Technical Papers
Aug 23, 2019

Wind Speed Field Simulation via Stochastic Harmonic Function Representation Based on Wavenumber–Frequency Spectrum

Publication: Journal of Engineering Mechanics
Volume 145, Issue 11

Abstract

Simulation of fluctuating wind speed field is of paramount significance in the design of large flexible structures. To circumvent the difficulty due to the decomposition of cross power spectral density (PSD) matrix and the interpolation between discretized spatial points, a wavenumber–frequency joint spectrum-based spectral representation method (SRM) has been developed recently. To further improve the efficiency and accuracy, the stochastic harmonic function (SHF) representation is extended in the present paper for the simulation of stationary and nonstationary fluctuating wind fields in two spatial dimensions. In contrast to the SRM, in addition to the phase angles, the frequencies and wavenumbers are also random variables over partitioned wavenumber–frequency subdomains. Furthermore, a strategy of dependent random frequencies and wavenumbers based on the SHF is proposed so that the number of random variables can be considerably reduced by 3/7. A new acceptance–rejection criterion, which avoids the artificial intervene, is suggested based on the p-power joint spectrum, and the subdomains are correspondingly determined by the Voronoi cell partitioning. For illustrative purposes, two numerical examples for the simulation of stationary and nonstationary fluctuating wind speed fields in two spatial dimensions are addressed, demonstrating the effectiveness of the proposed method in considerably reducing the random variables as well as the computational efforts.

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Acknowledgments

Financial supports from the National Natural Science Foundation of China (Grant Nos. 51725804, 11672209, and 11761131014) and the International Joint Research Program of Shanghai Municipal Government (Grant No. 18160712800) are highly appreciated.

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Go to Journal of Engineering Mechanics
Journal of Engineering Mechanics
Volume 145Issue 11November 2019

History

Received: Sep 3, 2018
Accepted: Mar 18, 2019
Published online: Aug 23, 2019
Published in print: Nov 1, 2019
Discussion open until: Jan 23, 2020

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Authors

Affiliations

Yupeng Song [email protected]
Ph.D. Student, State Key Laboratory of Disaster Reduction in Civil Engineering and College of Civil Engineering, Tongji Univ., 1239 Siping Rd., Shanghai 200092, PR China. Email: [email protected]
Professor, State Key Laboratory of Disaster Reduction in Civil Engineering and College of Civil Engineering, Tongji Univ., 1239 Siping Rd., Shanghai 200092, PR China (corresponding author). ORCID: https://orcid.org/0000-0001-8520-0383. Email: [email protected]
Michael Beer, M.ASCE [email protected]
Professor, Institute for Risk and Reliability, Leibniz Universität Hannover, Callinstr. 34, Hannover 30167, Germany; Professor, Institute for Risk and Uncertainty, Univ. of Liverpool, Liverpool L69 3GH, UK. Email: [email protected]
Liam Comerford, Ph.D. [email protected]
Research Scientist, Institute for Risk and Uncertainty, Univ. of Liverpool, Liverpool L69 3GH, UK. Email: [email protected]

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