Wind and Structures

Techno-Press (테크노프레스)
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Improved first-order method for estimating extreme wind pressure considering directionality for non-typhoon climates

  • Wang, Jingcheng (State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University) ;
  • Quan, Yong (State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University) ;
  • Gu, Ming (State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University)
  • Received : 2019.01.16
  • Accepted : 2020.11.21
  • Published : 2020.11.25
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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 non-typhoon climate with a high return period are estimated with consideration of directionality, using the relatively simple first-order 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.

Keywords

Acknowledgement

The present study is jointly supported by the National Natural Science Foundation (No. 51778493) and the State Key Laboratory of Disaster Reduction in Civil Engineering (Grant No. SLDRCE19-B-13), which are both gratefully acknowledged.

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