A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Simulation of stationary non-Gaussian multivariate wind pressures using moment-based piecewise Hermite polynomial model
https://orcid.org/0000-0003-0473-2631
Abstract The wind pressure at the flow separation region of building surfaces generally exhibits non-Gaussian characteristics and is modeled as a non-Gaussian random process. To evaluate the structural response under this non-Gaussian excitation, the time-domain response analysis is commonly used, especially in order to take into account the structural and aerodynamics nonlinearity. This makes the simulation of stationary non-Gaussian multivariate random processes becomes an essential task. The traditional correlation distortion simulation method based on the Hermite polynomial model (HPM) is widely used because it has relatively satisfactory simulation efficiency and is easy for the use. Nonetheless, its application range and simulation accuracy are restricted by the effective zone and modeling accuracy of the moment-based HPM. In this study, a novel correlation distortion simulation method using moment-based piecewise HPM (PHPM) is proposed, where the formulas of the PHPM corresponding to four cases, correlation distortion relationship and simulation scheme are developed. In comparison with the method using HPM, the proposed method has not only wider application range, but also higher simulation accuracy. To demonstrate the effectiveness of the proposed method, the simulations of measured univariate and multivariate non-Gaussian wind pressure data are conducted. Results show that for the example of wind pressures out of the monotonic region, which cannot be simulated by the method using HPM, the PDF and PSD of the simulated samples by the proposed method agree with the targets well. For the other examples, the simulation accuracy of the proposed method is overall higher than that of the simulation method using the moment-based HPM. These verify that the proposed method has larger applicability and higher accuracy than the simulation method using the HPM. Note that the proposed method can also be applied to simulate other non-Gaussian excitations such as the wind speed in the complex area.
Highlights The simulation of stationary non-Gaussian multivariate wind pressures is addressed. The Hermite polynomial model (HPM) and piecewise HPM (PHPM) are involved. A correlation distortion simulation method using moment-based PHPM is proposed. The proposed method can extend the application range of the method using HPM. Results show that the proposed method is of higher accuracy than that using HPM.
Simulation of stationary non-Gaussian multivariate wind pressures using moment-based piecewise Hermite polynomial model
https://orcid.org/0000-0003-0473-2631
Abstract The wind pressure at the flow separation region of building surfaces generally exhibits non-Gaussian characteristics and is modeled as a non-Gaussian random process. To evaluate the structural response under this non-Gaussian excitation, the time-domain response analysis is commonly used, especially in order to take into account the structural and aerodynamics nonlinearity. This makes the simulation of stationary non-Gaussian multivariate random processes becomes an essential task. The traditional correlation distortion simulation method based on the Hermite polynomial model (HPM) is widely used because it has relatively satisfactory simulation efficiency and is easy for the use. Nonetheless, its application range and simulation accuracy are restricted by the effective zone and modeling accuracy of the moment-based HPM. In this study, a novel correlation distortion simulation method using moment-based piecewise HPM (PHPM) is proposed, where the formulas of the PHPM corresponding to four cases, correlation distortion relationship and simulation scheme are developed. In comparison with the method using HPM, the proposed method has not only wider application range, but also higher simulation accuracy. To demonstrate the effectiveness of the proposed method, the simulations of measured univariate and multivariate non-Gaussian wind pressure data are conducted. Results show that for the example of wind pressures out of the monotonic region, which cannot be simulated by the method using HPM, the PDF and PSD of the simulated samples by the proposed method agree with the targets well. For the other examples, the simulation accuracy of the proposed method is overall higher than that of the simulation method using the moment-based HPM. These verify that the proposed method has larger applicability and higher accuracy than the simulation method using the HPM. Note that the proposed method can also be applied to simulate other non-Gaussian excitations such as the wind speed in the complex area.
Highlights The simulation of stationary non-Gaussian multivariate wind pressures is addressed. The Hermite polynomial model (HPM) and piecewise HPM (PHPM) are involved. A correlation distortion simulation method using moment-based PHPM is proposed. The proposed method can extend the application range of the method using HPM. Results show that the proposed method is of higher accuracy than that using HPM.
Simulation of stationary non-Gaussian multivariate wind pressures using moment-based piecewise Hermite polynomial model
https://orcid.org/0000-0003-0473-2631
Abstract The wind pressure at the flow separation region of building surfaces generally exhibits non-Gaussian characteristics and is modeled as a non-Gaussian random process. To evaluate the structural response under this non-Gaussian excitation, the time-domain response analysis is commonly used, especially in order to take into account the structural and aerodynamics nonlinearity. This makes the simulation of stationary non-Gaussian multivariate random processes becomes an essential task. The traditional correlation distortion simulation method based on the Hermite polynomial model (HPM) is widely used because it has relatively satisfactory simulation efficiency and is easy for the use. Nonetheless, its application range and simulation accuracy are restricted by the effective zone and modeling accuracy of the moment-based HPM. In this study, a novel correlation distortion simulation method using moment-based piecewise HPM (PHPM) is proposed, where the formulas of the PHPM corresponding to four cases, correlation distortion relationship and simulation scheme are developed. In comparison with the method using HPM, the proposed method has not only wider application range, but also higher simulation accuracy. To demonstrate the effectiveness of the proposed method, the simulations of measured univariate and multivariate non-Gaussian wind pressure data are conducted. Results show that for the example of wind pressures out of the monotonic region, which cannot be simulated by the method using HPM, the PDF and PSD of the simulated samples by the proposed method agree with the targets well. For the other examples, the simulation accuracy of the proposed method is overall higher than that of the simulation method using the moment-based HPM. These verify that the proposed method has larger applicability and higher accuracy than the simulation method using the HPM. Note that the proposed method can also be applied to simulate other non-Gaussian excitations such as the wind speed in the complex area.
Highlights The simulation of stationary non-Gaussian multivariate wind pressures is addressed. The Hermite polynomial model (HPM) and piecewise HPM (PHPM) are involved. A correlation distortion simulation method using moment-based PHPM is proposed. The proposed method can extend the application range of the method using HPM. Results show that the proposed method is of higher accuracy than that using HPM.
Simulation of stationary non-Gaussian multivariate wind pressures using moment-based piecewise Hermite polynomial model
Liu, Min (author) / Peng, Liuliu (author) / Huang, Guoqing (author) / Yang, Qingshan (author) / Jiang, Yan (author)
2019-11-08
Article (Journal)
Electronic Resource
English
Estimation of Peak Factor of Non-Gaussian Wind Pressures by Improved Moment-Based Hermite Model
| Online Contents | 2017
Estimation of Peak Factor of Non-Gaussian Wind Pressures by Improved Moment-Based Hermite Model
| Online Contents | 2017