NASA/CR–2015-218704/Volume III

Subsonic Ultra Green Aircraft Research:

Phase II – Volume III – Truss Braced Wing 

Aeroelastic Test Report

Marty K. Bradley, Timothy J. Allen, and Christopher K. Droney 

Boeing Research and Technology, Huntington Beach, California 

 

April 2014
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NASA/CR–2015-218704/Volume III

Subsonic Ultra Green Aircraft Research:

Phase II – Volume III – Truss Braced Wing 

Aeroelastic Test Report

Marty K. Bradley, Timothy J. Allen, and Christopher K. Droney 

Boeing Research and Technology, Huntington Beach, California 

National Aeronautics and 

Space Administration

Langley Research Center Prepared for Langley Research Center

Hampton, Virginia 23681-2199 under Contract NNL08AA16B

April 2014
Available from: 

NASA STI Program / Mail Stop 148 

NASA Langley Research Center 

Hampton, VA 23681-2199 

Fax: 757-864-6500 

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official endorsement, either expressed or implied, of such products or manufacturers by the National Aeronautics and 

Space Administration. 
NASA Contract NNL08AA16B – NNL11AA00T – Subsonic Ultra Green Aircraft Research – Phase II

VOLUME III - Truss Braced Wing Aeroelastic Test Report

Abstract 

This Test Report summarizes the Truss Braced Wing (TBW) Aeroelastic Test (Task 3.1) work 

accomplished by the Boeing Subsonic Ultra Green Aircraft Research (SUGAR) team, which 

includes the time period of February 2012 through June 2014. The team consisted of Boeing 

Research and Technology, Boeing Commercial Airplanes, Virginia Tech, and NextGen 

Aeronautics.

The model was fabricated by NextGen Aeronautics and designed to meet dynamically scaled 

requirements from the sized full scale TBW FEM. The test of the dynamically scaled SUGAR TBW 

half model was broken up into open loop testing in December 2013 and closed loop testing

from January 2014 to April 2014. Results showed the flutter mechanism to primarily be a 

coalescence of 2nd bending mode and 1st torsion mode around 10 Hz, as predicted by analysis.

Results also showed significant change in flutter speed as angle of attack was varied. This nonlinear behavior can be explained by including preload and large displacement changes to the 

structural stiffness and mass matrices in the flutter analysis. Control laws derived from both 

test system ID and FEM19 state space models were successful in suppressing flutter. The 

control laws were robust and suppressed flutter for a variety of Mach, dynamic pressures, and 

angle of attacks investigated.

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Acknowledgements

This project and report reflect the combined efforts of the SUGAR team. The team members are 

Boeing Research and Technology, Boeing Commercial Airplanes, the Virginia Institute of 

Technology, and NextGen Aeronautics. The coordinated effort of this team has produced this 

final report.

Funding for this effort is provided by the NASA Fundamental Aeronautics Program, through the 

Subsonic Fixed Wing organization. The contract number is NNL08AA16B task order 

NNL11AA00T.

The team would like to thank Erik Olson of the NASA Langley Research Center for his guidance 

as the NASA Contracting Officer Technical Representative (COTR), and the task technical advisor 

(TA) Bob Bartels. Additionally, Rob Scott provided significant expertise for the aeroelastic 

analysis and test activities. 

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Table of Contents

Abstract............................................................................................................................................ i

Acknowledgements..........................................................................................................................ii

Table of Contents............................................................................................................................iii

List of Tables and Figures................................................................................................................iv

Tables..........................................................................................................................................iv

Figures.........................................................................................................................................iv

1.0 Introduction ......................................................................................................................... 1

2.0 Dynamic Scale Factors and Requirements........................................................................... 2

2.1 Full Scale vs. Test Scale Configuration Differences............................................................. 3

3.0 Model Design and Analysis................................................................................................ 14

4.0 Dynamic Aeroelastic State Space Model ........................................................................... 18

5.0 Control Law Design ............................................................................................................ 19

5.1 Overview ........................................................................................................................... 19

5.2 System Identification Model Development...................................................................... 20

5.3 SysID Simulation................................................................................................................ 23

5.4 SysID Control Law Design.................................................................................................. 24

5.5 SysID Wind Tunnel Testing................................................................................................ 32

5.6 FEM19 Simulation and Control Law Design...................................................................... 33

5.7 FEM19 Wind Tunnel Testing............................................................................................. 39

5.8 System Identification Model Development – Version 2................................................... 40

5.9 Conclusions....................................................................................................................... 41

6.0 Test Procedures ................................................................................................................. 42

7.0 Test Results........................................................................................................................ 44

7.1 GVT and FEM Correlation ................................................................................................. 44

7.2 Doublet Lattice Aerodynamic Correction Factors Update................................................ 44

7.3 Pre-Holiday Flutter Points................................................................................................. 44

7.4 Non-linear Flutter Method ............................................................................................... 45

7.5 Pre-Holiday Flutter Test vs. Analysis................................................................................. 45

7.6 Post-Holiday Flutter Points............................................................................................... 45

7.7 Post-Holiday Stable Flutter Point Root Mean Square ...................................................... 45

7.8 Post-Holiday Dwell Points Damping Estimates................................................................. 46

7.9 Closed Loop Flutter........................................................................................................... 46

7.10 Closed Loop Gust .............................................................................................................. 47

8.0 Conclusions........................................................................................................................ 75

References .................................................................................................................................... 76

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List of Tables and Figures

Tables

Table 2.1 – SUGAR Wind Tunnel Model Scale Factor Equations.................................................... 4

Table 2.2 – Scale Factors................................................................................................................. 4

Table 2.3 – Wing Full Scale Mass Distribution................................................................................ 8

Table 2.4 – Strut and Jury Full Scale Mass Distribution.................................................................. 9

Table 2.5 – Scaled Beam-Rod FEM History................................................................................... 11

Table 5.1 – SysID to FEM19 Model Comparison - Frequency & Damping.................................... 22

Table 7.1 – GVT Frequency Summary........................................................................................... 49

Table 7.2 – Sine Wave Fit Results for AOA = -3 degrees............................................................... 64

Table 7.3 – Sine Wave Fit Results for AOA = -2 and -1 degrees ................................................... 65

Table 7.4 – Sine Wave Fit Results for AOA = 0 and 1 degrees...................................................... 66

Table 7.5 – Sine Wave Fit Results for AOA = +2 and +3 degrees.................................................. 67

Figures

Figure 2.1 – SUGAR Detailed FEM................................................................................................... 5

Figure 2.2 – Full Scale Wing Stiffness.............................................................................................. 5

Figure 2.3 – Strut Full Scale Stiffness.............................................................................................. 6

Figure 2.4 – Jury Full Scale Stiffness ............................................................................................... 6

Figure 2.5 – SUGAR Baseline Mass Component Summary............................................................. 7

Figure 2.6 – Wing and Control Surface Mass Section Breakdown ................................................. 7

Figure 2.7 – Strut and Jury Section Breakdown.............................................................................. 8

Figure 2.8 – Full Scale Beam Rod and Detailed FEMS................................................................... 10

Figure 2.9 – Flutter Result Comparison of Full Scale Detailed FEM to Beam Rod FEM................ 10

Figure 2.10 – Boundary Condition Study Flutter Comparison...................................................... 12

Figure 2.11 – Boundary Condition Study Mode Shapes............................................................... 12

Figure 2.12 – Fuselage Length Reduction..................................................................................... 13

Figure 2.13 – Flutter Ballast Weights............................................................................................ 13

Figure 3.1 – Wind Tunnel Model Overview.................................................................................. 15

Figure 3.2 – Equivalent Beam Design ........................................................................................... 15

Figure 3.3 – Control System Design.............................................................................................. 16

Figure 3.4 – Wind Tunnel Model Mounting Structure ................................................................. 16

Figure 3.5 – Instrumentation Summary........................................................................................ 17

Figure 3.6 – Critical Load Cases..................................................................................................... 17

Figure 5.1 – Model Definition Points............................................................................................ 20

Figure 5.2 – Bode Plot Comparison of SysID Model to FEM19 SSM............................................. 23

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Figure 5.3 – SysID Simulation........................................................................................................ 24

Figure 5.4 – SysID Controller......................................................................................................... 24

Figure 5.5 – Inboard Control Surface Open-Loop/Closed-Loop Bode Plot Comparison 

(Mach 0.65)........................................................................................................... 26

Figure 5.6 – Outboard Control Surface Open-Loop/Closed-Loop Bode Plot Comparison 

(Mach 0.65)........................................................................................................... 27

Figure 5.7 – SysID Mach 0.65 Nichols Plot.................................................................................... 28

Figure 5.8 – SysID Inboard Control Surface Open-Loop/Closed-Loop Bode Plot 

Comparison (Mach 0.7)......................................................................................... 29

Figure 5.9 – SysID Outboard Control Surface Open-Loop/Closed-Loop Bode Plot 

Comparison (Mach 0.7)......................................................................................... 30

