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Non-Gaussian time-dependent statistics of wind pressure processes on a roof structure
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  • Journal title : Wind and Structures
  • Volume 23, Issue 4,  2016, pp.275-300
  • Publisher : Techno-Press
  • DOI : 10.12989/was.2016.23.4.275
 Title & Authors
Non-Gaussian time-dependent statistics of wind pressure processes on a roof structure
Huang, M.F.; Huang, Song; Feng, He; Lou, Wenjuan;
 Abstract
Synchronous multi-pressure measurements were carried out with relatively long time duration for a double-layer reticulated shell roof model in the atmospheric boundary layer wind tunnel. Since the long roof is open at two ends for the storage of coal piles, three different testing cases were considered as the empty roof without coal piles (Case A), half coal piles inside (Case B) and full coal piles inside (Case C). Based on the wind tunnel test results, non-Gaussian time-dependent statistics of net wind pressure on the shell roof were quantified in terms of skewness and kurtosis. It was found that the direct statistical estimation of high-order moments and peak factors is quite sensitive to the duration of wind pressure time-history data. The maximum value of COVs (Coefficients of variations) of high-order moments is up to 1.05 for several measured pressure processes. The Mixture distribution models are proposed for better modeling the distribution of a parent pressure process. With the aid of mixture parent distribution models, the existing translated-peak-process (TPP) method has been revised and improved in the estimation of non-Gaussian peak factors. Finally, non-Gaussian peak factors of wind pressure, particularly for those observed hardening pressure process, were calculated by employing various state-of-the-art methods and compared to the direct statistical analysis of the measured long-duration wind pressure data. The estimated non-Gaussian peak factors for a hardening pressure process at the leading edge of the roof were varying from 3.6229, 3.3693 to 3.3416 corresponding to three different cases of A, B and C.
 Keywords
wind pressure;mixture distribution;non-Gaussian;peak factor;wind tunnel tests;
 Language
English
 Cited by
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