Extreme winds such as thunderstorm winds typically exhibit nonstationary characteristics. When these winds act on the structure, the time domain analysis method is used considering the structural and/or aerodynamic nonlinearity in the wind-induced structural response analysis. Because the time domain analysis method needs a sufficient number of wind speed samples, the efficient simulation of nonstationary winds becomes a crucial task. The time series method is more suitable in generating the nonstationary process due to the high efficiency. As a typical time series model, the autoregressive-generalized autoregressive conditional heteroskedasticity (AR-GARCH) model could be a good candidate to characterize these samples. In this paper, the method based on the multivariate AR-GARCH model is proposed to model and simulate the multivariate nonstationary wind speed process. Specifically, Baba-Engle-Kraft-Kroner (BEKK) model is adopted since it can maintain the positive definiteness of conditional covariance matrix. The numerical simulations based on samples with different time-varying variances obtained by spectral representation method (SRM) are given to demonstrate the applicability of the proposed method. The measured thunderstorm wind speed is adopted to illustrate and validate the accuracy of the proposed method. The results show that the time-varying variance and cross correlation can be satisfactorily maintained.

诸如雷暴风之类的极端风通常表现出非平稳特性。当这些风作用在结构上时，在风致结构响应分析中考虑结构和/或空气动力学非线性，使用时域分析方法。由于时域分析方法需要足够数量的风速样本，因此非平稳风的有效模拟成为一项至关重要的任务。时间序列方法由于效率高而更适合于生成非平稳过程。作为典型的时间序列模型，自回归广义自回归条件异方差模型（AR-GARCH）可能是表征这些样本的良好候选者。在本文中，提出了基于多元AR-GARCH模型的方法，对多元非平稳风速过程进行建模和仿真。具体而言，采用Baba-Engle-Kraft-Kroner（BEKK）模型，因为它可以保持条件协方差矩阵的正定性。给出了基于光谱表示法（SRM）的具有不同时变方差的样本的数值模拟，以证明该方法的适用性。采用实测雷暴风速来说明和验证所提方法的准确性。结果表明，可以满意地保持时变方差和互相关。给出了基于光谱表示法（SRM）的具有不同时变方差的样本的数值模拟，以证明该方法的适用性。采用实测雷暴风速来说明和验证所提方法的准确性。结果表明，可以满意地保持时变方差和互相关。给出了基于光谱表示法（SRM）的具有不同时变方差的样本的数值模拟，以证明该方法的适用性。采用实测雷暴风速来说明和验证所提方法的准确性。结果表明，可以满意地保持时变方差和互相关。