Abstract
A procedure is presented for estimating parametric probabilistic models of hurricane wind speeds from existing information on state-of-the-art estimates of wind speeds with various mean recurrence intervals (MRIs). Such models may be needed, for example, for the estimation of hurricane wind speeds with long MRIs required for the performance-based design of structures susceptible of experiencing nonlinear behavior. First, the procedure is applied to the case where that information is obtained from ASCE 7-10 wind maps, and examples are provided of its application to a number of coastal mileposts on the Gulf and Atlantic coasts. Next, the procedure is applied by using, in addition to theASCE 7-10 information, hurricane wind speeds with 1,000,000- and 10,000,000-year MRIs estimated in a 2011 Nuclear Regulatory Commission report. It is then argued that ASCE 7-10 Standard basic wind speeds for New York City are unconservative with respect to their counterparts specified in the Standard for other U.S. hurricane-prone locations. Finally, it is shown that, for the randomly selected cases examined in the paper, best fitting extreme value distributions of hurricane wind speeds typically have finite upper tails of the reverse Weibull type, rather than infinite upper tails of the Gumbel type. This result, if confirmed by additional studies, may help to change the still widely held belief that extreme wind speeds are appropriately modeled only by the Gumbel distribution.
Original language | English (US) |
---|---|
Title of host publication | Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures - Proceedings of the 11th International Conference on Structural Safety and Reliability, ICOSSAR 2013 |
Pages | 1299-1304 |
Number of pages | 6 |
State | Published - Dec 1 2013 |
Event | 11th International Conference on Structural Safety and Reliability, ICOSSAR 2013 - New York, NY, United States Duration: Jun 16 2013 → Jun 20 2013 |
Other
Other | 11th International Conference on Structural Safety and Reliability, ICOSSAR 2013 |
---|---|
Country/Territory | United States |
City | New York, NY |
Period | 6/16/13 → 6/20/13 |
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Safety, Risk, Reliability and Quality