A comprehensive analysis of the tail-dependent structure of wind loads and its engineering applications

Abstract

Wind load field characteristics on the roof surface of low-rise buildings based on field measurements have crucial engineering guidance value. In the background, tail-dependence structure from measured wind loads can assist in modeling the joint tail distribution of multivariate wind loads. In this study, the non-parameter estimation method, multi-copula function model and multivariate peak over threshold model are applied to estimate its precise value. The upper tail dependence coefficient's value is around 0.20 when the quantile for p(y) = 0.75. When p(y) = 0.95, the Gumbel copula overestimates the tail-dependence value slightly. Additionally, the lower tail-dependence values estimated by the Clayton copula are around 0.19 at 0.25 quantile. For extreme tail-dependence coefficients, little difference exists in the estimated results by the non-parameter estimation method and the peak over threshold model, in which its value varies from 0.80 to 0.90. Under roof pitch = 5°, its value exhibits some dispersion at different locations. An area weight function is applied to estimate the extreme tail-dependence value between critical regions. Then, the expectation function of tail dependence reaches the peak value in p(x) = 0.50, p(y) = 0.50 and it has different gradients for different variables and tail regions. Additionally, the lower tail dependence structure is significantly stronger than the upper tail dependence for wind loads with negative skewness. For application in wind engineering, potential applications in risk analysis for roof structures, extreme value estimation for local region block wind load, and wind load forecast for unmonitored locations are proposed.