Figure 5.10 – SysID Mach 0.7 Nichols Plot.................................................................................... 31

Figure 5.11 – Sample Tunnel Data Stability Margin Comparison................................................. 32

Figure 5.12 – SysID Controller – Open-loop/Closed-loop Demonstration ................................... 33

Figure 5.13 – FEM19 Simulation ................................................................................................... 34

Figure 5.14 – FEM19 Controller.................................................................................................... 34

Figure 5.15 – FEM19 Inboard Control Surface Open-Loop/Closed-Loop Bode Plot 

Comparison (Mach 0.7)......................................................................................... 36

Figure 5.16 – FEM19 Outboard Control Surface Open-Loop/Closed-Loop Bode Plot 

Comparison (Mach 0.7)......................................................................................... 37

Figure 5.17 – FEM19 Mach 0.7 Nichols Plot................................................................................. 38

Figure 5.18 – FEM19 Simulated Time Response ........................................................................... 39

Figure 5.19 – Fem19 Controller – Open-loop/Closed-loop Demonstration................................. 40

Figure 6.1 – Unstable Open Loop Flutter Point............................................................................ 43

Figure 7.1 – Pre-Holiday GVT vs FEM18........................................................................................ 47

Figure 7.2 – Pre-Holiday GVT vs FEM19........................................................................................ 48

Figure 7.3 – Strut Root Fairing Cutout and Wedge....................................................................... 48

Figure 7.4 – Post-Holiday GVT vs FEM20...................................................................................... 49

Figure 7.5 – FEM20 Wing Stiffness Distribution (Full Scale)......................................................... 50

Figure 7.6 – FEM20 Jury Stiffness Distribution (Full Scale)........................................................... 50

Figure 7.7 – Updated Static Aero Factors..................................................................................... 51

Figure 7.8 – Pre-Holiday Flutter Test Results Alpha=-3 ................................................................ 51

Figure 7.9 – Pre-Holiday Flutter Test Results Alpha = -1 .............................................................. 52

Figure 7.10 – Pre-Holiday Flutter Test Results Alpha = +1 ........................................................... 52

Figure 7.11 – Pre-Holiday Flutter Test Results Alpha = +3 ........................................................... 53

Figure 7.12 – Pre-Holiday Unstable Points................................................................................... 54

Figure 7.13 – Preload and Large Displacement Flutter ................................................................ 54

Figure 7.14 – Pre-Holiday Test vs Analysis.................................................................................... 55

Figure 7.15 – Post-Holiday Flutter Results Alpha –3 .................................................................... 55

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Figure 7.16 – Post-Holiday Flutter Results Alpha = -1 .................................................................. 56

Figure 7.17 – Post-Holiday Flutter Results Alpha = +1.................................................................. 56

Figure 7.18 – Post-Holiday Flutter Results Alpha = +3.................................................................. 57

Figure 7.19 – Pre-Holiday vs Post holiday Test Results................................................................ 57

Figure 7.20 – Post Test Analysis vs Test........................................................................................ 58

Figure 7.21 – Post-Holidays RMS Results Alpha = -3 .................................................................... 58

Figure 7.22 – Post-Holidays RMS Results Alpha = -1 .................................................................... 59

Figure 7.23 – Post-Holidays RMS Results Alpha = +1 ................................................................... 59

Figure 7.24 – Post-Holidays RMS Results Alpha = +3 ................................................................... 60

Figure 7.25 – Run 44 Tab Point 2007 Dwell Time History Data.................................................... 60

Figure 7.26 – Run 44 Tab Point 2007 Decay Time History............................................................ 61

Figure 7.27 – Run 44 Tab Point 2007 FFT ..................................................................................... 61

Figure 7.28 – Run 44 Tab Point 2007 3 Sine Wave Fit of Decay Time History.............................. 62

Figure 7.29 – Run 44 Tab Point 2007 3 Sine Wave Fit Results...................................................... 62

Figure 7.30 – Run 44 Tab Point 2007 3 Sine Wave Fit GUI ........................................................... 63

Figure 7.31 – Dwell Frequency and Damping Estimates Alpha = -3 degrees............................... 68

Figure 7.32 – Dwell Frequency and Damping Estimates Alpha = -2 & -1 degrees ....................... 68

Figure 7.33 – Dwell Frequency and Damping Estimates Alpha = 0 & +1 degrees........................ 69

Figure 7.34 – Dwell Frequency and Damping Estimates Alpha = 0 & +1 degrees........................ 69

Figure 7.35 – Post-Holiday Closed Loop Stable Alpha = -3 ........................................................... 70

Figure 7.36 – Post-Holiday Closed Loop Stable Alpha = -1 ........................................................... 70

Figure 7.37 – Post-Holiday Closed Loop Stable Alpha = +1 .......................................................... 71

Figure 7.38 – Post-Holiday Closed Loop Stable Alpha = +3 .......................................................... 71

Figure 7.39 – Gust Response RMS Mach = 0.65 Q = 50 Alpha = -3 ............................................... 72

Figure 7.40 – Gust Response RMS Mach = 0.7, Q = 57, Alpha = -3 ............................................... 72

Figure 7.41 – Gust Response RMS Mach = 0.75, Q=64, Alpha = -3 .............................................. 73

Figure 7.42 – Gust Response RMS Mach = 0.75, Q = 64, Alpha = -1 ............................................. 73

Figure 7.43 – Gust Response RMS Mach = 0.75, Q = 64, Alpha = +1............................................ 74

Figure 7.44 – Gust Response RMS Mach = 0.75, Q = 64, Alpha = +3............................................ 74

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1.0 Introduction

This test report documents the SUGAR TBW aeroelastic wind tunnel test (Task 3.1) which was 

conducted in the NASA TDT from Dec 2013 through April 2014. The basis for this test was the 

detailed FEM sizing/optimization performed in Task 2.1. This task produced a detailed FEM 

which met all strength, buckling, and flutter constraints. The results showed significant 

structural weight benefits of a truss-braced wing with minimal weight penalty to pass flutter.

The primary goal of the aeroelastic wind tunnel task was to validate the flutter results. The 

secondary goal was to investigate benefits of closed loop flutter suppression control laws. For 

assessing flutter suppression, the objective was to quantify the flutter speed increases and 

investigate control law effect on gust loads.

The Task 2.1 model chosen for the wind tunnel test is the configuration which has the strut 

attached at the front spar and sized with 1.09Vd flutter constraints. The 1.09Vd model is slightly 

softer than the full flutter margin 1.15Vd model and therefore should facilitate the 

demonstration of aeroelastic instabilities in the tunnel. The V strut configuration which has a 

strut attached to the wing front spar and another strut attached to the rear spar showed the 

most structural weight benefit. This configuration wasn’t chosen for the test due to concerns 

about drag and aerodynamic interference of the extra strut. Validating the flutter results for the 

front spar configuration should validate the flutter results on the V strut configuration since 

both analyses use the same methods.

The test was done on a dynamically scaled half model in R134 heavy gas. Dynamically scaled 

components include the wing, strut, and jury. Nearly rigid components include the fuselage, 

flow through nacelle, and engine pylon. The model was fixed on the electronic turn table which 

allowed angle of attack to vary. The model was tested open looped and closed looped using a 

hydraulically actuated inboard and outboard control surface. The model was instrumented with 

22 accelerometers, 10 strain gages and 2 RVDT’s to measure control surface deflection. Testing 

was done from Mach =.6 up to M=.94 for angles of attack from -3 to 5 degrees.

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2.0 Dynamic Scale Factors and Requirements

The testing of the dynamically scaled aeroelastic side mounted half span model was conducted

in R134 heavy gas at the Transonic Dynamics Tunnel (TDT) 16-by-16 foot transonic wind tunnel 

located at the Langley Research Center in Hampton, Virginia. 

When building a dynamic scaled wind tunnel model (WTM) several pieces of information, 

regarding the full scale aircraft, which must be determined before being transmitted to the 

model vendor. Those items are aircraft geometry, mass, stiffness and most importantly the 

scaling factors. 

The model dynamic scaling was selected to balance several considerations including TDT 

operating envelope, TDT test section size, and model manufacturability. Once the basic scale 

factors (length, density, and velocity) are determined the remaining are derived via the 

relations shown in Table 2.1. Scale factors for the test are shown in Table 2.2. 

The detailed structural finite element model (FEM), shown in Figure 2.1, was used as the 

starting point for the SUGAR wind tunnel model. This full scale FEM has a 170ft span. The FEM 

was developed for calculating structural loads and performing structural design, and is based on 

the Outer Mold Lines (OMLs) defined by the aerodynamics group. The FEM mesh was defined 

sufficient to capture potential local buckling behavior and provide good stress results and 

detailed control surface models were incorporated. The target (baseline) equivalent beam 

stiffnesses were calculated to match the stiffness distributions of the detailed FEM model. 

Equivalent beam full scale wing, strut and jury stiffness for scaling are shown in Figure 2.2

through Figure 2.4 The figures also show the elastic axis location of the equivalent beams.

