6.1.3 Emissions

The LTO NOx assessment is shown in figure 19. The predicted LTO NOx data for T16 (GEAE 

Intelligent combustor) reflects the potential benefit of the TAPS design to meet the program goal of 

reducing NOx by 50 percent from baseline QAT level, equivalent to 15 percent additional reduction from 

1996 ICAO limit. NASA’s active combustion control (T21) will remain the same NOx level as the QAT 

baseline.

6.1.4 Fan diameter and propulsion system weight 

Engine fan diameter, propulsion system weight and SFC are engine characteristics that have 

significant impact to aircraft fuel burn and design range. Weight is also considered an indicator of engine 

cost and engine manufacturers are always looking at ways to reduce weight in new designs. For this 

reason the fan diameter and propulsion system weight are included as system figures of merits. The 

technology evaluation for fan diameter and propulsion system weight are shown in figures 18 and 19. 

Figure 18.—Technology evaluation: Engine fan diameter. 

NASA/CR—2005-213972 24
Figure 19.—Technology evaluation: Total propulsion system weight. 

NASA/CR—2005-213972 25
6.2 Engine System Level Impact: Combined Technologies 

The engine system level impact was estimated by selecting the best technologies, among the 

incompatible technologies, and including all the beneficial technologies. There were three steps involved: 

Step (1): Selecting the best technology out of the incompatible ones based on the individual 

technology evaluation 

(a) Incompatible Acoustic related technologies: T1, T2, T3: 

T1 and T2 have the best acoustic benefits, while T2 has minimum impact on fuel burn and 

design range compared to T1. Selected T2. 

(b) Incompatible fan flow related related technologies: T15, T20 

The Shape Changing Airfoil (T15) uses SMA to change fan airfoil shape. The Variable Area Fan 

Nozzle via High Temperature SMA (T20) uses SMA to change fan nozzle area. These two technologies 

are not additive due to the following reasons: 

1. The SMA fan airfoil reduces the loss associated with off design operation by changing the blade 

camber. 

2. Variable fan nozzle area (A18) does not change the blade shape, but it does change the fan 

operating line. Opening A18 at part speed may also reduce the incidence loss. 

3. Based on the individual technology evaluation results, these two technologies have almost 

identical benefits. T15 is slightly better on design range, but more risky. For evaluation purpose, 

selected T20. 

(c) Combustion related technology: T16 and T21. 

T16 has 50 percent reduction on NOx while T21 has the same as the QAT baseline. Selected T16. 

Step (2): Excluding technologies with no system benefit within modeling capability. Excluded T22 

(magnetic bearing technology) 

Step (3): Combining all the selected technology to evaluate potential engine system level impact. The 

final system contains all the proposed technologies except T1, T3, T15, T21, and T22. The system level 

impacts based on the response surface equations are shown in table 3. With respect to the QAT baseline, 

SFC was improved by 1.7 delta percent, fuel burn improved by delta 2.0 percent, design range improved 

by delta 1.9 percent, Noise (cumulative margin) improved by 3.3 EPNdB, NOx reduced by 50 percent, 

and propulsion system weight reduced by 73 lbs. 

TABLE 3.—ENGINE SYSTEM LEVEL IMPACT 

SFC -1.7% Delta percent from baseline

Fuel Burn (at 5600NM) -2.0% Delta percent from baseline

Design Range 1.9% Delta percent from baseline

Noise cumulative margin 3.3 Delta EPNdB from baseline

NOX -50% Delta percent from baseline

Propulsion System Weight -73 Delta from baseline (lbs)

NASA/CR—2005-213972 26
7.0 Conclusions 

7.1 Deliverables Met 

For the Propulsion 21 system study, the following tasks were accomplished within the original work 

scope: 

• Reached agreement with NASA and Georgia Tech regarding work scope and baseline engine/AC 

definition; 

• Completed TIM for GEAE technology list; 

• Validated Response Surface Equations using JMP and PEZ tools; 

• Improved RSE fit accuracy based on Design Space Study; 

• Built the system model using the QAT as baseline AC and engine; 

• Generated response surface equations and transmitted to Georgia Tech. 

7.2 Additional Deliverables 

Additional results were delivered beyond the original work scope. These include: 

• Coordinated GE evaluation of NASA TIM; 

• Enhanced modeling capability for special technologies, including modulated cooling, cooled 

cooling, HPT ACC for EGT overshoot and deteriorated engines; 

• Evaluated/ranked individual new engine technology using One-on and One-off methods; 

• Evaluated deteriorated engine technology impact for HPT clearance control; 

• Estimated overall system impact by optimally combining technologies; 

• Compiled Technology Readiness Level; 

7.3 Engine System Level Impact 

The engine system level impact was estimated by the optimal combination of technologies, resulting 

in potential 3.3 EPNdB cumulative noise margin improvements, 2.0 percent fuel burn reduction and 

50 percent NOx emissions reduction from the QAT baseline. 

