H. Douglas Perkins

Glenn Research Center, Cleveland, Ohio

Jack Wilson

Arctic Slope Research Corporation, Cleveland, Ohio

Daniel P. Raymer

Conceptual Research Corporation, Playa Del Ray, California

An Evaluation of Performance Metrics for

High Effi ciency Tube-and-Wing Aircraft

Entering Service in 2030 to 2035

NASA/TM—2011-217264

November 2011
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H. Douglas Perkins

Glenn Research Center, Cleveland, Ohio

Jack Wilson

Arctic Slope Research Corporation, Cleveland, Ohio

Daniel P. Raymer

Conceptual Research Corporation, Playa Del Ray, California

An Evaluation of Performance Metrics for

High Effi ciency Tube-and-Wing Aircraft

Entering Service in 2030 to 2035

NASA/TM—2011-217264

November 2011

National Aeronautics and

Space Administration

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NASA/TM—2011-217264 1 

An Evaluation of Performance Metrics for High Efficiency 

Tube-and-Wing Aircraft Entering Service in 2030 to 2035 

H. Douglas Perkins 

National Aeronautics and Space Administration 

Glenn Research Center 

Cleveland, Ohio 44135 

Jack Wilson 

Arctic Slope Research Corporation 

Cleveland, Ohio 44135 

Daniel P. Raymer 

Conceptual Research Corporation 

Playa Del Ray, California 90296 

Abstract 

An analysis of basic vehicle characteristics required to meet the Fundamental Aeronautics 

Program’s 70 percent energy consumption reduction goal for commercial airliners in the 2030 to 

2035 timeframe was conducted. A total of 29 combinations of vehicle parasitic drag coefficient, 

vehicle induced drag coefficient, vehicle empty weight and engine Specific Fuel Consumption 

were used to create sized tube-and-wing vehicle models. The mission fuel burn for each of these 

sized vehicles was then compared to a baseline current technology vehicle. A response surface 

equation was generated of fuel burn reduction as a function of the four basic vehicle performance 

metrics, so that any values of the performance metrics up to a 50 percent reduction could be used 

to estimate fuel burn reduction of tube-and-wing aircraft for future studies. 

Introduction 

 In March of 2008, The NASA Fundamental Aeronautics Program released a set of four highlevel performance goals for commercial passenger aircraft expected to enter service between 

2030 and 2035. These goals can be summarized as follows. 

1. Maintain a 55 dB Day-Night Average Noise Level (55 LDN) at an average airport boundary. 

This noise level should be sufficient to keep all objectionable noise within the airport 

boundaries. 

2. Decrease Landing/Take-Off (LTO) NOx emissions to 75 percent below the level set at the 

sixth meeting of the Committee on Aviation Environmental Protection (CAEP/6). 

3. Decrease total mission energy consumption (fuel burn, if a constant fuel type is used) by 

70 percent over a comparable current state-of-the-art commercial airliner. 

4. Increase air traffic capacity by designing aircraft capable of using multiple existing smaller 

airports within a single metropolitan region, rather than requiring an increase in capacity at 

the current major airports. This is sometimes referred to as the metroplex concept. This 

requirement implies that large commercial aircraft be designed to utilize shorter runways 

(perhaps 5000 ft or less) than are typically available at the principal metropolitan airports. 

While each of these requirements can significantly impact aircraft design, the following study 

focuses on the 3rd goal, the reduction of mission energy consumption by 70 percent. This study 

was limited to this single performance goal to determine if the reduced energy consumption 

requirement could be met even without the constraints of the other three requirements, which was 

not clear at the time the NASA goals were established. 
NASA/TM—2011-217264 2 

The study that follows is an analysis of basic vehicle characteristics required to meet the 

70 percent energy consumption reduction goal. A total of 29 combinations of vehicle parasitic drag 

coefficient (CD0), vehicle induced drag coefficient (K), vehicle empty weight (We), and engine 

