Assessing probabilistic wind load effects via a multivariate extreme wind speed model: A unified framework to consider directionality and uncertainty

This study presents a new approach of estimating wind load effects (responses) for various mean recurrence intervals (MRIs) with consideration of both directionality and uncertainty of wind speed and wind load effects. The joint probability distribution model of directional extreme wind speeds is established based on extreme wind speed data using multivariate extreme value theory with Gaussian Copula. The distribution of yearly maximum wind load effect is then calculated through the exceeding probability of directional wind speeds over the corresponding levels. The uncertainty of extreme response conditional on wind speed and direction is further considered using the theorem of conditional probability. The proposed analytical framework can be considered as an analytical formulation of the existing approach based on historical directional wind speed data, but with an additional capability of accounting for the uncertainty of extreme response conditional on wind speed and direction. It can also be regarded as an extension of the existing fully probabilistic methods with an additional capability of accounting for directionality. Applications of the proposed approach are presented and the results are compared with those from the existing approach to demonstrate its accuracy. The characteristics of directionality factor for wind load effects are discussed. Finally, the influence of uncertainty of extreme response conditional on wind speed and direction is further examined.