The baseline component mass summary, for the half span full scale model, is shown in Figure 

2.5. The mass of the wing was broken into 19 sections with the control surfaces separated into 

additions sections as shown in Figure 2.6. The weight, C.G. and inertia for each section 

matching the full fuel mass case is listed in Table 2.3. In order to meet the stiffness 

requirements for the strut & jury, the target scaled weight could not be met. So, an estimate of 

the model beam’s weights (strut & jury) was scaled to full size thus requiring ~1490 lbs to be 

added to the detailed FEM. The strut and jury section breakdown and mass distribution are 

shown in Figure 2.7 and Table 2.4, respectively.

The goal of the analysis was to make a beam-rod FEM to become the “as built” analytical model 

of WTM. This analytical model would be used in all aspects of aeroelastic analyses to verify that 

the model was safe to operate in the wind tunnel. The first step in achieving this goal was to 

create full scale beam-rod FEM using the mass and stiffness that was presented in the previous 

section. A comparison of the full scale Detailed FEM and the Beam-Rod FEM is shown Figure 

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2.8. Flutter results of these two full scale FEMs are shown in Figure 2.9; the Beam-Rod results 

match the Detailed FEM very well.

The second step toward achieving an “as built” analytical model, was done by applying the 

scaling factors to the full scale model thus “shrinking it” to the same size as the WTM.

Coordinating with the model vendor was critical in order to determine what was achievable and 

match what is being designed and manufactured. The “as built” FEM was updated as the design 

matured; a history of FEM evolution is shown in Table 2.5. Analysis was conducted throughout 

the model construction time period and updates to the “as built” FEM were being made. 

The SUGAR WTM was attached to the Oscillating Turntable (OTT) mount residing on the east 

side of the TDT test section. A beam-rod FEM of the OTT was provided by NASA so it could be 

incorporated into the analysis. Wind tunnel boundary conditions have been studied to try and 

keep similitude with the free flying vehicle symmetric flutter mechanism. A comparison of 

flutter results for the free free detailed FEM and half model of the detailed FEM with the wind 

tunnel boundary conditions are shown in Figure 2.10. Flutter speeds have changed but the 

flutter mechanism is still a combination of the same primary modes. Also, as shown in Figure 

2.11, the wind tunnel boundary conditions cause a small change in primary mode shapes but 

the modes are similar to the free free modes. The z deflection for the plots is the average front 

and rear spar deflection. The torsional slope is the difference between the z defection at the 

front spar and rear spar divided by the x distance between the spars. Since we have good 

similitude with the fixed boundary conditions we were able to simplify the test versus a free 

flying model or a pitch and plunge free arrangement.

2.1 Full Scale vs. Test Scale Configuration Differences

This section describes configuration differences between the full scale analysis model and the 

test model. First, as shown in Figure 2.12 tunnel integration concerns required a fuselage length 

reduction from 18.7 ft to 13.4 ft. This change had no appreciable effect on the flutter results. 

The engine/nacelle position was moved 12.5 inches aft and 5 inches down. The tested position 

is a more realistic position for the engine/pylon. This difference did change the flutter solution 

but didn’t change the primary flutter mechanism. Finally, as the test analysis model was 

updated to the as built mass distribution the unstable flutter damping decreased to the point 

where it might not be larger than the inherent structural damping. Therefore, as shown in 

Figure 2.13, six ballast weights of just under 3 lbs each were added to aft section of the main 

spar. The ballast weights brought the flutter damping back to an acceptable value.

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Table 2.1 – SUGAR Wind Tunnel Model Scale Factor Equations

Table 2.2 – Scale Factors

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Figure 2.1 – SUGAR Detailed FEM

Figure 2.2 – Full Scale Wing Stiffness

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Figure 2.3 – Strut Full Scale Stiffness

Figure 2.4 – Jury Full Scale Stiffness

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Figure 2.5 – SUGAR Baseline Mass Component Summary

Figure 2.6 – Wing and Control Surface Mass Section Breakdown

1 3 5

7

9

11

13

15

17

19

2 4

6

8 10

12

14

16

18

Total weight = 20,993 lbs

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Table 2.3 – Wing Full Scale Mass Distribution

Figure 2.7 – Strut and Jury Section Breakdown

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Table 2.4 – Strut and Jury Full Scale Mass Distribution

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Figure 2.8 – Full Scale Beam Rod and Detailed FEMS

Figure 2.9 – Flutter Result Comparison of Full Scale Detailed FEM to Beam Rod FEM

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Table 2.5 – Scaled Beam-Rod FEM History

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Figure 2.10 – Boundary Condition Study Flutter Comparison

Figure 2.11 – Boundary Condition Study Mode Shapes

Damping (G)

1.09Vd

Antisymmetric 3.51 Hz

Symmetric 2.76 Hz

Free-Free 

-0.10

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0.04

0.06

0.08

0.10

0 50 100 150 200 250 300 350 400 450 500

Damping (G)

Speed (KEAS)

Wind Tunnel 

Boundary 

Conditions –

Half Model 

3.17 Hz

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0 200 400 600 800 1000

Z Deflection

Wing Sta (in)

Free Free Mode 11 1.95 Hz

Wind Tunnel Boundary Conditions - Half Model 1.96 Hz 0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0.0007

0.0008

0.0009

0.001

0 200 400 600 800 1000

Torsional Slope

Wing Sta (in)

Free Free Mode 11 1.95 Hz

Wind Tunnel Boundary Conditions - Half Model 1.96 Hz

Primary Bending Mode

Primary Torsion Mode

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0 200 400 600 800 1000

Z Deflection

Wing Sta (in)

Free Free Mode 16 3.04 Hz

Wind Tunnel Boundary Conditions - Half Model 3.43 Hz

-0.0008

-0.0007

-0.0006

-0.0005

-0.0004

-0.0003

-0.0002

-0.0001

0

0 200 400 600 800 1000

Torsional Slope

Wing Sta (in)

Free Free Mode 16 3.04 Hz

Wind Tunnel Boundary Conditions - Half Model 3.43 Hz

Z deflection is 

average front 

spar and rear 

spar deflection

Torsional slope 

is difference 

between front 

and rear spar z 

deflections 

divided by the 

x distance 

between spars

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Figure 2.12 – Fuselage Length Reduction

Figure 2.13 – Flutter Ballast Weights

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3.0 Model Design and Analysis

The main features of the model are shown in Figure 3.1. The model features the cruciform wing 

and strut beam, h section jury beam, rigid fuselage, flow through nacelle, and 2 actively 

controlled trailing edge surfaces.

The model uses a classical flutter model construction approach, where a single internal beam 

represents the entire stiffness composition of a wing or strut member, and segmented skins are 

used for an aerodynamic fairing that does not contribute additional stiffness. The process used 

to develop equivalent beam cross-sections to meet the stiffness requirements is shown in 

Figure 3.2. The large span wing couldn’t be machined as a single piece, so there are two wing 

beams with a joint in the middle. Stiffness requirements were met for the wing, strut, and jury. 

Mass requirements were met for the wing. Based on classic flutter model construction, model 

strut and jury mass estimates exceed scaled requirements. However, the extra mass was shown 

to be inconsequential to flutter results and acceptable for test.

Actuator system design (Figure 3.3) was based on the successful system used for a number of 

actively controlled flutter models, including the Boeing joined wing sensorcraft free-flying

model, and consisted of a high flow Moog servovalve, a custom designed hydraulic actuator, a 

coupler, and a RDVT sensor. Large hinge moment and high bandwidth requirements for flutter 

suppression were challenges for the control system design. The coupler wasn’t able to fit in the 

OML so a small cutout in the skin was made to accommodate it.

The mounting structure attaches to the electronic turn table and wing spar and strut as shown 

in Figure 3.4. A summary of the model instrumentation which included 22 accelerometers, 10 

strain gages, and 2 RVDT’s is shown in Figure 3.5. The model was designed to have the NASA 

model systems criteria required safety margin for the five design condition shown in Figure 3.6. 

Validation testing included actuator characterization, coupling strength, strain gage calibration, 

mass property verification, and GVTs. Actuator characterization involved recording the control 

surface position as it was commanded to sweep through a range of frequencies. Results 

showed actuator performance was adequate for flutter suppression control laws. A test was 

completed to determine hinge moment capability of the coupler, as spatial constraints forced 

the selection of an undersized model. The coupler hinge moment capability is lower than the 

actuator and close to some conservatively derived maximum hinge moment requirements. The 

strain gages were calibrated by recording values with a known applied load, and correlation 

with the finite element analysis result of each test case. The same loads were applied at a few 

times during testing to make sure the strains didn’t change. The model was weighted to make 

sure it matched the analysis model. GVTs were conducted in the model prep area, and in the 

tunnel with and without skin tape. There were also multiple GVTs over the course of the test to 

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verify that the model behavior was consistent. A comparison of the GVT results to the analysis 

model is documented in the test results section.

