Hostname: page-component-68945f75b7-qf55q Total loading time: 0 Render date: 2024-08-06T08:38:33.463Z Has data issue: false hasContentIssue false
  • English
  • Français

Impact of actuation and sensor measurement delays on stability of real-time hybrid aeroelastic simulation system

Published online by Cambridge University Press:  11 July 2024

W. Su Open the ORCID record for W. Su [Opens in a new window]  and
W. Song Open the ORCID record for W. Song [Opens in a new window]
W. Su*
Affiliation:
Department of Aerospace Engineering and Mechanics, The University of Alabama, Tuscaloosa, AL, USA
W. Song
Affiliation:
Department of Civil, Construction and Environmental Engineering, The University of Alabama, Tuscaloosa, AL, USA
*
Corresponding author: W. Su; Email: suw@eng.ua.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper is focused on the stability of real-time hybrid aeroelastic simulation systems for flexible wings. In a hybrid aeroelastic simulation, a coupled aeroelastic system is ‘broken down’ into an aerodynamic simulation subsystem and a structural vibration testing subsystem. The coupling between structural dynamics and aerodynamics is achieved by real-time communication between the two subsystems. Real-time hybrid aeroelastic simulations can address the limitations associated with conventional aeroelastic testing performed within a wind tunnel or with pure computational aeroelastic simulation. However, as the coupling between structural dynamics and aerodynamics is completed through the real-time actuation and sensor measurement, their delays may inherently impact the performance of hybrid simulation system and subsequently alter the measured aeroelastic stability characteristics of the flexible wings. This study aims to quantify the impact of actuation and sensor measurement delays on the measured aeroelastic stability, e.g. the flutter boundary, of flexible wings during real-time hybrid simulations, especially when different aerodynamic models are implemented.

