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Multivariate stationary non-Gaussian process simulation for wind pressure fields

Multivariate stationary non-Gaussian process simulation for wind pressure fields
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摘要 Stochastic simulation is an important means of acquiring fluctuating wind pressures for wind induced response analyses in structural engineering. The wind pressure acting on a large-span space structure can be characterized as a stationary non-Gaussian field. This paper reviews several simulation algorithms related to the Spectral Representation Method (SRM) and the Static Transformation Method (STM). Polynomial and Exponential transformation functions (PSTM and ESTM) are discussed. Deficiencies in current algorithms, with respect to accuracy, stability and efficiency, are analyzed, and the algorithms are improved for better practical application. In order to verify the improved algorithm, wind pressure fields on a large-span roof are simulated and compared with wind tunnel data. The simulation results fit well with the wind tunnel data, and the algorithm accuracy, stability and efficiency are shown to be better than those of current algorithms. Stochastic simulation is an important means of acquiring fluctuating wind pressures for wind induced response analyses in structural engineering. The wind pressure acting on a large-span space structure can be characterized as a stationary non-Gaussian field. This paper reviews several simulation algorithms related to the Spectral Representation Method (SRM) and the Static Transformation Method (STM). Polynomial and Exponential transformation functions (PSTM and ESTM) are discussed. Deficiencies in current algorithms, with respect to accuracy, stability and efficiency, are analyzed, and the algorithms are improved for better practical application. In order to verify the improved algorithm, wind pressure fields on a large-span roof are simulated and compared with wind tunnel data. The simulation results fit well with the wind tunnel data, and the algorithm accuracy, stability and efficiency are shown to be better than those of current algorithms.
出处 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2016年第4期729-742,共14页 地震工程与工程振动(英文刊)
基金 National Natural Science Foundation of China under Grant Nos.51278160,51478155,51378147
关键词 stochastic simulation non-Gaussian process static transformation method wind pressure field stochastic simulation non-Gaussian process static transformation method wind pressure field
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