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Simulation of stationary Gaussian stochastic wind velocity field

  • Ding, Quanshun (State Key Lab for Disaster Reduction in Civil Engineering, Tongji University) ;
  • Zhu, Ledong (State Key Lab for Disaster Reduction in Civil Engineering, Tongji University) ;
  • Xiang, Haifan (State Key Lab for Disaster Reduction in Civil Engineering, Tongji University)
  • Received : 2005.05.23
  • Accepted : 2006.04.05
  • Published : 2006.06.25

Abstract

An improvement to the spectral representation algorithm for the simulation of wind velocity fields on large scale structures is proposed in this paper. The method proposed by Deodatis (1996) serves as the basis of the improved algorithm. Firstly, an interpolation approximation is introduced to simplify the computation of the lower triangular matrix with the Cholesky decomposition of the cross-spectral density (CSD) matrix, since each element of the triangular matrix varies continuously with the wind spectra frequency. Fast Fourier Transform (FFT) technique is used to further enhance the efficiency of computation. Secondly, as an alternative spectral representation, the vectors of the triangular matrix in the Deodatis formula are replaced using an appropriate number of eigenvectors with the spectral decomposition of the CSD matrix. Lastly, a turbulent wind velocity field through a vertical plane on a long-span bridge (span-wise) is simulated to illustrate the proposed schemes. It is noted that the proposed schemes require less computer memory and are more efficiently simulated than that obtained using the existing traditional method. Furthermore, the reliability of the interpolation approximation in the simulation of wind velocity field is confirmed.

Keywords

Acknowledgement

Supported by : National Science Foundation of China

References

  1. Cao, Y. H., Xiang, H. E, and Zhou, Y. (2000), 'Simulation of stochastic wind velocity field on long-span bridges', J. Eng. Mech., ASCE, 126(1), 1-6 https://doi.org/10.1061/(ASCE)0733-9399(2000)126:1(1)
  2. Deodatis, G. (1996), 'Simulation of ergodic multivariate stochastic processes', J. Eng. Mech. ASCE, 122(8), 778-787 https://doi.org/10.1061/(ASCE)0733-9399(1996)122:8(778)
  3. Deodatis, G. and Shinozuka, M. (1989), 'Simulation of seismic ground motion using stochastic waves', J. Engrg. Mech., ASCE, 115(12), 2723-2737 https://doi.org/10.1061/(ASCE)0733-9399(1989)115:12(2723)
  4. Di Paola, M. (1998), 'Digital simulation of wind field velocity', J. Wind Eng. Ind. Aerodyn., 74-76, 91-109
  5. Grigoriu, M. (2000), 'A spectral representation based model for Monte Carlo simulation', Prob. Eng. Mech., 15, 365-370 https://doi.org/10.1016/S0266-8920(99)00038-7
  6. Kovacs, I., Svensson, H. S., and Jordet, E. (1992), 'Analytical aerodynamic investigation of cable-stayed Helgeland Bridge', J. Struct. Eng., ASCE, 118(1), 147-168 https://doi.org/10.1061/(ASCE)0733-9445(1992)118:1(147)
  7. Li Yongle, Liao Haili, and Qiang Shizhong (2004), 'Simplifying the simulation of stochastic wind velocity fields for long cable-stayed bridges', Compu. Struct., 82, 1591-1598 https://doi.org/10.1016/j.compstruc.2004.05.007
  8. Li, Y. and Kareem, A. (1993), 'Simulation of multivariate random processes: hybrid DFT and digital filtering approach', J. Eng. Mech., ASCE, 119(5), 1078-1098 https://doi.org/10.1061/(ASCE)0733-9399(1993)119:5(1078)
  9. Mann, J. (1998), 'Wind field simulation', Probabilistic Eng. Mech., 13, 269-282 https://doi.org/10.1016/S0266-8920(97)00036-2
  10. Shinozuka, M. (1971), 'Simulation of multivariate and multidimensional random processes', J. Acoust. Soc. Amer., 49, 357-368 https://doi.org/10.1121/1.1912338
  11. Shinozuka, M. (1974), 'Digital simulation of random processes in engineering mechanics with the aid of FFT technique', Stochastic Problems in Mechanics, S. T. Ariaratnam and H. H. E. Leipholz, eds., University of Waterloo Press, Ontario, Canada, 277-286
  12. Shinozuka, M. (1987), 'Stochastic fields and their digital simulation', Stochastic Methods in Structural Dynamics, G. I. Schuler and M. Shinozuka, eds., Martinus Nijhoff Publishers, Dordrecht, The Netherlands, 93-133
  13. Shinozuka, M. and Deodatis, G. (1991), 'Simulation of stochastic processes by spectral representation', Appl. Mech. Rev., 44(4), 191-204 https://doi.org/10.1115/1.3119501
  14. Shinozuka, M. and Jan, C. M. (1972), 'Digital simulation of random processes and its applications', J. Sound Vib., 25(10), 111-128 https://doi.org/10.1016/0022-460X(72)90600-1
  15. Shinozuka, M., Yun C. B., and Seya, H. (1990), 'Stochastic methods in wind engineering', J. Wind Eng. Ind. Aerodyn., 36, 829-843 https://doi.org/10.1016/0167-6105(90)90080-V
  16. Simiu, E. and Scanlan, R. H. (1986), Wind Effects on Structures, Wiley, New York
  17. Solari, G. and Carassale, L. (2000), 'Modal transformation tools in structural dynamics and wind engineering', Wind and Struct., An Int. J., 3(4), 221-241 https://doi.org/10.12989/was.2000.3.4.221
  18. Spanos, P. D. and Zeldin, R. A. (1998), 'Monte Carlo treatment of random fields: a broad perspective', Appl. Mech. Rev., 51(3), 219-237 https://doi.org/10.1115/1.3098999
  19. Yamazaki, F. and Shinozuka, M. (1988), 'Digital generation of non-Gaussian stochastic fields', J. Eng. Mech. ASCE, 114(7), 1183-1197 https://doi.org/10.1061/(ASCE)0733-9399(1988)114:7(1183)
  20. Yang, J. (1972), 'Simulation of random envelope processes', J. Sound Vib., 21(1), 73-85 https://doi.org/10.1016/0022-460X(72)90207-6
  21. Yang, W. W., Chang, T. Y. P., and Chang, C. C. (1997), 'An efficient wind field simulation technique for bridges', J. Wind Eng. Ind. Aerodyn., 67-68, 697-708

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