Specific Fuel Consumption (C) were used to create sized tube-and-wing vehicle models. The 

mission fuel burn for each of these sized vehicles was then compared to a baseline current 

technology vehicle. A response surface equation was generated of fuel burn reduction as a function 

of the four basic vehicle performance metrics, so that any values of the performance metrics up to a 

50 percent reduction could be used to estimate fuel burn reduction of tube-and-wing aircraft for 

future studies. The baseline vehicle selected for this study is the Boeing 737-800 with CFM56-7B27 

engines. Actual data from the baseline vehicle was not used in preparing the baseline analysis case 

in order to avoid any use of proprietary information. Instead, models of a similar aircraft and engine 

combination were created that met the published performance of the 737-800 from company 

websites and public sources such as Jane’s All The World’s Aircraft (Ref. 1). 

Baseline Vehicle Characteristics and Performance 

 As a first step, the reference vehicle, typical of a Boeing 737-800 with CFM56-7B27 engines, 

was modeled. The Conceptual Research Corporation aircraft conceptual design software RDSPro (Ref. 2) was used to model the baseline aircraft. Table I gives the publically available data for 

this aircraft from Reference 3, along with calculated reference values for C, CD0, and K at cruise. 

Additional detailed geometric data for the reference aircraft, scaled from Reference 3, is given in 

Appendix A. Geometric data required for the model but not publically available was estimated 

based on previous modeling activities for similar aircraft and is provided in Appendix B, along 

with a summary of the principle geometric features of the aircraft as generated by the RDS-Pro 

software. Figure 1 shows two views of the modeled aircraft, without control surfaces, generated 

by the RDS-Pro software. 

With the geometric data assembled, RDS-Pro was used to generate L/D characteristics and 

drag curves, Appendix C, and a weight breakdown, Appendix E, for the aircraft. The 

miscellaneous weight value in the weight breakdown was adjusted slightly to make the calculated 

vehicle empty weight exactly equal to the published weight. Typical turbofan specific fuel 

consumption and thrust characteristics were calibrated to published data for the CFM56-7B27 

(Ref. 4), and are provided in Appendix D. 

 As a validation check, a standard commercial airliner mission, including a 200 nmi diversion 

allowance, was analyzed for the modeled reference vehicle. The mission was optimized for range 

by varying cruise altitude and Mach number as needed for best performance. The resulting 

calculation yielded a maximum cruise range of 2774 nmi, which compared acceptably to the 

published value of 2820 nmi (Ref. 3). 

TABLE I.—REFERENCE VEHICLE SPECIFICATIONS 

Passengers and Crew 162 to 189 

Maximum takeoff weight 174,200 lb 

Empty weight 91,990 lb 

Maximum fuel load 46,750 lb 

Cargo capacity 1,555 ft3

Cruise speed 0.785 Mach 

Engines 2 

Cruise specific fuel consumption 0.64 lbm/hr/lbf 

Total SLS thrust 54,600 lb 

Vehicle length 129.6 ft 

Wing span 112.6 ft 

Cruise CD0 0.0241 

Cruise K 0.0376 

 
NASA/TM—2011-217264 3 

Figure 1.—Top and side views of RDS-Pro 737 model. 

Design Parameter Exploration 

 In order to study the individual and combined effects of the four principle vehicle 

performance metrics (CD0, K, We, and C), a 4-parameter Box-Behnken (Ref. 5) design space 

exploration was undertaken. Three levels of parameter improvement relative to the baseline 

vehicle were used, a 50 percent improvement, a 25 percent improvement, and no improvement, in 

various combinations given in Appendix F. In addition to the 25 cases required for the BoxBehnken design, four cases were added with a 50 percent improvement in a single parameter, 

representing the corners of the design space. 

 In performing the vehicle sizing for each case, the vehicle thrust to weight ratio, the wing 

loading, and the tail volume coefficient were held constant. The fuselage size was held constant 

to allow for a true-scale representation of the re-sized aircraft. Photo-scaling was not used. Using 

the RDS-Pro software, it was not necessary to specify exactly how the parameter improvements 

were achieved technologically, only that the parameter was improved by the specified amount. 

