Wind and Structures
Volume 31, Number 5, 2020, pages 473-482
DOI: 10.12989/was.2020.31.5.473
Improved first-order method for estimating extreme wind pressure considering directionality for non-typhoon climates
Jingcheng Wang, Yong Quan and Ming Gu
Abstract
The first-order method for estimating the extreme wind pressure on building envelopes with consideration of the
directionality of wind speed and wind pressure is improved to enhance its computational efficiency. In this improved method,
the result is obtained directly from the empirical distribution of a random selection of annual maximum wind pressure samples
generated by a Monte Carlo method, rather than from the previously utilized extreme wind pressure probability distribution. A
discussion of the relationship between the first- and full-order methods indicates that when extreme wind pressures in a nontyphoon climate with a high return period are estimated with consideration of directionality, using the relatively simple firstorder method instead of the computationally intensive full-order method is reasonable. The validation of this reasonableness is
equivalent to validating two assumptions to improve its computational efficiency: 1) The result obtained by the full-order
method is conservative when the extreme wind pressure events among different sectors are independent. 2) The result obtained
by the first-order method for a high return period is not significantly affected when the extreme wind speeds among the different
sectors are assumed to be independent. These two assumptions are validated by examples in different regions and theoretical
derivation.
Key Words
wind load; extreme wind pressure; directionality; first-order method; full-order method; probability; Gaussian copula; return period; building envelopes
Address
Jingcheng Wang:State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China
/State Grid Shanghai Cable Company, Shanghai 200072, China
Yong Quan:State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China
Ming Gu:State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China