Figure 3.1 – Wind Tunnel Model Overview

Figure 3.2 – Equivalent Beam Design

2 Active 

Surfaces

Cruciform Wing 

Beam

Flow-Thru

Nacelle

Cruciform 

Strut 

H-Section Jury 

Beam 

Rigid Fuselage

Side-wall 

Mounted

Scaled Stiffness Targets  Section Solver  Initial CAD Layout

Y-location out-plane in-plane torque

[in] EI11 EI22 GJ

1.875 2.86E+06 1.55E+08 3.40E+06

5.636 3.15E+06 1.35E+08 3.40E+06

11.134 3.51E+06 6.83E+07 3.40E+06

18.344 3.38E+06 6.76E+07 3.40E+06

25.541 3.28E+06 5.75E+07 3.40E+06

32.823 3.16E+06 5.30E+07 3.40E+06

Variables 2A 2B 2a 2b

[in] 0.817 0.382 0.214 0.101

Yna Iopx Iipz J

[in] [in^4] [in^4] [in^4]

NA 0.0038 0.029 0.0114

Yna Iopx Iipz J

[in] [in^4] [in^4] [in^4]

NA 0.0039 0.0293 0.0115

Total Iopx Iipz J

[in] [in^4] [in^4] [in^4]

-9.7619E-08 -0.00004 -0.00029 -0.000115

Error % -3.0 -1.00 -1.00 -1.00

Variable V > Than V < Than

Htot 0.375 0.825

Wtot 0.500 9.000

Wsb 0.125 6.000

Tsb 0.100 0.101

Iopx 0.99 1.01

Iipz 0.99 1.01

J 0.99 1.01

Out-plane error [%]

In-plane error [%]

Torsional error [%]

Solver Constraints

Description

Total Height [in]

Total Width [in]

Side Block Width [in]

Side Block Thickness [in]

Section 

Property 

Error

Boeing SUGAR - Cruciform Cross-Section Solver

Center Block Side Blocks

Current 

Section 

Properties

Target 

Section 

Properties

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Figure 3.3 – Control System Design

Figure 3.4 – Wind Tunnel Model Mounting Structure

Side view from east wall

ETT

Strut Flange

Spar

Wing 

Spar

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Figure 3.5 – Instrumentation Summary

Figure 3.6 – Critical Load Cases

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4.0 Dynamic Aeroelastic State Space Model

The current process takes the analysis modes and unsteady doublet lattice aerodynamics and 

generates a dynamic aeroelastic state space model which is used to develop control laws. 

Unsteady aerodynamics is represented by a P-transform method in the time domain requiring 

no additional aero states. Multiple models were generated as the analysis FEM matured. Final 

models were based on FEM19 which was used to generate the tested control laws. Models 

included 40 states for 20 flexible modes up to 100 Hz. Models contain outputs at all 

accelerometer locations consisting of displacement, rate, and acceleration in all three 

coordinate directions and rotational displacement and rate about all three coordinate 

directions. Models contain inputs consisting of the inboard and outboard wing trailing edge 

control surface deflection, rate, and acceleration to accommodate coupling actuator dynamics. 

Final FEM19 models include 13 dynamic pressures at Mach =0.75 and two dynamic pressures at 

Mach = 0.6, 0.65, and 0.7 . 

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5.0 Control Law Design

5.1 Overview

Two separate control law designs were developed and tested in the closed-loop testing at the 

TDT. The first design was developed for a pair of System Identification (SysID) models of the 

TBW model. The SysID models were derived from control surface sweeps performed in openloop testing. The second control law was designed for the FEM19 State Space Model (SSM) 

dynamics. Both control law designs were based on Linear Quadratic Regulator (LQR) design 

techniques with a Kalman Filter state estimator. Both “designs” are actually comprised of 

several point designs (2 SysID models and 18 SSMs) and employ a “nearest neighbor” algorithm 

based on Mach and dynamic pressure (Q) to perform “gain scheduling”. Figure 5.1 shows where 

the various models (SysID and SSMs) were defined in relation to the pre-holiday flutter 

boundaries. Both designs proved to be robust to variations in Mach, Q, and angle of attack 

(AOA).

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Figure 5.1 – Model Definition Points

5.2 System Identification Model Development

The SysID methods employed to derive the two models were based on methods developed 

previously for the Aerodynamic Efficiency Improvement program. The SysID method uses an 

optimizer to tune the simulation model to match the test data collected in the control surface 

sweeps. The derived models were based on open-loop control surface sweeps at Mach 0.65, Q 

53.9 psf (TDT Run 10, Tab Points 529 and 530) and Mach 0.7, Q 61.6 psf (Run 10, Tab Points 551 

and 552). All of the sweeps were performed at an AOA of -3°. The FEM19 SSMs were used as a 

starting point in the process. The up side to the SysID modeling is that if the process converges 

to a solution, you have a high degree of confidence in the model. The down sides to this 

approach to model generation are the necessity for open-loop control surface sweeps and the 

large amount of memory and processor capacity required. Each of these models took over a 

day to generate, even given the fairly accurate starting point. The original plan for the TDT tests 

was to forgo the SysID step in order to save time and just use the FEM models for designing the 

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controller. The variation in the TBW model’s GVT data from pre-holiday to post-holiday 

provided both more time to develop the SysID models and the desire to make sure more wind 

tunnel time wasn’t lost tuning the controller once testing began.

A comparison of the SysID model’s mode frequencies and damping is shown in Table 5.1. Figure 

5.2 shows a comparison of the Mach 0.65 SysID model to its FEM19 SSM counterpart at for the 

inboard control surface to the outboard wing tip (forward) accelerometer (Z axis). In general, 

the SysID and FEM19 models agree fairly well, but the FEM19 models tend to be more 

attenuated in the 5 to 10 Hz range.

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Table 5.1 – SysID to FEM19 Model Comparison - Frequency & Damping

Mach 0.65 Mach 0.70

SysID

Freq (Hz)

FEM19

Freq (Hz)

SysID

Damping

FEM19

Damping

SysID

Freq (Hz)

FEM19

Freq (Hz)

SysID

Damping

FEM19

Damping

5.67 6.03 0.0082 0.0081 5.70 6.03 0.0063 0.0066

6.24 6.02 0.0724 0.0773 6.35 6.14 0.0717 0.0806

9.78 9.98 0.0189 0.0207 9.99 10.20 0.0122 0.0106

11.03 10.91 0.0219 0.0277 10.93 10.78 0.0392 0.0397

19.56 18.74 0.0252 0.0205 19.59 18.78 0.0238 0.0214

25.79 25.67 0.0682 0.0105 26.73 25.63 0.0124 0.0119

28.04 27.77 0.0010 0.0117 28.22 27.78 0.0011 0.0121

28.33 28.37 0.0102 0.0267 28.60 28.39 0.0227 0.0286

29.36 28.87 0.0023 0.0122 29.38 28.84 0.0017 0.0134

38.62 38.62 0.0090 0.0090 38.64 38.64 0.0092 0.0092

40.21 40.21 0.0231 0.0231 40.21 40.21 0.0257 0.0257

46.92 46.92 0.0106 0.0106 46.94 46.94 0.0109 0.0109

48.09 48.09 0.0231 0.0231 48.05 48.05 0.0263 0.0263

61.52 61.52 0.0064 0.0064 61.52 61.52 0.0066 0.0066

68.32 68.32 0.0082 0.0082 68.32 68.32 0.0085 0.0085

76.34 76.34 0.0088 0.0088 76.35 76.35 0.0094 0.0094

82.76 82.76 0.0158 0.0158 82.80 82.80 0.0174 0.0174

87.47 87.47 0.0083 0.0083 87.48 87.48 0.0086 0.0086

93.16 93.16 0.0068 0.0068 93.16 93.16 0.0071 0.0071

95.11 95.11 0.0079 0.0079 95.12 95.12 0.0082 0.0082

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Figure 5.2 – Bode Plot Comparison of SysID Model to FEM19 SSM

5.3 SysID Simulation

The SysID version of the Simulink simulation is shown in Figure 5.3. From the beginning, the 

simulation architecture was designed so that inserting the controller in the TDT’s dSpace 

control system would be as easy as possible. For the sake of clarity, the controller interfaces 

depicted in the figures have been simplified to just their core components. The actuator block 

(shown in orange) contains the model of the actuators. The outputs of the actuator are the 

inputs to the plant (control surface positions, velocities, and accelerations) and the sensed 

position of the control surfaces (the RVDT signals). The actuator model is followed by the plant 

(in state space form), the outputs of which (Y) are the accelerometer readings. The primary 

inputs to the SysID controller are the accelerometer readings (filtered through the dSpace 

system) and the RVDT signals. The current tunnel Mach and Q are input for nearest neighbor 

gain scheduling.