Each vehicle was required to perform the same sizing mission as the reference vehicle. The 

resulting fuel burn reduction for each sized vehicle is also listed in Appendix F. 

 A regression analysis using the statistical analysis software package Sigmastat (Ref. 6) was 

then performed to fit fuel burn results to the four performance metric values. All of the input 

performance metrics and the resulting fuel burn were normalized to the values for the reference 

vehicle, renamed ܥ଴஽′ , ܭᇱ

ᇱܥ ,

, ܹ௘′ and ܨ′. An acceptable statistical fit for fuel burn (ܨ′ (was not 

found based on the four original vehicle performance metrics. However, since fuel burn is 

directly proportional to thrust and specific fuel consumption, and thrust is proportional to drag, 

which is in turn proportional to Take-Off Gross Weight (்ܹை′) (since wing loading is held 
NASA/TM—2011-217264 4 

constant for this sizing study), then logically ܨ′ should be a function of ்ܹை′, rather than ܹ௘′. 

Having determined that ்ܹை′ could be accurately obtained from a fit of the four original vehicle 

performance metrics, Equations (1) and (2) was fit from the values of ܥ଴஽

ᇱ , ܭᇱ

ᇱܥ ,

, and ்ܹை′ and 

found to accurately predict fuel burn for a tube-and-wing configuration flying the design mission. 

Since all the values in Equations (1) and (2) are normalized to their values for the reference 

vehicle, given in Table I, each parameter has a value of unity for no improvement, and an 

improved value between zero and unity. As a measure of the accuracy of the regression fit, ்ܹை′

and ܨ′ for the baseline case are calculated to be 0.999 and 0.998, respectively when calculated 

using these expressions. The standard deviation was calculated to be 0.0024. 

′଴஽ܥ0.0653 ൅ ′ܥ0.515 ൅ ′ܭ0.234 ൅ ′଴஽ܥ0.551 ൌ ′ை்ܹ

′ܥ0.104 ൅ ଶ

ଶ ൅ 0.546ܹ௘′

ଶ െ

′ܭ0.429 െ ′௘′ܹ஽଴ܥ0.52 െ ′ܥ′଴஽ܥ0.946 െ ′ܭ′଴஽ܥ0.341′ܭ′௘0.23ܹ ൅ ′ܥ′௘0.463ܹ െ ′ܥ

൅ ′ܥ

′ܥ′ܭ′଴஽ܥ0.536 ൅ ′ܥ′௘′ܹ଴஽ܥ0.917

ܨᇱ ൌ 0.0718 െ 0.154ܥ଴஽′ ൅ 0.0861ܭᇱ െ 0.0722ܥᇱ െ 0.197்ܹை′ െ 0.0652ܭᇱଶ െ 0.0522ܥᇱଶ ൅

൅ ′ை′்ܹ஽଴ܥ′ܭ0.0801 ൅ ′଴஽ܥ′ܭ′ܥ0.0504 ൅ ′ை′்ܹܥ0.579 ൅ ′ை′்ܹ஽଴ܥ0.276 ൅ ᇱܥ′଴஽ܥ0.175

′ை′்ܹܭ′ܥ0.221

 Using these relationships, exploration into what combinations of vehicle performance metrics 

could potentially meet the 70 percent fuel burn reduction goal becomes simple. Figure 2 shows 

the fuel burn reduction as a function of performance metric improvement for each of the metrics 

taken separately, and also for simultaneous improvement in all four metrics taken together in 

equal percentages. These calculations are limited to a 50 percent performance metric 

improvement in any single metric, as that is the extent of the original improvements used to 

develop the curve fit. Improvements beyond this point represent extrapolation beyond the existing 

data, and are subject to significant error. 

Figure 2.—Performance metric analysis results. 

