scholarly journals Further Analysis of Non-Gaussian Wind Pressure Peak Factor Calculation

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Tao Ye ◽  
Ledong Zhu ◽  
Zhongxu Tan ◽  
Lanlan Li
Keyword(s):  
Time Series ◽  
Pressure Coefficient ◽  
Wind Pressure ◽  
Time Interval ◽  
Peak Factor ◽  
Pressure Time ◽  
Wind Pressure Coefficient ◽  
Non Gaussian ◽  
The Relationship ◽  
Guarantee Rate

The wind pressure time history of high-rise building cladding is mostly non-Gaussian distribution, and there is a one-to-one correspondence between a specified guarantee rate and its corresponding peak factor. A stepwise search method for calculating the peak factor of non-Gaussian wind pressure and a gradual independent segmentation method for extracting independent peak values have been proposed to determine the relationship accurately in the previous study. Based on the given experiment and calculation results in the existing research results, more analysis can be given to enrich the study on this topic. In this paper, some characteristics of wind pressure coefficient time series in time and frequency domain are analysed. Based on the basic theory of fractal, the R/S analysis of wind pressure time series is made, and the fractal characteristics of wind pressure coefficient time series are explained. Based on the statistical theory, the relationship characteristics between high-order statistics and peak factors are studied. The correlation between the guarantee rate and the corresponding peak factor is analysed, and the guarantee rates calculated by the Davenport peak factor method are evaluated. The power spectrum characteristics of fluctuating wind pressure are analysed and the relationship between turbulence characteristic frequency and optimal observation time interval is discussed.

Synthesis of non-Gaussian wind pressure time series on low building roofs

1999 ◽  
Vol 21 (12) ◽  
pp. 1086-1100 ◽  
Author(s):  
K Suresh Kumar ◽  
T Stathopoulos
Keyword(s):  
Time Series ◽  
Wind Pressure ◽  
Pressure Time ◽  
Non Gaussian

CFD Modeling of Pressure Coefficients for a Natural Ventilation Study in an Experimental Low Rise Building

2013 ◽  
Author(s):  
Robel Kiflemariam ◽  
Cheng-Xian Lin
Keyword(s):  
Natural Ventilation ◽  
Pressure Coefficient ◽  
Wind Pressure ◽  
Analytical Models ◽  
Cfd Modeling ◽  
Engineering Practice ◽  
Pressure Coefficients ◽  
Wind Pressure Coefficient ◽  
Detailed Assessment ◽  
Ventilation Rates

Mean wind pressure coefficient (Cp) is one of the major input data for natural ventilation study using building energy simulation approach. Due to their importance, they need to be accurately determined. In current engineering practice, tables and analytical Cp models only give mostly averaged results for simpler models and configurations. Considering the limitation of tables and analytical models, Computational Fluid Dynamics (CFD) could provide a means for an accurate and detailed assessment of Cp. In this paper, we make use of a relatively high resolution, detailed experiments done at Florida Intentional University to validate a CFD modeling of the pressure coefficients Cp. The results show that existing CFD model has a good agreement with experimental results and gives important information of distribution of Cp values over the surface. The local values of the Cp are investigated. In addition, the CFD derived Cp and discharge coefficient (Cd) values are utilized in semi-analytical ventilation models in order to get a more accurate value of ventilation rates.

scholarly journals ESTIMATION OF PEAK FACTOR FOR NON-GAUSSIAN WIND PRESSURE

2002 ◽  
Vol 67 (557) ◽  
pp. 79-84 ◽  
Author(s):  
Kazuyoshi NISHIJIMA ◽  
Jun KANDA ◽  
Hang CHOI
Keyword(s):  
Wind Pressure ◽  
Peak Factor ◽  
Non Gaussian

Mean Wind Pressure Field on the Typical Large-Span Roof Structures

2012 ◽  
Vol 166-169 ◽  
pp. 19-24
Author(s):  
Fang Hui Li ◽  
Ming Gu ◽  
Zhen Hua Ni ◽  
Shi Zhao Shen
Keyword(s):  
Pressure Field ◽  
Pressure Coefficient ◽  
Wind Pressure ◽  
Pressure Data ◽  
Shape Factors ◽  
Local Shape ◽  
Wind Pressure Coefficient ◽  
The Mean ◽  
Urban Terrain ◽  
Wind Pressures

The wind tunnel tests of some typical large roofs, including a saddle roof, pitched roof and domes, are carried out with various terrains which cover suburban and urban exposures. The wind pressure data of roofs are obtained by using the synchronous multi-pressure scanning technique. The wind pressure coefficient and local shape factors of the wind load was investigated. The effects of various terrains on wind pressures of roofs are discussed. From the results, we can see mean pressures of these roofs exposed to the mean pressures exposed to the suburban terrain are 2 or 3 times those exposed to the urban terrain. And the terrains are no directly influence to the wind pressure shape factors.

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