Computational Aeroelastic Analysis of the Semi-Span Super-Sonic Transport (S4T) Wind-Tunnel Model

Sanetrik, Mark D.; Silva, Walter A.; Hur, Jiyoung

doi:10.2514/6.2012-1556

Cited by 3 publications

(4 citation statements)

References 5 publications

(8 reference statements)

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“…The analytical and measured frequencies and descriptions of the mode shapes are shown in Table 1. 38 Comparisons of the analytical and measured frequencies give indications of the success level of the stiffness tuning exercise. The scatter among the measured values for each modal frequency also provides an indication of the variation associated with measuring the frequencies.…”

Section: A Hardware Characterization Testingmentioning

confidence: 99%

“…The FEM utilized in this study for the baseline analysis cases is the unmodified model from the S 4 T team that is detailed by Sanetrik. 38 The FEM elements, emphasizing the fuselage, are shown in Figures 3, 4 and 5. Figure 5 in particular shows the flexible fuselage beam material property segments that will be modified as part of the uncertainty propagation studies.…”

Section: B Structural Modelmentioning

confidence: 99%

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Aeroelastic Uncertainty Quantification Studies Using the S4T Wind Tunnel Model

Nikbay

Heeg

2017

55th AIAA Aerospace Sciences Meeting

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This paper originates from the joint efforts of an aeroelastic study team in the Applied Vehicle Technology Panel from NATO Science and Technology Organization, with the Task Group number AVT-191, titled "Application of Sensitivity Analysis and Uncertainty Quantification to Military Vehicle Design." We present aeroelastic uncertainty quantification studies using the SemiSpan Supersonic Transport wind tunnel model at the NASA Langley Research Center. The aeroelastic study team decided treat both structural and aerodynamic input parameters as uncertain and represent them as samples drawn from statistical distributions, propagating them through aeroelastic analysis frameworks. Uncertainty quantification processes require many function evaluations to asses the impact of variations in numerous parameters on the vehicle characteristics, rapidly increasing the computational time requirement relative to that required to assess a system deterministically. The increased computational time is particularly prohibitive if high-fidelity analyses are employed. As a remedy, the Istanbul Technical University team employed an Euler solver in an aeroelastic analysis framework, and implemented reduced order modeling with Polynomial Chaos Expansion and Proper Orthogonal Decomposition to perform the uncertainty propagation. The NASA team chose to reduce the prohibitive computational time by employing linear solution processes. The NASA team also focused on determining input sample distributions.

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Section: A Hardware Characterization Testingmentioning

confidence: 99%

Section: B Structural Modelmentioning

confidence: 99%

Aeroelastic Uncertainty Quantification Studies Using the S4T Wind Tunnel Model

Nikbay

Heeg

2017

55th AIAA Aerospace Sciences Meeting

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“…The amplitude of the excitation can also be varied to assess the impact on the signal-to-noise ratio. Under the S4T program, reduced order models using non-linear CFD codes are being developed 20 . These models can be implemented in the simulation and investigated using CPE and compared with the experimental test results.…”

Section: Future Workmentioning

confidence: 99%

Analytical and Experimental Evaluation of Digital Control Systems for the Semi-Span Super-Sonic Transport (S4T) Project

Wieseman¹,

Christhilf²,

Perry³

2012

53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference

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An important objective of the Semi-Span Super-Sonic Transport (S 4 T) wind tunnel model program was the demonstration of Flutter Suppression (FS), Gust Load Alleviation (GLA), and Ride Quality Enhancement (RQE). It was critical to evaluate the stability and robustness of these control laws analytically before testing them and experimentally while testing them to ensure safety of the model and the wind tunnel. MATLAB based software was applied to evaluate the performance of closed-loop systems in terms of stability and robustness. Existing software tools were extended to use analytical representations of the S 4 T and the control laws to analyze and evaluate the control laws prior to testing. Lessons were learned about the complex windtunnel model and experimental testing. The open-loop flutter boundary was determined from the closed-loop systems. A MATLAB/Simulink Simulation developed under the program is available for future work to improve the CPE process. This paper is one of a series of that comprise a special session, which summarizes the S 4 T wind-tunnel program. Nomenclature CLO = control law output CPE = controller performance evaluation FRF = frequency response function or frequency responses det = determinant G = open-loop plant FLAP = wing trailing edge control surface FLAPCOM = command to FLAP FLAPEXC = excitation to FLAP HT = horizontal tail HTCOM = command to HT HTEXC = excitation to HT IBMID15I = accelerometer located on the inboard middle section of the wing LTI = linear time invariant state-space representation of a system. MIMO = multi-input multi-output NIBAFTZ = nacelle inboard aft accelerometer in the z direction ! = dynamic pressure, psf RCV = ride control vane SISO = single-input single-output ! ! = time history of ith excitation to control surface ! ! = time history of ith control law output ! ! = time history of ith plant output ! ! = matrix of frequency responses of control law outputs to excitations ! ! = matrix of frequency responses of plant outputs to excitations σ = singular value Subscripts f = flutter

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“…7 The state-space plant models were generated using a NASTRAN structural Finite Element Model (FEM) as well as several methods for calculating the unsteady Generalized Aerodynamic Forces (GAF's). [8][9][10] For some of the models, modifications were made to the FEM to adjust wind-off frequencies to better match S 4 T experimental data. 11 These linear state-space models were used for control law design.…”

Section: Flap Rcv Htmentioning
confidence: 99%

Characteristics of Control Laws Tested on the Semi-Span Super-Sonic Transport (S4T) Wind-Tunnel Model
Christhilf¹,
Moulin²,
Ritz³
et al. 2012
53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
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Computational Aeroelastic Analysis of the Semi-Span Super-Sonic Transport (S4T) Wind-Tunnel Model

Cited by 3 publications

References 5 publications

Aeroelastic Uncertainty Quantification Studies Using the S4T Wind Tunnel Model

Aeroelastic Uncertainty Quantification Studies Using the S4T Wind Tunnel Model

Analytical and Experimental Evaluation of Digital Control Systems for the Semi-Span Super-Sonic Transport (S4T) Project

Characteristics of Control Laws Tested on the Semi-Span Super-Sonic Transport (S4T) Wind-Tunnel Model

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