DOI QR코드

DOI QR Code

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)
  • 투고 : 2005.05.23
  • 심사 : 2006.04.05
  • 발행 : 2006.06.25

초록

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.

키워드

과제정보

연구 과제 주관 기관 : National Science Foundation of China

참고문헌

  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

피인용 문헌

  1. Error Assessment for Spectral Representation Method in Wind Velocity Field Simulation vol.136, pp.9, 2010, https://doi.org/10.1061/(ASCE)EM.1943-7889.0000058
  2. A Cyber-Based Data-Enabled Virtual Organization for Wind Load Effects on Civil Infrastructures: VORTEX-Winds vol.3, 2017, https://doi.org/10.3389/fbuil.2017.00048
  3. CONTROL OF WIND-INDUCED RESPONSE OF TRANSMISSION TOWER-LINE SYSTEM BY USING MAGNETORHEOLOGICAL DAMPERS vol.09, pp.04, 2009, https://doi.org/10.1142/S0219455409003235
  4. Spline-Interpolation-Based FFT Approach to Fast Simulation of Multivariate Stochastic Processes vol.2011, 2011, https://doi.org/10.1155/2011/842183
  5. Wind tunnel tests and numerical approach for long span bridges: The Messina bridge vol.122, 2013, https://doi.org/10.1016/j.jweia.2013.07.012
  6. An efficient simulation method for vertically distributed stochastic wind velocity field based on approximate piecewise wind spectrum vol.151, 2016, https://doi.org/10.1016/j.jweia.2016.01.005
  7. Study of the approximate approaches to the POD based spectral representation method vol.56, pp.4, 2013, https://doi.org/10.1007/s11431-013-5180-y
  8. New formulation of Cholesky decomposition and applications in stochastic simulation vol.34, 2013, https://doi.org/10.1016/j.probengmech.2013.04.003
  9. An efficient framework for the elasto-plastic reliability assessment of uncertain wind excited systems vol.58, 2016, https://doi.org/10.1016/j.strusafe.2015.09.001
  10. An improved approximation for the spectral representation method in the simulation of spatially varying ground motions vol.29, 2012, https://doi.org/10.1016/j.probengmech.2011.12.001
  11. Random function representation of stationary stochastic vector processes for probability density evolution analysis of wind-induced structures vol.106, 2018, https://doi.org/10.1016/j.ymssp.2018.01.011
  12. Wind tunnel: a fundamental tool for long-span bridge design vol.11, pp.4, 2015, https://doi.org/10.1080/15732479.2014.951860
  13. Passive Winglet Control of Flutter and Buffeting Responses of Suspension Bridges 2017, https://doi.org/10.1142/S0219455418500724
  14. Online Simultaneous Reconstruction of Wind Load and Structural Responses-Theory and Application to Canton Tower vol.30, pp.8, 2015, https://doi.org/10.1111/mice.12134
  15. Scheme and application of phase delay spectrum towards spatial stochastic wind fields vol.16, pp.5, 2013, https://doi.org/10.12989/was.2013.16.5.433
  16. Simulation of non-stationary wind velocity field on bridges based on Taylor series vol.169, 2017, https://doi.org/10.1016/j.jweia.2017.07.005
  17. Efficacy of Interpolation-Enhanced Schemes in Random Wind Field Simulation over Long-Span Bridges vol.23, pp.3, 2018, https://doi.org/10.1061/(ASCE)BE.1943-5592.0001203
  18. Review for dynamic researches in civil engineering in recent years vol.53, pp.5, 2010, https://doi.org/10.1007/s11431-010-0186-1
  19. An experimental validation of a band superposition model of the aerodynamic forces acting on multi-box deck sections vol.113, 2013, https://doi.org/10.1016/j.jweia.2012.12.005
  20. An efficient Cholesky decomposition and applications for the simulation of large-scale random wind velocity fields pp.2048-4011, 2018, https://doi.org/10.1177/1369433218810642
  21. LES of wind environments in urban residential areas based on an inflow turbulence generating approach vol.24, pp.1, 2006, https://doi.org/10.12989/was.2017.24.1.001
  22. Reduced-Hermite bifold-interpolation assisted schemes for the simulation of random wind field vol.53, pp.None, 2006, https://doi.org/10.1016/j.probengmech.2018.08.002
  23. Reliability-based design optimization of trusses under dynamic shakedown constraints vol.60, pp.3, 2006, https://doi.org/10.1007/s00158-019-02259-x
  24. Wind Velocity Field Simulation Based on Enhanced Closed-Form Solution of Cholesky Decomposition vol.146, pp.2, 2020, https://doi.org/10.1061/(asce)em.1943-7889.0001712
  25. Application of Time-Frequency Interpolation and Proper Orthogonal Decomposition in Nonstationary Wind-Field Simulation vol.146, pp.5, 2020, https://doi.org/10.1061/(asce)em.1943-7889.0001761
  26. Error Analysis of Multivariate Wind Field Simulated by Interpolation-Enhanced Spectral Representation Method vol.146, pp.6, 2020, https://doi.org/10.1061/(asce)em.1943-7889.0001783
  27. IABSE Task Group 3.1 Benchmark Results. Part 1: Numerical Analysis of a Two-Degree-of-Freedom Bridge Deck Section Based on Analytical Aerodynamics vol.30, pp.3, 2006, https://doi.org/10.1080/10168664.2019.1639480
  28. IABSE Task Group 3.1 Benchmark Results. Part 2: Numerical Analysis of a Three-Degree-of-Freedom Bridge Deck Section Based on Experimental Aerodynamics vol.30, pp.3, 2020, https://doi.org/10.1080/10168664.2019.1661331
  29. Simulation of nonstationary wind in one-spatial dimension with time-varying coherence by wavenumber-frequency spectrum and application to transmission line vol.75, pp.4, 2006, https://doi.org/10.12989/sem.2020.75.4.425
  30. Fast simulation of large-scale non-stationary wind velocities based on adaptive interpolation reconstruction scheme vol.33, pp.1, 2006, https://doi.org/10.12989/was.2021.33.1.055
  31. Simulation of ergodic multivariate stochastic processes: An enhanced spectral representation method vol.161, pp.None, 2006, https://doi.org/10.1016/j.ymssp.2021.107949
  32. Reliability-based design optimization of structural systems under stochastic excitation: An overview vol.166, pp.None, 2006, https://doi.org/10.1016/j.ymssp.2021.108397