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Figure 5.3 – SysID Simulation

5.4 SysID Control Law Design

Figure 5.4 shows the controller design for the SysID system, again slightly simplified. A nearest 

neighbor algorithm is used to determine which set of gains / state space model to use this pass 

through the controller. There is some hysteresis built into the algorithm to prevent bouncing 

between the point designs when the tunnel is near a boundary condition. All of the gains, etc., 

are predetermined to minimize computational overhead and make the controller block as fast 

as possible. Tests showed the controller needed to be run at 500 Hz minimum, but the dSpace 

system was able to run at 1000 Hz for the tests.

Figure 5.4 – SysID Controller

The sensed control surface positions and filtered accelerometer outputs are combined and fed 

through a Kalman filter state space estimator to calculate the estimator outputs �X��. The 

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resulting outputs from the estimator (X�) are multiplied by the LQR gains. A “Cmd Filter” is then 

applied to obtain the two control surface commands for output to the actuators.

The estimator coefficients are derived by first designing the full order estimator gains. The gains 

are then applied to the SysID model to form a state space model. The state space model is 

reduced to 10 states (“balanced” reduction) and discretized at the dSpace frequency, 1000 Hz, 

with “tustin” pre-warping.

The LQR gains are derived using a full order LQR design process primarily weighting the first 5 

modes (10 states) with heaviest weighting on the 10 and 20 Hz modes.

The “Cmd filter” is second order, 15 Hz, 0.65 damping, “tustin” pre-warping, that has been 

discretized to 1000 Hz.

The weightings for the LQR gains were tuned to achieve our primary goal of actively damping 

the 10 Hz flutter mode while maintaining good stability margins. Figures 5.5 and 5.6 show the 

resulting Bode plots for both the inboard and outboard control surfaces at the Mach 0.65 

condition. The plots show the 10 Hz mode has been attenuated approximately 9 db in the 

inboard loop and approximately 15 db in the outboard loop. In Figure 5.7, the Nichols plots for 

both of the control surface loops, shows the robust margins of 9 db gain and 45° phase 

(depicted as black diamond shapes in the plot) have been maintained. Figures 5.8, 5.9, and 5.10

show similar plots for the Mach 0.7 condition. This condition is closer to the flutter condition 

and as such was harder to control resulting in slightly lower, but still acceptable, margins. The 

final designs were simulated in the time domain and proved to be stable.

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Figure 5.5 – Inboard Control Surface Open-Loop/Closed-Loop Bode Plot Comparison (Mach 0.65)

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Figure 5.6 – Outboard Control Surface Open-Loop/Closed-Loop Bode Plot Comparison (Mach 0.65)

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Figure 5.7 – SysID Mach 0.65 Nichols Plot

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Figure 5.8 – SysID Inboard Control Surface Open-Loop/Closed-Loop Bode Plot Comparison (Mach 0.7)

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Figure 5.9 – SysID Outboard Control Surface Open-Loop/Closed-Loop Bode Plot Comparison (Mach 0.7)

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Figure 5.10 – SysID Mach 0.7 Nichols Plot

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5.5 SysID Wind Tunnel Testing

Code was inserted in the controller to gather data that could be used to validate the stability 

margins derived from the simulation against actual test data. Unfortunately, the data gathered 

was too noisy to quantifiably validate the simulation. Figure 5.11 shows one of the better plots 

of this data. The plot compares the stability margins derived from one of the early TDT runs 

(Run 48, Tab Point 2354, Mach 0.7, Q 61.2 psf) to the expected simulation results.

Figure 5.11 – Sample Tunnel Data Stability Margin Comparison

An example of the controller actually controlling flutter is shown in Figure 5.12. The TDT 

operators have the ability to turn the controller on and off in real time and the plot shows one 

of these occasions where the TBW is in a flutter condition. The data in red shows the wing 

beginning to flutter, while the data in blue shows flutter being controlled. The SysID controller 

supported TDT runs 48 through 54 where Mach varied from 0.23 up to 0.81, Q varied between 

10 and 97 psf, and AOA varied from -3° to 1°. Almost all of testing with the SysID controller was 

based on the one design point at Mach 0.65, Q 53.9 psf, and entailed no gain scheduling. In all 

these cases where the controller was engaged, flutter was controlled.

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Figure 5.12 – SysID Controller – Open-loop/Closed-loop Demonstration

5.6 FEM19 Simulation and Control Law Design

Since a functioning controller was in place, there was time to attempt to design a new 

controller based on the FEM19 SSMs. Based on experience with the SysID gain design process, 

some changes were incorporated for the FEM19 controller. The FEM19 simulation architecture 

is essentially the same as the SysID version. The main difference is that the actuator commands 

are fed back within the controller, so the RVDT outputs are no longer required to be input to 

the controller. Figure 5.13 shows the FEM19 simulation.

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Figure 5.13 – FEM19 Simulation

The FEM19 controller architecture (Figure 5.14) is “essentially” the same as the SysID 

controller. The major difference is the actuator commands are fed back instead of using the 

RVDT signals. The other obvious change is the lack of LQR gains in the diagram. The gains are 

there, they’ve just been embedded in the estimator’s realization prior to calculating the 

estimator coefficients. Also, a 15° limit is imposed on the actuator commands and the 

hysteresis in the nearest neighbor algorithm was modified such that the states and actuator 

commands could be zeroed out briefly when transitioning between design points. The “Cmd 

filter” frequency was increased to 40 Hz (second order, 40 Hz, 0.65 damping, “tustin” prewarping, that has been discretized to 1000 Hz).

Figure 5.14 – FEM19 Controller

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The process for deriving the LQR and estimator gains is fundamentally different from the SysID 

version. In order to increase stability margins, the FEM19 SSM was augmented with a pair of 

second order filters (40 Hz, 0.98 damping) to model the two actuator’s states and allow the LQR 

process to put gains on them. In order to keep the LQR gains on the actuator’s states in check, 

the system was augmented with a pair of third order filters effectively penalizing very high 

gains to prevent driving the actuator bandwidth too high because of its inherent non-linearities.

The third order filter is a second order filter (10 Hz, 0.6 damping) over a second order filter (100 

Hz, 0.7 damping) multiplied by a first order filter (101 Hz). The LQR gains are derived using a full 

order LQR design process on the augmented model primarily weighting the first 5 modes with 

heaviest weighting on the 10 Hz flutter mode. It was found that heavily weighting the third 

state of the third order filter kept the actuator gains within the desired range.

The estimator gains are calculated and the LQR gains are embedded into estimator to form a 

new state space model. This model is reduced (balanced reduction) to 20 states (10 modes) and 

discretized at 1000 Hz.

The weightings for the LQR gains were tuned to actively damp the 10 Hz flutter mode while 

maintaining good stability margins. Figures 5.15, 5.16, and 5.17 show the resulting Bode and 

Nichols plots at the Mach 0.7 condition. The plots show that the 10 Hz mode has been 

attenuated about 7 db in the inboard loop and about 6 db in the outboard loop, but the robust 

margins (9 db and 45°) were maintained. In fact, the robust margins were maintained for all but 

the two most unstable cases (Mach 0.75, Q 137.7 psf and Mach 0.75, Q 160.6 psf) and the 

nominal margins (6 db and 30°) were maintained in those cases.

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Figure 5.15 – FEM19 Inboard Control Surface Open-Loop/Closed-Loop Bode Plot Comparison (Mach 0.7)

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Figure 5.16 – FEM19 Outboard Control Surface Open-Loop/Closed-Loop Bode Plot Comparison (Mach 0.7)

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Figure 5.17 – FEM19 Mach 0.7 Nichols Plot

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The final designs were tested in the time domain. Figure 5.18 shows a comparison of the 

simulated time responses, with the control loops open and closed, for one of the unstable cases 

(Mach 0.75, Q 68.9 psf). As expected, the open loop accelerations grow unbounded.

Figure 5.18 – FEM19 Simulated Time Response

5.7 FEM19 Wind Tunnel Testing

Figure 5.19 shows an example of the controller controlling flutter at an unstable condition.

Again, the data in red shows the wing beginning to flutter when the controller is turned off and 

the data in blue shows controller damping out the flutter. The FEM19 controller supported TDT 

runs 55 through 63 where Mach varied from 0.35 up to 0.83, Q varied between 21 and 115 psf, 

and AOA varied from -3° to 5°.

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Figure 5.19 – Fem19 Controller – Open-loop/Closed-loop Demonstration

5.8 System Identification Model Development – Version 2

With two functioning controllers in hand, a decision was made to try and develop a controller 

based on control surface sweeps at an unstable point. In order to do this, of course, a controller 

would have to be functioning at the time to keep flutter attenuated. Data was acquired, but 

several issues prevented the models from converging to a solution. Large amplitude, high 

frequency sweeps were required to overcome the inherent noise in the system. However, the 

combination of amplitudes and frequencies required were too high for the actuators which 

became flow rate limited. Also, some unexpected non-linearities became apparent in the data 

that could not be accounted for in the SysID process. Between the actuator limitations, the 

inherent noise in the system, and the non-linearities, the SysID process failed to converge on a 

solution.