7.4 Modeling Shortfalls and Improvement Needs 

Some technologies were not assessed to their full potential benefits due the modeling capability; 

while other technologies could have been evaluated to higher accuracy with improvement on the tools. 

The following are modeling shortfalls or future improvement needs: 

(1) The model used did not consider life related benefits. This impact the assessment for magnetic 

bearings, combustion control, malfunction and operation error reduction, disk life meter, sub 

system health management, as all these technologies have the potential for hardware life related 

benefits. 

(2) The model did not have the capability for thermal dynamic/transition analysis. This capability 

will be ideal for EGT overshoot analysis. 

(3) Need to better understand future NASA technologies, especially the implementation techniques 

and feasibilities, in order to better simulate and include in future evaluations. 

NASA/CR—2005-213972 27
8.0 Recommendations for Future Work 

Recommendations for future work include short term and long-term items. These include, but not 

limited to: 

(A) Short term 

Add the following figures of merits to the system study beside SFC, fuel burn, design range, emission 

and acoustics: 

(1) Manufacturing cost, 

(2) Maintenance cost, 

(3) Customer value analysis 

(B) Long term 

(1) Validate, improve and enhance the life prediction model; 

(2) Add the thermal dynamic/transition analysis modeling capabilities. 

(3) Further investigate NASA technologies showing significant performance improvement and/or 

noise and emission reduction 

(4) Potential improvements to cycle/systems modeling that would aid deterioration modeling and 

deterioration technology impact assessment. Types of deterioration include 

 Increased tip clearances 

 Open seal clearances 

 Airfoil surface roughness 

 Blade leading edge damage (FOD) 

 Bushing, shroud leakage 

 Airfoil/other hardware dirt buildup 

Linking these effects via some physics based models to cycle component/systems modeling is the key 

to assessing deterioration reduction technologies. The deterioration reduction technologies (intelligent and 

other....) then must be characterized consistent with the physics based model inputs. 

9.0 Work Element Schedule 

Figure 20 shows the detailed schedule for the system study work element. 

ID Propulsion 21 System Studies

1 Task 1 - Establish baseline engine & airplane models

3 Task 2 - Define TAD & TIM for Proposed Technologies

4 - Technology Audit Datasheets

5 - Technology Impact Matrix (GEAE + NASA Tech)

6 - Response Surface Equations (GEAE + NASA Tech)

7 Task 3 - Complete & Support GT One-Off technology ranking

8 Task 4 - Complete & Support GT Engine level system impact 

9 Task 5 - Support GT Identifying Modeling shortfalls 

10 Deliverables

11 - Task Plan

12 - Quarterly Reports

13 - Final Oral Presentation

14 - Final Written Report

Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May

3rd Quarter 4th Quarter 1st Quarter 2nd Quar

Figure 20.—Schedule plan.

NASA/CR—2005-213972 28
This publication is available from the NASA Center for AeroSpace Information, 301–621–0390.

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NASA CR—2005–213972

E–15290

WBS–22–714–92–50

NAS3–01135

Work element 4.1, Task order 23

36

System Study

Technology Assessment and Prioritizing

General Electric Aircraft Engines

Propulsion systems (aircraft)

Unclassified -Unlimited

Subject Category: 07

General Electric Aircraft Engines

One Neumann Way

Cincinnati, Ohio 45215–1915

Project Manager, Clayton L. Meyers, Aeronautics Division, NASA Glenn Research Center, organization code PRV,

216–433–3882.

The objective of this NASA funded project is to assess and prioritize advanced technologies required to achieve the goals

for an “Intelligent Propulsion System” through collaboration among GEAE, NASA, and Georgia Tech. Key GEAE

deliverables are parametric response surface equations (RSE’s) relating technology features to system benefits (sfc, weight,

fuel burn, design range, acoustics, emission, etc...) and listings of Technology Impact Matrix (TIM) with benefits, debits,

and approximate readiness status. TIM has been completed for GEAE and NASA proposed technologies. The combined

GEAE and NASA TIM input requirement is shown in Table.1. In the course of building the RSE’s and TIM, significant

parametric technology modeling and RSE accuracy improvements were accomplished. GEAE has also done preliminary

ranking of the technologies using Georgia Tech/GEAE USA developed technology evaluation tools. System level impact

was performed by combining beneficial technologies with minimum conflict among various system figures of merits to

assess their overall benefits to the system. The shortfalls and issues with modeling the proposed technologies are identified,

and recommendations for future work are also proposed.