Probabilistic modeling of multivariate extreme non-Gaussian wind loads and its applications in envelope engineering

Abstract

Probabilistic modeling for non-Gaussian wind load fields under extreme winds is crucial to the quantitative risk and reliability analysis of envelope structures. Based on the multi-point synchronous wind load data during typhoons, a probabilistic model is proposed to characterize multivariate non-Gaussian wind loads to improve the accuracy of the risk analysis considering data dimension reduction. In the proposed model, the Pareto distribution function is utilized to fit the marginal distribution, and the copula function is employed to construct the dependent structure of wind loads from different locations. In the marginal fitted results, the extreme wind load value in the edge region is about 0.10–0.15 higher than those from inner measurement points at quantile p = 95 %. In addition, the variation gradient from the different variable directions is approximately equal, and a sharp variation occurs at the point (0.10, 0.10) for bivariate joint distributions. Engineering applications given in this article are composed of three parts: calculating regional exceeding probability, estimating wind load vector under a specific regional exceeding probability, and determining the location of joint extreme wind loads using the joint gradient value. Finally, risk analysis of existing roof coverings is carried out, the edge corner region is weaker, and two engineering recommendations are given. For determining the regional design wind load, a comprehensive calculation framework considering the temporal dependence of different locations is established, and the reduction rates are in the range (5 %, 25 %).