Details
| Original language | English |
|---|---|
| Article number | 106264 |
| Journal | Mechanical Systems and Signal Processing |
| Volume | 133 |
| Early online date | 12 Aug 2019 |
| Publication status | Published - 1 Nov 2019 |
Abstract
Wind field simulation and wind-induced reliability assessment are two critical steps in wind-induced vibration analysis and design of super high-rise buildings. Owing to its simple algorithm and rigorous theoretical basis, the spectral representation method (SRM) is widely used in practice. However, the SRM still encounters the computational challenge due to the Cholesky decomposition with respect to the crossing-power spectral density (PSD) matrix, particularly in the simulation of multi-variate random processes of large-size wind fluctuation fields. To circumvent this challenge, the stochastic harmonic function based spectral representation method (SHF-SRM) proposed in recent years is extended to the simulation of multi-variate random processes. In conjunction with the probability density evolution method (PDEM), the stochastic response analysis and reliability assessment of wind-induced random vibration of structures is addressed. For illustrative purposes, the wind field simulation and wind-induced vibration and reliability assessment of a 417.7 m high building are carried out. The numerical example proves the effectiveness of the SHF-SRM in simulating multi-variate random processes, and reveals the value of reliability assessment in terms of the global reliability and the time-variant reliability for the enhancement of wind-resistant design of high-rise buildings.
Keywords
- Multi-variate random processes, Probability density evolution method, Reliability assessment, Stochastic harmonic function, Super high-rise buildings, Wind field simulation
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Computer Science(all)
- Signal Processing
- Engineering(all)
- Civil and Structural Engineering
- Engineering(all)
- Aerospace Engineering
- Engineering(all)
- Mechanical Engineering
- Computer Science(all)
- Computer Science Applications
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In: Mechanical Systems and Signal Processing, Vol. 133, 106264, 01.11.2019.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Stochastic harmonic function based wind field simulation and wind-induced reliability of super high-rise buildings
AU - Chen, Jianbing
AU - Chen, Youwei
AU - Peng, Yongbo
AU - Zhu, Shiyun
AU - Beer, Michael
AU - Comerford, Liam
N1 - Funding information: The supports of the National Natural Science Foundation of China (Grant Nos. 11672209 , 51538010 , 51725804 , 51878505 , and 11761131014 ), and the National Key R&D Program of China (Grant No. 2017YFC0803300 ) are highly appreciated. The authors are grateful to Mr Guangjing Sha and Mr Xi Zhu for their helps in preparing this article.
PY - 2019/11/1
Y1 - 2019/11/1
N2 - Wind field simulation and wind-induced reliability assessment are two critical steps in wind-induced vibration analysis and design of super high-rise buildings. Owing to its simple algorithm and rigorous theoretical basis, the spectral representation method (SRM) is widely used in practice. However, the SRM still encounters the computational challenge due to the Cholesky decomposition with respect to the crossing-power spectral density (PSD) matrix, particularly in the simulation of multi-variate random processes of large-size wind fluctuation fields. To circumvent this challenge, the stochastic harmonic function based spectral representation method (SHF-SRM) proposed in recent years is extended to the simulation of multi-variate random processes. In conjunction with the probability density evolution method (PDEM), the stochastic response analysis and reliability assessment of wind-induced random vibration of structures is addressed. For illustrative purposes, the wind field simulation and wind-induced vibration and reliability assessment of a 417.7 m high building are carried out. The numerical example proves the effectiveness of the SHF-SRM in simulating multi-variate random processes, and reveals the value of reliability assessment in terms of the global reliability and the time-variant reliability for the enhancement of wind-resistant design of high-rise buildings.
AB - Wind field simulation and wind-induced reliability assessment are two critical steps in wind-induced vibration analysis and design of super high-rise buildings. Owing to its simple algorithm and rigorous theoretical basis, the spectral representation method (SRM) is widely used in practice. However, the SRM still encounters the computational challenge due to the Cholesky decomposition with respect to the crossing-power spectral density (PSD) matrix, particularly in the simulation of multi-variate random processes of large-size wind fluctuation fields. To circumvent this challenge, the stochastic harmonic function based spectral representation method (SHF-SRM) proposed in recent years is extended to the simulation of multi-variate random processes. In conjunction with the probability density evolution method (PDEM), the stochastic response analysis and reliability assessment of wind-induced random vibration of structures is addressed. For illustrative purposes, the wind field simulation and wind-induced vibration and reliability assessment of a 417.7 m high building are carried out. The numerical example proves the effectiveness of the SHF-SRM in simulating multi-variate random processes, and reveals the value of reliability assessment in terms of the global reliability and the time-variant reliability for the enhancement of wind-resistant design of high-rise buildings.
KW - Multi-variate random processes
KW - Probability density evolution method
KW - Reliability assessment
KW - Stochastic harmonic function
KW - Super high-rise buildings
KW - Wind field simulation
UR - http://www.scopus.com/inward/record.url?scp=85070378424&partnerID=8YFLogxK
U2 - 10.1016/j.ymssp.2019.106264
DO - 10.1016/j.ymssp.2019.106264
M3 - Article
AN - SCOPUS:85070378424
VL - 133
JO - Mechanical Systems and Signal Processing
JF - Mechanical Systems and Signal Processing
SN - 0888-3270
M1 - 106264
ER -