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Scheme and application of phase delay spectrum towards spatial stochastic wind fields

  • Yan, Qi (School of Civil Engineering, Tongji University) ;
  • Peng, Yongbo (State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University) ;
  • Li, Jie (School of Civil Engineering, Tongji University)
  • 투고 : 2011.12.14
  • 심사 : 2012.06.20
  • 발행 : 2013.05.01

초록

A phase delay spectrum model towards the representation of spatial coherence of stochastic wind fields is proposed. Different from the classical coherence functions used in the spectral representation methods, the model is derived from the comprehensive description of coherence of fluctuating wind speeds and from the thorough analysis of physical accounts of random factors affecting phase delay, building up a consistent mapping between the simulated fluctuating wind speeds and the basic random variables. It thus includes complete probabilistic information of spatial stochastic wind fields. This treatment prompts a ready and succinct scheme for the simulation of fluctuating wind speeds, and provides a new perspective to the accurate assessment of dynamic reliability of wind-induced structures. Numerical investigations and comparative studies indicate that the developed model is of rationality and of applicability which matches well with the measured data at spatial points of wind fields, whereby the phase spectra at defined datum mark and objective point are feasibly obtained using the numerical scheme associated with the starting-time of phase evolution. In conjunction with the stochastic Fourier amplitude spectrum that we developed previously, the time history of fluctuating wind speeds at any spatial points of wind fields can be readily simulated.

키워드

참고문헌

  1. Aung, N.N., Ye, J.H. and Masters, F.J. (2012), "Simulation of multivariate non-Gaussian wind pressure on spherical latticed structures", Wind Struct., 15(3), 223-245. https://doi.org/10.12989/was.2012.15.3.223
  2. Chen, J.J. (1994), "Analysis of engineering structures response to random wind excitation", Comput. Struct., 51(6), 687-693. https://doi.org/10.1016/S0045-7949(05)80007-0
  3. Collins, R., Basu, B. and Broderick, B.M. (2008), "Bang-bang and semiactive control with variable stiffness TM ds", J. Struct. Eng. - ASCE, 134(2), 310-317. https://doi.org/10.1061/(ASCE)0733-9445(2008)134:2(310)
  4. Davenport, A.G. (1961), "The spectrum of horizontal gustiness near the ground in high winds", Q. J. Roy. Meteor. Soc., 87, 194-211. https://doi.org/10.1002/qj.49708737208
  5. Davenport, A.G. (1967), "Gust loading factors", J. Struct. Division - ASCE, 93, 11-34.
  6. Ding, Q.S., Zhu, L.D. and Xiang, H.F. (2006), "Simulation of stationary Gaussian stochastic wind velocity field", Wind Struct., 9(3), 231-243. https://doi.org/10.12989/was.2006.9.3.231
  7. Dyrbye, C. and Hansen, S.O. (1997), Wind Loads on Structures, John Wiley & Sons, New York.
  8. Harris, R.I. (1971), "The nature of wind", In The Modern Design of Wind-Sensitive Structures, Construction Industry Research and Information Association, London.
  9. Hu, L., Li, L. and Gu M. (2010), "Error assessment for spectral representation method in wind velocity field simulation", J. Eng. Mech. - ASCE, 136(9), 1090-1104. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000058
  10. Kareem, A. (2008), "Numerical simulation of wind effects: A probabilistic perspective", J. Wind Eng. Ind. Aerod., 96, 1472-1497. https://doi.org/10.1016/j.jweia.2008.02.048
  11. Kristensen, L., Panofsky, H.A. and Smith, S.D. (1981), "Lateral coherence of longitudinal wind components in strong winds", Bound-Lay. Meteorol, 21, 199-205. https://doi.org/10.1007/BF02033937
  12. Li, J., Yan, Q. and Chen, J.B. (2012), "Stochastic modeling of engineering dynamic excitations for stochastic dynamics of structures", Probab. Eng. Mech., 27(1), 19-28. https://doi.org/10.1016/j.probengmech.2011.05.004
  13. Li, J., Peng, Y.B. and Yan, Q. (2013), "Modeling and simulation of fluctuating wind speeds using evolutionary phase spectrum", Probab. Eng. Mech., 32, 48-55. https://doi.org/10.1016/j.probengmech.2013.01.001
  14. Liu, G., Xu, Y.L. and Zhu, L.D. (2004), "Time domain buffeting analysis of long suspension bridges under skew winds", Wind Struct., 7(6), 421-447. https://doi.org/10.12989/was.2004.7.6.421
  15. Maeda, J. and Makino, M. (1980), "Classification of customary proposed equations related to the component of the mean wind direction in the structure of atmospheric turbulence and these fundamental properties", T. Architect. Inst., 287, 77. https://doi.org/10.3130/aijsaxx.287.0_77
  16. Panofsky, H.A. and McCormick, R.A. (1954), "Properties of spectra of atmospheric turbulence at 100 metres", Q. J. Roy. Meteorol. Soc., 80, 546-564. https://doi.org/10.1002/qj.49708034604
  17. Panofsky, H.A. and Singer, I.A. (1965), "Vertical structure of turbulence", Q. J. Roy. Meteorol. Soc., 91, 339-344. https://doi.org/10.1002/qj.49709138908
  18. Paroka, D. and Umeda, N. (2006), "Capsizing probability prediction for a large passenger ship in irregular beam wind and waves: Comparison of analytical and numerical methods", J. Ship Res., 50(4), 371-377.
  19. Rice, S.O. (1954), "Mathematical analysis of random noise", In Selected Papers on Noise and Stochastic Processes, edited by N. Wax. Dover, 133-294.
  20. Saranyasoontorn, K., Manuel, L. and Veers, P.S. (2004), "A comparison of standard coherence models for inflow turbulence with estimates from field measurements", J. Solar Energy Eng. T. - ASME, 126(4), 1069-1082. https://doi.org/10.1115/1.1797978
  21. Schlez, W. and Infield, D. (1998), "Horizonal, two point coherence for separations greater than measurement height", Bound-Lay. Meteorol., 87(3), 459-480. https://doi.org/10.1023/A:1000997610233
  22. Seong, S.H. and Peterka, J.A. (2001), "Experiments on Fourier phases for synthesis of non-Gaussian spikes in turbulence time series", J. Wind Eng.Ind. Aerod., 89, 421-443. https://doi.org/10.1016/S0167-6105(00)00073-8
  23. Shinozuka, M. and Deodatis, G. (1997), "Simulation of stochastic processes and fields", Probab. Eng. Mech., 12(4), 203-207.
  24. Shinozuka, M. and Jan, C.M. (1972), "Digital simulation of random process and its application", J. Sound Vib., 25(1), 111-128. https://doi.org/10.1016/0022-460X(72)90600-1
  25. Welch, P.D. (1967), "The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms", IEEE T. Audio Elect., AU-15, 17-20.
  26. Ye, J.H., Ding, J.H and Liu, C.Y. (2012), "Numerical simulation of non-Gaussian wind load", Sci. China- Technol. Sci., 55(1), 1-13.
  27. Ying, Z.G., Ni, Y.Q. and Ko, J.M. (2005), "Semi-active optimal control of linearized systems with multi-degree of freedom and application", J. Sound Vib., 279(1-2), 373-388. https://doi.org/10.1016/j.jsv.2003.11.004
  28. Zheng, S.X., Liao, H.L. and Li, Y.L. (2007), "Stability of suspension bridge catwalks under a wind load", Wind Struct., 10(4), 367-382. https://doi.org/10.12989/was.2007.10.4.367

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