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 SR...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.展开更多
This paper analyses and compares the property of the Modified Bayesian Directional spectrum analysis Method （MBDM） and the Modified Maximum Lkelihood Method （MMLM） that can he used to estimate directional spectrum...This paper analyses and compares the property of the Modified Bayesian Directional spectrum analysis Method （MBDM） and the Modified Maximum Lkelihood Method （MMLM） that can he used to estimate directional spectrum and reflected coefficient of phase-locked wave field overlapped by multi directional irregular incident and reflected waves. The numerical test verifies the results under different wave conditions, different measurement systems, and different reflection features. The computation speed and stability of the two methods is also compared. The analysis addresses that the MBDM is better than the MMLM for directional spectrum estimating, while the MMLM is better than the MBDM for reflected coefficient estimation and calculating speed and stability.展开更多
基金Project supported by the National Natural Science Foundation of China (No.90915004)the Six Talents Peak in Jiangsu Province(No.2008178)the 333 High-Level Talent Training Project of Jiangsu Province,China
文摘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.
文摘This paper analyses and compares the property of the Modified Bayesian Directional spectrum analysis Method （MBDM） and the Modified Maximum Lkelihood Method （MMLM） that can he used to estimate directional spectrum and reflected coefficient of phase-locked wave field overlapped by multi directional irregular incident and reflected waves. The numerical test verifies the results under different wave conditions, different measurement systems, and different reflection features. The computation speed and stability of the two methods is also compared. The analysis addresses that the MBDM is better than the MMLM for directional spectrum estimating, while the MMLM is better than the MBDM for reflected coefficient estimation and calculating speed and stability.
