Estimation of extremes of non-Gaussian wind pressure on building roof: Sampling error in moment-based translation process model with no monotonic limit

2019 ◽  
Vol 23 (4) ◽  
pp. 810-826 ◽  
Author(s):  
Fengbo Wu ◽  
Min Liu ◽  
Qingshan Yang ◽  
Liuliu Peng
Keyword(s):  
Hermite Polynomial ◽  
Sampling Error ◽  
Polynomial Model ◽  
Wind Pressure ◽  
Transformation Model ◽  
Sampling Errors ◽  
Translation Process ◽  
Building Roof ◽  
Wind Pressures ◽  
Non Gaussian

Estimation of extremes of non-Gaussian wind pressure on building roof is necessary for cladding design. When limited length of non-Gaussian wind pressure is used for calculation, the estimated extreme involves sampling error. The moment-based Hermite polynomial model is extensively applied for estimation of extreme wind pressure due to the straightforwardness and accuracy, however, Hermite polynomial model has a monotonic limit resulting in a restricted application region of skewness and kurtosis combination. However, another two moment-based translation process models with no monotonic limit including Johnson transformation model and piecewise Hermite polynomial model have attracted some attention as these two models can be applied to a broader region of skewness and kurtosis combination. The sampling error in estimation of extremes of non-Gaussian wind pressure on building roof by Hermite polynomial model is proposed in the literature recently. Nevertheless, the sampling errors in Johnson transformation model and piecewise Hermite polynomial model have not been addressed. In this study, sampling errors in estimation of extremes of non-Gaussian wind pressures by Johnson transformation model are investigated. Formulations for estimating sampling errors of newly defined statistical moments and subsequent extremes in piecewise Hermite polynomial model are presented. The performance of sampling errors in Hermite polynomial model, Johnson transformation model, and piecewise Hermite polynomial model are finally compared with each other. Based on very long wind pressures from wind tunnel tests, it is shown that the sampling error of minimum wind pressure (suction) in Hermite polynomial model is generally the smallest compared to Johnson transformation model and piecewise Hermite polynomial model, while that of maximum wind pressure in piecewise Hermite polynomial model seems to be the smallest.

WIND PRESSURE DISTRIBUTION ON NORTH-LIGHT INDUSTRIAL BUILDING ROOF STUDY

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Astha Verma ◽  
Ashok Kumar Ahuja
Keyword(s):  
Boundary Layer ◽  
Experimental Study ◽  
Wind Tunnel ◽  
Pressure Distribution ◽  
Wind Pressure ◽  
Closed Circuit ◽  
Industrial Building ◽  
Building Roof ◽  
Pressure Coefficients ◽  
Wind Pressures

Present paper describes details of the experimental study carried out on the models of industrial building with north-light roof in order to generate the information about wind pressure distribution on it. The models are tested in a closed circuit boundary layer wind tunnel to measure values of wind pressures on roof surface. Four cases namely one, two, three and four spans are considered. The side of Perspex sheet model in case of multi-span study places plywood models. Wind is made to hit the models at 13 wind incidence angles from 0° to 180° at an interval of 15°. Values of mean wind pressure coefficients are evaluated from the measured values of wind pressures and contours are plotted.

Modeling of wind-induced pressure fluctuations on roofs of low-rise buildings

1999 ◽  
Vol 26 (4) ◽  
pp. 453-467 ◽  
Author(s):  
K Suresh Kumar
Keyword(s):  
Time Series ◽  
Pressure Fluctuations ◽  
Wind Pressure ◽  
Fourier Amplitude ◽  
Simulation Methodology ◽  
Fatigue Design ◽  
Building Modeling ◽  
Wind Pressures ◽  
Non Gaussian ◽  
Simulation Scheme

A systematic study on the modeling of wind-induced pressures on low building roofs with application to extreme value and fatigue analysis is described in this paper. Extensive wind tunnel measurements form a basis to carry out the modeling. Based on the Fourier representation of time series, a general approach for simulating Gaussian as well as non-Gaussian wind pressure fluctuations has been presented. Both Fourier amplitude and phase required for the simulations are modeled individually. A simple stochastic model is proposed for the generation of Fourier phase of non-Gaussian time series. An empirical model has been suggested for the synthetic generation of normalized spectra; synthetic spectra are utilized for the generation of Fourier amplitude part. Towards the generalization of the simulation scheme, the standard spectral shapes associated with various zones of each roof and their parameters are established. The efficiency of this simulation methodology is illustrated with several examples. Applications of the simulation methodology have also been discussed. The established simulation scheme can be used to generate fluctuating wind pressures on low building roofs in a generic fashion not only for the evaluation of extreme pressures but also for fatigue design purposes.Key words: low-rise building, modeling, roofs, wind pressure.

scholarly journals On the Use of the Cubic Translation to Model Bimodal Wind Pressures

2019 ◽  
Vol 15 (2) ◽  
pp. 20-32
Author(s):  
François Rigo ◽  
Thomas Andrianne ◽  
Vincent Denoël
Keyword(s):  
Bimodal Distribution ◽  
Wind Pressure ◽  
Wind Engineering ◽  
Pressure Data ◽  
Direct Evaluation ◽  
Translation Model ◽  
Background Turbulence ◽  
Wind Pressures ◽  
Non Gaussian ◽  
Flat Roof

Abstract The cubic translation model is a well know tool in wind engineering, which provides a mathematical description of a non-Gaussian pressure as a cubic transformation of a Gaussian process. This simple model is widely used in practice since it offers a direct evaluation of the peak factors as a function of the statistics of the wind pressure data. This transformation is rather versatile but limited to processes which are said to be in the monotonic region. For processes falling outside this domain, this paper describes an alternative which is based on the physics of the wind flow. First, it is shown, with a classical example of a flow involving corner vortices on a flat roof, that the pressure data which does not meet the monotonic criterion is in fact associated with a bimodal distribution. Then, the proposed approach is to decompose this data into the two governing modes (slow background turbulence and fast corner vortices) and apply the usual translation model to each of them.

Numerical Study of the Effect of Wall Opening on Wind Pressures on Low-Rise Gable-Roofed Buildings

2012 ◽  
Vol 424-425 ◽  
pp. 857-860 ◽  
Author(s):  
Shui Fu Chen ◽  
Miao Yu ◽  
Dong Yao Wang
Keyword(s):  
Numerical Simulation ◽  
Pressure Distribution ◽  
Numerical Study ◽  
Wind Pressure ◽  
Front Wall ◽  
Building Roof ◽  
Wind Resistance ◽  
Wind Pressures ◽  
Wall Openings ◽  
Numerical Simulation Technique

The external and internal wind pressure distribution characteristics on the roof surface of a low-rise gable-roofed building with wall openings are studied by means of the numerical simulation technique. The validity and accuracy of the numerical simulation is first demonstrated by comparison with the existing full-scale experimental results. In order to investigate the effect of wall opening locations on the pressure distribution, a parametric analysis is carried out to a typical gable-roofed building with different wall opening conditions. The analysis results indicate that wall opening locations have no significant effect on the external wind pressure but have considerable influence on the internal wind pressure. The cases of two opposite wall openings appear to be more favorable than those of single front wall openging for wind resistance of the building roof, if the angle of approaching wind flow from the inner normal line of the front wall is smaller than 90°.

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