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Wind and Structures
  Volume 29, Number 6, December 2019, pages 389-403

Dimension-reduction simulation of stochastic wind velocity fields by two continuous approaches
Zhangjun Liu, Chenggao He, Zenghui Liu and Hailin Lu

    In this study, two original spectral representations of stationary stochastic fields, say the continuous proper orthogonal decomposition (CPOD) and the frequency-wavenumber spectral representation (FWSR), are derived from the Fourier-Stieltjes integral at first. Meanwhile, the relations between the above two representations are discussed detailedly. However, the most widely used conventional Monte Carlo schemes associated with the two representations still leave two difficulties unsolved, say the high dimension of random variables and the incompleteness of probability with respect to the generated sample functions of the stochastic fields. In view of this, a dimension-reduction model involving merely one elementary random variable with the representative points set owing assigned probabilities is proposed, realizing the refined description of probability characteristics for the stochastic fields by generating just several hundred representative samples with assigned probabilities. In addition, for the purpose of overcoming the defects of simulation efficiency and accuracy in the FWSR, an improved scheme of non-uniform wavenumber intervals is suggested. Finally, the Fast Fourier Transform (FFT) algorithm is adopted to further enhance the simulation efficiency of the horizontal stochastic wind velocity fields. Numerical examples fully reveal the validity and superiority of the proposed methods.
Key Words
    stochastic wind velocity field; continuous proper orthogonal decomposition; frequency-wavenumber spectral representation; dimension reduction; non-uniform wavenumber intervals; FFT algorithm
Zhangjun Liu, Zenghui Liu and Hailin Lu: School of Civil Engineering and Architecture, Wuhan Institute of Technology, Wuhan 430074, P.R. China
Chenggao He: College of Civil Engineering & Architecture, China Three Gorges University, Yichang 443002, P.R. China

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