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Adjusted Equivalent Static Wind Loads for non-Gaussian linear static analysis
Blaise, Nicolas; Denoël, Vincent
2015In Proceedings of the 14th International Conference on Wind Engineering
Peer reviewed
 

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Keywords :
Non-Gaussian; Equivalent static wind loads
Abstract :
[en] In this paper, we propose a parametric bi-cubic model for the joint probability distribution of wind aerodynamic pressures and structural responses. This non-Gaussian model is a bivariate extension of the well-known Hermite polynomial transformation. It offers a new way to determine Equivalent Static Wind Loads, with the embedded feature to –at least partly– capture the non-Gaussianity of the aerodynamic pressures and responses. In a second step, based on the observation that this model as well as the usual LRC method or the conditional sampling technique, fail in reproducing structural responses that do not overestimate the extreme values resulting from a complete structural analysis, we propose a two-step adjustment procedure that restores the non-overestimation condition and the recovery of the considered structural response. With the example of a boundary layer flow around a duo-pitched roof, it is demonstrated that the Equivalent Static Wind Loads, adjusted or not, obtained with the proposed model of non-Gaussian joint probability density function reconstruct the envelope of structural response more efficiently than with the other two techniques.
Disciplines :
Civil engineering
Author, co-author :
Blaise, Nicolas ;  Université de Liège > Département ArGEnCo > Analyse sous actions aléatoires en génie civil
Denoël, Vincent  ;  Université de Liège > Département ArGEnCo > Analyse sous actions aléatoires en génie civil
Language :
English
Title :
Adjusted Equivalent Static Wind Loads for non-Gaussian linear static analysis
Publication date :
June 2015
Event name :
14th international conference on wind engineering
Event date :
June 21-26, 2015
Audience :
International
Main work title :
Proceedings of the 14th International Conference on Wind Engineering
Peer reviewed :
Peer reviewed
Available on ORBi :
since 29 June 2015

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