Keywords

aeroelastic systemreal-time hybrid simulationstabilityactuation delaysensor measurement delay
Type
Research Article
Information
The Aeronautical Journal , First View , pp. 1 - 16
Check for updates
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Royal Aeronautical Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Samani, I. and Hixon, R. An improved method for mean flow boundary conditions for computational aeroacoustics. Aerosp. Sci. Technol., 2020, 105, art. 106012. doi: 10.1016/j.ast.2020.106012 CrossRefGoogle Scholar
Neves, A.F., Lawson, N.J., Bennett, C.J., Khanal, B. and Hoff, R.I. Unsteady aerodynamics analysis and modelling of a Slingsby firefly aircraft: detached-eddy simulation model and flight test validation. Aerosp. Sci. Technol., 2020, 106, art. 106179. doi: 10.1016/j.ast.2020.106179 CrossRefGoogle Scholar
Eugeni, M., Saltari, F. and Mastroddi, F. Structural Damping Models for Passive Aeroelastic Control. Aerosp. Sci. Technol., 2021, 118, art. 107011. doi: 10.1016/j.ast.2021.107011 CrossRefGoogle Scholar
Chen, P.-C., Zhang, Z., Zhou, Z., Wang, X.Q. and Mignolet, M.P. Nonlinear structural damping effects on F-16 limit cycle oscillations. AIAA 2018 SciTech Forum, 2018, AIAA-2018-2064.Google Scholar
Glaessgen, E.H., Reeder, J.R., Sleight, D.W., Wang, J.T., Raju, I.S. and Harris, C.E. Debonding failure of a sandwich-composite cryogenic fuel tank with internal core pressure. J. Spacecraft Rockets, 2005, 42, (4), pp 613–627. doi: 10.2514/1.5567 CrossRefGoogle Scholar
Raju, I.S., Murthy, P.L.N., Patel, N.R., et al. Best practices for reliable and robust spacecraft structures. In 48th AIAA ASME ASCE AHS ASC Structures, Structural Dynamics, and Materials Conference, Honolulu, HI, 2007, AIAA-2007-2270.CrossRefGoogle Scholar
Bushnell, D.M. Scaling: wind tunnel to flight. Annu. Rev. Fluid Mech., 2006, 38, pp 111–128. doi: 10.1146/annurev.fluid.38.050304.092208 CrossRefGoogle Scholar
Katz, J. and Plotkin, A. Low-Speed Aerodynamics, 2nd ed., Cambridge Aerospace Series, New York, NY, USA: Cambridge University Press, 2001. ISBN: 978-0-521-66219-2.CrossRefGoogle Scholar
Wan, Z. and Cesnik, C.E.S. Geometrically nonlinear aeroelastic scaling for very flexible aircraft. AIAA J., 2014, 52, (10), pp 2251–2260. doi: 10.2514/1.J052855 CrossRefGoogle Scholar
Anders, J.B., Anderson, W.K. and Murthy, A.V. The use of heavy gas for increased reynolds numbers in transonic wind tunnels. In 20th AIAA Advanced Measurement and Ground Testing Technology Conference, Albuquerque, NM, 1998, AIAA-1998-2882.CrossRefGoogle Scholar
Hackett, J.E. and Cooper, K.R. Extensions to Maskell’s theory for blockage effects on bluff bodies in a closed wind tunnel. Aeronaut. J., 2001, 16105, (1050), pp 409–418. doi: 10.1017/S0001924000012380 CrossRefGoogle Scholar
Belligoli, Z., Dwight, R.P. and Eitelberg, G. Nonlinear wind-tunnel wall-interference corrections using data assimilation. AIAA J., 2021, 59, (2), pp 596–606. doi: 10.2514/1.J059558 CrossRefGoogle Scholar
Bertram, A., Hoffmann, N., Goertz, S., Gebbink, R. and Janssen, S.R. An alternative wind tunnel data correction based on CFD and experimental data in the transonic flow regime. AIAA Aviation 2021 Forum, 2021, AIAA-2021-2982.CrossRefGoogle Scholar
Boria, F., Stanford, B., Bowman, S. and Ifju, P. Evolutionary optimization of a morphing wing with wind-tunnel hardware in the loop. AIAA J., 2009, 47, (2), pp 399–409. doi: 10.2514/1.38941 CrossRefGoogle Scholar
Bradley, T.H., Moffitt, B.A., Mavris, D.N., Fuller, T.F. and Parekh, D.E. Hardware-in-the-loop testing of a fuel cell aircraft powerplant. J. Propul. Power, 2009, 25, (6), pp 1336–1344. doi: 10.2514/1.40805.CrossRefGoogle Scholar
Strub, G., Theodoulis, S., Gassmann, V., Dobre, S. and Basset, M. Pitch axis control for a guided projectile in a wind tunnel hardware-in-the-loop setup. J. Spacecr. Rockets, 2015, 52, (6), pp 1614–1626. doi: 10.2514/1.A33330 CrossRefGoogle Scholar
Zappulla, R. II, Virgili-Llop, J., Zagaris, C., Park, H. and Romano, M. Dynamic air-bearing hardware-in-the-loop testbed to experimentally evaluate autonomous spacecraft proximity maneuvers. J. Spacecr. Rockets, 2017, 54, (4), pp 825–839. doi: 10.2514/1.A33769 CrossRefGoogle Scholar
Waszniowski, L., Hanzálek, Z. and Doubrava, J. Aircraft control system validation via hardware-in-the loop simulation. J. Aircr., 2011, 48, (4), pp 1466–1468. doi: 10.2514/1.C031229 CrossRefGoogle Scholar
