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Identification of flutter derivatives of bridge decks using CFD-based discrete-time aerodynamic models

  • Zhu, Zhiwen (Center of Wind Engineering, Hunan University) ;
  • Gu, Ming (State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University)
  • Received : 2011.04.22
  • Accepted : 2013.10.13
  • Published : 2014.03.25

Abstract

This paper presents a method to extract flutter derivatives of bridge decks based on a combination of the computational fluid dynamics (CFD), system simulations and system identifications. The incompressible solver adopts an Arbitrary Lagrangian-Eulerian (ALE) formulation with the finite volume discretization in space. The imposed sectional motion in heaving or pitching relies on exponential time series as input, with aerodynamic forces time histories acting on the section evaluated as output. System identifications are carried out to fit coefficients of the inputs and outputs of ARMA models, as to establish discrete-time aerodynamic models. System simulations of the established models are then performed as to obtain the lift and moment exerting on the sections to a sinusoidal displacement. It follows that flutter derivatives are identified. The present approaches are applied to a hexagon thin plate and a real bridge deck. The results are compared to the Theodorsen closed-form solution and those from wind tunnel tests. Satisfactory agreements are observed.

Keywords

Acknowledgement

Supported by : China Natural Science Foundation

References

  1. Brar, P.S., Raul, R. and Scanlan, R.H. (1996), "Numerical calculation of flutter derivatives via indicial functions", J. Fluid. Struct., 10(4), 337-351. https://doi.org/10.1006/jfls.1996.0022
  2. Brockwell, P. J. and Davis, R.A. (2009), Time series: theory and methods (2nd Ed.), New York, Springer.
  3. Bruno, L., Canuto, C. and Fransos, D. (2009), "Stochastic aerodynamics and aeroelasticity of a flat plate via generalized Polynomial Chaos", J. Fluid Struct., 25, 1158-1176. https://doi.org/10.1016/j.jfluidstructs.2009.06.001
  4. Bruno, L. and Fransos, D. (2008), "Evaluation of Reynolds number effects on flutter derivatives of a flat plate by means of a computational approach", J. Fluid. Struct., 24(7), 1058-1076. https://doi.org/10.1016/j.jfluidstructs.2008.03.001
  5. Frandsen, J.B. (2004), "Numerical bridge deck studies using finite elements, Part I: flutter", J. Fluid. Struct., 19(2), 171-191. https://doi.org/10.1016/j.jfluidstructs.2003.12.005
  6. Fransos, D. and Bruno, L. (2006), "Determination of the aeroelastic transfer functions for streamlined bodies by means of a Navier-Stokes solver", Math. Comput. Model., 43(5-6), 506-529. https://doi.org/10.1016/j.mcm.2005.10.002
  7. Ge, Y.J. and Xiang, H.F. (2008), "Computational models and methods for aerodynamic flutter of long-span bridges", J. Wind Eng. Ind. Aerod., 96(10-11), 1912-1924. https://doi.org/10.1016/j.jweia.2008.02.017
  8. Gu, M. and Qin, X.R. (2004), "Direct identification of flutter derivatives and aerodynamic admittances of bridge decks", Eng. Struct., 26(14), 2161-2172. https://doi.org/10.1016/j.engstruct.2004.07.015
  9. Gu, M., Zhang, R.X. and Xiang, H.F. (2000), "Identification of flutter derivatives of bridge decks", J. Wind Eng. Ind. Aerod., 84(2), 151-162. https://doi.org/10.1016/S0167-6105(99)00051-3
  10. Huang, L. and Liao, H. (2011), "Identification of flutter derivatives of bridge deck under multi-frequency vibration", Eng. Appl. Comput. Fluid. Mech., 5(1) , 16-25.
  11. Jeong, U.Y. and Kwon, S.D. (2003), "Sequential numerical procedures for predicting flutter velocity of bridge sections", J. Wind Eng. Ind. Aerod., 91(1-2), 291-305. https://doi.org/10.1016/S0167-6105(02)00352-5
  12. Larsen, A. and Walther, J.H. (1997), "Aeroelastic analysis of bridge girder sections based on discrete vortex simulation", J. Wind Eng. Ind.Aerod., 67-68, 253-265. https://doi.org/10.1016/S0167-6105(97)00077-9
  13. Lin, Z.X. and Xiang, H.F. (1995), Researches on wind-induced instability of Humen Bridge in erection stage, Technical Report of State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University, Shanghai, (in Chinese).
  14. Nomura, T. and Hughes, T.J.R. (1992), "An arbitrary Lagrangian-Eulerian finite element method for interaction of fluid and a rigid body", Comput. Meth. Appl., 95(1), 115-138. https://doi.org/10.1016/0045-7825(92)90085-X
  15. Scanlan, R.H. and Tomko J.J. (1971), "Airfoil and bridge deck flutter derivatives", J. Eng. Mech. - ASCE, 97(6), 1171-1737.
  16. Shirai, S. and Ueda, T. (2003), "Aerodynamic simulation by CFD on flat box girder of super-long-span suspension bridge", J. Wind Eng. Ind Aerod., 91(1-2), 279-290. https://doi.org/10.1016/S0167-6105(02)00351-3
  17. Starossek, U. and Aslan, H. (2009), "Experimental and numerical identification of flutter derivatives for nine bridge deck sections", Wind Struct., 12(6), 519-540. https://doi.org/10.12989/was.2009.12.6.519
  18. Theodorsen, T. (1935), General theory of aerodynamic instability and the mechanism of flutter, NACA Report No.496, 413-433.
  19. Vairo, G. (2003), "A numerical model for wind loads simulation on long-span bridges", Simul. Model. Pract. Th., 11(5-6), 315-351. https://doi.org/10.1016/S1569-190X(03)00053-4
  20. Zhu, Z.W., Chen Z.Q. and Gu, M. (2009), "CFD based simulations of flutter characteristics of ideal thin plates with and without central slot", Wind Struct., 12(1), 1-19. https://doi.org/10.12989/was.2009.12.1.001
  21. Zhu, Z.W., Gu, M. and Chen, Z.Q. (2007), "Wind tunnel and CFD study on identification of flutter derivatives of a long-span self-anchored suspension bridge", Comput. Aided Civil Infrastruct. Eng., 22(8), 541-554. https://doi.org/10.1111/j.1467-8667.2007.00509.x

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