0

0.2

0.4

0.6

0.8

1

0.5 0.6 0.7 0.8 0.9 1

We'

C'

K'

CD0'

All 4 Simultaneously

Fraction of Total Mission Fuel Burn Versus Baseline

Target

Fraction of Aircraft Performance Metric Versus Baseline

(2) 

(1) 
NASA/TM—2011-217264 5 

Examination of Figure 2 indicates that even a 50 percent improvement in a single 

performance metric is insufficient to reach the 70 percent fuel burn reduction goal. It is also 

evident that improvements in specific fuel combustion yield the greatest fuel burn reduction, 

followed by empty weight, parasitic drag, and induced drag, respectively. If these improvements 

are taken in equal proportion simultaneously, it is shown that a 30 percent improvement in all 

four metrics is required to meet the fuel burn reduction goal. While even a 30 percent 

improvement in any single metric is very challenging, it is not inconceivable that such an 

improvement could be made. 

Summary and Conclusions 

 In order to evaluate the possibility of meeting the Subsonic Fixed Wing N+3 generation of 

aircraft performance goal of 70 percent fuel burn reduction , a total of 29 advanced tube-and-wing 

aircraft conceptual designs were generated and compared to a validated current technology 

baseline aircraft flying the same design mission. A statistical curve fit of fuel burn versus the four 

fundamental performance metrics of vehicle parasitic drag, vehicle induced drag, vehicle empty 

weight, and engine specific fuel consumption was generated. Evaluation of this curve fit showed 

that up to a 50 percent improvement in any single vehicle performance metric would not result in 

an aircraft capable of meeting the fuel burn reduction goal, but that a 30 percent simultaneous 

improvement in all four of the performance metrics would result in an aircraft capable of meeting 

the goal. 

The statistical curve fit of fuel burn also provides a simple tool for evaluating the overall 

effect of proposed technology advances on tube-and-wing aircraft performance, provided that 

their effect on the four fundamental vehicle performance metrics can be estimated, without 

having to undertake a full vehicle conceptual design. 

References 

1. Jane’s All The World’s Aircraft Website, URL: http://jawa.janes.com, January 2009. 

2. Raymer, D., “RDS-Professional in Action: Aircraft Design on a Personal Computer,” 

SAE/AIAA Paper 96-5567, October 1996. 

3. Boeing Commercial Airplanes, “737 Airplane Characteristics for Airport Planning,” 

Publication D6-58325-6, October 2005. 

4. CFM56 Engine Website, URL: http://www.cfm56.com, January 2009. 

5. Montgomery, D.C., Design and Analysis of Experiments, John Wiley & Sons, New York, 

2001. 

6. SigmaStat website, URL: http://www.aspiresoftwareintl.com/html/systat.html. 

 

NASA/TM—2011-217264 7 

Appendix A—Reference Vehicle (Boeing 737-800) Detailed Geometry 

Fuselage: 

Length = 124.93 ft 

Height = 13.16 ft 

Width = 12.34 ft 

Cabin width = 11.58 ft 

Fineness ratio = 10.21 

Wing: 

Span = 112.60 ft 

Trapezoidal area = 1340.94 ft2

Aspect ratio = 9.45 

Taper ratio = 0.159 

Mean aerodynamic 

Chord (MAC) = 12.99 ft 

Dihedral angle = 6

1/4 Chord sweep 

Angle = 25.02

Flap span/Wing span = 0.599 

Flap area/Wing area = 0.3 

Tail Fin: 

Height = 23.49 ft 

Area = 284.59 ft2

Rudder area = 56.19 ft2

Aspect ratio = 1.91 

Taper ratio = 0.271 

1/4 Chord sweep = 35

Tail Horizontal Stabilizer:

Span = 47.08 ft 

Tailplane area = 352.83 ft2

Elevators area = 70.50 ft2

Aspect ratio = 6.16 

Taper ratio = 0.203 

Dihedral angle = 7

1/4 Chord sweep 

Angle = 30

 
 
