Hu Weicheng, Yang Qingshan, Peng Liuliu, Liu Linya, Zhang Pengfei, Li Shaopeng, Wu Jun
State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure, East China Jiaotong University, Nanchang, 330013, China.
Jiangxi Comprehensive Transportation Development Research Center, Nanchang, 330002, China.
Heliyon. 2024 Jul 25;10(15):e35195. doi: 10.1016/j.heliyon.2024.e35195. eCollection 2024 Aug 15.
Wind velocity is usually assumed to obey a stationary stochastic process in wind engineering, and this may cause significant bias in describing extremely severe strong wind such as typhoons and thunderstorms. To take into account the non-stationary characteristics of extreme wind, a novel evolutionary power spectral density (EPSD) model is proposed, and the spectral representation method (SRM) is introduced to simulate the whole process of strong winds. Firstly, the wavelet transform (WT) method is adopted to capture the three-dimensional time-varying properties of the low-frequency mean winds, and the associated turbulence features, including turbulent intensity, gust factor, probability density function, and power spectrum, are analyzed in depth. Secondly, the measured horizontal EPSD of strong winds are estimated. Thirdly, the performance of the proposed EPSD model is validated. Finally, the whole process of non-stationary strong winds are simulated and discussed. The results show that the proposed EPSD models are in good agreement with the measured EPSD, and the time-frequency features of the power spectrum of the simulated winds are well reproduced, which provides a powerful tool for large eddy simulation and wind engineering studies under non-stationary extreme wind climate.
在风工程中，风速通常被假定为服从平稳随机过程，而这在描述诸如台风和雷暴等极端强风时可能会导致显著偏差。为了考虑极端风的非平稳特性，提出了一种新颖的演化功率谱密度（EPSD）模型，并引入谱表示法（SRM）来模拟强风的全过程。首先，采用小波变换（WT）方法捕捉低频平均风的三维时变特性，并深入分析相关的湍流特征，包括湍流强度、阵风因子、概率密度函数和功率谱。其次，估计实测强风的水平EPSD。第三，验证所提出的EPSD模型的性能。最后，模拟并讨论非平稳强风的全过程。结果表明，所提出的EPSD模型与实测EPSD吻合良好，模拟风功率谱的时频特征得到了很好的再现，这为非平稳极端风气候下的大涡模拟和风工程研究提供了有力工具。
