Similar articles

Abstract: Simulation for stochastic wind field is very important in analyzing dynamic responses of large complex structures due to strong wind. The typical simulation method is the spectrum representation method (SRM), but the SRM has drawbacks of inferior precision in lower frequency and slow calculating speed. In view of this, the modified Fourier spectrum method (MFSM) is introduced into the simulation of stochastic wind field in this paper. In this method, phase information of wind velocity time history is determined by cross power spectral density (CPSD) between adjacent points, and the wind velocity time history with time and space correlation is generated by iterative modification for CPSD considering auto power spectral density (APSD). Simulation of the wind field for a long-span bridge is undertaken to verify the effectiveness of the MFSM. Simulation results of the SRM and the MFSM are compared. It can be concluded that the MFSM is more accurate and has higher calculation speed than the SRM.

[1]Backström, D., Nilsson, A.C., 2007. Modeling the vibration of sandwich beams using frequency-dependent parameters. Journal of Vibration and Control, 300(3):589-611.

[2]Chondros, T.G., Dimarogonas, A.D., 1989. Dynamic sensitivity of structures to cracks. Journal of Vibration, Acoustics, Stress and Reliability in Design, 111:251-256.

[3]Davenport, A.G., 1961. The spectrum of horizontal gustiness near the ground in high winds. Quarterly Journal of the Royal Meteorological Society, 87(372):194-211.

[4]Deodatis, G., 1996. Simulation of ergodic multivariate stochastic processes. Journal of Engineering Mechanics, 122(8):778-787.

[5]Islam, N., Zaheer, M.M., Ahmed, S., 2009. Double hinged articulated tower interaction with wind and waves. Journal of Wind Engineering and Industrial Aerodynamics, 97(5-6):287-297.

[6]Kaimal, J.C., Wyngaad, J.C., Izumi, Y., Cote, O.R., 1972. Spectral characteristics of surface layer turbulence. Quarterly Journal of the Royal Meteorological Society, 98(417):563-589.

[7]Lazzari, M., Vitaliani, R., Majowiecki, M., Saetta, A., 2003. Dynamic behavior of a tensegrity system subjected to follower wind loading. Computers and Structures, 81(22-23):2199-2217.

[8]Li, H.N, Bai, F.L., Li, T., Hao, H., 2011. Response of a transmission tower-line system at a canyon site to spatially varying ground motions. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 12(2):103-120.

[9]Mason, M.S., Wood, G.S., Fletcher, D.F., 2009. Numerical simulation of downburst winds. Journal of Wind Engineering and Industrial Aerodynamics, 97(11-12):523-539.

[10]Mazanoglu, K., Yesilyurt, I., Sabuncu, M., 2009. Vibration analysis of multiple-cracked non-uniform beams. Journal of Vibration and Control, 320(4):977-989.

[11]GB 50009-2001. Load Code for the Design of Building Structures. Ministry of Construction of People’s Republic of China. China Architecture and Building Press, Beijing (in Chinese).

[12]Miyata, T., Yamada, H., Katsuchi, H., Kitagawa, M., 2001. Full scale measurement of Akashi-Kaikyo Bridge during typhoon. Wind Engineering, 89(9):341-344.

[13]Moustafa, A., Takewak, I., 2009. Use of probabilistic and deterministic measures to identify unfavorable earthquake records. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 10(5):619-634.

[14]Samaras, E., Shinozuka, M., Tsurui, A., 1985. ARMA representation of random processes. Journal of Engineering Mechanics, 111(3):449-461.

[15]Shinozuka, M., Jan, C.M., 1972. Digital simulation of random processes and its applications. Journal of Sound and Vibration, 25(1):111-128.

[16]Wang, J., Hu, X., 2006. Application of Matlab in Treatment of Vibration Signal. China Water Power Press, Beijing (in Chinese).

[17]Xu, Y.L., Zhu, L.D., Wong, K.Y., Chan, K.W.Y., 2001. Field measurement results of Tsing Ma Suspension Bridge during Typhoon Victor. Structural Engineering and Mechanics, 10(6):545-559.