NASA/TM—2011-217264 9 

Appendix B—Reference Vehicle (Boeing 737-800) 

RDS-Pro CAD Model Geometry 

TABLE II.—AIRFOIL GEOMETRY 

Parameter Wing Horizontal tail Vertical tail 

Reference area (ft2) 1255.16 352.84 284.60 

Aspect ratio 10.08 6.16 1.91 

Taper ratio 0.27 0.20 0.27 

Leading edge sweep (degrees) 28.72 34.41 40.38 

1⁄4 Chord sweep (degrees) 26.15 30.00 35.00 

Airfoil type Boeing 737 Scaled NACA 64A Scaled NACA 64A 

Thickness/chord ratio (%) 14.90 12.00 12.00 

Dihedral (degrees) 6.00 7.00 0.00 

Incidence (degrees) 0.00 0.00 0.00 

Twist (degrees) 0.00 0.00 0.00 

Span (ft) 112.48 46.62 23.32 

Root chord (ft) 17.57 12.58 19.21 

Tip chord (ft) 4.75 2.55 5.21 

Mean Aerodynamic Chord (MAC) (ft) 12.39 8.68 13.55 

Distance of MAC from vehicle 

centerline (ft) 

22.74 9.08 9.43 

TABLE III.—SUMMARY OF AIRCRAFT COMPONENT GEOMETRY 

 Fuselage Wing Horizontal tail Vertical tail Engine nacelle

Length (ft) 124.93 50.71 23.31 23.32 14.68 

Width (ft) 12.34 36.41 18.52 38.20 7.25 

Height (ft) 12.34 2.85 1.51 2.55 6.78 

A-Max (ft2) 131.03 45.58 12.59 57.60 40.72 

L/D (Equivalent) 9.67 6.66 5.82 2.72 2.04 

Total surface area (ft2) 4316.37 2326.63 721.10 717.38 307.55 

Surface area + Ends (ft2) 4320.34 2372.31 734.22 777.38 351.47 

Total volume (ft3) 12433.46 1360.46 244.63 433.22 503.07 

 
 
NASA/TM—2011-217264 11 

Appendix C—RDS-Pro Reference Vehicle Estimated 

Aerodynamic Performance 

Figure 3.—Vehicle L/D versus free stream Mach number. 

Figure 4.—Vehicle parasitic drag coefficient versus free stream Mach number. 

2

4

6

8

10

12

14

16

18

0.3 0.4 0.5 0.6 0.7 0.8 0.9

Sea Level

10000 ft

20000 ft

30000 ft

40000 ft

50000 ft

L/D

Mach Number

0.02

0.022

0.024

0.026

0.028

0.03

0.032

0.034

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Sea Level

10000 ft

20000 ft

30000 ft

40000 ft

50000 ft

Cd0

Mach Number
NASA/TM—2011-217264 12 

Figure 5.—Vehicle induced drag coefficient versus fee stream Mach number 

as a function of vehicle lift coefficient, CL. 

 

0.03

0.04

0.05

0.06

0.07

0.08

0 0.2 0.4 0.6 0.8 1

CL=0.65 and Below

CL=0.8

CL=1.0

CL=1.2

CL=1.4

Induced Drag Coefficient, K

Mach Number
NASA/TM—2011-217264 13 

Appendix D—RDS-Pro Reference Vehicle Engine Performance 

Figure 6.—Engine specific fuel consumption versus free stream Mach number. 

Figure 7.—Engine thrust versus free stream Mach number. 

