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solution, Thomas is able to show LCO amplitude and stability characteristics that correlate reasonably well with flight test results. Neural Networks Johnson 42-46 investigates the use of artificial neural networks (ANN) to model aircraft LCO behavior. The initial neural network designs perform well in predicting amplitude and frequency over a range of Mach numbers for the flutter and typical LCO type configurations. However they do not predict the decreasing amplitude character that the non-typical LCO cases exhibit at higher Mach numbers. Dawson 47-49 evaluates subsequent neural network designs utilizing an analytical eigenvector descriptor feature attempting to improve the predictive capability with respect to non-typical LCO predictions. This network design performs well in predicting the LCO amplitudes of all types of aeroelastic conditions, including non-typical LCO. CFD-FASTRAN The Air Force SEEK EAGLE Office (AFSEO) explores the commercial CFD Fluid- structure Interaction (FSI) solver, CFD-FASTRAN. 50 AFSEO attempts to show that CFD- FASTRAN can accurately run a transient-aeroelastic F-16 wing and launcher case joined by overset grids. The grids are created and successfully used by CFD-FASTRAN in steady cases, but the results still need to be confirmed. AFSEO is unable to validate ESI Group’s ability to run transient aeroelastic problems. CAP-TSD Batina 51-60 uses a transonic small-disturbance approach to investigate a full-span F-16 aircraft with a clean-wing (no stores/pylons/launchers) configuration. He examines steady flow conditions as well as rigid-body pitch oscillations of the entire aircraft and shows that the transonic small-disturbance theory provided a viable solution for aeroelastic applications on fighter aircraft. Haller 61 accomplishes further transonic small-disturbance evaluations based on 32
Batina’s work and uses an F-16 half-span model with the Computational Aeroelasticity Program Transonic Small-Disturbance (CAP-TSD). He examines steady flow solutions and compares these to wind-tunnel test results. 62 Pitt 63 applies the CAP-TSD approach to transonic flutter analysis of the F-15 and F/A-18. Denegri 64,65 applies the medium-fidelity time-domain computational physics approach of CAP-TSD to LCO prediction and extends the steady CAP-TSD analysis of Batina and Haller and the transonic flutter analysis of Pitt by examining a typical F-16 LCO test case. 23,24 Discrepancies between the aerodynamic model and the wind tunnel and CFD results are noted and may be the primary causes of the observed differences between the aeroelastic computational and flight test results. Denegri continues to apply the CAP-TSD approach in the Medium-Fidelity Flutter Analysis Tool (MEDFFAT). 66 MEDFFAT overcomes the linear transonic physics limitations of current commercial off-the-shelf (COTS) software by automatically generating transonic computational grids for the aircraft and its stores based on a single linear panel model, solving the nonlinear aeroelastic equations, and interpolating the solutions between the aircraft and stores grids. NONLINAE Cunningham develops NONLINAE, a semi-empirical method for LCO prediction based on his observation of shock induced trailing edge separation (SITES) during LCO wind tunnel testing. 67-72 He shows that nonlinear aerodynamic forces arising from SITES are a dominant mechanism in transonic LCO. He investigates several transonic LCO cases and demonstrates success with an analytical approach, NONLINAE, which uses both steady and unsteady wind- tunnel data for the aerodynamic forces and a linear dynamics model for the structural motions. His time lag-based model shows good correlation to test results for configurations that exhibit 33
Page 1 and 2: TEMPORAL ANALYSIS OF TRANSONIC FLOW
Page 3 and 4: To Dodjie 3
Page 5 and 6: TABLE OF CONTENTS ACKNOWLEDGMENTS .
Page 7 and 8: Summary ...........................