Elston, J., Argrow, B., Frew, E., Houston, A. and Straka, J. Evaluation of unmanned aircraft systems for severe storm sampling using hardware-in-the-loop simulations. J. Aerosp. Comput. Inf. Commun., 2011, 8, (9), pp 269–294. doi: 10.2514/1.53737 CrossRefGoogle Scholar
Goppert, J., Shull, A., Sathyamoorthy, N., Liu, W., Hwang, I. and Aldridge, H. Software hardware-in-the-loop analysis of cyberattacks on unmanned aerial systems. J. Aerosp. Inf. Syst., 2014, 11, (5), pp 337–343. doi: 10.2514/1.I010114 Google Scholar
Patel, A.V., Patel, V.V., Deodhare, G. and Chetty, S. Clearance of flight-control-system software with hardware-in-loop test platform. J. Aircr., 2014, 51, (3), pp 748–760. doi: 10.2514/1.C032404 CrossRefGoogle Scholar
Fritz, M., Winter, S., Freund, J., Pflueger, S., Zeile, O., Eickhoff, J., and Roeser, H.-P. Hardware-in-the-loop environment for verification of a small satellite’s on-board software. Aerosp. Sci. Technol., 2015, 47, pp. 388–395. doi: 10.1016/j.ast.2015.09.020 CrossRefGoogle Scholar
Mahin, S.A. and Shing, P.B. Pseudodynamic method for seismic testing. J. Struct. Eng., 1985, 111, (7), pp 1482–1503. doi: 10.1061/(ASCE)0733-9445(1985)111:7(1482)CrossRefGoogle Scholar
Nakashima, M., Kato, H. and Takaoka, E. Development of real-time pseudo dynamic testing. Earthquake Eng. Struct. Dyn., 1992, 21, (1), pp 79–92. doi: 10.1002/eqe.4290210106 CrossRefGoogle Scholar
Shing, P.B., Bursi, O.S. and Vannan, M.T. Pseudodynamic tests of a concentrically braced frame using substructuring techniques. J. Constr. Steel Res., 1994, 29, (1–3), pp 121–148. doi: 10.1016/0143-974X(94)90059-0 CrossRefGoogle Scholar
Su, W. and Song, W. A real-time hybrid aeroelastic simulation platform for flexible wings. Aerosp. Sci. Technol., 2019, 95, art. 105513. doi: 10.1016/j.ast.2019.105513 CrossRefGoogle Scholar
Maghareh, A., Dyke, S.J., Prakash, A. and Rhoads, J.F. Establishing a stability switch criterion for effective implementation of real-time hybrid simulation. Smart Struct. Syst., 2014, 14, (6), pp 1221–1245. doi: 10.12989/SSS.2014.14.6.1221 CrossRefGoogle Scholar
Hayati, S. and Song, W. An optimal discrete-time Feedforward compensator for real-time hybrid simulation. Smart Struct. Syst., 2017, 20, pp 483–498. doi: 10.1007/978-3-319-54777-0_27 Google Scholar
Hayati, S. and Song, W. Design and performance evaluation of an optimal discrete-time Feedforward controller for servo-hydraulic compensation. J. Eng. Mech., 2018, 144, art. 04017163. doi: 10.1061/(ASCE)EM.1943-7889.0001399 CrossRefGoogle Scholar
Chen, C. and Ricles, J.M. Analysis of actuator delay compensation methods for real-time testing. Eng. Struct., 2009, 31, (11), pp 2643–2655. doi: 10.1016/j.engstruct.2009.06.012 CrossRefGoogle Scholar
Peters, D.A. and Johnson, M.J. Finite-state airloads for deformable airfoils on fixed and rotating wings. In Symposium on Aeroelasticity and Fluid Structure Interaction, ASME Winter Annual Meeting, AD-44, edited by Friedmann, P.P. and Chang, J.C.I.. New York, NY: American Society of Mechanical Engineers, 1994, pp 1–28.Google Scholar
Peters, D.A., Karunamoorthy, S. and Cao, W.-M. Finite state induced flow models part i: two-dimensional thin airfoil. J. Aircr., 1995, 32, (2), pp 313–322. doi: 10.2514/3.46718 CrossRefGoogle Scholar
Peters, D.A. and He, C.-J. Finite state induced flow models part II: three-dimensional rotor disk. J. Aircr., 1995, 32, (2), pp 323–333. doi: 10.2514/3.46719 CrossRefGoogle Scholar
Jones, R.T. The unsteady lift of a wing of finite aspect ratio. Tech. Rep. NACA TR-681, NASA, Washington, DC, 1940.Google Scholar
Eversman, W. and Tewari, A. Consistent rational-function approximation for unsteady aerodynamics. Aerosp. Sci. Technol., 1991, 28, (9), pp 545–552. doi: 10.2514/3.46062 Google Scholar
Wright, J.R. and Cooper, J.E., Introduction to Aircraft Aeroelasticity and Loads, 2nd ed.. West Sussex, UK: Wiley, 2014, pp 450–453.CrossRefGoogle Scholar
Hang, X., Fei, Q. and Su, W. On tracking aeroelastic modes in stability analysis using left and right eigenvectors. AIAA J., 2019, 57, (10), pp 4447–4457. doi: 10.2514/1.J057297 CrossRefGoogle Scholar
Tang, D. and Dowell, E.H. Experimental and theoretical study on aeroelastic response of high-aspect-ratio wings. AIAA J., 2001, 39, (8), pp 1430–1441. doi: 10.2514/2.1484 CrossRefGoogle Scholar