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5.9 Conclusions

The main conclusion that can be drawn from this control law effort is that the LQR design 

process worked very well in this instance, allowing the 10 Hz flutter mode to be targeted 

directly in the gain design process. The cycle time for iterations was reduced and the ability to 

switch from the SysID models over to the FEM models was very smooth. The FEM19 SSMs 

based on the pre-holiday model proved to be sufficient for designing a robust control system, 

potentially reducing the need for open-loop testing in the future. Flutter suppression was 

demonstrated with two different control systems that proved to be very robust over a wide 

range of Mach, Q, and AOA.

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6.0 Test Procedures

Test points investigated include flutter points, control surface sweeps, gust vane oscillation 

points, and control surface dwells.

Flutter points involve slowly increasing Mach and dynamic pressure along constant pressure H 

lines while visually monitoring model vibration as well as PSDs and time histories for signs of 

instability. Any sign of instability and a bypass valve button is pushed and the tunnel winds 

down. An example of an unstable open loop flutter point is shown in Figure 6.1. The plot is a 

time history of the nacelle pylon accelerometer. The flutter points were run both open and 

closed looped. Once the control laws allowed the Mach and dynamic pressure to increase past 

the open loop flutter boundary a technique was used to open the loop and quickly close the 

loop and see if the open loop system looked stable. This technique allowed for determining the 

back side of the Mach dip open loop flutter boundary.

Control surface sweeps involve running a fixed amplitude sweep from 0 to 30 Hz to generate 

the data required for the system ID control laws. The sweeps were run inboard alone, outboard 

alone, and both inboard and outboard. The sweeps were run both open looped and closed 

loop. The response due to the control sweeps for the closed loop point in the open loop 

unstable region was lost in the overall noise and insufficient for system ID.

The gust vanes were oscillated both open and closed loop to investigate the control laws effect 

on gust loads.

Control surface dwells involve oscillating the control surface at the 10 Hz flutter frequency and 

then stopping the oscillation and recording the response. This technique allows for a good 

estimate of system damping in the open loop stable region.

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Figure 6.1 – Unstable Open Loop Flutter Point

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7.0 Test Results

Testing was broken up into pre-holiday open loop testing and post-holiday closed loop testing.

7.1 GVT and FEM Correlation

GVTs were run to correlate our analysis model to the test frequencies and mode shapes. The 

final preholiday in tunnel GVT results were compared to the pretest FEM18 analysis model

results. A comparison of the analysis and test frequencies and modal assurance criteria(MAC) is 

shown in Figure 7.1. The two primary flutter modes are second bending mode 3 and first 

torsion mode 4. The GVT vs. FEM18 frequencies are significantly different and the mode 3 MAC 

was .9. FEM19 was created to better match the preholiday GVT result. This was mostly

accomplished by removing the electronic turn table model we had attached to the FEM. In

addition, small changes to the wing stiffness were required. A comparison of preholiday GVT 

and FEM 19 is shown in Figure 7.2. This shows a very good comparison between test and 

analysis. After the preholiday testing a cutout was made in a fairing at the root of the strut. It 

was suspected that there wasn’t enough clearance between the strut root joint and the fairing 

and some fouling was occurring. This was tested by looking at GVT results with and without a 

wedge added which contacted the fairing. The cut out and wedge are shown in Figure 7.3. A 

summary of GVT frequencies showing which GVTs the FEMS are based on is shown in Table 7.1. 

The table shows significant difference in Mode 3 frequencies pre and post holidays. Part of the 

difference is due to the post holiday cutout in the strut root fairing. The GVT results with the 

wedge included don’t get all the way back to the pre holiday values. A FEM20 was created by 

updating stiffnesses again to match the post holiday GVT results. The post holiday GVT is 

compared to FEM20 in Figure 7.4. Again, there is good correlation between test and analysis. 

The resulting FEM20 equivalent beam full scale wing, strut and jury stiffness for scaling are 

compared to the baseline stiffness in Figure 7.5 and Figure 7.6. Note, the strut stiffness 

distribution did not change from the baseline; and the jury stiffness distribution was set to a 

constant value because of the size and ability to manufacture in order to keep within mold-line.

7.2 Doublet Lattice Aerodynamic Correction Factors Update

To improve the test vs. analysis comparisons, the doublet lattice static aerodynamic correction 

factors, described in Section 2.1.8.5 of the TBW Final Report (Volume I – Truss Braced Wing 

Design Exploration), were updated to better match all the test mean wing strain gage results.

This was done for Machs 0.7, 0.75, and 0.82. Figure 7.7 shows the improved correlation with 

test results for the outboard root strain gage at Mach = 0.7.

7.3 Pre-Holiday Flutter Points

All the pre-holiday flutter points at alpha -3, -1, +1, and +3, are shown in Figure 7.8 through 

Figure 7.11. Blue Xs are stable and red Xs are unstable. The pre-holiday unstable points for the 

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four angles of attack are shown in Figure 7.12. The results show a significant variation with 

angle of attack. This is in contrast to tradition linear flutter results which don’t change for 

different angles of attack or loads. This angle of attack variation is unique to the truss braced 

wing due to its large in-plane loads and reduced stiffness of the inboard wing. 

7.4 Non-linear Flutter Method

A method to include preload and large displacement effects in the flutter analysis is shown in 

Figure 7.13. The process starts by generating loads in Nastran solution 144. Next the loads are

applied to the model in a Nastran solution 106 nonlinear run including the large displacement 

parameter. Finally the linear solution 145 is run from a restart of the stiffness and mass matrix 

output from the 106 run.

7.5 Pre-Holiday Flutter Test vs. Analysis

Pre-holiday flutter comparison between test and analysis is shown in Figure 7.14. The 

comparison is with the static corrections from Section 7.2 used in the solution 144 analysis, and 

no corrections to the doublet lattice unsteady aerodynamics for the flutter solution 145 

analysis. The black line shows the traditional linear 145 solution. The analysis including the 

preload and large displacements predicts an angle of attack trend which matches the test data. 

The analysis also is accurate in predicting the minimum flutter speed at each angle of attack. 

The Mach trend using the theoretical doublet lattice does not match the test data.

7.6 Post-Holiday Flutter Points

Post-holiday alpha -3, -1, +1, and +3, flutter points are shown in Figure 7.15 through Figure 

7.18. At alpha -3 degrees, stable points were found at dynamic pressures above the unstable 

region. The pre-holiday and post-holiday flutter test results are shown in Figure 7.19. The 

trends are very similar. The post-holiday flutter speeds have increased as would be expected 

due to the increase separation between the primary modes post holiday. The post-holiday 

analysis vs. test is shown in figure Figure 7.20. Again, angle of attack trend and minimum flutter 

speed modeled well.

7.7 Post-Holiday Stable Flutter Point Root Mean Square

The post-holiday stable flutter points root mean square (RMS) results for the wing tip, nacelle 

pylon, outboard strut, and wing root accelerometers are shown in Figure 7.21 through Figure 

7.24. All plots show a sharp rise in RMS as the flutter boundary is approached except the strut 

gage. The strut gage peaks at lower Machs than the flutter boundary. The strut gage peaks 

between M=0.72 to M=0.74. The alpha = -3 results show peak RMS values in the high Q region 

above the unstable region.

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7.8 Post-Holiday Dwell Points Damping Estimates

Dwell time history decays were recorded at some 102 points, varying in Angle Of Attack (AOA), 

Mach, and/or dynamic pressure. A technique, scripted in Matlab, of fitting a set of damped sine 

waves to the decay response was employed to access modal damping. On average 3 sine waves 

were used to best fit the response, with one frequency and corresponding damping capturing a 

majority of the response.

The basic steps in the process for a given dwell are illustrated using Run Number 44 Tab Point

2007. The raw time history for this Tab Point is plotted in Figure 7.25. Next, the decay portion 

of the time history to be fit is select and is displayed in Figure 7.26. A Fast Fourier transform

(FFT) is performed on the time history to assess the frequency content of the decay which 

provides a start point for the fit process, the FFT results are shown in Figure 7.27. The 3 sine 

wave fit for the decay time history is shown in Figure 7.28. The comparison of the 3 sine waves 

that make up the total fit are shown Figure 7.29. The Matlab GUI with fit results, Run Number 

44 Tab Point 2007, is shown in Figure 7.30. The fit frequency values are in Hertz and the 

damping values are zeta.

A total of 82 dwells were fit and damping values recorded. One accelerometer, Measurand ID 

“ACCWINP”, on the wing nacelle pylon was used for all the dwell data reduction. The data is 

shown in Table 7.2 through Table 7.5 for the AOA‘s of -3, -2, -1. 0 +1, +2, and+3. The damping 

value being reported is structural damping, g, which is two times zeta (from fit process output).

A positive damping value means the sine wave response is diverging while a negative value 

means the response is damping out.

The estimated damping results for all the dwells are plotted in Figure 7.31 through Figure 7.34. 