 

0.3

0.35

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0 0.2 0.4 0.6 0.8

Sea Level

5000 ft

10000 ft

15000 ft

20000 ft

25000 ft

30000 ft

35000 ft

39000 ft

Specific Fuel Consumption (lbm-hr/lbf)

Mach Number

0

5000

10000

15000

20000

25000

30000

0 0.2 0.4 0.6 0.8

Sea Level

5000 ft

10000 ft

15000 ft

20000 ft

25000 ft

30000 ft

35000 ft

39000 ft

Thrust (lbs)

Mach Number
 
NASA/TM—2011-217264 15 

Appendix E—RDS-Pro Reference Vehicle Weights Breakdown 

(All weights are given in pounds) 

Structures: 

Wing = 16506.7 

Horizontal tail = 2010.8 

Vertical tail = 700.5 

Fuselage = 17940.3 

Main landing gear = 3908.5 

Nose landing gear = 908.7 

Nacelle = 2921.2 

Total = 44896.7 

Propulsion: 

Engines = 10432.0 

Engine controls = 42.0 

Starters = 174.9 

Fuel system = 623.0 

Total = 11271.9 

Equipment: 

Flight controls = 3758.5 

Instruments = 202.1 

Hydraulics = 1347.5 

Electrical = 2834.8 

Avionics = 1840.3 

Furnishings = 8147.2 

Air conditioning = 2074.7 

Anti-ice = 1742.0 

Handling gear = 52.3 

APU installed = 880.0 

Total = 22879.4 

Miscellaneous = 12942.5 

Total Empty Weight = 91990.5 

Useful Load: 

Crew = 400.0 

Fuel = 38629.3 

Oil = 110.2 

Payload (Maximum) = 13910.0 

Passengers = 29160.0 

Total = 82209.5 

Total takeoff gross weight = 174200.0 

 
 
NASA/TM—2011-217264 17 

Appendix F—Matrix of Aircraft Performance Metrics 

Table IV contains the initial percent improvement in each of the four principle performance 

metrics for each of the aircraft designs used in the study. The final column shows the percentage 

reduction in fuel burn for the sized aircraft resulting from the design parameter improvements 

specified. 

TABLE IV.—PERCENT IMPROVEMENT OF EACH 

PERFORMANCE METRIC AND RESULTING 

FUEL BURN REDUCTION BY DESIGN CASE 

Case CD0, 

Percent 

K, 

Percent 

SFC, 

Percent 

We, 

Percent 

Percent fuel 

burn reduction 

1 0 0 25 25 50.2 

2 50 50 25 25 73.2 

3 0 50 25 25 62.1 

4 50 0 25 25 65.4 

5 0 25 0 25 36.3 

6 50 25 0 25 57.0 

7 0 25 50 25 72.1 

8 50 25 50 25 80.0 

9 0 25 25 0 39.8 

10 50 25 25 0 58.2 

11 0 25 25 50 66.8 

12 50 25 25 50 76.7 

13 25 0 0 25 39.8 

14 25 50 0 25 55.2 

15 25 0 50 25 73.5 

16 25 50 50 25 79.3 

17 25 0 25 0 42.9 

18 25 50 25 0 56.9 

19 25 0 25 50 68.6 

20 25 50 25 50 75.8 

21 25 25 50 0 68.4 

22 25 25 0 0 27.7 

23 25 25 50 50 82.0 

24 25 25 0 50 61.0 

25 25 25 50 25 62.8 

26 50 0 0 0 33.1 

27 0 50 0 0 26.4 

28 0 0 50 0 58.2 

29 0 0 0 50 47.3 
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An analysis of basic vehicle characteristics required to meet the Fundamental Aeronautics Program’s 70 percent energy consumption 

reduction goal for commercial airliners in the 2030 to 2035 timeframe was conducted. A total of 29 combinations of vehicle parasitic drag 

coefficient, vehicle induced drag coefficient, vehicle empty weight and engine Specific Fuel Consumption were used to create sized tubeand-wing vehicle models. The mission fuel burn for each of these sized vehicles was then compared to a baseline current technology 

vehicle. A response surface equation was generated of fuel burn reduction as a function of the four basic vehicle performance metrics, so 

that any values of the performance metrics up to a 50 percent reduction could be used to estimate fuel burn reduction of tube-and-wing 

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