Buy article PDF
The purchased file will be sent to you
via email after the payment is completed.
US$ 35
|
Wind and Structures Volume 31, Number 5, November 2020 , pages 473-482 DOI: https://doi.org/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 | ||