The frequency and structural damping”g” values are labeled for each point; positive damping 

values are highlighted in red. The results show the damping values getting smaller as the flutter 

boundary is approached. There is also a section of low damping that occurs at lower Machs and 

Q than the flutter boundary. Damping then increases as the Mach and Q increases before 

reducing again before the flutter boundary. Some of the estimated values show small positive 

damping. It should be noted that all dwell points were stable and the positive damping means

there was a limit cycle oscillation or the model was approaching flutter onset. These positive 

damping results illustrate the difficulty in estimating damping using the test data. The values 

were positive in the time slice analyzed but the results would’ve been negative if a different 

time slice was chosen.

7.9 Closed Loop Flutter

Control laws for both system ID and FEM19 SSM were successful in suppressing flutter. The 

control laws were robust and suppressed flutter for a variety of Mach, dynamic pressures, and 

angle of attacks investigated. The post-holiday test results for alpha = -3,-1, +1, and +3 shown in 

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Figure 7.35 through Figure 7.38 include the stable closed loop points. The results show the 

stable closed loop test points going through the open loop unstable region and staying stable to 

much higher dynamic pressures.

7.10 Closed Loop Gust

A comparison of open and closed loop gust response RMS for the inboard wing strain gage are 

shown in Figure 7.39 through Figure 7.44. The gust responses were recorded as the airvane 

oscillation system (AOS) was swept from 0.5 to 13.5 Hz in 100 seconds, then a dwell at 13.5 Hz 

for 10 seconds, followed by a sweep from 13.5 Hz to 0.5 Hz in 60 seconds. The control laws 

used for the plotted results were based on the FEM19 SSM. The results show a peak response 

at the first bending mode and a smaller peak at the second bending mode. The second bending 

mode is a primary flutter mode and its gust response grows as the Mach and dynamics pressure 

approach the unstable region. The flutter suppression designed control laws show a large 

amount of gust load alleviation(GLA) at the second bending peak and a small amount of load 

alleviation everywhere else. A PSD type gust analysis would show some amount of GLA since 

the resulting load is a result of input gusts at all frequencies. A tuned discrete gust critical at the 

flutter frequency would show significant GLA while a tuned gust critical at other frequencies 

would show a small amount of GLA.

Figure 7.1 – Pre-Holiday GVT vs FEM18

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Figure 7.2 – Pre-Holiday GVT vs FEM19

Figure 7.3 – Strut Root Fairing Cutout and Wedge

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Table 7.1 – GVT Frequency Summary

Figure 7.4 – Post-Holiday GVT vs FEM20

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Figure 7.5 – FEM20 Wing Stiffness Distribution (Full Scale)

Figure 7.6 – FEM20 Jury Stiffness Distribution (Full Scale)

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Figure 7.7 – Updated Static Aero Factors

Figure 7.8 – Pre-Holiday Flutter Test Results Alpha=-3 

-1500

-1000

-500

0

500

1000

1500

2000

0 10 20 30 40 50 60 70 80

Bending Moment (in-lb)

Dynamic Pressure

 

Scaled Test Results AOA -3

Analysis AOA -3 Baseline Aero Factors

Analysis AOA -3 Updated Aero Factors

Scaled Test Results AOA -1

Analysis AOA -1 Baseline Aero Factors

Analysis AOA -1 Updated Aero Factors

Mach = .7

10

100

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3

Mach Number, M

 

8 MW

20

30

40

50

60

70

80

90 6 MW

4 MW

Motor Speed = 235 RPM

Vane Angle = 18 Degrees

H=50 PSF

75

 

100

150

200

300

1

Dynamic Pressure, Q, PSF

 

 

 

 

Stable

Unstable

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Figure 7.9 – Pre-Holiday Flutter Test Results Alpha = -1 

Figure 7.10 – Pre-Holiday Flutter Test Results Alpha = +1

10

100

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3

Mach Number, M

8 MW

20

30

40

50

60

70

80

90 6 MW

4 MW

Motor Speed = 235 RPM

Vane Angle = 18 Degrees

H=50 PSF

75

100

150

200

300

Stable

Unstable

1

Dynamic Pressure, Q, PSF

 

 

 

 

10

100

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3

Mach Number, M

 

 

8 MW

20

30

40

50

60

70

80

90 6 MW

4 MW

Motor Speed = 235 RPM

Vane Angle = 18 Degrees

H=50 PSF

75

 

100

150

200

300

Stable

Unstable

1

Dynamic Pressure, Q, PSF

 

 

 

 

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Figure 7.11 – Pre-Holiday Flutter Test Results Alpha = +3

10

100

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3

Mach Number, M

8 MW

20

30

40

50

60

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80

90 6 MW

4 MW

Motor Speed = 235 RPM

Vane Angle = 18 Degrees

H=50 PSF

75

100

150

200

300

Stable

Unstable

1

Dynamic Pressure, Q, PSF

 

 

 

 

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Figure 7.12 – Pre-Holiday Unstable Points

Figure 7.13 – Preload and Large Displacement Flutter

0

20

40

60

80

100

120

0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85

Flutter Dynamic Pressure (PSF)

Mach

Test Data -3 AOA

Test Data -1 AOA

Test Data 1 AOA

Test Data 3 AOA

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Figure 7.14 – Pre-Holiday Test vs Analysis

Figure 7.15 – Post-Holiday Flutter Results Alpha –3 

0

20

40

60

80

100

120

0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85

Flutter Dynamic Pressure (PSF)

Mach

Test Data -3 AOA

Test Data -1 AOA

Test Data 1 AOA

Test Data 3 AOA

v19 FEM No Preload No Large Disp

v19 FEM Preload + Large Disp -3 AOA

v19 FEM Preload + Large Disp -1 AOA

v19 FEM Preload + Large Disp -3 AOA Updated Steady Aero Corrections

v19 FEM Preload + Large Disp -1 AOA Updated Steady Aero Corrections

v19 FEM Preload + Large Disp +1 AOA Updated Steady Aero Correction

V19 FEM Preload + Large Disp +3 AOA Updated Steady Aero Corrections

No UnsteadyAero Corrections

10

100

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3

Mach Number, M

 

8 MW

20

30

40

50

60

70

80

90 6 MW

4 MW

Motor Speed = 235 RPM

Vane Angle = 18 Degrees

H=50 PSF

75

 

100

150

200

300

1

Dynamic Pressure, Q, PSF

 

 

 

 

Stable

Unstable

Estimated Flutter Boundary

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Figure 7.16 – Post-Holiday Flutter Results Alpha = -1 

Figure 7.17 – Post-Holiday Flutter Results Alpha = +1

10

100

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3

Mach Number, M

8 MW

20

30

40

50

60

70

80

90 6 MW

4 MW

Motor Speed = 235 RPM

Vane Angle = 18 Degrees

H=50 PSF

75

100

150

200

300

Stable

Unstable

Estimated Flutter Boundary

1

Dynamic Pressure, Q, PSF

 

 

 

 

10

100

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3

Mach Number, M

 

8 MW

20

30

40

50

60

70

80

90 6 MW

4 MW

Motor Speed = 235 RPM

Vane Angle = 18 Degrees

H=50 PSF

75

 

100

150

200

300

Stable

Unstable

Estimated Flutter Boundary

1

Dynamic Pressure, Q, PSF

 

 

 

 

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Figure 7.18 – Post-Holiday Flutter Results Alpha = +3

Figure 7.19 – Pre-Holiday vs Post holiday Test Results

10

100

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3

Mach Number, M

8 MW

20

30

40

50

60

70

80

90 6 MW

4 MW

Motor Speed = 235 RPM

Vane Angle = 18 Degrees

H=50 PSF

75

100

150

200

300

Stable

Unstable

Estimated Flutter Boundary

1

Dynamic Pressure, Q, PSF

 

 

 

 

0

20

40

60

80

100

120

0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85

Dynamic Pressure (PSF)

Mach

Pre Holiday Alpha = -3

Pre Holiday Alpha = -1

Pre Holiday Alpha = 1

Pre Holiday Alpha = 3

Post Holiday Alpha = -3

Post Holiday Alpha = -1

Post Holiday Alpha = 1

Post Holiday Alpha = 3

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Figure 7.20 – Post Test Analysis vs Test

Figure 7.21 – Post-Holidays RMS Results Alpha = -3 

0

20

40

60

80

100

120

0.68 0.7 0.72 0.74 0.76 0.78 0.8 0.82 0.84

Dynamic Pressure (PSF)

Mach

Post Holidays Test Alpha = -3

Post Holidays Test Alpha = -1

Post Holidays Test Alpha = 1

Post Holidays Test Alpha = 3

FEM 20 Analysis Alpha = -3

FEM 20 Analysis Alpha = -1

FEM 20 Analysis Alpha = 1

FEM 20 Analysis Alpha = 3

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Figure 7.22 – Post-Holidays RMS Results Alpha = -1 

Figure 7.23 – Post-Holidays RMS Results Alpha = +1

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Figure 7.24 – Post-Holidays RMS Results Alpha = +3

Figure 7.25 – Run 44 Tab Point 2007 Dwell Time History Data

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Figure 7.26 – Run 44 Tab Point 2007 Decay Time History