Page 9 and 10: LIST OF FIGURES Figure page 2-1 F-1
Page 11 and 12: 6-9 Lissajous plots of upper surfac
Page 13 and 14: 6-45 2-D (left column) and 3-D (rig
Page 15 and 16: incrementally since this capability
Page 17 and 18: are not sufficient to provide an an
Page 19 and 20: 4. Contribute to the work of others
Page 21 and 22: Classical aircraft flutter is chara
Page 23 and 24: Popular methods for finding the sol
Page 25 and 26: LCO amplitude but not the mechanism
Page 27 and 28: speed for the particular configurat
Page 29 and 30: Denegri 23 explains the flutter fli
Page 31: Doublet-lattice Denegri 1, 7,12,13
Page 35 and 36: As a result of Denegri’s previous
Page 37 and 38: Figure 2-1. F-16 store stations. Fi
Page 39 and 40: Figure 2-5. Flutter flight test bui
Page 41 and 42: Stokes (RANS) equations on hybrid u
Page 43 and 44: CHAPTER 4 ANALYSIS TECHNIQUES Intro
Page 45 and 46: time-localization cannot be determi
Page 47 and 48: A B C D E Figure 4-3. Analysis of s
Page 49 and 50: (CFD) analyses in order to capture
Page 51 and 52: the appropriate time step for the n
Page 53 and 54: Wing1, is the wing-only (no fuselag
Page 55 and 56: similar to DES but with modificatio
Page 57 and 58: Figure 5-1. Time step comparison of
Page 59 and 60: A B Figure 5-3. Flow results for 8
Page 61 and 62: A B Figure 5-5. Flow results for 8
Page 63 and 64: Figure 5-7. Turbulence model compar
Page 65 and 66: Figure 5-9. CFD vs. wind tunnel com
Page 67 and 68: Figure 5-11. CFD vs. wind tunnel co
Page 69 and 70: Figure 5-13. CFD vs. wind tunnel co
Page 71 and 72: server cluster comprised of 5,120 p
Page 73 and 74: of oscillation. The 88% span locati
Page 75 and 76: since it is proportional to lift, a
Page 77 and 78: of phase. Figure 6-10 B) and D) are
Page 79 and 80: The instantaneous Cp measurements p
Page 81 and 82: D Lissajous plots with time being t
Page 83 and 84:
frequency of 8Hz. The wavelet plot
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vortex is observed travelling outbo
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near 70% chord and the second near
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expected from a lift curve slope. A
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shape of this Lissajous is nonlinea
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occurring at harmonics, and assumes
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the same direction of rotation on t
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the roll cycle, and the black arrow
Page 99 and 100:
B) shows the fast Fourier transform
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is that shock separation aft of the
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on the upper surface, a much larger
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Figure 6-1. F-16 wing planform with
Page 107 and 108:
A C B Figure 6-4. DDES of F-16 in s
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Cp (Non-dimensional) Cp (Non-dimens
Page 111 and 112:
-Cp (Non-dimensional) A -Cp (Non-di
Page 113 and 114:
Page 115 and 116:
-Cp (Non-dimensional) A Time (sec)
Page 117 and 118:
A B Figure 6-14. DDES-SARC of F-16
Page 119 and 120:
Page 121 and 122:
Figure 6-18. Lissajous plots of upp
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-Cp (Non-dimensional) Frequency (Hz
Page 125 and 126:
-Cp (Non-dimensional) A Frequency (
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Page 129 and 130:
Page 131 and 132:
Page 133 and 134:
Page 135 and 136:
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Page 141 and 142:
Page 143 and 144:
A B D Figure 6-40. DDES of F-16 in
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Page 147 and 148:
Page 149 and 150:
Page 151 and 152:
Page 153 and 154:
Page 155 and 156:
Page 157 and 158:
Impact on Future Design of Aircraft
Page 159 and 160:
The size of the Mach=1 iso-surface
Page 161 and 162:
these cases in order to identify th
Page 163 and 164:
15. Dawson, K. S., and Sussinham, J
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41. Thomas, J. P., Dowell, E. H., a
Page 167 and 168:
67. Cunningham, A. M., Jr., and den
Page 169 and 170:
93. Parker, G. H., Maple, R. C., an
Page 171 and 172:
121. Travin, A. K., Shur, M. L., Sp
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