Fractal-based numerical simulation of multivariate typhoon wind speeds utilizing weierstrass mandelbrot function

被引：0

作者：

Cai, Kang ^{[1
,2
,3
,4
]}

Huang, Mingfeng ^{[1
,5
]}

Li, Qiang ^{[6
,7
]}

Wang, Qing ^{[8
]}

Ni, Yi-Qing ^{[3
,4
]}

机构：

[1] Institute of Structural Engineering, College of Civil Engineering and Architecture, Zhejiang University, Hangzhou

[2] Center for Balance Architecture, Zhejiang University, Hangzhou

[3] Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon

[4] Hong Kong Branch of the National Engineering Research Center on Rail Transit Electrification and Automation, Hung Hom, Kowloon

[5] School of Civil Engineering and Architecture, Guangxi University, Nanning

[6] School of Civil Engineering and Architecture, Ningbo Tech University, Ningbo

[7] Ningbo Research Institute, Zhejiang University, Ningbo

[8] Zhejiang Huadong Mapping and Engineering Safety Technology co., Ltd, Hangzhou

来源：

Journal of Infrastructure Intelligence and Resilience | 2025年 / 4卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Fractal dimension; Simulation of multivariate nonstationary wind speeds; Structure function method; Weierstrass mandelbrot function;

D O I：

10.1016/j.iintel.2024.100135

中图分类号：

学科分类号：

摘要：

This paper proposes a fractal-based technique for simulating multivariate nonstationary wind fields by the stochastic Weierstrass Mandelbrot function. Upon conducting a systematic fractal analysis, it was found that the structure function method is more suitable and reliable than the box counting method, variation method, and R/S analysis method for estimating the fractal dimension of the stochastic wind speed series. Wind field measurement at the meteorological gradient tower with a height of 356 m in Shenzhen was conducted during Typhoon Mandelbrot (1983). Significant non-stationary properties and fractal dimensions of typhoon wind speed data at various heights were analyzed and used to demonstrate the effectiveness of the proposed multivariate typhoon wind speed simulation method. The multivariate wind speed components simulated by the proposed fractal-based method are in good agreement with the measured records in terms of the fractal dimension, standard deviation, probability density function, wind spectrum and cross-correlation coefficient. © 2024 The Authors

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