Figure 7.27 – Run 44 Tab Point 2007 FFT

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Figure 7.28 – Run 44 Tab Point 2007 3 Sine Wave Fit of Decay Time History

Figure 7.29 – Run 44 Tab Point 2007 3 Sine Wave Fit Results

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Figure 7.30 – Run 44 Tab Point 2007 3 Sine Wave Fit GUI

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Table 7.2 – Sine Wave Fit Results for AOA = -3 degrees

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Table 7.3 – Sine Wave Fit Results for AOA = -2 and -1 degrees

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Table 7.4 – Sine Wave Fit Results for AOA = 0 and 1 degrees

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Table 7.5 – Sine Wave Fit Results for AOA = +2 and +3 degrees

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Figure 7.31 – Dwell Frequency and Damping Estimates Alpha = -3 degrees

Figure 7.32 – Dwell Frequency and Damping Estimates Alpha = -2 & -1 degrees

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Figure 7.33 – Dwell Frequency and Damping Estimates Alpha = 0 & +1 degrees

Figure 7.34 – Dwell Frequency and Damping Estimates Alpha = 0 & +1 degrees

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Figure 7.35 – Post-Holiday Closed Loop Stable Alpha = -3 

Figure 7.36 – Post-Holiday Closed Loop Stable Alpha = -1 

10

100

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3

Mach Number, M

8 MW

20

30

40

50

60

70

80

90 6 MW

4 MW

Motor Speed = 235 RPM

Vane Angle = 18 Degrees

H=50 PSF

75

100

150

200

300

400

1

Dynamic Pressure, Q, PSF

 

 

 

Stable

Unstable

Estimated Flutter Boundary

Closed Loop Stable

10

100

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3

Mach Number, M

 

8 MW

20

30

40

50

60

70

80

90 6 MW

4 MW

Motor Speed = 235 RPM

Vane Angle = 18 Degrees

H=50 PSF

75

 

100

150

200

300

1

Dynamic Pressure, Q, PSF

 

 

 

 

 

Stable

Unstable

Estimated Flutter Boundary

Closed Loop Stable

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Figure 7.37 – Post-Holiday Closed Loop Stable Alpha = +1

Figure 7.38 – Post-Holiday Closed Loop Stable Alpha = +3

10

100

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3

Mach Number, M

8 MW

20

30

40

50

60

70

80

90 6 MW

4 MW

Motor Speed = 235 RPM

Vane Angle = 18 Degrees

H=50 PSF

75

100

150

200

300

1

Dynamic Pressure, Q, PSF

 

 

 

Stable

Unstable

Estimated Flutter Boundary

Closed Loop Stable

10

100

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3

Mach Number, M

 

8 MW

20

30

40

50

60

70

80

90 6 MW

4 MW

Motor Speed = 235 RPM

Vane Angle = 18 Degrees

H=50 PSF

75

 

100

150

200

300

1

Dynamic Pressure, Q, PSF

 

 

 

 

Stable

Unstable

Estimated Flutter Boundary

Closed Loop Stable

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Figure 7.39 – Gust Response RMS Mach = 0.65 Q = 50 Alpha = -3 

Figure 7.40 – Gust Response RMS Mach = 0.7, Q = 57, Alpha = -3 

First Bending

Second Bending

First Bending

Second Bending

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Figure 7.41 – Gust Response RMS Mach = 0.75, Q=64, Alpha = -3 

Figure 7.42 – Gust Response RMS Mach = 0.75, Q = 64, Alpha = -1 

First Bending

Second 

Bending

First Bending

Second 

Bending

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Figure 7.43 – Gust Response RMS Mach = 0.75, Q = 64, Alpha = +1

Figure 7.44 – Gust Response RMS Mach = 0.75, Q = 64, Alpha = +3

First Bending

Second 

Bending

First Bending

Second 

Bending

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8.0 Conclusions

1. Analysis accurately predicted the flutter mechanism would be a coalescence of Mode 3 

and Mode 4 at around 10 Hz. 

2. Flutter results showed significant variation with different angles of attack. This appears 

to be a characteristic of the TBW configuration. Angle of attack variations are modeled 

fairly accurately using a non linear method which accounts for preload and large 

displacement effects.

3. The analysis using theoretical doublet lattice aerodynamics didn’t produce the observed 

sharp decrease in flutter speed with Mach but was fairly accurate in predicting 

minimum flutter speed. These predictions may not be accurate for different TBW 

vehicle geometries and/or aerodynamic configurations. 

4. No evidence was found of strut buffet causing vibration problems.

5. Flutter suppression was successfully demonstrated using control laws derived from test 

system ID data and analysis models.

6. Even though the control laws were designed for flutter suppression, the control laws do 

provide some gust load alleviation as well. 

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References

1. Development of Framework for Truss-Braced Wing Conceptual MDO. Gur, O., et al., et al.

Orlando : 51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials 

Conference, April 12-15 2010. AIAA-2010-2754.

2. Niu, C. Y. Michael. Airframe Structural Design: Practical Design Information and Data On 

Aircraft Structures. s.l. : Adaso Adastra Engineering Center, 1999. 9627128090.

3. Federal Aviation Administration. Electronic Code of Federal Regulations. Government 

Printing Office. [Online] January 11, 2012. [Cited: January 13, 2012.] 

http://ecfr.gpoaccess.gov/cgi/t/text/textidx?c=ecfr&sid=96784884300b9846bc7a9ce5f552f5d3&tpl=/ecfrbrowse/Title14/14cfr25_main

_02.tpl. Part 25.

4. Bradley, Marty K. and Droney, Christopher K. Subsonic Ultra Green Aircraft Research: Phase I 

Final Report. s.l. : NASA, 2011. CR-2011-216847.

76
REPORT DOCUMENTATION PAGE Form Approved

OMB No. 0704-0188

2. REPORT TYPE 

Contractor Report

 4. TITLE AND SUBTITLE

Subsonic Ultra Green Aircraft Research: Phase II – Volume III – Truss 

Braced Wing Aeroelastic Test Report

5a. CONTRACT NUMBER

NNL08AA16B

 6. AUTHOR(S)

Bradley, Marty K.; Allen, Timothy J.; Droney, Christopher K.

 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

 

The Boeing Company 5301 Bolsa Ave, MC H017-D334 

Huntington Beach, California 92647-2099

 

 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)

National Aeronautics and Space Administration

Washington, DC 20546-0001

 8. PERFORMING ORGANIZATION

 REPORT NUMBER

10. SPONSOR/MONITOR'S ACRONYM(S)

NASA

13. SUPPLEMENTARY NOTES

Test Report

Langley Technical Monitor: Erik D. Olson

12. DISTRIBUTION/AVAILABILITY STATEMENT

Unclassified - Unlimited

Subject Category 05

Availability: NASA STI Program (757) 864-9658

19a. NAME OF RESPONSIBLE PERSON

STI Help Desk (email: help@sti.nasa.gov)

14. ABSTRACT

This Test Report summarizes the Truss Braced Wing (TBW) Aeroelastic Test work accomplished by the Boeing Subsonic Ultra Green Aircraft Research 

(SUGAR) team, consisting of Boeing Research and Technology, Boeing Commercial Airplanes, Virginia Tech, and NextGen Aeronautics. The model was 

fabricated by NextGen Aeronautics and designed to meet dynamically scaled requirements from the sized full scale TBW FEM. The test of the dynamically 

scaled SUGAR TBW half model was broken up into open loop testing in December 2013 and closed loop testing from January 2014 to April 2014. Results 

showed the flutter mechanism to primarily be a coalescence of 2nd bending mode and 1st torsion mode around 10 Hz, as predicted by analysis. Results also 

showed significant change in flutter speed as angle of attack was varied. This non-linear behavior can be explained by including preload and large 

displacement changes to the structural stiffness and mass matrices in the flutter analysis. Control laws derived from both test system ID and FEM19 state space 

models were successful in suppressing flutter. The control laws were robust and suppressed flutter for a variety of Mach, dynamic pressures, and angle of 

attacks investigated. 

15. SUBJECT TERMS

Aerodynamics; Aeroelastic testing; Control law; Dynamic scaling; Finite-element analysis; Flutter suppression; Ground 

vibration testing; Non-linear flutter; State space; System identification

18. NUMBER

 OF 

 PAGES

87

19b. TELEPHONE NUMBER (Include area code)

(757) 864-9658

a. REPORT

U

c. THIS PAGE

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b. ABSTRACT

U

17. LIMITATION OF 

 ABSTRACT

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Prescribed by ANSI Std. Z39.18

Standard Form 298 (Rev. 8-98)

3. DATES COVERED (From - To)

February 2012 - June 2014

5b. GRANT NUMBER

5c. PROGRAM ELEMENT NUMBER

5d. PROJECT NUMBER

5e. TASK NUMBER

NNL11AA00T

5f. WORK UNIT NUMBER

081876.01.07.02 

11. SPONSOR/MONITOR'S REPORT

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NASA/CR-2015-218704/Volume III

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