Simulation of Stochastic Wind Field on Long Span Cable-stayed Bridge
- DOI
- 10.2991/978-94-6463-398-6_66How to use a DOI?
- Keywords
- able-stayed; FFT; Bridge; Stochastic wind field
- Abstract
The quick and efficient simulation of wind speed profiles is a necessary condition for performing time history response analysis of bridges. This paper introduces the harmonic synthesis method for simulating wind fields and applies it to simulate the random wind field at the location of the Hanjia River Yangtze River Bridge on the Yuli Railway. The paper also provides a detailed comparison of the effects of different aerodynamic admittance functions on the fluctuating wind speed spectrum. The explicit Cholesky decomposition of the wind speed spectrum density matrix is performed, and the simulation efficiency is greatly improved by using FFT techniques. A wind field simulation program is developed, and the correctness of the program is verified by comparing the wind speed spectrum and correlation functions, laying a solid foundation for the effective analysis of wind-induced vibrations in structures.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yongyi Yang AU - Zizhen Zhang AU - Jizhong Yang PY - 2024 DA - 2024/04/24 TI - Simulation of Stochastic Wind Field on Long Span Cable-stayed Bridge BT - Proceedings of the 2023 5th International Conference on Hydraulic, Civil and Construction Engineering (HCCE 2023) PB - Atlantis Press SP - 674 EP - 683 SN - 2589-4943 UR - https://doi.org/10.2991/978-94-6463-398-6_66 DO - 10.2991/978-94-6463-398-6_66 ID - Yang2024 ER -